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Record 1 of 58Title: Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran Author(s): Pourghasemi, HR (Pourghasemi, Hamid Reza); Pradhan, B (Pradhan, Biswajeet); Gokceoglu, C (Gokceoglu, Candan)Source: NATURAL HAZARDS Volume: 63 Issue: 2 Pages: 965-996 DOI: 10.1007/s11069-012-0217-2 Published: SEP 2012 Times Cited in Web of Science Core Collection: 41 Total Times Cited: 41 Cited References: Akgun A, 2008, ENVIRON GEOL, V54, P1127, DOI 10.1007/s00254-007-0882-8 Akgun A, 2012, ENVIRON MONIT ASSESS, V184, P5453, DOI 10.1007/s10661-011-2352-8 Akgun A, 2012, COMPUT GEOSCI-UK, V38, P23, DOI 10.1016/j.cageo.2011.04.012 Akgun A, 2010, ENVIRON EARTH SCI, V61, P595, DOI 10.1007/s12665-009-0373-1 Aleotti P, 1999, B ENG ENV, V58, P21, DOI DOI 10.1007/S100640050066 Althuwaynee OF, 2012, COMPUT GEOSCI-UK, V44, P120, DOI 10.1016/j.cageo.2012.03.003 Alvarez Grima M, 2000, NEUROFUZZY MODELING Ayalew L, 2004, LANDSLIDES, V1, P73, DOI 10.1007/s10346-003-0006-9 Ayalew L, 2005, ENG GEOL, V81, P432, DOI 10.1016/j.enggeo.2005.08.004 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Baeza C, 2001, EARTH SURF PROC LAND, V26, P1251, DOI 10.1002/esp.263 Barredo J.I., 2000, INT J APPL EARTH OBS, V2, P9, DOI DOI 10.1016/S0303-2434(00)85022-9 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Beven K. J., 1979, HYDROL SCI B, V24, P43, DOI [10.1080/02626667909491834, DOI 10.1080/02626667909491834] Biswajeet P, 2010, DISASTER ADV, V3, P26 Bonham-Carter G.F., 1994, COMPUTER METHODS GEO, V13, P398 Brenning A, 2005, NAT HAZARD EARTH SYS, V5, P853 Bui DT, 2012, CATENA, V96, P28, DOI 10.1016/j.catena.2012.04.001 CARRARA A, 1995, ADV NAT TECHNOL HAZ, V5, P135 Clerici A, 2002, GEOMORPHOLOGY, V48, P349, DOI 10.1016/S0169-555X(02)00079-X Clerici A, 2006, ENVIRON GEOL, V50, P941, DOI 10.1007/s00254-006-0264-7 Constantin M, 2011, ENVIRON EARTH SCI, V63, P397, DOI 10.1007/s12665-010-0724-y Dai FC, 2001, ENVIRON GEOL, V40, P381, DOI 10.1007/s002540000163 Duman TY, 2006, ENVIRON GEOL, V51, P241, DOI 10.1007/s00254-006-0322-1 Eastman RJ, 2003, IDRISI KILIMANJARO G, P328 Ercanoglu M, 2002, ENVIRON GEOL, V41, P720, DOI 10.1007/s00254-001-0454-2 Ercanoglu M, 2008, B ENG GEOL ENVIRON, V67, P565, DOI 10.1007/s10064-008-0170-1 Ercanoglu M, 2004, NAT HAZARDS, V32, P1, DOI 10.1023/B:NHAZ.0000026786.85589.4a Ercanoglu M, 2004, ENG GEOL, V75, P229, DOI 10.1016/j.enggeo.2004.06.001 Erner A, 2010, LANDSLIDES, V7, P55 Falaschi F, 2009, NAT HAZARDS, V50, P551, DOI 10.1007/s11069-009-9356-5 Fernandez CI, 1999, EARTH SURF PROC LAND, V24, P537, DOI 10.1002/(SICI)1096-9837(199906)24:6<537::AID-ESP965>3.3.CO;2-Y Foumelis M, 2004, B GEOL SOC GREECE, VXXXVI, P904 Gokceoglu C, 1996, ENG GEOL, V44, P147, DOI 10.1016/S0013-7952(97)81260-4 Guzzetti F, 1999, GEOMORPHOLOGY, V31, P81 Hines J. W., 1997, FUZZY NEURAL APPROAC Hutchinson J N, 1995, P 6 INT S LANDSL CHR, P1805 Iranian Landslide Working Party (ILWP), 2007, IR LANDSL LIST FOR, P60 JUANG CH, 1992, J GEOTECH ENG-ASCE, V118, P475, DOI 10.1061/(ASCE)0733-9410(1992)118:3(475) Kanungo DP, 2005, P 2 IND INT C ART IN, P1222 Komac M, 2006, GEOMORPHOLOGY, V74, P17, DOI 10.1016/j.geomorph.2005.07.005 Lee S, 2005, INT J REMOTE SENS, V26, P1477, DOI 10.1080/01431160412331331012 Lee S, 2006, J EARTH SYST SCI, V115, P661, DOI 10.1007/s12040-006-0004-0 Lee S, 2007, LANDSLIDES, V4, P33, DOI 10.1007/s10346-006-0047-y Lee S, 2004, ENG GEOL, V71, P289, DOI 10.1016/S0013-7952(03)00142-X Lee S, 2001, ENVIRON GEOL, V40, P1095, DOI 10.1007/s002540100310 Lee S, 2006, ENVIRON GEOL, V50, P847, DOI 10.1007/s00254-006-0256-7 Lee S, 2009, AM GEOPH UN FALL M 2 Lee S, 2004, INT J REMOTE SENS, V25, P2037, DOI 10.1080/01431160310001618734 Malczweski J, 1999, GIS MULTICRITERIA DE, P392 MOORE ID, 1986, WATER RESOUR RES, V22, P1350, DOI 10.1029/WR022i008p01350 MOORE ID, 1991, HYDROL PROCESS, V5, P3, DOI 10.1002/hyp.3360050103 MOORE ID, 1992, J SOIL WATER CONSERV, V47, P423 Mowen X, 2003, J GEOTECH GEOENVIRON, V129, P1109 Nefeslioglu HA, 2008, ENG GEOL, V97, P171, DOI 10.1016/j.enggeo.2008.01.004 Nefeslioglu HA, 2008, GEOMORPHOLOGY, V94, P401, DOI 10.1016/j.geomorph.2006.10.036 Nefeslioglu HA, 2010, MATH PROBL ENG, DOI 10.1155/2010/901095 Nie HF, 2001, P 22 AS C REM SENS C, V1, P660 Ocakoglu F, 2002, GEOMORPHOLOGY, V42, P329, DOI 10.1016/S0169-555X(01)00094-0 Oh HJ, 2011, COMPUT GEOSCI-UK, V37, P1264, DOI 10.1016/j.cageo.2010.10.012 Pachauri AK, 1998, ENVIRON GEOL, V36, P325 Park NW, 2011, ENVIRON EARTH SCI, V62, P367, DOI 10.1007/s12665-010-0531-5 Pourghasemi H, 2013, GEOMAT NAT HAZ RISK, V4, P93, DOI 10.1080/19475705.2012.662915 Pourghasemi HR, 2008, THESIS TARBIAT MODAR Pourghasemi HR, 2013, ARAB J GEOSCI, V6, P2351, DOI 10.1007/s12517-012-0532-7 Pouydal CP, 2010, ENVIRON EARTH SCI, V61, P1049 Pradhan B, 2011, ENVIRON EARTH SCI, V63, P329, DOI 10.1007/s12665-010-0705-1 Pradhan B, 2010, ENVIRON MODELL SOFTW, V25, P747, DOI 10.1016/j.envsoft.2009.10.016 Pradhan B, 2009, INT J PHYS SCI, V4, P1 Pradhan B, 2010, ADV SPACE RES, V45, P1244, DOI 10.1016/j.asr.2010.01.006 Pradhan B, 2011, INT J REMOTE SENS, V32, P4075, DOI 10.1080/01431161.2010.484433 Pradhan B, 2010, J INDIAN SOC REMOT, V38, P301, DOI 10.1007/s12524-010-0020-z Pradhan B, 2006, ADV SPACE RES, V37, P698, DOI 10.1016/j.asr.2005.03.137 Pradhan B, 2010, COMPUT ENVIRON URBAN, V34, P216, DOI 10.1016/j.compenvurbsys.2009.12.004 Pradhan B, 2007, EARTH SCI FRONTIER, V14, P143, DOI DOI 10.1016/S1872-5791(08)60008-1 Pradhan B, 2010, ARAB J GEOSCI, V3, P319, DOI 10.1007/s12517-009-0089-2 Pradhan B, 2010, ENVIRON ENG GEOSCI, V16, P107 Pradhan B., 2009, APPL GEOMATICS, V1, P3 Pradhan B, 2011, ENVIRON ECOL STAT, V18, P471, DOI 10.1007/s10651-010-0147-7 Pradhan B., 2008, J APPL REMOTE SENS, V2, P1, DOI DOI 10.1117/12.821511 Pradhan B, 2010, ENVIRON EARTH SCI, V60, P1037, DOI 10.1007/s12665-009-0245-8 Pradhan B, 2010, IEEE T GEOSCI REMOTE, V48, P4164, DOI 10.1109/TGRS.2010.2050328

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Pradhan B, 2010, GEOMAT NAT HAZ RISK, V1, P199, DOI 10.1080/19475705.2010.498151 Pradhan B, 2010, PHOTOGRAMM FERNERKUN, P17, DOI 10.1127/1432-8364/2010/0037 Pradhan Biswajeet, 2010, Geo-spatial Information Science, V13, DOI 10.1007/s11806-010-0236-7 Mohan V. Ram, 2011, International Journal of Geomatics and Geosciences, V1 Saaty T. L, 1980, ANAL HIERARCHY PROCE SAATY TL, 1977, J MATH PSYCHOL, V15, P234, DOI 10.1016/0022-2496(77)90033-5 Saaty T. L., 1994, FUNDAMENTALS DECISIO Saaty TL, 2000, DECISION MAKING LEAD Saaty TL, 2001, MODELS METHODS CONCE Saha AK, 2005, LANDSLIDES, V2, P61, DOI 10.1007/s10346-004-0039-8 Saha AK, 2002, INT J REMOTE SENS, V23, P357, DOI 10.1080/01431160010014260 Sezer EA, 2011, EXPERT SYST APPL, V38, P8208, DOI 10.1016/j.eswa.2010.12.167 SWETS JA, 1988, SCIENCE, V240, P1285, DOI 10.1126/science.3287615 Bui DT, 2012, COMPUT GEOSCI-UK, V45, P199, DOI 10.1016/j.cageo.2011.10.031 Tunusluoglu MC, 2008, ENVIRON GEOL, V54, P9, DOI 10.1007/s00254-007-0788-5 Vahidnia MH, 2010, COMPUT GEOSCI-UK, V36, P1101, DOI 10.1016/j.cageo.2010.04.004 den Eeckhaut M, 2006, GEOMORPHOLOGY, V76, P392, DOI 10.1016/j.geomorph.2005.12.003 Van Westen CJ, 1990, 6 IAEG C BALK ROTT, V1, P265 Van Westen CJ, 1999, NAT HAZARDS, V20, P137, DOI 10.1023/A:1008036810401 Varnes D., 1978, LANDSLIDES ANAL CONT, P11 Varnes DJ, 1981, AAPG BULL, V12, P489 Voogd H, 1983, MULTICRITERIA EVALUA Wang HB, 2005, ENVIRON GEOL, V47, P956, DOI 10.1007/s00254-005-1225-2 Wilson J., 2000, TERRAIN ANAL PRINCIP Xu C, 2012, J EARTH SCI-CHINA, V23, P97, DOI 10.1007/s12583-012-0236-7 Yagi H, 2003, 42 ANN M JAP LANDSL, P209 Yalcin A, 2007, NAT HAZARDS, V41, P201, DOI 10.1007/s11069-006-9030-0 Yalcin A, 2008, CATENA, V72, P1, DOI 10.1016/j.catena.2007.01.003 Yao X, 2008, GEOMORPHOLOGY, V101, P572, DOI 10.1016/j.geomorph.2008.02.011 Yesilnacar E, 2005, ENG GEOL, V79, P251, DOI 10.1016/j.enggeo.2005.02.002 Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9 Yoshimatsu H, 2006, LANDSLIDES, V3, P149, DOI 10.1007/s10346-005-0031-y Youssef AM, 2009, NAT HAZARD EARTH SYS, V9, P751 Youssef AM, 2012, ENVIRON EARTH SCI, V65, P119, DOI 10.1007/s12665-011-1071-3 ZADEH LA, 1965, INFORM CONTROL, V8, P338, DOI 10.1016/S0019-9958(65)90241-X ZADEH LA, 1973, IEEE T SYST MAN CYB, VSMC3, P28, DOI 10.1109/TSMC.1973.5408575Cited Reference Count: 118 Abstract: The main goal of this study is to produce landslide susceptibility maps of a landslide-prone area (Haraz) in Iran by using both fuzzy logic and analytical hierarchy process (AHP) models. At first, landslide locations were identified by aerial photographs and field surveys, and a total of 78 landslides were mapped from various sources. Then, the landslide inventory was randomly split into a training dataset 70 % (55 landslides) for training the models and the remaining 30 % (23 landslides) was used for validation purpose. Twelve data layers, as the landslide conditioning factors, are exploited to detect the most susceptible areas. These factors are slope degree, aspect, plan curvature, altitude, lithology, land use, distance from rivers, distance from roads, distance from faults, stream power index, slope length, and topographic wetness index. Subsequently, landslide susceptibility maps were produced using fuzzy logic and AHP models. For verification, receiver operating characteristics curve and area under the curve approaches were used. The verification results showed that the fuzzy logic model (89.7 %) performed better than AHP (81.1 %) model for the study area. The produced susceptibility maps can be used for general land use planning and hazard mitigation purpose.Accession Number: WOS:000306589100034 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslide; Susceptibility mapping; Fuzzy logic; AHP; GIS; Haraz; Remote sensing; IranKeyWords Plus: REMOTE-SENSING DATA; ARTIFICIAL NEURAL-NETWORK; MULTIVARIATE STATISTICAL TECHNIQUES; WEIGHTED LINEAR COMBINATION; CONDITIONAL ANALYSIS METHOD; LOGISTIC-REGRESSION MODELS; SUPPORT VECTOR MACHINE; BLACK-SEA REGION; FREQUENCY RATIO; NW TURKEYAddresses: [Pradhan, Biswajeet] Univ Putra Malaysia UPM, Spatial & Numer Modeling Res Grp, Inst Adv Technol ITMA, Fac Engn, Serdang 43400, Selangor Darul, Malaysia. [Pourghasemi, Hamid Reza] Tarbiat Modares Univ TMU, Coll Nat Resources & Marine Sci, Dept Watershed Management Engn, Tehran, Iran. [Gokceoglu, Candan] Hacettepe Univ, Dept Geol Engn, Appl Geol Div, Fac Engn, Ankara, Turkey. Reprint Address: Pradhan, B (reprint author), Univ Putra Malaysia UPM, Spatial & Numer Modeling Res Grp, Inst Adv Technol ITMA, Fac Engn, Serdang 43400, Selangor Darul, Malaysia.E-mail Addresses: [email protected] Identifiers:

Author ResearcherID Number ORCID NumberGokceoglu, Candan E-3259-2013 0000-0003-4762-9933 Pradhan, Biswajeet E-8226-2010 0000-0001-9863-2054 Publisher: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences; Water ResourcesResearch Areas: Geology; Meteorology & Atmospheric Sciences; Water ResourcesIDS Number: 976MO ISSN: 0921-030X 29-char Source Abbrev.: NAT HAZARDS ISO Source Abbrev.: Nat. Hazards Source Item Page Count: 32 Record 2 of 58Title: An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm Author(s): Akgun, A (Akgun, A.); Sezer, EA (Sezer, E. A.); Nefeslioglu, HA (Nefeslioglu, H. A.); Gokceoglu, C (Gokceoglu, C.); Pradhan, B (Pradhan, B.) Source: COMPUTERS & GEOSCIENCES Volume: 38 Issue: 1 Pages: 23-34 DOI: 10.1016/j.cageo.2011.04.012 Published: JAN 2012 Times Cited in Web of Science Core Collection: 37 Total Times Cited: 39 Cited References: Akgun A, 2007, ENVIRON GEOL, V51, P1377, DOI 10.1007/s00254-006-0435-6 Akgun A, 2008, ENVIRON GEOL, V54, P1127, DOI 10.1007/s00254-007-0882-8 Akgun A, 2010, ENVIRON EARTH SCI, V61, P595, DOI 10.1007/s12665-009-0373-1 Alvarez GM, 1999, INT J ROCK MECH MIN, V36, P339 Alvarez Grima M, 2000, NEUROFUZZY MODELING Anbalagan R, 1996, ENG GEOL, V43, P237, DOI 10.1016/S0013-7952(96)00033-6 ArcGIS, 2008, ARCGIS VERSION 9 3 Arora MK, 2004, INT J REMOTE SENS, V25, P559, DOI 10.1080/0143116031000156819 Atkinson PM, 1998, COMPUT GEOSCI-UK, V24, P373, DOI 10.1016/S0098-3004(97)00117-9



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J., 1995, FUZZY LOGIC ENG APPL Saboya F, 2006, ENG GEOL, V86, P211, DOI 10.1016/j.enggeo.2006.05.001 Setnes M, 1998, IEEE T SYST MAN CY C, V28, P165, DOI 10.1109/5326.661100 Sezer EA, 2011, EXPERT SYST APPL, V38, P8208, DOI 10.1016/j.eswa.2010.12.167 Soeters R., 1996, LANDSLIDES INVESTIGA, V247, P129 Sonmez H, 2003, ENG APPL ARTIF INTEL, V16, P251, DOI 10.1016/S0952-1976(03)00002-2 Sonmez H, 2004, INT J ROCK MECH MIN, V41, P717, DOI 10.1016/j.ijrmms.2004.01.011 Tunusluoglu MC, 2008, ENVIRON GEOL, V54, P9, DOI 10.1007/s00254-007-0788-5 Turer D, 2008, ENVIRON GEOL, V55, P1001, DOI 10.1007/s00254-007-1049-3 Turrini MC, 1998, ENG GEOL, V50, P255, DOI 10.1016/S0013-7952(98)00022-2 Weier J, 2005, MEASURING VEGETATION Wilson J., 2000, TERRAIN ANAL PRINCIP WOOD EF, 1990, REV GEOPHYS, V28, P1, DOI 10.1029/RG028i001p00001 Yagiz S, 2010, EXPERT SYST APPL, V37, P2265, DOI 10.1016/j.eswa.2009.07.046 Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9 Yilmaz I, 2010, ENVIRON EARTH SCI, V60, P505, DOI 10.1007/s12665-009-0191-5 Yilmaz L, 2009, COMPUT GEOSCI, V35, P1125 Zinko U, 2005, ECOSYSTEMS, V8, P430, DOI 10.1007/s10021-003-0125-0 ZWEIG MH, 1993, CLIN CHEM, V39, P561Cited Reference Count: 85 Abstract: In this study, landslide susceptibility mapping using a completely expert opinion-based approach was applied for the Sinop (northern Turkey) region and its close vicinity. For this purpose, an easy-to-use program, "MamLand," was developed for the construction of a Mamdani fuzzy inference system and employed in MATLAB. Using this newly developed program, it is possible to construct a landslide susceptibility map based on expert opinion. In this study, seven conditioning parameters characterising topographical, geological, and environmental conditions were included in the FIS. A landslide inventory dataset including 351 landslide locations was obtained for the study area. After completing the data production stage of the study, the data were processed using a soft computing approach, i.e., a Mamdani-type fuzzy inference system. In this system, only landslide conditioning data were assessed, and landslide inventory data were not included in the assessment approach. Thus, a file depicting the landslide susceptibility degrees for the study area was produced using the Mamdani FIS. These degrees were then exported into a GIS environment, and a landslide susceptibility map was produced and assessed in point of statistical interpretation. For this purpose, the obtained landslide susceptibility map and the landslide inventory data were compared, and an area under curve (AUC) obtained from receiver operating characteristics (ROC) assessment was carried out. From this assessment, the AUG value was found to be 0.855, indicating that this landslide susceptibility map, which was produced in a data-independent manner, was successful. (C) 2011 Elsevier Ltd. All rights reserved.Accession Number: WOS:000298524100003 Language: EnglishDocument Type: ArticleAuthor Keywords: Mamdani fuzzy inference system; Landslide susceptibility; Geographical Information Systems (GIS); Sinop (Turkey)



KeyWords Plus: ARTIFICIAL NEURAL-NETWORKS; UNIAXIAL COMPRESSIVE STRENGTH; BLACK-SEA REGION; WEIGHTED JOINT DENSITY; REMOTE-SENSING DATA; LOGISTIC-REGRESSION; NW TURKEY; CONDITIONAL-PROBABILITY; SAMPLING STRATEGIES; AREAAddresses: [Gokceoglu, C.] Hacettepe Univ, Geol Engn Dept, TR-06800 Ankara, Turkey. [Akgun, A.] Middle E Tech Univ, Min Engn Dept, TR-06531 Ankara, Turkey. [Sezer, E. A.] Hacettepe Univ, Dept Comp Engn, TR-06800 Ankara, Turkey. [Nefeslioglu, H. A.] Gen Directorate Mineral Res & Explorat, Dept Geol Res, TR-06520 Ankara, Turkey. [Pradhan, B.] Univ Putra Malaysia, Inst Adv Technol, Serdang 43400, Malaysia. [Pradhan, B.] Univ Putra Malaysia, Spatial & Numer Modelling Lab, Serdang 43400, Malaysia. Reprint Address: Gokceoglu, C (reprint author), Hacettepe Univ, Geol Engn Dept, TR-06800 Ankara, Turkey.E-mail Addresses: [email protected] Identifiers:

Author ResearcherID Number ORCID NumberGokceoglu, Candan E-3259-2013 0000-0003-4762-9933 Pradhan, Biswajeet E-8226-2010 0000-0001-9863-2054 Sezer, Ebru Akcapinar H-5566-2011 0000-0002-9287-2679 Jingwei Li, Jingwei E-2396-2014 Publisher: PERGAMON-ELSEVIER SCIENCE LTD Publisher Address: THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND Web of Science Categories: Computer Science, Interdisciplinary Applications; Geosciences, MultidisciplinaryResearch Areas: Computer Science; GeologyIDS Number: 868LF ISSN: 0098-3004 29-char Source Abbrev.: COMPUT GEOSCI-UK ISO Source Abbrev.: Comput. Geosci. Source Item Page Count: 12 Record 3 of 58Title: Application of an evidential belief function model in landslide susceptibility mapping Author(s): Althuwaynee, OF (Althuwaynee, Omar F.); Pradhan, B (Pradhan, Biswajeet); Lee, S (Lee, Saro)Source: COMPUTERS & GEOSCIENCES Volume: 44 Pages: 120-135 DOI: 10.1016/j.cageo.2012.03.003 Published: JUL 2012 Times Cited in Web of Science Core Collection: 34 Total Times Cited: 34 Cited References: Akgun A, 2007, ENVIRON GEOL, V51, P1377, DOI 10.1007/s00254-006-0435-6 Akgun A, 2008, ENVIRON GEOL, V54, P1127, DOI 10.1007/s00254-007-0882-8 Akgun A., 2011, ENV MONITORING ASSES Akgun A, 2012, LANDSLIDES, V9, P93, DOI 10.1007/s10346-011-0283-7 Akgun A, 2010, ENVIRON EARTH SCI, V61, P595, DOI 10.1007/s12665-009-0373-1 Akgun A., 2011, COMPUT GEOSCI, V38, P23 Alansi A. W., 2009, EUR J SCI RES, V31, P88 Alexander DE, 2008, GEOMORPHOLOGY, V94, P261, DOI 10.1016/j.geomorph.2006.09.022 An P., 1992, P INT GEOSC REM SENS, P34, DOI 10.1109/IGARSS.1992.576620 An P., 1994, NONRENEWABLE RESOURC, V3, P60, DOI DOI 10.1007/BF02261716 Anderson MG, 2010, ENVIRON MANAGE, V45, P807, DOI 10.1007/s00267-010-9431-4 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Bai SB, 2011, ENVIRON EARTH SCI, V62, P139, DOI 10.1007/s12665-010-0509-3 Ballabio C., 2012, MATH GEOSCI, P1 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Brenning A, 2005, NAT HAZARD EARTH SYS, V5, P853 Bui DT, 2011, NAT HAZARDS, V59, P1413, DOI 10.1007/s11069-011-9844-2 Caniani D, 2008, NAT HAZARDS, V45, P55, DOI 10.1007/s11069-007-9169-3 Carranza EJM, 2009, ORE GEOL REV, V35, P383, DOI 10.1016/j.oregeorev.2009.01.001 Carranza EJM, 2008, ORE GEOL REV, V33, P536, DOI 10.1016/j.oregeorev.2007.07.001 Carranza E.J.M., 2005, NATURAL RESOURCES RE, V14, P47, DOI DOI 10.1007/S11053-005-4678-9 Carranza E.J.M., 2002, NATURAL RESOURCES RE, V11, P45, DOI 10.1023/A:1014287720379 Carranza E.J.M., 2010, ORE GEOLOGY REV Carranza E.J.M., 2002, ITC INT I GEOINFORMA Chauhan S, 2010, LANDSLIDES, V7, P411, DOI 10.1007/s10346-010-0202-3 Cheng S, 2012, ECOL INDIC, V15, P263, DOI 10.1016/j.ecolind.2011.09.028 Chung CJF, 2003, NAT HAZARDS, V30, P451, DOI 10.1023/B:NHAZ.0000007172.62651.2b Dahal RK, 2008, ENVIRON GEOL, V54, P311, DOI 10.1007/s00254-007-0818-3 Dai F. C., 2004, B ENG GEOL ENVIRON, V63, P315, DOI DOI 10.1007/S10064-004-0245-6 Dempster A., 1968, J ROY STAT SOC, V30, P205 DEMPSTER AP, 1967, ANN MATH STAT, V38, P325, DOI 10.1214/aoms/1177698950 Ercanoglu M, 2004, ENG GEOL, V75, P229, DOI 10.1016/j.enggeo.2004.06.001 Ermini L, 2005, GEOMORPHOLOGY, V66, P327, DOI 10.1016/j.geomorph.2004.09.025 Evett SR, 2006, VADOSE ZONE J, V5, P894, DOI 10.2136/vzj2005.0149 Gokceoglu C, 2005, ENG GEOL, V81, P65, DOI 10.1016/j.enggeo.2005.07.011 Gomez H, 2005, ENG GEOL, V78, P11, DOI 10.1016/j.enggeo.2004.10.004 Gorsevski PV, 2006, GEOMORPHOLOGY, V80, P178, DOI 10.1016/j.geomorph.2006.02.011 Gorsevski PV, 2010, COMPUT GEOSCI-UK, V36, P1005, DOI 10.1016/j.cageo.2010.03.001 Gray DH, 1982, BIOTECHNICAL SLOPE P Guzzetti F, 1999, GEOMORPHOLOGY, V31, P181, DOI 10.1016/S0169-555X(99)00078-1 Jenness J. S., 2011, DEM SURFACE TOOLS V Kanungo DP, 2006, ENG GEOL, V85, P347, DOI 10.1016/j.enggeo.2006.03.004 Lai S.H., 2008, I ENG MALAYSIA, V69, P13 Lee S, 2007, LANDSLIDES, V4, P327, DOI 10.1007/s10346-007-0088-x Lee S, 2007, LANDSLIDES, V4, P33, DOI 10.1007/s10346-006-0047-y Lee S, 2004, ENG GEOL, V71, P289, DOI 10.1016/S0013-7952(03)00142-X Lee S, 2009, AM GEOPH UN FALL M 2 Lee S, 2003, ENVIRON GEOL, V44, P820, DOI 10.1007/s00254-003-0825-y Malaysian Meteorological Department Services Survey MMD, MAL MET DEP SERV SUR MOON WM, 1990, IEEE T GEOSCI REMOTE, V28, P711 Nefeslioglu HA, 2008, ENG GEOL, V97, P171, DOI 10.1016/j.enggeo.2008.01.004 Nefeslioglu HA, 2010, MATH PROBL ENG, DOI 10.1155/2010/901095 Noor M.J.M.M., 1988, STRENGTH DURABILITY, V28, P735 Oh HJ, 2009, ENVIRON GEOL, V57, P641, DOI 10.1007/s00254-008-1342-9 Oh HJ, 2011, COMPUT GEOSCI-UK, V37, P1264, DOI 10.1016/j.cageo.2010.10.012 PARK NW, 2010, ENVIRON EARTH SCI, V62, P367, DOI DOI 10.1007/S12665-010-0531-5 Poli S., 2007, NAT RESOUR RES, V16, P121, DOI DOI 10.1007/S11053-007-9043-8



Pradhan B, 2011, ENVIRON EARTH SCI, V63, P329, DOI 10.1007/s12665-010-0705-1 Pradhan B, 2010, ENVIRON MODELL SOFTW, V25, P747, DOI 10.1016/j.envsoft.2009.10.016 Pradhan B, 2010, INT J COMPUT INT SYS, V3, P370 Pradhan B, 2010, J INDIAN SOC REMOT, V38, P301, DOI 10.1007/s12524-010-0020-z Pradhan B, 2006, ADV SPACE RES, V37, P698, DOI 10.1016/j.asr.2005.03.137 Pradhan B, 2010, COMPUT ENVIRON URBAN, V34, P216, DOI 10.1016/j.compenvurbsys.2009.12.004 Pradhan B, 2010, ARAB J GEOSCI, V3, P319, DOI 10.1007/s12517-009-0089-2 Pradhan B, 2010, LANDSLIDES, V7, P13, DOI 10.1007/s10346-009-0183-2 Pradhan B, 2010, ENVIRON ENG GEOSCI, V16, P107 Pradhan B, 2011, ENVIRON ECOL STAT, V18, P471, DOI 10.1007/s10651-010-0147-7 Pradhan B, 2010, ENVIRON EARTH SCI, V60, P1037, DOI 10.1007/s12665-009-0245-8 Pradhan B, 2010, DISASTER ADV, V3, P26 Pradhan B, 2010, IEEE T GEOSCI REMOTE, V48, P4164, DOI 10.1109/TGRS.2010.2050328 Pradhan B., 2010, FERNERKUNDUNG GEOINF, V1, P17 Pradhan Biswajeet, 2010, Geo-spatial Information Science, V13, DOI 10.1007/s11806-010-0236-7 Scott W.B., 1921, INTRO GEOLOGY Sentz K., 2002, COMBINATION EVIDENCE Sezer EA, 2011, EXPERT SYST APPL, V38, P8208, DOI 10.1016/j.eswa.2010.12.167 Shafer G, 1976, MATH THEORY EVIDENCE Sui D.Z., 2008, REMOTE SENSING BASED Sujatha E., 2012, J INDIAN SOC REMOTE Tangestani MH, 2004, AUST J EARTH SCI, V51, P439, DOI 10.1111/j.1400-0952.2004.01068.x Tangestani MH, 2009, J ASIAN EARTH SCI, V35, P66, DOI 10.1016/j.jseaes.2009.01.002 Tien Bui D., 2011, COMPUTERS GEOSCIENCE Vahidnia MH, 2010, COMPUT GEOSCI-UK, V36, P1101, DOI 10.1016/j.cageo.2010.04.004 van Westen CJ, 2008, ENG GEOL, V102, P112, DOI 10.1016/j.enggeo.2008.03.010 Van Westen CJ, 1999, NAT HAZARDS, V20, P137, DOI 10.1023/A:1008036810401 WALLEY P, 1987, ANN STAT, V15, P1439, DOI 10.1214/aos/1176350603 Wang YM, 2008, EXPERT SYST APPL, V34, P3099, DOI 10.1016/j.eswa.2007.06.026 Wilson J., 2000, TERRAIN ANAL PRINCIP WOOD EF, 1990, REV GEOPHYS, V28, P1, DOI 10.1029/RG028i001p00001 Wright DF, 1996, GEOLOGICAL SURVEY CA, V426, P339 Xie MW, 2004, ENVIRON GEOL, V46, P840, DOI 10.1007/s00254-004-1069-1 Xu C, 2012, J EARTH SCI-CHINA, V23, P97, DOI 10.1007/s12583-012-0236-7 Yao X, 2008, GEOMORPHOLOGY, V101, P572, DOI 10.1016/j.geomorph.2008.02.011 Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9 Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2010, ENVIRON EARTH SCI, V60, P505, DOI 10.1007/s12665-009-0191-5 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P297, DOI 10.1007/s10064-009-0185-2Cited Reference Count: 96 Abstract: The objective of this paper is to exploit the potential application of an evidential belief function model to landslide susceptibility mapping at Kuala Lumpur city and surrounding areas using geographic information system (GIS). At first, a landslide inventory map was prepared using aerial photographs, high resolution satellite images and field survey. A total 220 landslides were mapped and an inventory map was prepared. Then the landslide inventory was randomly split into a testing dataset 70% (153 landslides) and remaining 30% (67 landslides) data was used for validation purpose. Fourteen landslide conditioning factors such as slope, aspect, curvature, altitude, surface roughness, lithology, distance from faults, ndvi (normalized difference vegetation index), land cover, distance from drainage, distance from road. spi (stream power index), soil type, precipitation, were used as thematic layers in the analysis. The Dempster-Shafer theory of evidence model was applied to prepare the landslide susceptibility maps. The validation of the resultant susceptibility maps were performed using receiver operating characteristics (ROC) and area under the curve (AUC). The validation results show that the area under the curve for the evidential belief function (the belief map) model is 0.82 (82%) with prediction accuracy 0.75 (75%). The results of this study indicated that the EBF model can be effectively used in preparation of landslide susceptibility maps. (C) 2012 Elsevier Ltd. All rights reserved.Accession Number: WOS:000306034100014 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslide susceptibility; EBF model; GIS; Malaysia; Remote sensing; Kuala LumpurKeyWords Plus: ARTIFICIAL NEURAL-NETWORKS; SPATIAL PREDICTION MODELS; SUPPORT VECTOR MACHINE; LOGISTIC-REGRESSION; FREQUENCY RATIO; CONDITIONAL-PROBABILITY; SAMPLING STRATEGIES; CATCHMENT-AREA; FUZZY-LOGIC; GISAddresses: [Althuwaynee, Omar F.; Pradhan, Biswajeet] Univ Putra Malaysia, Dept Civil Engn, Spatial & Numer Modelling Lab, Fac Engn, Serdang 43400, Selangor Darul, Malaysia. [Lee, Saro] Korea Inst Geosci & Mineral Resources KIGAM, Taejon 305350, South Korea. Reprint Address: Pradhan, B (reprint author), Univ Putra Malaysia, Dept Civil Engn, Spatial & Numer Modelling Lab, Fac Engn, Serdang 43400, Selangor Darul, Malaysia.E-mail Addresses: [email protected] Identifiers:

Author ResearcherID Number ORCID NumberLee, Saro H-6003-2012 0000-0003-0409-8263 Pradhan, Biswajeet E-8226-2010 0000-0001-9863-2054 Publisher: PERGAMON-ELSEVIER SCIENCE LTD Publisher Address: THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND Web of Science Categories: Computer Science, Interdisciplinary Applications; Geosciences, MultidisciplinaryResearch Areas: Computer Science; GeologyIDS Number: 969CU ISSN: 0098-3004 29-char Source Abbrev.: COMPUT GEOSCI-UK ISO Source Abbrev.: Comput. Geosci. Source Item Page Count: 16

Funding:

Funding Agency Grant NumberAlexander von Humboldt (AvH) foundation, Germany

Authors would like to thank two anonymous reviewers and Isik Yilmaz for their careful review of the original manuscript and their valuable comments. The authors would also like to thank the Malaysian Remote Sensing Agency (ARSM), Dept. of Mapping (JUPEM), Malaysian Meteorological Department (MMD), Dept. of Mineral & Geosciences (JMG) for providing various datasets used in this analysis. Financial aid received from Alexander von Humboldt (AvH) foundation, Germany is greatly appreciated.Record 4 of 58Title: Landslide susceptibility mapping using index of entropy and conditional probability models in GIS: Safarood Basin, Iran Author(s): Pourghasemi, HR (Pourghasemi, Hamid Reza); Mohammady, M (Mohammady, Majid); Pradhan, B (Pradhan, Biswajeet) Source: CATENA Volume: 97 Pages: 71-84 DOI: 10.1016/j.catena.2012.05.005 Published: OCT 2012 Times Cited in Web of Science Core Collection: 27



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Author ResearcherID Number ORCID NumberPradhan, Biswajeet E-8226-2010 0000-0001-9863-2054 Publisher: ELSEVIER SCIENCE BV Publisher Address: PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS Web of Science Categories: Geosciences, Multidisciplinary; Soil Science; Water ResourcesResearch Areas: Geology; Agriculture; Water ResourcesIDS Number: 981RV ISSN: 0341-8162 29-char Source Abbrev.: CATENA ISO Source Abbrev.: Catena Source Item Page Count: 14 Record 5 of 58Title: Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling-Narayanghat road section in Nepal Himalaya Author(s): Devkota, KC (Devkota, Krishna Chandra); Regmi, AD (Regmi, Amar Deep); Pourghasemi, HR (Pourghasemi, Hamid Reza); Yoshida, K (Yoshida, Kohki); Pradhan, B (Pradhan, Biswajeet); Ryu, IC (Ryu, In Chang); Dhital, MR (Dhital, Megh Raj); Althuwaynee, OF (Althuwaynee, Omar F.)Source: NATURAL HAZARDS Volume: 65 Issue: 1 Pages: 135-165 DOI: 10.1007/s11069-012-0347-6 Published: JAN 2013 Times Cited in Web of Science Core Collection: 23 Total Times Cited: 23 Cited References: Adhikari TL, 2009, INT SEM HAZ MAN SUST Ahmad R, 2010, INT GEOINF RES DEV J, V1 Akgun A, 2008, ENVIRON GEOL, V54, P1127, DOI 10.1007/s00254-007-0882-8 Akgun A, 2012, ENVIRON MONIT ASSESS, V184, P5453, DOI 10.1007/s10661-011-2352-8 Akgun A, 2012, COMPUT GEOSCI-UK, V38, P23, DOI 10.1016/j.cageo.2011.04.012 Aleotti P, 1999, B ENG ENV, V58, P21, DOI DOI 10.1007/S100640050066 Althuwaynee OF, 2012, COMPUT GEOSCI-UK, V44, P120, DOI 10.1016/j.cageo.2012.03.003 Atkinson PM, 1998, COMPUT GEOSCI-UK, V24, P373, DOI 10.1016/S0098-3004(97)00117-9 Ayalew L, 2004, LANDSLIDES, V1, P73, DOI 10.1007/s10346-003-0006-9 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Bednarik M, 2012, NAT HAZARDS, V64, P547, DOI 10.1007/s11069-012-0257-7 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Bonham-Carter G.F., 1991, GEOGRAPHICAL INFORMA, V2, P171 Brabb E.E., 1984, P 4 INT S LANDSL TOR, V1, P307 Brenning A, 2005, NAT HAZARD EARTH SYS, V5, P853 BRUNSDEN D., 1975, Q J ENG GEOL, V8, P227, DOI DOI 10.1144/GSL.QJEG.1975.008.04.01 Bui DT, 2012, CATENA, V96, P28, DOI 10.1016/j.catena.2012.04.001 Bui DT, 2012, GEOMORPHOLOGY, V171, P12, DOI 10.1016/j.geomorph.2012.04.023 Can T, 2005, GEOMORPHOLOGY, V72, P250, DOI 10.1016/j.geomorph.2005.05.011 Choi J, 2012, ENG GEOL, V124, P12, DOI 10.1016/j.enggeo.2011.09.011 Chung C. J. F., 2005, LANDSLIDE HAZARD RIS, P139 Chung CJF, 2003, NAT HAZARDS, V30, P451, DOI 10.1023/B:NHAZ.0000007172.62651.2b Chung CJF, 1999, PHOTOGRAMM ENG REM S, V65, P1389 Constantin M, 2011, ENVIRON EARTH SCI, V63, P397, DOI 10.1007/s12665-010-0724-y Dahal RK, 2008, GEOMORPHOLOGY, V102, P496, DOI 10.1016/j.geomorph.2008.05.041 Dahal RK, 2012, GEOMAT NAT HAZ RISK, V3, P161, DOI 10.1080/19475705.2011.629007 Dahal RK, 2008, GEOMORPHOLOGY, V100, P429, DOI 10.1016/j.geomorph.2008.01.014 Deoja B, 1991, ICIMOD KATHM Dhakal AS, 2000, PHOTOGRAMM ENG REM S, V66, P981 Dhital MR, 2000, J NEPAL GEOL SOC, V22, P533 Dhital MR, 2006, J NEPAL GEOL SOC, V31, P59



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Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2010, ENVIRON EARTH SCI, V60, P505, DOI 10.1007/s12665-009-0191-5 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P297, DOI 10.1007/s10064-009-0185-2 Zare M, 2013, ARAB J GEOSCI, V6, P2873, DOI 10.1007/s12517-012-0610-xCited Reference Count: 128 Abstract: Landslide susceptibility maps are vital for disaster management and for planning development activities in the mountainous country like Nepal. In the present study, landslide susceptibility assessment of Mugling-Narayanghat road and its surrounding area is made using bivariate (certainty factor and index of entropy) and multivariate (logistic regression) models. At first, a landslide inventory map was prepared using earlier reports and aerial photographs as well as by carrying out field survey. As a result, 321 landslides were mapped and out of which 241 (75 %) were randomly selected for building landslide susceptibility models, while the remaining 80 (25 %) were used for validating the models. The effectiveness of landslide susceptibility assessment using GIS and statistics is based on appropriate selection of the factors which play a dominant role in slope stability. In this case study, the following landslide conditioning factors were evaluated: slope gradient; slope aspect; altitude; plan curvature; lithology; land use; distance from faults, rivers and roads; topographic wetness index; stream power index; and sediment transport index. These factors were prepared from topographic map, drainage map, road map, and the geological map. Finally, the validation of landslide susceptibility map was carried out using receiver operating characteristic (ROC) curves. The ROC plot estimation results showed that the susceptibility map using index of entropy model with AUC value of 0.9016 has highest prediction accuracy of 90.16 %. Similarly, the susceptibility maps produced using logistic regression model and certainty factor model showed 86.29 and 83.57 % of prediction accuracy, respectively. Furthermore, the ROC plot showed that the success rate of all the three models performed more than 80 % accuracy (i.e. 89.15 % for IOE model, 89.10 % for LR model and 87.21 % for CF model). Hence, it is concluded that all the models employed in this study showed reasonably good accuracy in predicting the landslide susceptibility of Mugling-Narayanghat road section. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose.Accession Number: WOS:000312087100009 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslides; Susceptibility; Index of entropy; Certainty factor; Logistic regression; Geographic information systems (GIS); Remote sensing; NepalKeyWords Plus: ARTIFICIAL NEURAL-NETWORK; WEIGHTS-OF-EVIDENCE; SPATIAL PREDICTION MODELS; FREQUENCY RATIO; FUZZY-LOGIC; NW TURKEY; CONDITIONAL-PROBABILITY; SAMPLING STRATEGIES; LINEAR COMBINATION; LIKELIHOOD RATIOAddresses: [Pradhan, Biswajeet; Althuwaynee, Omar F.] Univ Putra Malaysia, Fac Engn, GIS RC, Serdang 43400, Selangor Darul, Malaysia. [Devkota, Krishna Chandra; Ryu, In Chang] Kyungpook Natl Univ, Dept Geol, Taegu 702701, South Korea. [Devkota, Krishna Chandra] Natl Disaster Management Inst, Minist Publ Adm & Secur, Seoul 121719, South Korea. [Regmi, Amar Deep; Yoshida, Kohki] Shinshu Univ, Fac Sci, Dept Geol, Matsumoto, Nagano 3908621, Japan. [Pourghasemi, Hamid Reza] TMU, Coll Nat Resources & Marine Sci, Tehran, Iran. [Dhital, Megh Raj] Tribhuvan Univ, Cent Dept Geol, Kathmandu, Nepal. Reprint Address: Pradhan, B (reprint author), Univ Putra Malaysia, Fac Engn, GIS RC, Serdang 43400, Selangor Darul, Malaysia.E-mail Addresses: [email protected] Identifiers:

Author ResearcherID Number ORCID NumberPradhan, Biswajeet E-8226-2010 0000-0001-9863-2054 Publisher: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences; Water ResourcesResearch Areas: Geology; Meteorology & Atmospheric Sciences; Water ResourcesIDS Number: 050XC ISSN: 0921-030X 29-char Source Abbrev.: NAT HAZARDS ISO Source Abbrev.: Nat. Hazards Source Item Page Count: 31

Funding:

Funding Agency Grant NumberMEXT (Ministry of Education, Culture, Sports, Science and Technology, Japan) BK21 Energy Resources and Environmental Geology Team, Kyungpook National University, Republic of Korea

The authors are thankful to anonymous reviewers for their valuable comments which were very useful in bringing the manuscript into its present form. The authors also express their gratitude to MEXT (Ministry of Education, Culture, Sports, Science and Technology, Japan) for funding for the present study. Mr. Binod Regmi, Mr. Ishan Basyal and Miss. Shristi Bhusal are sincerely acknowledged for their great help during the field work and in writing this manuscript. This research was supported by the BK21 and the Energy Resources and Environmental Geology Team, Kyungpook National University, Republic of Korea.

Record 6 of 58Title: Landslide susceptibility assessment using the bivariate statistical analysis and the index of entropy in the Sibiciu Basin (Romania) Author(s): Constantin, M (Constantin, Mihaela); Bednarik, M (Bednarik, Martin); Jurchescu, MC (Jurchescu, Marta C.); Vlaicu, M (Vlaicu, Marius) Source: ENVIRONMENTAL EARTH SCIENCES Volume: 63 Issue: 2 Pages: 397-406 DOI: 10.1007/s12665-010-0724-y Published: MAY 2011 Times Cited in Web of Science Core Collection: 23 Total Times Cited: 23 Cited References: BALTEANU D, 1983, EXPT TEREN GEOMORFOL, P157 BALTEANU D, 1994, GEOMORPHOLOGICAL HAZ, P24 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 BEDNARIK M, 2007, THESIS BRATISLAVA, P130 BOGDAN O, 1977, SCGGG GEOGR, V24, P31 BOGDAN O, 1999, RISCURILE CLIMATICE, P280 Brabb E.E., 1985, P 4 INT C FIELD WORK, P17 CARRARA A, 1995, GEOGRAPHICAL INFORM, P35 CARRARA A, 1991, EARTH SURF PROCESSES, V16, P427, DOI 10.1002/esp.3290160505 CIOACA A, 1993, STUDII CERCETARI GEO, V40, P43 CLERICI A, 2009, NAT HAZARDS, DOI DOI 10.1007/SL1069-009-9349-4 Clerici A, 2006, ENVIRON GEOL, V50, P941, DOI 10.1007/s00254-006-0264-7 CONSTANTIN M, 2006, PROGNOZA ALUNECARILO, P99 Constantin M., 2006, CIVIL ENG J, V48, P52 Constantin M., 2005, J JPN SOC EROSION CO, V58, P59 Constantin M., 2008, P INT C MAN LANDSL H, P510 GLADE T, 2001, LANDSLIDE HAZARD ASS, P153 Guzzetti F, 1999, GEOMORPHOLOGY, V31, P181, DOI 10.1016/S0169-555X(99)00078-1 Guzzetti F, 2006, GEOMORPHOLOGY, V81, P166, DOI 10.1016/j.geomorph.2006.04.007 Ielenicz M., 1999, T JAPANESE GEOMORPHO, V20, P287 IELENICZ M, 1984, MUNTII CIUCAS BUZAU, P146 Moreiras SM, 2005, GEOMORPHOLOGY, V66, P345, DOI 10.1016/j.genmorph.2004.09.019 Paudits P, 2002, P 1 EUR C LANDSL SWE, P437 Soeters R., 1996, LANDSLIDES INVESTIGA, V247, P129 SORRISOVALVO M, 2002, LANDSLIDES INVENTORY



Van Westen C.J., 2004, LANDSLIDES EVALUATIO, P39 Varnes DJ, 1984, LANDSLIDE HAZARD ZON, P63 Vlcko J, 1980, MINERALIA SLOVACA, V12, P275Cited Reference Count: 28 Abstract: The Sibiciu Basin is located in Romania between the Buzu Mountains and the Buzau Subcarpathians (Curvature Carpathians and Subcarpathians). The geology of the basin consists of Paleogene flysch deposits represented by an alternation of sandstones, marls, clays and schists and Neogene deposits represented by marls, clays and sands. The area is affected by different types of landslides (shallow, medium-deep and deep-seated failures). In Romania, in the last decades, direct and indirect methods have been applied for landslide susceptibility assessment. The most utilized before 2000 were based on qualitative approaches. This study evaluates the landslide susceptibility in the Sibiciu Basin using a bivariate statistical analysis and an index of entropy. A landslide inventory map was prepared, and a susceptibility estimate was assessed based on the following parameters which influence the landslide occurrence: slope angle, slope aspect, curvature, lithology and land use. The landslide susceptibility map was divided into five classes showing very low to very high landslide susceptibility areas.Accession Number: WOS:000289560900018 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslide susceptibility; Bivariate statistical analysis; Index of entropy; Sibiciu Basin; Buzau Mountains; RomaniaKeyWords Plus: HAZARD; VALLEY; MODELSAddresses: [Constantin, Mihaela; Jurchescu, Marta C.; Vlaicu, Marius] Acad Romana, Inst Geog, Bucharest 023993 20, Romania. [Bednarik, Martin] Comenius Univ, Dept Engn Geol, Bratislava 84215, Slovakia. Reprint Address: Constantin, M (reprint author), Acad Romana, Inst Geog, Str D Racovita 12, Bucharest 023993 20, Romania.E-mail Addresses: [email protected]: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Environmental Sciences; Geosciences, Multidisciplinary; Water ResourcesResearch Areas: Environmental Sciences & Ecology; Geology; Water ResourcesIDS Number: 750PQ ISSN: 1866-6280 29-char Source Abbrev.: ENVIRON EARTH SCI ISO Source Abbrev.: Environ. Earth Sci. Source Item Page Count: 10

Funding:

Funding Agency Grant NumberNational University Research Council of Romania (CNCSIS) PNII-IDEI_367

The present study was supported by the Ministry of Education and Research through the grant in aid PNII-IDEI_367 (2007-2010) funded through The National University Research Council of Romania (CNCSIS). The kind cooperation with Department of Engineering Geology, Comenius University, Bratislava, is fully appreciated.

Record 7 of 58Title: Landslide susceptibility mapping at Golestan Province, Iran: A comparison between frequency ratio, Dempster-Shafer, and weights-of-evidence models Author(s): Mohammady, M (Mohammady, Majid); Pourghasemi, HR (Pourghasemi, Hamid Reza); Pradhan, B (Pradhan, Biswajeet)Source: JOURNAL OF ASIAN EARTH SCIENCES Volume: 61 Special Issue: SI Pages: 221-236 DOI: 10.1016/j.jseaes.2012.10.005 Published: NOV 15 2012 Times Cited in Web of Science Core Collection: 18 Total Times Cited: 18 Cited References: Akgun A, 2007, ENVIRON GEOL, V51, P1377, DOI 10.1007/s00254-006-0435-6 Akgun A, 2008, ENVIRON GEOL, V54, P1127, DOI 10.1007/s00254-007-0882-8 Akgun A, 2012, COMPUT GEOSCI-UK, V38, P23, DOI 10.1016/j.cageo.2011.04.012 Akgun A., 2011, ENV MONITORING ASSES Akgun A, 2010, ENVIRON EARTH SCI, V61, P595, DOI 10.1007/s12665-009-0373-1 Althuwaynee OF, 2012, COMPUT GEOSCI-UK, V44, P120, DOI 10.1016/j.cageo.2012.03.003 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Bai S, 2010, ENVIRON EARTH SCI, V62, P139 Bednarik M., 2012, NATURAL HAZARDS Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Bonham-Carter G.F., 1994, COMPUTER METHODS GEO, V13, P398 Bonham-Carter G.F., 1988, AM SOC PHOTOGRAMMETR Bui DT, 2012, CATENA, V96, P28, DOI 10.1016/j.catena.2012.04.001 Bui D.T., 2011, COMPUTERS G IN PRESS Bui D.T., 2012, GEOMORPHOLOGY Bui DT, 2011, NAT HAZARDS, V59, P1413, DOI 10.1007/s11069-011-9844-2 Can T, 2005, GEOMORPHOLOGY, V72, P250, DOI 10.1016/j.geomorph.2005.05.011 Caniani D, 2008, NAT HAZARDS, V45, P55, DOI 10.1007/s11069-007-9169-3 CARRARA A, 1995, ADV NAT TECHNOL HAZ, V5, P135 Cervi F, 2010, LANDSLIDES, V7, P433, DOI 10.1007/s10346-010-0207-y Chauhan S, 2010, INT J APPL EARTH OBS, V12, P340, DOI 10.1016/j.jag.2010.04.006 Chung CJF, 2003, NAT HAZARDS, V30, P451, DOI 10.1023/B:NHAZ.0000007172.62651.2b DEMPSTER AP, 1967, ANN MATH STAT, V38, P325, DOI 10.1214/aoms/1177698950 Dimri S, 2007, LANDSLIDES, V4, P101 Eemini L., 2005, GEOMORPHOLOGY, V66, P327 Glade T, 1998, ENVIRON GEOL, V35, P160 Goesevski P.V., 2006, T GIS, V10, P395 Goesevski P.V., 2010, COMPUT GEOSCI, V36, P1005 Golstan Regional Water Co, 2007, GOL PROV MET INF REP Hengl T, 2003, DIGITAL TERRAIN ANAL Kanungo D, 2008, LANDSLIDES, V5, P407, DOI 10.1007/s10346-008-0134-3 Komac M, 2006, GEOMORPHOLOGY, V74, P17, DOI 10.1016/j.geomorph.2005.07.005 Lee S, 2006, NAT HAZARD EARTH SYS, V6, P687 Lee S, 2006, J EARTH SYST SCI, V115, P661, DOI 10.1007/s12040-006-0004-0 Lee S, 2006, MATH GEOL, V38, P199, DOI 10.1007/s11004-005-9012-x Lee S, 2004, INT J GEOGR INF SCI, V18, P789, DOI 10.1080/13658810410001702003 Lee S, 2007, LANDSLIDES, V4, P33, DOI 10.1007/s10346-006-0047-y Lee S, 2005, ENVIRON GEOL, V48, P778, DOI 10.1007/s00254-005-0019-x Lei TC, 2011, ENVIRON EARTH SCI, V63, P981, DOI 10.1007/s12665-010-0775-0 Mathew J, 2007, CURR SCI INDIA, V92, P628 Mohammady M., 2010, J RANGE WATERSHED MA, V62, P539 MOORE ID, 1986, WATER RESOUR RES, V22, P1350, DOI 10.1029/WR022i008p01350 MOORE ID, 1991, HYDROL PROCESS, V5, P3, DOI 10.1002/hyp.3360050103 Nefeslioglu HA, 2008, GEOMORPHOLOGY, V94, P401, DOI 10.1016/j.geomorph.2006.10.036 Nefeslioglu HA, 2010, MATH PROBL ENG, DOI 10.1155/2010/901095 Neuhauser B, 2007, GEOMORPHOLOGY, V86, P12, DOI 10.1016/j.geomorph.2006.08.002



Oh HJ, 2011, COMPUT GEOSCI-UK, V37, P1264, DOI 10.1016/j.cageo.2010.10.012 Oh HJ, 2011, ENVIRON EARTH SCI, V64, P395, DOI 10.1007/s12665-010-0864-0 Park NW, 2011, ENVIRON EARTH SCI, V62, P367, DOI 10.1007/s12665-010-0531-5 Pourghasemi H., 2012, TERRIGENOUS MASS MOV, P23, DOI DOI 10.1007/978-3-642-25495-6-2 Pourghasemi HR, 2012, NAT HAZARDS, V63, P965, DOI 10.1007/s11069-012-0217-2 Pourghasemi H.R., 2012, ARABIAN J GEOSCIENCE Pourghasemi H.R., 2012, GEOMATICS NATURAL HA Pourghasemi HR, 2012, CATENA, V97, P71, DOI 10.1016/j.catena.2012.05.005 Pradhan B, 2011, ENVIRON EARTH SCI, V63, P329, DOI 10.1007/s12665-010-0705-1 Pradhan B, 2010, ENVIRON MODELL SOFTW, V25, P747, DOI 10.1016/j.envsoft.2009.10.016 Pradhan B, 2010, ADV SPACE RES, V45, P1244, DOI 10.1016/j.asr.2010.01.006 Pradhan B, 2011, INT J REMOTE SENS, V32, P4075, DOI 10.1080/01431161.2010.484433 Pradhan B, 2010, INT J COMPUT INT SYS, V3, P370 Pradhan B, 2010, J INDIAN SOC REMOT, V38, P301, DOI 10.1007/s12524-010-0020-z Pradhan B, 2012, ENVIRON MONIT ASSESS, V184, P715, DOI 10.1007/s10661-011-1996-8 Pradhan B, 2010, ARAB J GEOSCI, V3, P319, DOI 10.1007/s12517-009-0089-2 Pradhan B, 2010, LANDSLIDES, V7, P13, DOI 10.1007/s10346-009-0183-2 Pradhan B, 2010, ENVIRON ENG GEOSCI, V16, P107 Pradhan B, 2011, ENVIRON ECOL STAT, V18, P471, DOI 10.1007/s10651-010-0147-7 Pradhan B., 2012, COMPUTER GE IN PRESS Pradhan B, 2010, ENVIRON EARTH SCI, V60, P1037, DOI 10.1007/s12665-009-0245-8 Pradhan B, 2010, DISASTER ADV, V3, P26 Pradhan B, 2010, IEEE T GEOSCI REMOTE, V48, P4164, DOI 10.1109/TGRS.2010.2050328 Pradhan B, 2010, GEOMAT NAT HAZ RISK, V1, P199, DOI 10.1080/19475705.2010.498151 Pradhan B, 2010, PHOTOGRAMM FERNERKUN, P17, DOI 10.1127/1432-8364/2010/0037 Pradhan Biswajeet, 2010, Geo-spatial Information Science, V13, DOI 10.1007/s11806-010-0236-7 Sezer EA, 2011, EXPERT SYST APPL, V38, P8208, DOI 10.1016/j.eswa.2010.12.167 Shafer G, 1976, MATH THEORY EVIDENCE Tangestani MH, 2009, J ASIAN EARTH SCI, V35, P66, DOI 10.1016/j.jseaes.2009.01.002 Bui DT, 2012, MATH PROBL ENG, DOI 10.1155/2012/974638 Vahidnia MH, 2010, COMPUT GEOSCI-UK, V36, P1101, DOI 10.1016/j.cageo.2010.04.004 Van Western C.J., 2002, USE WEIGHTS EVIDENCE Varnes D.J., 1978, LANDSLIDES ANAL CONT, V176, P12 Wan S, 2010, NAT HAZARDS, V52, P211, DOI 10.1007/s11069-009-9366-3 Wan S, 2012, INT J GEOGR INF SCI, V26, P747, DOI 10.1080/13658816.2011.613397 Wan SA, 2009, ENG GEOL, V108, P237, DOI 10.1016/j.enggeo.2009.06.014 Wan SA, 2009, KNOWL-BASED SYST, V22, P580, DOI 10.1016/j.knosys.2009.07.008 Yeon YK, 2010, ENG GEOL, V116, P274, DOI 10.1016/j.enggeo.2010.09.009 Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9 Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2010, ENVIRON EARTH SCI, V60, P505, DOI 10.1007/s12665-009-0191-5 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P297, DOI 10.1007/s10064-009-0185-2 Zare M., 2012, ARABIAN J GEOSCIENCECited Reference Count: 89 Abstract: The purpose of the present study is to investigate the landslide susceptibility mapping using three statistical models such as frequency ratio, Dempster-Shafer, and weights-of-evidence at southern part of Golestan province. At first, landslide locations were identified from the interpretation of aerial photographs, and field surveys. A total of 392 landslides were mapped in GIS out of which 275 (70%) locations were chosen for the modeling purpose and the remaining 118 (30%) cases were used for the model validation. Then layers of the landslide conditioning factors were prepared. The relationship between the conditioning factors and the landslides were calculated using three models. For verification, the results were compared with landslides which were not used during the training of the models. Subsequently, the ROC (Receiver operating characteristic) curves and area under the curves (AUC) for three landslide susceptibility maps were constructed and the areas under curves were assessed for validation purpose. The validation results showed that the area under the curve for frequency ratio, Dempster-Shafer, and weights-of-evidence models are 0.8013 (80.13%), 0.7832 (78.32%), and 0.7460 (74.60%) with prediction accuracy 0.7516 (75%), 0.7396 (73%), and 0.6998 (69%) respectively. The results revealed that frequency ratio model has higher AUC than the other models. In general, all the three models produced reasonable accuracy. The resultant maps would be useful for general land use planning. (C) 2012 Elsevier Ltd. All rights reserved.Accession Number: WOS:000314004800016 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslides; Frequency ratio; Dempster-Shafer; Weights-of-evidence; Geographic information systems (GIS); Iran; Remote sensingKeyWords Plus: ARTIFICIAL NEURAL-NETWORKS; HOA BINH PROVINCE; LOGISTIC-REGRESSION; FUZZY-LOGIC; CONDITIONAL-PROBABILITY; SPATIAL PREDICTION; AREA; MALAYSIA; TURKEY; GISAddresses: [Pradhan, Biswajeet] Univ Putra Malaysia, GISRC, Serdang 43400, Selangor, Malaysia. [Pradhan, Biswajeet] Univ Putra Malaysia, Dept Civil Engn, Fac Engn, Serdang 43400, Selangor, Malaysia. Reprint Address: Pradhan, B (reprint author), Univ Putra Malaysia, Dept Civil Engn, Fac Engn, Serdang 43400, Selangor, Malaysia.E-mail Addresses: [email protected]; [email protected]; [email protected] Identifiers:

Author ResearcherID Number ORCID NumberPradhan, Biswajeet E-8226-2010 0000-0001-9863-2054 Publisher: PERGAMON-ELSEVIER SCIENCE LTD Publisher Address: THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND Web of Science Categories: Geosciences, MultidisciplinaryResearch Areas: GeologyIDS Number: 077CF ISSN: 1367-9120 29-char Source Abbrev.: J ASIAN EARTH SCI ISO Source Abbrev.: J. Asian Earth Sci. Source Item Page Count: 16 Record 8 of 58Title: Comparison of different models for susceptibility mapping of earthquake triggered landslides related with the 2008 Wenchuan earthquake in China Author(s): Xu, C (Xu, Chong); Xu, XW (Xu, Xiwei); Dai, FC (Dai, Fuchu); Saraf, AK (Saraf, Arun K.)Source: COMPUTERS & GEOSCIENCES Volume: 46 Pages: 317-329 DOI: 10.1016/j.cageo.2012.01.002 Published: SEP 2012 Times Cited in Web of Science Core Collection: 18 Total Times Cited: 34 Cited References: Aleotti P, 1999, B ENG ENV, V58, P21, DOI DOI 10.1007/S100640050066 ANBALAGAN R, 1992, ENG GEOL, V32, P269, DOI 10.1016/0013-7952(92)90053-2 Arora MK, 2004, INT J REMOTE SENS, V25, P559, DOI 10.1080/0143116031000156819 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Beven K. J., 1979, HYDROL SCI B, V24, P43, DOI [10.1080/02626667909491834, DOI 10.1080/02626667909491834]



Brenning A, 2005, NAT HAZARD EARTH SYS, V5, P853 Chauhan S, 2010, INT J APPL EARTH OBS, V12, P340, DOI 10.1016/j.jag.2010.04.006 Chung CJF, 1999, PHOTOGRAMM ENG REM S, V65, P1389 Dahal RK, 2008, ENVIRON GEOL, V54, P311, DOI 10.1007/s00254-007-0818-3 Dai F. C., 2004, B ENG GEOL ENVIRON, V63, P315, DOI DOI 10.1007/S10064-004-0245-6 Dai FC, 2011, J ASIAN EARTH SCI, V40, P883, DOI 10.1016/j.jseaes.2010.04.010 Dai FC, 2002, ENG GEOL, V64, P65, DOI 10.1016/S0013-7952(01)00093-X Dai FC, 2001, ENVIRON GEOL, V40, P381, DOI 10.1007/s002540000163 Dai FC, 2003, EARTH SURF PROC LAND, V28, P527, DOI 10.1002/esp.456 Gallus D, 2008, HEADWAY SPATIAL DATA, P55, DOI DOI 10.1007/978-3-540-68566-1_4 Garcia-Rodriguez MJ, 2008, GEOMORPHOLOGY, V95, P172, DOI 10.1016/j.geomorph.2007.06.001 Hastie T, 2001, ELEMENTS STAT LEARNI He YP, 2008, EARTH SURF PROC LAND, V33, P380, DOI 10.1002/esp.1562 KEEFER DK, 1984, GEOL SOC AM BULL, V95, P406 Lee CT, 2008, ENG GEOL, V100, P43, DOI 10.1016/j.enggeo.2008.03.004 Lee S, 2004, ENVIRON MANAGE, V34, P223, DOI 10.1007/s00267-003-0077-3 Magliulo P, 2008, NAT HAZARDS, V47, P411, DOI 10.1007/s11069-008-9230-x Nefeslioglu HA, 2008, ENG GEOL, V97, P171, DOI 10.1016/j.enggeo.2008.01.004 Oh HJ, 2011, ENVIRON EARTH SCI, V62, P935, DOI 10.1007/s12665-010-0579-2 Pareek N, 2010, LANDSLIDES, V7, P191, DOI 10.1007/s10346-009-0192-1 PARK NW, 2010, ENVIRON EARTH SCI, V62, P367, DOI DOI 10.1007/S12665-010-0531-5 Pradhan B, 2010, ENVIRON MODELL SOFTW, V25, P747, DOI 10.1016/j.envsoft.2009.10.016 Pradhan B, 2006, ADV SPACE RES, V37, P698, DOI 10.1016/j.asr.2005.03.137 Pradhan B, 2010, LANDSLIDES, V7, P13, DOI 10.1007/s10346-009-0183-2 Pradhan B, 2010, ENVIRON EARTH SCI, V60, P1037, DOI 10.1007/s12665-009-0245-8 Pradhan B., 2008, EARTH SCI FRONTIERS, V14, P143, DOI DOI 10.1016/S1872-5791(08)60008-1 Pradhan Biswajeet, 2010, Geo-spatial Information Science, V13, DOI 10.1007/s11806-010-0236-7 Saha AK, 2005, LANDSLIDES, V2, P61, DOI 10.1007/s10346-004-0039-8 Scholkopf B, 2000, NEURAL COMPUT, V12, P1207, DOI 10.1162/089976600300015565 Sezer EA, 2011, EXPERT SYST APPL, V38, P8208, DOI 10.1016/j.eswa.2010.12.167 Singh LP, 2005, LANDSLIDES, V2, P221, DOI 10.1007/s10346-005-0059-z Suzen ML, 2004, ENG GEOL, V71, P303, DOI 10.1016/S0013-7952(03)00143-1 Tax DMJ, 1999, PATTERN RECOGN LETT, V20, P1191, DOI 10.1016/S0167-8655(99)00087-2 US Geological Survey, 2008, ADV NATL SEISMIC SYS Vapnik V., 1995, NATURE STAT LEARNING [许冲 XU Chong], 2009, [遥感学报, Journal of Remote Sensing], V13, P745 Xu XW, 2009, ACTA GEOL SIN-ENGL, V83, P673 Xu XW, 2009, GEOLOGY, V37, P515, DOI 10.1130/G25462A.1 Yalcin A, 2008, CATENA, V72, P1, DOI 10.1016/j.catena.2007.01.003 Yao X, 2008, GEOMORPHOLOGY, V101, P572, DOI 10.1016/j.geomorph.2008.02.011 Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9 Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P459, DOI 10.1007/s10064-009-0188-z Yilmaz I, 2010, ENVIRON EARTH SCI, V60, P505, DOI 10.1007/s12665-009-0191-5 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P297, DOI 10.1007/s10064-009-0185-2Cited Reference Count: 51 Abstract: The main purpose of this study is to compare the following six GIS-based models for susceptibility mapping of earthquake triggered landslides: bivariate statistics (BS), logistic regression (LR), artificial neural networks (ANN), and three types of support vector machine (SVM) models that use the three different kernel functions linear, polynomial, and radial basis. The models are applied in a tributary watershed of the Fu River, a tributary of the Jialing River, which is part of the area of China affected by the May 12, 2008 Wenchuan earthquake. For this purpose, eleven thematic data layers are used: landslide inventory, slope angle, aspect, elevation, curvature, distance from drainages, topographic wetness index (TWI), distance from main roads, distance from surface rupture, peak ground acceleration (PGA), and lithology. The data layers were specifically constructed for analysis in this study. In the subsequent stage of the study, susceptibility maps were produced using the six models and the same input for each one. The validations of the resulting susceptibility maps were performed and compared by means of two values of area under curve (AUC) that represent the respective success rates and prediction rates. The AUC values obtained from all six results showed that the LR model provides the highest success rate (AUC = 80.34) and the highest prediction rate (AUC = 80.27). The SVM (radial basis function) model generates the second-highest success rate (AUC = 80.302) and the second-highest prediction rate (AUC = 80.151), which are close to the value from the LR model. The results using the SVM (linear) model show the lowest AUC values. The AUC values from the SVM (linear) model are only 72.52 (success rates) and 72.533 (prediction rates). Furthermore, the results also show that the radial basis function is the most appropriate kernel function of the three kernel functions applied using the SVM model for susceptibility mapping of earthquake triggered landslides in the study area. The paper also provides a counter-example for the widely held notion that validation performances of the results from application of the models obtained from soft computing techniques (such as ANN and SVM) are higher than those from applications of LR and BA models. (C) 2012 Elsevier Ltd. All rights reserved.Accession Number: WOS:000307924200036 Language: EnglishDocument Type: ArticleAuthor Keywords: Earthquake triggered landslides; Landslide susceptibility mapping; Bivariate statistics; Logistic regression; Artificial neural networks; Support vector machineKeyWords Plus: ARTIFICIAL NEURAL-NETWORKS; SUPPORT VECTOR MACHINE; LOGISTIC-REGRESSION; CONDITIONAL-PROBABILITY; BIVARIATE STATISTICS; SAMPLING STRATEGIES; PREDICTION MODELS; HONG-KONG; GIS; TURKEYAddresses: [Xu, Chong; Xu, Xiwei] China Earthquake Adm, Inst Geol, Key Lab Act Tecton & Volcano, Beijing 100029, Peoples R China. [Xu, Chong; Dai, Fuchu] Chinese Acad Sci, Inst Geol & Geophys, Beijing 100029, Peoples R China. [Saraf, Arun K.] Indian Inst Technol Roorkee, Dept Earth Sci, Roorkee 247667, Uttar Pradesh, India. Reprint Address: Xu, XW (reprint author), China Earthquake Adm, Inst Geol, Key Lab Act Tecton & Volcano, Beijing 100029, Peoples R China.E-mail Addresses: [email protected] Identifiers:

Author ResearcherID Number ORCID NumberXu, Chong B-6460-2012 0000-0002-3956-4925 Publisher: PERGAMON-ELSEVIER SCIENCE LTD Publisher Address: THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND Web of Science Categories: Computer Science, Interdisciplinary Applications; Geosciences, MultidisciplinaryResearch Areas: Computer Science; GeologyIDS Number: 994IN ISSN: 0098-3004 29-char Source Abbrev.: COMPUT GEOSCI-UK ISO Source Abbrev.: Comput. Geosci. Source Item Page Count: 13

Funding:

Funding Agency Grant NumberNational Science Foundation of China 40821160550



40974057 International Scientific joint project of China 2009DFA21280 Doctoral Candidate Innovation Research Support Program by Science & Technology Review kjdb200902-5

This research is supported by the National Science Foundation of China (grant No. 40821160550 & 40974057), International Scientific joint project of China (grant No. 2009DFA21280), and the Doctoral Candidate Innovation Research Support Program by Science & Technology Review (grant kjdb200902-5).

Record 9 of 58Title: Landslide susceptibility mapping at Vaz Watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms Author(s): Zare, M (Zare, Mohammad); Pourghasemi, HR (Pourghasemi, Hamid Reza); Vafakhah, M (Vafakhah, Mahdi); Pradhan, B (Pradhan, Biswajeet)Source: ARABIAN JOURNAL OF GEOSCIENCES Volume: 6 Issue: 8 Pages: 2873-2888 DOI: 10.1007/s12517-012-0610-x Published: AUG 2013 Times Cited in Web of Science Core Collection: 16 Total Times Cited: 16 Cited References: Akgun A, 2007, ENVIRON GEOL, V51, P1377, DOI 10.1007/s00254-006-0435-6 Akgun A, 2008, ENVIRON GEOL, V54, P1127, DOI 10.1007/s00254-007-0882-8 Akgun A, 2012, ENVIRON MONIT ASSESS, V184, P5453, DOI 10.1007/s10661-011-2352-8 Akgun A, 2012, COMPUT GEOSCI-UK, V38, P23, DOI 10.1016/j.cageo.2011.04.012 Akgun A, 2012, LANDSLIDES, V9, P93, DOI 10.1007/s10346-011-0283-7 Akgun A, 2010, ENVIRON EARTH SCI, V61, P595, DOI 10.1007/s12665-009-0373-1 Aleotti P, 1999, B ENG ENV, V58, P21, DOI DOI 10.1007/S100640050066 Althuwaynee OF, 2012, COMPUT GEOSCI, DOI [10.1016/j.cageo.2012.03.003, DOI 10.1016/J.CAGE0.2012.03.003] Ayalew L, 2005, ENG GEOL, V81, P432, DOI 10.1016/j.enggeo.2005.08.004 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Bai S, 2010, ENVIRON EARTH SCI, V62, P139 Basheer IA, 2000, J MICROBIOL METH, V43, P3, DOI 10.1016/S0167-7012(00)00201-3 Baum E. 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Pradhan B, 2010, DISASTER ADV, V3, P26 Pradhan B, 2010, GEOMAT NAT HAZ RISK, V1, P199, DOI 10.1080/19475705.2010.498151 Saito H, 2009, GEOMORPHOLOGY, V109, P108, DOI 10.1016/j.geomorph.2009.02.026 Sezer EA, 2011, EXPERT SYST APPL, V38, P8208, DOI 10.1016/j.eswa.2010.12.167 Soeters R, 1994, 247 TRANSP RES BOARD, V247, P129 Song KY, 2012, ADV SPACE RES, V49, P978, DOI 10.1016/j.asr.2011.11.035 Swingler K, 1996, APPL NEURAL NETWORKS Bui DT, 2012, COMPUT GEOSCI-UK, V45, P199, DOI 10.1016/j.cageo.2011.10.031 Vahidnia MH, 2010, COMPUT GEOSCI-UK, V36, P1101, DOI 10.1016/j.cageo.2010.04.004 Van Westen CJ, 2003, NAT HAZARDS, V30, P399, DOI 10.1023/B:NHAZ.0000007097.42735.9e Varnes D. J., 1984, LANDSLIDE HAZARD ZON Varnes D.J., 1978, LANDSLIDES ANAL CONT, V176, P12 Wan SA, 2009, ENG GEOL, V108, P237, DOI 10.1016/j.enggeo.2009.06.014 Wijesinghe P, 2008, NOVEL APPROACH RSS C Xu C, 2012, GEOMORPHOLOGY, DOI [10.1016/j.geomorph.2011.12.040, DOI 10.1016/J.GE0M0RPH.2011.12.040] Yao X, 2008, GEOMORPHOLOGY, V101, P572, DOI 10.1016/j.geomorph.2008.02.011 Yeon YK, 2010, ENG GEOL, V116, P274, DOI 10.1016/j.enggeo.2010.09.009 Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9 Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2012, NEURAL COMPUT APPL, V21, P957, DOI 10.1007/s00521-011-0535-4 Yilmaz I, 2010, ENVIRON EARTH SCI, V60, P505, DOI 10.1007/s12665-009-0191-5 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P297, DOI 10.1007/s10064-009-0185-2 Zezere JL, 1999, GEOMORPHOLOGY, V30, P133, DOI 10.1016/S0169-555X(99)00050-1Cited Reference Count: 102 Abstract: Landslide susceptibility and hazard assessments are the most important steps in landslide risk mapping. The main objective of this study was to investigate and compare the results of two artificial neural network (ANN) algorithms, i.e., multilayer perceptron (MLP) and radial basic function (RBF) for spatial prediction of landslide susceptibility in Vaz Watershed, Iran. At first, landslide locations were identified by aerial photographs and field surveys, and a total of 136 landside locations were constructed from various sources. Then the landslide inventory map was randomly split into a training dataset 70 % (95 landslide locations) for training the ANN model and the remaining 30 % (41 landslides locations) was used for validation purpose. Nine landslide conditioning factors such as slope, slope aspect, altitude, land use, lithology, distance from rivers, distance from roads, distance from faults, and rainfall were constructed in geographical information system. In this study, both MLP and RBF algorithms were used in artificial neural network model. The results showed that MLP with Broyden-Fletcher-Goldfarb-Shanno learning algorithm is more efficient than RBF in landslide susceptibility mapping for the study area. Finally the landslide susceptibility maps were validated using the validation data (i.e., 30 % landslide location data that was not used during the model construction) using area under the curve (AUC) method. The success rate curve showed that the area under the curve for RBF and MLP was 0.9085 (90.85 %) and 0.9193 (91.93 %) accuracy, respectively. Similarly, the validation result showed that the area under the curve for MLP and RBF models were 0.881 (88.1 %) and 0.8724 (87.24 %), respectively. The results of this study showed that landslide susceptibility mapping in the Vaz Watershed of Iran using the ANN approach is viable and can be used for land use planning.Accession Number: WOS:000322028400012 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslide; Susceptibility; Artificial neural networks; Geographic Information Systems (GIS); Vaz Watershed; IranKeyWords Plus: SUPPORT VECTOR MACHINE; LOGISTIC-REGRESSION; CONDITIONAL-PROBABILITY; DARJEELING HIMALAYAS; SAMPLING STRATEGIES; SPATIAL PREDICTION; FREQUENCY RATIO; DECISION-TREE; ASTER IMAGERY; AREA NORTHAddresses: [Zare, Mohammad] Univ Tehran, Coll Nat Resources, Tehran, Iran. [Pourghasemi, Hamid Reza] TMU, Coll Nat Resources & Marine Sci, Mazandaran, Iran. [Vafakhah, Mahdi] TMU, Fac Nat Resources & Marine Sci, Mazandaran, Iran. [Pradhan, Biswajeet] Univ Putra Malaysia, Inst Adv Technol, Spatial & Numer Modeling Lab, Serdang 43400, Selangor Darul, Malaysia. [Pradhan, Biswajeet] Univ Putra Malaysia, Fac Engn, Dept Civil Engn, Spatial & Numer Modeling Res Grp, Serdang 43400, Selangor Darul, Malaysia. Reprint Address: Pradhan, B (reprint author), Univ Putra Malaysia, Fac Engn, Dept Civil Engn, Spatial & Numer Modeling Res Grp, Serdang 43400, Selangor Darul, Malaysia.E-mail Addresses: [email protected]; [email protected] Identifiers:

Author ResearcherID Number ORCID NumberPradhan, Biswajeet E-8226-2010 0000-0001-9863-2054 Publisher: SPRINGER HEIDELBERG Publisher Address: TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY Web of Science Categories: Geosciences, MultidisciplinaryResearch Areas: GeologyIDS Number: 186FV ISSN: 1866-7511 eISSN: 1866-7538 29-char Source Abbrev.: ARAB J GEOSCI ISO Source Abbrev.: Arab. J. Geosci. Source Item Page Count: 16 Record 10 of 58Title: A short review on the surficial impacts of underground mining Author(s): Altun, AO (Altun, Aysen Oksan); Yilmaz, I (Yilmaz, Isik); Yildirim, M (Yildirim, Mustafa)Source: SCIENTIFIC RESEARCH AND ESSAYS Volume: 5 Issue: 21 Pages: 3206-3212 Published: NOV 4 2010 Times Cited in Web of Science Core Collection: 16 Total Times Cited: 17 Cited References: Allen CW, 1934, T AM I MIN MET ENG, V109, P195 *BELM LTD, 1981, COMM INV BELM MIN TR, V1 BETOURNAY M, 1987, P 28 US ROCK MECH S, P1197 BETOURNAY MC, 1988, 8817TR MRL CANMET DI, P45 BETOURNAY MC, 2002, INT TECHN GROUP AB U, P1 BETOURNAY MC, 1994, P 1 N AM ROCK MECH S, P987 BETOURNAY MC, 1995, THESIS MCGILL U, P611 BETOURNAY MC, 1997, 97058CR CANMET MMSL, P55 BLODGETT SB, 2002, TECHNICAL REPORT UND, P50 CHARETTE F, 1992, 9204 CANMET MRL EN M, P81 CHARETTE F, 1993, 93059 CANMET MRL CL, P65 CRANE WR, 1929, US BUR MIN B, P295 *GOLD ASS, 1990, CROWN PILL STAB BACK *GROUP CONS ROCH L, 1985, SURF PILL*GROUP CONS ROCH L, 1984, SURF PILLHAMRIN H, 1980, GUIDE UNDERGROUND MI, P40 HEDLEY DGF, 1979, 7947 CANMET MRL TR E, P110 Hustrulid W. A., 2001, UNDERGROUND MINING M



Li WX, 2006, INT J ROCK MECH MIN, V43, P503, DOI 10.1016/j.ijrmms.2005.09.008 Li W.X., 2003, MATH PRACT THEORY, V33, P26 MALGOT J, 2004, ENG GEOLOGY INFRASTR, V104, P694 Marschalko M, 2009, ACTA MONTAN SLOVACA, V14, P232 Marschalko M, 2008, ACTA MONTAN SLOVACA, V13, P58 Marschalko M, 2009, SGEM 2009: 9TH INTERNATIONAL MULTIDISCIPLINARY SCIENTIFIC GEOCONFERENCE, VOL I, CONFERENCE PROCEEDING, P221 Marschalko M, 2008, SGEM 2008: 8TH INTERNATIONAL SCIENTIFIC CONFERENCE, VOL I, CONFERENCE PROCEEDINGS, P315 Marschalko M, 2008, ARCH MIN SCI, V53, P397 *MIRZ ENG, 1986, SAMPL FIELD TEST MOD Perski Z., 2003, P 11 FIG S DEF MEAS, P1 *QUEENS U, 1987, SEISM CHAR DISC AN R RAO MVR, 2004, PREDICTION SURFACE S, P71 Rice GS, 1934, T AM I MIN MET ENG, V109, P118 ROBERTSON S, 1984, ROCK MECH STUDY THOM, P55 SOLIMAN MM, 1998, ENV HYDROGEOLOGY, P386 [宋彦辉 SONG Yanhui], 2003, [灾害学, Journal of Catastrophology], V18, P32 Tang Fu-quan, 2009, Journal of Coal Science and Engineering (China), V15, DOI 10.1007/s12404-009-0403-3 *TROW ENG, 1988, DET SURF CROWN PILL Wang B. W., 1995, P 3 CAN C COMP APPL, P390 *WESTM CAN LTD, 1991, STAB OV HANG WALL Whittaker BN, 1989, SUBSIDENCE OCCURRENC, P528 Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2006, ENVIRON GEOL, V49, P708, DOI 10.1007/s00254-005-0112-1 Yilmaz I, 2008, COMPUT GEOSCI-UK, V34, P993, DOI 10.1016/j.cageo.2007.06.008 Yilmaz I, 2005, ENVIRON GEOL, V47, P175, DOI 10.1007/s00254-004-1141-xCited Reference Count: 43 Abstract: Subsidence in terrains is one of the most serious geological hazards because they can effect slopes and damage engineering structures, settlement areas, natural lakes, and allow infiltration of contaminant into the groundwater. Causes of underground mining activities such as subsidence, slope deformation, etc. are very important problems in most countries and these types of impacts are very well known in coal, metal and other types of mining. The main aim of this article is to provide technical documentation of environmental impacts related to underground mining, to discuss significant impacts on the environment and land- use during and/or after underground mining projects. Identification, measuring and mitigation of the effect of underground mining activities for practitioners is also aimed in this short review article. This short review article will also be important in order to better understand the nature and magnitude of displacements that can affect surface infrastructure.Accession Number: WOS:000284553700002 Language: EnglishDocument Type: ReviewAuthor Keywords: Underground mining; subsidence; collapse; slope deformation; surfaceKeyWords Plus: TURKEY; SUSCEPTIBILITY; MICHIGAN; YALOVAAddresses: [Altun, Aysen Oksan; Yilmaz, Isik; Yildirim, Mustafa] Cumhuriyet Univ, Dept Geol Engn, Fac Engn, TR-58140 Sivas, Turkey. Reprint Address: Yilmaz, I (reprint author), Cumhuriyet Univ, Dept Geol Engn, Fac Engn, TR-58140 Sivas, Turkey.E-mail Addresses: [email protected]: ACADEMIC JOURNALS Publisher Address: P O BOX 5170-00200 NAIROBI, VICTORIA ISLAND, LAGOS 73023, NIGERIA Web of Science Categories: Multidisciplinary SciencesResearch Areas: Science & Technology - Other TopicsIDS Number: 684MJ ISSN: 1992-2248 29-char Source Abbrev.: SCI RES ESSAYS ISO Source Abbrev.: Sci. Res. Essays Source Item Page Count: 7 Record 11 of 58Title: Landslide susceptibility analysis in the Hoa Binh province of Vietnam using statistical index and logistic regression Author(s): Bui, DT (Dieu Tien Bui); Lofman, O (Lofman, Owe); Revhaug, I (Revhaug, Inge); Dick, O (Dick, Oystein)Source: NATURAL HAZARDS Volume: 59 Issue: 3 Pages: 1413-1444 DOI: 10.1007/s11069-011-9844-2 Published: DEC 2011 Times Cited in Web of Science Core Collection: 14 Total Times Cited: 17 Cited References: Atkinson PM, 1998, COMPUT GEOSCI-UK, V24, P373, DOI 10.1016/S0098-3004(97)00117-9 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Bai SB, 2010, GEOMORPHOLOGY, V115, P23, DOI 10.1016/j.geomorph.2009.09.025 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Brenning A, 2005, NAT HAZARD EARTH SYS, V5, P853 Can T, 2005, GEOMORPHOLOGY, V72, P250, DOI 10.1016/j.geomorph.2005.05.011 Cevik E, 2003, ENVIRON GEOL, V44, P949, DOI 10.1007/s00254-003-0838-6 Chung CJF, 2003, NAT HAZARDS, V30, P451, DOI 10.1023/B:NHAZ.0000007172.62651.2b Dai FC, 2002, GEOMORPHOLOGY, V42, P213, DOI 10.1016/S0169-555X(01)00087-3 Dai FC, 2001, ENVIRON GEOL, V40, P381, DOI 10.1007/s002540000163 Donati L, 2002, ENG GEOL, V63, P277, DOI 10.1016/S0013-7952(01)00087-4 Falaschi F, 2009, NAT HAZARDS, V50, P551, DOI 10.1007/s11069-009-9356-5 GALANG JS, 2004, THESIS STATE U BLACK Gokceoglu C, 1996, ENG GEOL, V44, P147, DOI 10.1016/S0013-7952(97)81260-4 Guzzetti F, 1999, GEOMORPHOLOGY, V31, P181, DOI 10.1016/S0169-555X(99)00078-1 Hosmer DW, 2000, APPL LOGISTIC REGRES Hue TT, 2004, INVESTIGATION ASSESS JADE S, 1993, ENG GEOL, V36, P91, DOI 10.1016/0013-7952(93)90021-4 Lee S, 2005, INT J REMOTE SENS, V26, P1477, DOI 10.1080/01431160412331331012 Lee S, 2007, LANDSLIDES, V4, P327, DOI 10.1007/s10346-007-0088-x Lee S, 2001, ENVIRON GEOL, V40, P1095, DOI 10.1007/s002540100310 Long N.T., 2008, THESIS VRIJE U BRUSS Magliulo P, 2008, NAT HAZARDS, V47, P411, DOI 10.1007/s11069-008-9230-x Menard S., 1995, APPL LOGISTIC REGRES My NQ, 2007, CONSTRUCTION ENV HAZ NANDI A, 2008, GEORISK, V1, P12 Ohlmacher GC, 2007, ENG GEOL, V91, P117, DOI 10.1016/j.enggeo.2007.01.005 Ohlmacher GC, 2003, ENG GEOL, V69, P331, DOI 10.1016/S0013-7952(03)00069-3 Oztekin B, 2005, ENVIRON GEOL, V49, P124, DOI 10.1007/s00254-005-0071-6 Suzen ML, 2004, ENVIRON GEOL, V45, P665, DOI 10.1007/s00254-003-0917-8 Thach NN, 2002, APPL REMOTE SENSING Thinh DV, 2005, INVESTIGATED REPORT Van T.T., 2002, ASSESSMENT PREDICTIO Van T.T., 2006, INVESTIGATION ASSESS Van Westen C.J., 1997, STAT LANDSLIDE HAZAR



Van Den Eeckhaut M, 2010, GEOMORPHOLOGY, V115, P141, DOI 10.1016/j.geomorph.2009.09.042 vanWesten CJ, 1997, GEOL RUNDSCH, V86, P404 Varnes D. J., 1984, LANDSLIDE HAZARD ZON Wang HB, 2005, PROG PHYS GEOG, V29, P548, DOI [10.1191/0309133305pp462ra, 10.1191/0309133305pp463ra] Wieczorek G.F., 1984, B ASS ENG GEOLOGISTS, V21, P337 Yalcin A, 2008, CATENA, V72, P1, DOI 10.1016/j.catena.2007.01.003 Yesilnacar E, 2005, ENG GEOL, V79, P251, DOI 10.1016/j.enggeo.2005.02.002 Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2010, ENVIRON EARTH SCI, V60, P505, DOI 10.1007/s12665-009-0191-5 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P297, DOI 10.1007/s10064-009-0185-2 Zhou G, 2003, ENG GEOL, V68, P373, DOI 10.1016/S0013-7952(02)00241-7Cited Reference Count: 46 Abstract: The purpose of this study is to evaluate and compare the results of applying the statistical index and the logistic regression methods for estimating landslide susceptibility in the Hoa Binh province of Vietnam. In order to do this, first, a landslide inventory map was constructed mainly based on investigated landslide locations from three projects conducted over the last 10 years. In addition, some recent landslide locations were identified from SPOT satellite images, fieldwork, and literature. Secondly, ten influencing factors for landslide occurrence were utilized. The slope gradient map, the slope curvature map, and the slope aspect map were derived from a digital elevation model (DEM) with resolution 20 x 20 m. The DEM was generated from topographic maps at a scale of 1:25,000. The lithology map and the distance to faults map were extracted from Geological and Mineral Resources maps. The soil type and the land use maps were extracted from National Pedology maps and National Land Use Status maps, respectively. Distance to rivers and distance to roads were computed based on river and road networks from topographic maps. In addition, a rainfall map was included in the models. Actual landslide locations were used to verify and to compare the results of landslide susceptibility maps. The accuracy of the results was evaluated by ROC analysis. The area under the curve (AUC) for the statistical index model was 0.946 and for the logistic regression model, 0.950, indicating an almost equal predicting capacity.Accession Number: WOS:000296475400011 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslide susceptibility; Logistic regression; Statistical index; Hoa Binh provinceKeyWords Plus: ARTIFICIAL NEURAL-NETWORKS; SPATIAL PREDICTION MODELS; BIVARIATE STATISTICS; LANTAU-ISLAND; REGION TURKEY; HONG-KONG; GIS; HAZARD; SLOPE; PROBABILITYAddresses: [Dieu Tien Bui; Lofman, Owe; Revhaug, Inge; Dick, Oystein] Norwegian Univ Life Sci, Dept Math Sci & Technol, N-1432 As, Norway. Reprint Address: Bui, DT (reprint author), Norwegian Univ Life Sci, Dept Math Sci & Technol, POB 5003IMT, N-1432 As, Norway.E-mail Addresses: [email protected] Identifiers:

Author ResearcherID Number ORCID NumberTien Bui, Dieu K-2125-2012 Jingwei Li, Jingwei E-2396-2014 Publisher: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences; Water ResourcesResearch Areas: Geology; Meteorology & Atmospheric Sciences; Water ResourcesIDS Number: 840XM ISSN: 0921-030X 29-char Source Abbrev.: NAT HAZARDS ISO Source Abbrev.: Nat. Hazards Source Item Page Count: 32

Funding:

Funding Agency Grant NumberNorwegian Quota scholarship

This research was funded by the Norwegian Quota scholarship. The data analysis and write-up were carried out as a part of the first author's PhD studies at the Geomatics section, Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Norway. I would like to thank Dr. Tran Tan Van, director of Vietnam Institute of Geosciences and Mineral Resources, for valuable comments.

Record 12 of 58Title: GIS-based bivariate statistical modelling for earthquake-triggered landslides susceptibility mapping related to the 2008 Wenchuan earthquake, China Author(s): Xu, C (Xu, Chong); Xu, XW (Xu, Xiwei); Yao, Q (Yao, Qi); Wang, YY (Wang, Yanying)Source: QUARTERLY JOURNAL OF ENGINEERING GEOLOGY AND HYDROGEOLOGY Volume: 46 Issue: 2 Pages: 221-236 DOI: 10.1144/qjegh2012- 006 Published: MAY 2013 Times Cited in Web of Science Core Collection: 12 Total Times Cited: 16 Cited References: Aleotti P, 1999, B ENG ENV, V58, P21, DOI DOI 10.1007/S100640050066 Arora MK, 2004, INT J REMOTE SENS, V25, P559, DOI 10.1080/0143116031000156819 Baeza C, 2001, EARTH SURF PROC LAND, V26, P1251, DOI 10.1002/esp.263 Bai SB, 2009, PEDOSPHERE, V19, P14, DOI 10.1016/S1002-0160(08)60079-X Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Binaghi E, 1998, NAT HAZARDS, V17, P77, DOI 10.1023/A:1008001724538 Brenning A, 2005, NAT HAZARD EARTH SYS, V5, P853 Carrara A, 1999, NAT HAZARDS, V20, P117, DOI 10.1023/A:1008097111310 Chung CJF, 1999, PHOTOGRAMM ENG REM S, V65, P1389 Dahal RK, 2008, GEOMORPHOLOGY, V102, P496, DOI 10.1016/j.geomorph.2008.05.041 Dahal RK, 2008, ENVIRON GEOL, V54, P311, DOI 10.1007/s00254-007-0818-3 Dai FC, 2011, J ASIAN EARTH SCI, V40, P883, DOI 10.1016/j.jseaes.2010.04.010 Dai FC, 2001, ENVIRON GEOL, V40, P381, DOI 10.1007/s002540000163 Dong JJ, 2009, EARTH SURF PROC LAND, V34, P1612, DOI 10.1002/esp.1850 Gallus D, 2008, HEADWAY SPATIAL DATA, P55, DOI DOI 10.1007/978-3-540-68566-1_4 Gao KC, 2005, INT GEOSCI REMOTE SE, P5227 Garcia-Rodriguez MJ, 2008, GEOMORPHOLOGY, V95, P172, DOI 10.1016/j.geomorph.2007.06.001 Godt JW, 2008, ENG GEOL, V102, P214, DOI 10.1016/j.enggeo.2008.03.019 Gorum T, 2011, GEOMORPHOLOGY, V133, P152, DOI 10.1016/j.geomorph.2010.12.030 Griffiths JS, 2002, Q J ENG GEOL HYDROGE, V35, P9 Gulla G, 2008, GEOMORPHOLOGY, V99, P39, DOI 10.1016/j.geomorph.2007.10.005 Gunther A, 2009, NAT HAZARD EARTH SYS, V9, P687 Gupta P, 1997, Q J ENG GEOL, V30, P27, DOI 10.1144/GSL.QJEGH.1997.030.P1.03 Guzzetti F, 1999, GEOMORPHOLOGY, V31, P181, DOI 10.1016/S0169-555X(99)00078-1 Harp EL, 2011, ENG GEOL, V122, P9, DOI 10.1016/j.enggeo.2010.06.013 Hasegawa Shuichi, 2009, Geotechnical and Geological Engineering, V27, DOI 10.1007/s10706-008-9242-z Havenith HB, 2006, LANDSLIDES, V3, P39, DOI 10.1007/s10346-005-0005-0 He YP, 2008, EARTH SURF PROC LAND, V33, P380, DOI 10.1002/esp.1562



Jibson RW, 2011, ENG GEOL, V122, P43, DOI 10.1016/j.enggeo.2010.09.017 Jibson RW, 2000, ENG GEOL, V58, P271, DOI 10.1016/S0013-7952(00)00039-9 Kamp U, 2010, NAT HAZARDS, V54, P1, DOI 10.1007/s11069-009-9451-7 Kamp U, 2008, GEOMORPHOLOGY, V101, P631, DOI 10.1016/j.geomorph.2008.03.003 Keefer D.K., 1984, GEOL SOC AM BULL, V95, P406, DOI DOI 10.1130/0016-7606(1984)95<406:LCBE>2.0.C0;2 Kong WK, 2002, Q J ENG GEOL HYDROGE, V35, P213, DOI 10.1144/1470-9236/2000-39 Lan HX, 2004, ENG GEOL, V76, P109, DOI 10.1016/j.enggeo.2004.06.009 Lee CT, 2008, ENG GEOL, V100, P43, DOI 10.1016/j.enggeo.2008.03.004 Lee C.T., 2004, P INT S LANDSL DEBR Lee S, 2006, NAT HAZARD EARTH SYS, V6, P687 Lee S, 2004, INT J GEOGR INF SCI, V18, P789, DOI 10.1080/13658810410001702003 Lin M.-L., 2003, ENG GEOL, V71, P63, DOI DOI 10.1016/S0013-7952(03)00126-1 Liu J.G., 2003, GEOSC REM SENS S 200, V2, P1302 Luzi L, 1999, NAT HAZARDS, V20, P57, DOI 10.1023/A:1008162814578 Marquinez J, 2003, NAT HAZARDS, V30, P341, DOI 10.1023/B:NHAZ.0000007170.21649.e1 Mason PJ, 2002, Q J ENG GEOL HYDROGE, V35, P317, DOI 10.1144/1470-9236/00047 Mathew J, 2007, CURR SCI INDIA, V92, P628 Mavrouli O, 2009, NAT HAZARD EARTH SYS, V9, P1763 Meunier P, 2007, GEOPHYS RES LETT, V34, DOI 10.1029/2007GL031337 Meunier P, 2008, EARTH PLANET SC LETT, V275, P221, DOI 10.1016/j.epsl.2008.07.020 Miles SB, 1999, SOIL DYN EARTHQ ENG, V18, P305, DOI 10.1016/S0267-7261(98)00048-7 Neuhauser B, 2007, GEOMORPHOLOGY, V86, P12, DOI 10.1016/j.geomorph.2006.08.002 Oh HJ, 2011, ENVIRON EARTH SCI, V62, P935, DOI 10.1007/s12665-010-0579-2 Pareek N, 2010, LANDSLIDES, V7, P191, DOI 10.1007/s10346-009-0192-1 PARK NW, 2010, ENVIRON EARTH SCI, V62, P367, DOI DOI 10.1007/S12665-010-0531-5 Pistocchi A, 2002, ENVIRON GEOL, V41, P765, DOI 10.1007/s002540100440 Pradhan B., 2008, EARTH SCI FRONTIERS, V14, P143, DOI DOI 10.1016/S1872-5791(08)60008-1 Remondo J, 2003, NAT HAZARDS, V30, P267, DOI 10.1023/B:NHAZ.0000007202.12543.3a Saha AK, 2005, LANDSLIDES, V2, P61, DOI 10.1007/s10346-004-0039-8 Saha AK, 2002, INT J REMOTE SENS, V23, P357, DOI 10.1080/01431160010014260 Saleh B., 2000, J URBAN PLANNING DEV, V126, P1 Sarkar S, 2008, J MT SCI-ENGL, V5, P52, DOI 10.1007/s11629-008-0052-9 Sato H.P., 2005, B GEOGRAPHICAL SURVE, V52, P23 Sezer EA, 2011, EXPERT SYST APPL, V38, P8208, DOI 10.1016/j.eswa.2010.12.167 Shaban A, 2001, B ENG GEOL ENVIRON, V60, P93 Tassetti N., 2008, EARSeL eProceedings, V7, P59 Thapa P.B., 2007, B DEP GEOLOGY, V10, P63 Thiery Y, 2007, GEOMORPHOLOGY, V92, P38, DOI 10.1016/j.geomorph.2007.02.020 Varnes DJ, 1984, NATURAL HAZARDS, V3 Wachal D. J., 2000, GeoJournal, V51, P245, DOI 10.1023/A:1017524604463 Wasowski J, 2011, ENG GEOL, V122, P1, DOI 10.1016/j.enggeo.2011.06.001 Weiss AD, 2006, TOPOGRAPHIC POSITION Xu C, 2012, CHINESE J GEOPHYS-CH, V55, P2994, DOI 10.6038/j.issn.0001-5733.2012.09.018 Xu C, 2012, J EARTH SCI-CHINA, V23, P97, DOI 10.1007/s12583-012-0236-7 Xu C, 2013, ARAB J GEOSCI, V6, P3827, DOI 10.1007/s12517-012-0646-y Xu C, 2012, COMPUT GEOSCI-UK, V46, P317, DOI 10.1016/j.cageo.2012.01.002 Xu C, 2012, GEOMORPHOLOGY, V145, P70, DOI 10.1016/j.geomorph.2011.12.040 Xu C, 2012, ENVIRON EARTH SCI, V66, P1603, DOI 10.1007/s12665-012-1624-0 Xu C, 2013, LANDSLIDES, V10, P421, DOI 10.1007/s10346-012-0340-x Xu C, 2012, ENG GEOL, V133, P40, DOI 10.1016/j.enggeo.2012.02.017 Xu C, 2012, DISASTER ADV, V5, P1297 [徐锡伟 XU Xiwei], 2008, [地震地质, Seismology and Geology], V30, P597 Xu XW, 2010, CHINESE J GEOPHYS-CH, V53, P2321, DOI 10.3969/j.issn.0001-5733.2010.10.006 Xu XW, 2009, ACTA GEOL SIN-ENGL, V83, P673 Xu XW, 2009, GEOLOGY, V37, P515, DOI 10.1130/G25462A.1 Xu ZQ, 2008, EPISODES, V31, P291 Yalcin A, 2008, CATENA, V72, P1, DOI 10.1016/j.catena.2007.01.003 Yao X, 2008, GEOMORPHOLOGY, V101, P572, DOI 10.1016/j.geomorph.2008.02.011 Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9 Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P297, DOI 10.1007/s10064-009-0185-2Cited Reference Count: 89 Abstract: The main purpose of this research is to evaluate the modelling capability and predictive power of a bivariate statistical method for earthquake-triggered landslide susceptibility mapping. A weight index (W-i) model was developed for the 2008 Wenchuan earthquake region in Sichuan Province, China, using a wide range of optical remote sensing data, and carried out on the basis of a geographic information system (GIS) platform. The 2008 Wenchuan earthquake triggered 196007 landslides, with a total area of 1150.43 km(2), in an approximately oblong area around the Yingxiu-Beichuan coseismic surface fault-rupture (the Yingxiu-Beichuan fault). The landslides of the study area were mapped using visual interpretation of high-resolution satellite images and aerial photographs, both pre-and post-earthquake, and checked in the field at various locations. As a consequence, a nearly complete inventory of landslides triggered by the Wenchuan earthquake was constructed. Topographic and geological data and earthquake-related information were collected, processed and constructed into a spatial database using GIS and image processing technologies. A total of 10 controlling parameters associated with the earthquake-triggered landslides were selected, including elevation, slope angle, slope aspect, slope curvature, slope position, lithology, seismic intensity, peak ground acceleration (PGA), distance from the Yingxiu-Beichuan fault, and distance along this fault. To assist with the development of the model, the complete dataset of 196007 landslides was randomly partitioned into two subsets; a training dataset, which contains 70% of the data (137204 landslides, with a total area of 809.96 km(2)), and a testing dataset accounting for 30% of the data (58803 landslides, with a total area of 340.47 km(2)). A landslide susceptibility index map was generated using the training dataset, the 10 impact factors, and the W-i model. In addition, for a conditionally dependent factor analysis, seven other factor-combination cases were also used to construct landslide susceptibility index maps. Finally, these eight landslide susceptibility maps were compared with the training data and testing data to obtain model capability (success rate) and predictive power (predictive rate) information. The validation results show that the success and predictive rates of the W-i modelling exceeded 90% for the approaches that include the use of seismic factors. The final landslide susceptibility map can be used to identify and delineate unstable susceptibility-prone areas, and help planners to choose favourable locations for development schemes, such as infrastructure, construction and environmental protection schemes. The generic component of this research would allow application in other regions affected by high-intensity earthquakes and unstable terrain covering very large areas.Accession Number: WOS:000319199400009 Language: EnglishDocument Type: ArticleKeyWords Plus: SUPPORT VECTOR MACHINE; WEIGHTS-OF-EVIDENCE; ARTIFICIAL NEURAL-NETWORKS; SPATIAL PREDICTION MODELS; BHAGIRATHI GANGA VALLEY; ROCK SLOPE STABILITY; HAZARD ZONATION; LOGISTIC-REGRESSION; HONG-KONG; REGIONAddresses: [Xu, Chong; Xu, Xiwei] China Earthquake Adm, Inst Geol, Key Lab Act Tecton & Volcano, Beijing 100029, Peoples R China. [Yao, Qi] China Earthquake Networks Ctr, Beijing 100045, Peoples R China. [Wang, Yanying] NE Normal Univ, Sch Urban & Environm Sci, Changchun 130024, Jilin, Peoples R China. Reprint Address: Xu, C (reprint author), China Earthquake Adm, Inst Geol, Key Lab Act Tecton & Volcano, POB 9803, Beijing 100029, Peoples R China.E-mail Addresses: [email protected] Identifiers:



Author ResearcherID Number ORCID NumberXu, Chong B-6460-2012 0000-0002-3956-4925 Publisher: GEOLOGICAL SOC PUBL HOUSE Publisher Address: UNIT 7, BRASSMILL ENTERPRISE CENTRE, BRASSMILL LANE, BATH BA1 3JN, AVON, ENGLAND Web of Science Categories: Engineering, Geological; Geosciences, MultidisciplinaryResearch Areas: Engineering; GeologyIDS Number: 147WE ISSN: 1470-9236 29-char Source Abbrev.: Q J ENG GEOL HYDROGE ISO Source Abbrev.: Q. J. Eng. Geol. Hydrogeol. Source Item Page Count: 16

Funding:


This research is supported by the National Science Foundation of China (grant No. 41202235). We thank C. J. van Westen, S. Xu, X. Yao, F. Dai, F. Shi, H. He and X. Wu for their help in providing some of the remote sensing images for compiling the inventory of landslides triggered by the 2008 Wenchuan earthquake. We sincerely thank T. A. Dijkstra and the anonymous reviewers for their constructive comments that improved the paper.

Record 13 of 58Title: Prediction and comparison of urban growth by land suitability index mapping using GIS and RS in South Korea Author(s): Park, S (Park, Soyoung); Jeon, S (Jeon, Seongwoo); Kim, S (Kim, Shinyup); Choi, C (Choi, Chuluong)Source: LANDSCAPE AND URBAN PLANNING Volume: 99 Issue: 2 Pages: 104-114 DOI: 10.1016/j.landurbplan.2010.09.001 Published: FEB 28 2011 Times Cited in Web of Science Core Collection: 11 Total Times Cited: 16 Cited References: Allen J, 2003, CONSERV ECOL, V8 Angillieri MYE, 2010, GEOMORPHOLOGY, V114, P396, DOI 10.1016/j.geomorph.2009.08.003 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Clarke KC, 1997, ENVIRON PLANN B, V24, P247, DOI 10.1068/b240247 CONGALTON RG, 1983, PHOTOGRAMM ENG REM S, V49, P69 CONGALTON RG, 1991, REMOTE SENS ENVIRON, V37, P35, DOI 10.1016/0034-4257(91)90048-B Dai FC, 2001, ENG GEOL, V61, P257, DOI 10.1016/S0013-7952(01)00028-X Dragicevic S, 2000, FUZZY SET SYST, V113, P69, DOI 10.1016/S0165-0114(99)00013-5 GARRETT JH, 1994, J COMPUT CIVIL ENG, V8, P129, DOI 10.1061/(ASCE)0887-3801(1994)8:2(129) Gomez H, 2005, ENG GEOL, V78, P11, DOI 10.1016/j.enggeo.2004.10.004 Hu ZY, 2007, COMPUT ENVIRON URBAN, V31, P667, DOI 10.1016/j.compenvurbsys.2006.11.001 Jensen J.R., 1996, INTRO DIGITAL IMAGE JEONG JJ, 2002, J KOREA PLANNERS ASS, V37, P27 Kang BK, 1993, J GEOGRAPHIC INFORM, V5, P27 Kim JI, 2007, J KOREA PLANNERS ASS, V42, P31 KIM TJ, 2006, RES SEOUL OTHER CITI, V7, P95 Landis JD, 1997, LAND US MOD WO UNPUB Lee H.Y., 2008, J KOREAN URBAN GEOGR, V11, P1 Lee S, 2005, ENVIRON GEOL, V47, P982, DOI 10.1007/s00254-005-1228-z Lee S, 2007, LANDSLIDES, V4, P33, DOI 10.1007/s10346-006-0047-y Lee S, 2004, ENG GEOL, V71, P289, DOI 10.1016/S0013-7952(03)00142-X Lee S, 2006, ENVIRON GEOL, V50, P847, DOI 10.1007/s00254-006-0256-7 Lee S, 2003, ENVIRON GEOL, V44, P820, DOI 10.1007/s00254-003-0825-y Lee S, 2000, J GIS ASS KOREA, V8, P141 Li X, 2001, ENVIRON PLANN A, V33, P1445, DOI 10.1068/a33210 Liu Y., 2003, Computers, Environment and Urban Systems, V27, DOI 10.1016/S0198-9715(02)00069-8 LOMBARDO ST, 1986, ENVIRON PLANN A, V18, P341, DOI 10.1068/a180341 Long Ying, 2009, Tsinghua Science and Technology, V14, DOI 10.1016/S1007-0214(09)70149-X McFadden D, 1973, FRONTIERS ECONOMETRI PAOLA JD, 1995, INT J REMOTE SENS, V16, P3033 Pijanowski BC, 2002, COMPUT ENVIRON URBAN, V26, P552 Pontius RG, 2001, AGR ECOSYST ENVIRON, V85, P239, DOI 10.1016/S0167-8809(01)00187-6 Rumelhart D.E., 1986, PARALLEL DISTRIBUTED, V1, P318 SAATY TL, 1977, J MATH PSYCHOL, V15, P234, DOI 10.1016/0022-2496(77)90033-5 Saaty T.L., 1991, PREDICTION PROJECTIO, P251 Silva E. A., 2002, Computers, Environment and Urban Systems, V26, DOI 10.1016/S0198-9715(01)00014-X SWETS JA, 1988, SCIENCE, V240, P1285, DOI 10.1126/science.3287615 TOBLER WR, 1970, ECON GEOGR, V46, P234, DOI 10.2307/143141 Turner AK, 1996, LANDSLIDES INVESTIGA Uy Pham Duc, 2008, Urban Forestry & Urban Greening, V7, P25, DOI 10.1016/j.ufug.2007.09.002 Vaidya OS, 2006, EUR J OPER RES, V169, P1, DOI 10.1016/j.ejor.2004.04.028 Veldkamp A, 1996, ECOL MODEL, V85, P253, DOI 10.1016/0304-3800(94)00151-0 Verburg PH, 2002, ENVIRON MANAGE, V30, P391, DOI 10.1007/s00267-002-2630-x Wu F, 1998, ENVIRON PLANN B, V25, P103, DOI 10.1068/b250103 WU F, 2000, GIS GEOCOMPUTATION, P73 Wu FL, 2002, INT J GEOGR INF SCI, V16, P795, DOI 10.1080/13658810210157769 Wu FL, 1997, URBAN STUD, V34, P1851, DOI 10.1080/0042098975286 Yesilnacar E, 2005, ENG GEOL, V79, P251, DOI 10.1016/j.enggeo.2005.02.002 Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Zhou WY, 1999, IEEE T GEOSCI REMOTE, V37, P771 ZURADA JM, 1992, INTRO ARTIFICIAL NEU, P162Cited Reference Count: 51 Abstract: This study compares land suitability index (LSI) maps created using a geographic information system (GIS) with frequency ratio (FR), analytical hierarchy process (AHP), logistic regression (LR), and artificial neural network (ANN) approaches to forecasting urban land-use changes. Various social, political, topographic, and geographic factors were used as predictors of land-use change, including elevation, slope, aspect, distance from roads and urban areas, road ratio, land use, environmental score, and legal restrictions. Then. LSI maps were created using FR, AHP, LR, and ANN approaches, and significance and correlation were examined among the models using relative operating characteristic (ROC), overall accuracy, and kappa analyses. The ROC analyses gave results of 0.940, 0.937, 0.922, and 0.891 for the LR, FR, AHP, and ANN LSI maps, respectively. The highest correlation was found between the LR and AHP LSI maps (0.816911), and the lowest correlation was between the ANN and FR LSI maps (0.759701). The ANN approach produced the highest overall accuracy at 92.3%, followed by 91.74% for FR, 89.12% for AHP, and 88.93% for LR. In the kappa analysis, the highest (K) over cap statistic was 45.38% for FR, followed by 40.84% for ANN, 30 representing the city area. the ANN method had a relatively high value of 71.71%, and the FR, LR, and AHP methods had similar accuracies of 57.68, 55.05, and 54.31%, respectively. These results indicate that the FR, AHP, LR, and ANN approaches produced similar LSI maps for Korea. (C) 2010 Elsevier B.V. All rights reserved.Accession Number: WOS:000286541400005 Language: English



Document Type: ArticleAuthor Keywords: Land suitability index map; Geographic information system; Frequency ratio; Analytical hierarchy process; Logistic regression; Artificial neural networkKeyWords Plus: BACKPROPAGATION NEURAL-NETWORKS; LOGISTIC-REGRESSION MODELS; LANDSLIDE SUSCEPTIBILITY; CELLULAR-AUTOMATA; FREQUENCY RATIO; CALIBRATION; REGION; CLASSIFICATION; SIMULATION; ACCURACYAddresses: [Jeon, Seongwoo] Korea Environm Inst, Korea Adaptat Ctr Climate Change, Seoul 122706, South Korea. [Park, Soyoung; Choi, Chuluong] Pukyong Natl Univ, Dept Geoinformat Engn, Pusan 608737, South Korea. [Kim, Shinyup] Minist Environm Republ Korea, Dept Environm Data, Gwacheon Si 427729, Gyeonggi Do, South Korea. [Kim, Shinyup] Minist Environm Republ Korea, Informat Off, Gwacheon Si 427729, Gyeonggi Do, South Korea. Reprint Address: Jeon, S (reprint author), Korea Environm Inst, Korea Adaptat Ctr Climate Change, 290 Jinheung Ro, Seoul 122706, South Korea.E-mail Addresses: [email protected]; [email protected]; [email protected]; [email protected] Identifiers:

Author ResearcherID Number ORCID NumberZhao, Kefei A-1080-2012 0000-0002-0369-0874 Publisher: ELSEVIER SCIENCE BV Publisher Address: PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS Web of Science Categories: Ecology; Environmental Studies; Geography; Geography, Physical; Urban StudiesResearch Areas: Environmental Sciences & Ecology; Geography; Physical Geography; Urban StudiesIDS Number: 710UB ISSN: 0169-2046 29-char Source Abbrev.: LANDSCAPE URBAN PLAN ISO Source Abbrev.: Landsc. Urban Plan. Source Item Page Count: 11

Funding:

Funding Agency Grant NumberKorea Ministry of Environment Korea Environment Institute

This research was financially supported by Korea Ministry of Environment and Korea Environment Institute.

Record 14 of 58Title: Using DOProC Method in Structural Reliability Assessment Author(s): Krejsa, M (Krejsa, Martin); Janas, P (Janas, Petr); Cajka, R (Cajka, Radim)Edited by: Wang CK; Guo JSource: MECHATRONICS AND APPLIED MECHANICS II, PTS 1 AND 2 Book Series: Applied Mechanics and Materials Volume: 300-301 Pages: 860-869 DOI: 10.4028/www.scientific.net/AMM.300-301.860 Published: 2013 Times Cited in Web of Science Core Collection: 8 Total Times Cited: 8 Cited References: Akramin MRM, 2011, APPL MECH MATER, V52-54, P1358, DOI 10.4028/www.scientific.net/AMM.52-54.1358 Bergmeister K, 2009, STRUCT INFRASTRUCT E, V5, P267, DOI 10.1080/15732470601185612 Cajka R., 2012, RECENT RES ENV GEOLO, P447 Cajka R., 2012, P 8 INT C ENG COMP T, DOI [10.4203/ccp.100.114, DOI 10.4203/CCP.100.114] Cajka R, 2012, APPL MECH MATER, V188, P247, DOI 10.4028/www.scientific.net/AMM.188.247 Cajka R., 2012, ENERGY ENV STRUCTURA, V4, P435 Cajka R, 2005, IABSE Conference New Delhi, India 2005, P551 Der Kiureghian A, 1998, STRUCT SAF, V20, P37, DOI 10.1016/S0167-4730(97)00026-X Helton JC, 2003, RELIAB ENG SYST SAFE, V81, P23, DOI 10.1016/S0951-8320(03)00058-9 Janas P., 2010, T VSB TU OSTRAVA COS, V10, P1, DOI [10.2478/v10160-010-0010-7, DOI 10.2478/V10160-010-0010-7] Janas P, 2010, RELIABILITY, RISK AND SAFETY: THEORY AND APPLICATIONS VOLS 1-3, P1467 Janas P., 2009, P 12 INT C CIV STRUC Kala Z, 2007, THIN WALL STRUCT, V45, P861, DOI 10.1016/j.tws.2007.08.007 Konecny P, 2009, CIVIL COMP PROCEED, P542 Kralik J, 2010, RELIABILITY, RISK AND SAFETY: THEORY AND APPLICATIONS VOLS 1-3, P1369 Krejsa M., 2012, P 11 INT C COMP STRU, DOI [10.4203/ccp.99.113., DOI 10.4203/CCP.99.113] Krejsa M., 2011, T VSB TU OSTRAVA CON, V11, P1, DOI [10.2478/v10160-011-0007-x, DOI 10.2478/V10160-011-0007-X] Krejsa M., 2012, T VSB TU OSTRAVA CON, V12, P1, DOI [10.2478/v10160-012-0003-9, DOI 10.2478/V10160-012-0003-9] Krivy V., 2012, P 5 WSEAS INT C NAT Lokaj A, 2012, APPL MECH MATER, V137, P95, DOI 10.4028/www.scientific.net/AMM.137.95 Marschalko M, 2008, ARCH MIN SCI, V53, P397 RACKWITZ R, 1978, COMPUT STRUCT, V9, P489, DOI 10.1016/0045-7949(78)90046-9 Sejnoha M, 2007, PROBABILIST ENG MECH, V22, P206, DOI 10.1016/j.probengmech.2006.11.003 Thacker BH, 2006, STRUCT SAF, V28, P83, DOI 10.1016/j.strusafe.2004.11.003 Tvedt L, 2006, STRUCT SAF, V28, P150, DOI 10.1016/j.strusafe.2005.03.003 Vorechovsky M, 2009, PROBABILIST ENG MECH, V24, P452, DOI 10.1016/j.probengmech.2009.01.004Cited Reference Count: 26 Abstract: Reliability of load-carrying structures has been assessed by various calculation procedures based on probability theory and mathematic statistics, which have been becoming more and more popular. The calculation procedures are well-suited for the design of elements in load-carrying structures with the required level of reliability if at least some input parameters are random and contribute to a qualitatively higher level of the reliability assessment and, in turn, higher safety of those who use the buildings and facilities. This paper discusses application of the original and new probabilistic methods the Direct Optimized Probabilistic Calculation ("DOProC"), which uses a purely numerical approach without any simulation techniques. This provides more accurate solutions to probabilistic tasks, and, in some cases, to considerably faster completion of computations.Accession Number: WOS:000320567900167 Language: EnglishDocument Type: Proceedings PaperConference Title: 2nd International Conference on Mechatronics and Applied Mechanics (ICMAM2012) Conference Title: 2nd International Conference on Mechatronics and Applied Mechanics (ICMAM2012) Conference Date: DEC 06-07, 2012 Conference Date: DEC 08-09, 2012 Conference Location: Hong Kong, PEOPLES R CHINA Conference Location: Taipei, PEOPLES R CHINA Author Keywords: Direct Optimized Probabilistic Calculation; DOProC method; reliability assessment; probability of failure; failure function; load effect; structural resistance; probability distributionKeyWords Plus: UNCERTAINTYAddresses: [Krejsa, Martin; Janas, Petr] Tech Univ Ostrava, Fac Civil Engn, Dept Struct Mech, Ostrava 70833, Czech Republic. Reprint Address: Krejsa, M (reprint author), Tech Univ Ostrava, Fac Civil Engn, Dept Struct Mech, Ludvika Podeste 1875-17, Ostrava 70833, Czech Republic.E-mail Addresses: [email protected]; [email protected]; [email protected] Identifiers:



Author ResearcherID Number ORCID NumberCajka, Radim F-2889-2010 0000-0002-2346-062X Krejsa, Martin D-2107-2011 0000-0003-0571-2616 Publisher: TRANS TECH PUBLICATIONS LTD Publisher Address: LAUBLSRUTISTR 24, CH-8717 STAFA-ZURICH, SWITZERLAND Web of Science Categories: Engineering, Mechanical; Materials Science, Multidisciplinary; MechanicsResearch Areas: Engineering; Materials Science; MechanicsIDS Number: BFM85 ISSN: 1660-9336 ISBN: 978-3-03785-651-229-char Source Abbrev.: APPL MECH MATER Source Item Page Count: 10 Record 15 of 58Title: Landslide susceptibility mapping using Bayesian approach in the Sultan Mountains (AkAYehir, Turkey) Author(s): Ozdemir, A (Ozdemir, Adnan)Source: NATURAL HAZARDS Volume: 59 Issue: 3 Pages: 1573-1607 DOI: 10.1007/s11069-011-9853-1 Published: DEC 2011 Times Cited in Web of Science Core Collection: 8 Total Times Cited: 8 Cited References: Agterberg P, 2002, NAT RESOUR RES, V11, P249 Akgun A, 2008, ENVIRON GEOL, V54, P1127, DOI 10.1007/s00254-007-0882-8 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Saha AK, 2002, INT J REMOTE SENS, V23, P357, DOI 10.1080/01431160010014260 Sezer EA, 2011, EXPERT SYST APPL, V38, P8208, DOI 10.1016/j.eswa.2010.12.167 Sterlacchini S, 2011, GEOMORPHOLOGY, V125, P51, DOI 10.1016/j.geomorph.2010.09.004 Suzen ML, 2004, ENG GEOL, V71, P303, DOI 10.1016/S0013-7952(03)00143-1 TARBOTON D.G., 2002, TERRAIN ANAL USING D Vahidnia MH, 2010, COMPUT GEOSCI-UK, V36, P1101, DOI 10.1016/j.cageo.2010.04.004 Van Westen C.J., 2004, LANDSLIDES EVALUATIO, P39 Van Den Eeckhaut M, 2009, NAT HAZARD EARTH SYS, V9, P507 Van Den Eeckhaut M, 2010, GEOMORPHOLOGY, V115, P141, DOI 10.1016/j.geomorph.2009.09.042 van Westen CJ, 2008, ENG GEOL, V102, P112, DOI 10.1016/j.enggeo.2008.03.010 Van Westen CJ, 2003, NAT HAZARDS, V30, P399, DOI 10.1023/B:NHAZ.0000007097.42735.9e Wang HB, 2005, ENVIRON GEOL, V47, P956, DOI 10.1007/s00254-005-1225-2 Wilson JP, 2000, TERRAIN ANAL PRINCIP, P479 WU WM, 1995, WATER RESOUR RES, V31, P2097, DOI 10.1029/95WR01136 Yeon YK, 2010, ENG GEOL, V116, P274, DOI 10.1016/j.enggeo.2010.09.009 Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9 Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Youssef AM, 2009, NAT HAZARD EARTH SYS, V9, P751 Zhou CH, 2002, GEOMORPHOLOGY, V43, P197, DOI 10.1016/S0169-555X(01)00130-1 Zhu CH, 2009, 2009 INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND INFORMATION APPLICATION TECHNOLOGY, VOL III, PROCEEDINGS,, P342, DOI 10.1109/ESIAT.2009.187Cited Reference Count: 91 Abstract: Landslides cause heavy damage to property and infrastructure, in addition to being responsible for the loss of human lives in many parts of the Turkey. The paper presents GIS-based spatial data analysis for landslide susceptibility mapping in the regions of the Sultan Mountains, West of AkAYehir, and central part of Turkey. Landslides occur frequently in the area and seriously affect local living conditions. Therefore, spatial analysis of landslide susceptibility in the Sultan Mountains is important. The relationships between landslide distributions with the 19 landslide affecting parameters were analysed using a Bayesian model. In the study area, 90 landslides were observed. The landslides were randomly subdivided into 80 training landslides and 10 test landslides. A landslide susceptibility map was produced by using the training landslides. The test landslides were used in the accuracy control of the produced landslide susceptibility map. Approximately 9% of the study area was classified as high susceptibility zone. Medium, low and very low susceptibility zones covered 8, 23 and 60% of the study area, respectively. Most of the locations of the observed landslides actually fall into moderate (17.78%) and high (77.78. %) susceptibility zones of the produced landslide susceptibility map. This validates the applicability of proposed methods, approaches and the classification scheme. The high susceptibility zone is along both sides of the AkAYehir Fault and at the north-eastern slope of the Sultan Mountains. It was determined that the surface area of the Harlak and Deresenek formations, which have attained lithological characteristics of clayey limestone with a broken and separated base, and where area landslides occur, possesses an elevation of 1,100-1,600 m, a slope gradient of 25A degrees-35A degrees and a slope aspect of 22.5A degrees-157.5A degrees facing slopes.Accession Number: WOS:000296475400019 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslide; Susceptibility; GIS; Weights of evidence; The Sultan Mountains; TurkeyKeyWords Plus: ARTIFICIAL NEURAL-NETWORKS; CONDITIONAL ANALYSIS METHOD; REMOTE-SENSING DATA; OF-EVIDENCE MODEL; LOGISTIC-REGRESSION; PREDICTION MODELS; HAZARD ASSESSMENT; LIKELIHOOD RATIO; FREQUENCY RATIO; LANTAU-ISLANDAddresses: Selcuk Univ, Dept Geol Engn, Konya, Turkey. Reprint Address: Ozdemir, A (reprint author), Selcuk Univ, Dept Geol Engn, Konya, Turkey.E-mail Addresses: [email protected]: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences; Water ResourcesResearch Areas: Geology; Meteorology & Atmospheric Sciences; Water ResourcesIDS Number: 840XM ISSN: 0921-030X 29-char Source Abbrev.: NAT HAZARDS ISO Source Abbrev.: Nat. Hazards Source Item Page Count: 35 Record 16 of 58Title: Different types of learning algorithms of artificial neural network (ANN) models for prediction of gross calorific value (GCV) of coals Author(s): Yilmaz, I (Yilmaz, Isik); Erik, NY (Erik, Nazan Yalcin); Kaynar, O (Kaynar, Oguz)Source: SCIENTIFIC RESEARCH AND ESSAYS Volume: 5 Issue: 16 Pages: 2242-2249 Published: AUG 18 2010 Times Cited in Web of Science Core Collection: 8 Total Times Cited: 8 Cited References: Alvarez GM, 1999, INT J ROCK MECH MIN, V36, P339 *ASTM, 2004, 2004 ANN BOOK ASTM S, P504 BIANCHINI M, 1995, IEEE T NEURAL NETWOR, V6, P749, DOI 10.1109/72.377979 Broomhead D. 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Cited Reference Count: 31 Abstract: Correlations are very significant from earliest days, in some cases, it is essential as it is difficult to measure the amount directly, and in other cases, it is desirable to ascertain the results with other tests through correlations. Soft computing techniques are now being used as alternative statistical tools, and new techniques such as; artificial neural networks, fuzzy inference systems, genetic algorithms, etc. and their hybrid forms have been employed for developing of the predictive models to estimate the needed parameters, in the recent years. Determination of gross calorific value (GCV) of coals is very important to characterize coal and organic shales; it is difficult, expensive, time consuming and is a destructive analysis. In this paper, use of different learning algorithms of artificial neural networks such as MLP, RBF (exact), RBF (k-means) and RBF (SOM) for prediction of GCV was described. As a result of this paper, all models exhibited high performance for predicting GCV. Although the four different algorithms of ANN have almost the same prediction capability, accuracy of MLP has relatively higher than other models. The use of soft computing techniques will provide new approaches and methodologies in prediction of some parameters in the investigations about the fuels.Accession Number: WOS:000282053800019 Language: EnglishDocument Type: ArticleAuthor Keywords: ANN; MLP; RBF; soft computing; coal; gross calorific valueKeyWords Plus: ROCK PARAMETERS; CLASSIFICATION; LANDSLIDEAddresses: [Yilmaz, Isik; Erik, Nazan Yalcin] Cumhuriyet Univ, Fac Engn, Dept Geol Engn, TR-58140 Sivas, Turkey. [Kaynar, Oguz] Cumhuriyet Univ, Dept Management Informat Syst, TR-58140 Sivas, Turkey. Reprint Address: Yilmaz, I (reprint author), Cumhuriyet Univ, Fac Engn, Dept Geol Engn, TR-58140 Sivas, Turkey.E-mail Addresses: [email protected]: ACADEMIC JOURNALS Publisher Address: P O BOX 5170-00200 NAIROBI, VICTORIA ISLAND, LAGOS 73023, NIGERIA IDS Number: 653AI ISSN: 1992-2248 29-char Source Abbrev.: SCI RES ESSAYS ISO Source Abbrev.: Sci. Res. Essays Source Item Page Count: 8 Record 17 of 58Title: A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey Author(s): Ozdemir, A (Ozdemir, Adnan); Altural, T (Altural, Tolga)Source: JOURNAL OF ASIAN EARTH SCIENCES Volume: 64 Pages: 180-197 DOI: 10.1016/j.jseaes.2012.12.014 Published: MAR 5 2013 Times Cited in Web of Science Core Collection: 7 Total Times Cited: 8 Cited References: Akgun A, 2008, ENVIRON GEOL, V54, P1127, DOI 10.1007/s00254-007-0882-8 Akgun A, 2011, LANDSLIDES, DOI 10.1007/s10346-011-0283-7 Akgun A, 2010, ENVIRON EARTH SCI, V61, P595, DOI 10.1007/s12665-009-0373-1 Ayalew L, 2004, GEOMORPHOLOGY, V57, P95, DOI 10.1016/S0169-555X(03)00085-0 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Barbieri G, 2009, 18 WORLD IMACS MODSI Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Begueria S, 2006, NAT HAZARDS, V37, P315, DOI 10.1007/s11069-005-5182-6 Chen R.H., 1995, URBAN DISASTER MITIG, P231, DOI 10.1016/B978-008041920-6/50024-5 Clark W.A., 1986, STAT METHODS GEOGRAP Conforti M., 2011, NAT HAZARDS Corsini A, 2009, GEOMORPHOLOGY, V111, P79, DOI 10.1016/j.geomorph.2008.03.015 Dai FC, 2001, ENVIRON GEOL, V40, P381, DOI 10.1007/s002540000163 Demirkol C., 1977, 6305 MAD TETK AR ENS El Khattabi J, 2004, ENG GEOL, V71, P255, DOI 10.1016/S0013-7952(03)00137-6 Fernandes NF, 2004, CATENA, V55, P163, DOI 10.1016/S0341-8162(03)00115-2 Fourniadis IG, 2007, GEOMORPHOLOGY, V84, P126, DOI 10.1016/j.geomorph.2006.07.020 Galli M, 2008, GEOMORPHOLOGY, V94, P268, DOI 10.1016/j.geomorph.2006.09.023 Gemitzi A., 2010, GLOBAL NEST J, V12, P1 Gokceoglu C, 2005, ENG GEOL, V81, P65, DOI 10.1016/j.enggeo.2005.07.011 Guzzetti F, 2006, GEOMORPHOLOGY, V81, P166, DOI 10.1016/j.geomorph.2006.04.007 Guzzetti F, 2005, GEOMORPHOLOGY, V72, P272, DOI 10.1016/j.geomorph.2005.06.002 Havenith HB, 2006, LANDSLIDES, V3, P39, DOI 10.1007/s10346-005-0005-0 Hosmer DW, 2000, APPL LOGISTIC REGRES ILWIS, 2001, ILWIS 3 0 US GUID Intarawichian N., 2008, THESIS SURANAREE U T Intarawichian N, 2011, ENVIRON EARTH SCI, V64, P2271, DOI 10.1007/s12665-011-1055-3 Iverson RM, 1997, ANNU REV EARTH PL SC, V25, P85, DOI 10.1146/annurev.earth.25.1.85 Kanungo DP, 2006, ENG GEOL, V85, P347, DOI 10.1016/j.enggeo.2006.03.004 Khanh NQ, 2009, LANDSLIDE HAZARD ASS Lee S, 2005, INT J REMOTE SENS, V26, P1477, DOI 10.1080/01431160412331331012 Lee S, 2005, ENVIRON GEOL, V47, P982, DOI 10.1007/s00254-005-1228-z Lee S, 2007, LANDSLIDES, V4, P33, DOI 10.1007/s10346-006-0047-y Lee S, 2006, ENVIRON GEOL, V50, P847, DOI 10.1007/s00254-006-0256-7 Long N.T., 2008, THESIS U BRUSSEL Mathew J, 2007, INT J REMOTE SENS, V28, P2257, DOI 10.1080/01431160600928583 Menard S., 2002, APPL LOGISTIC REGRES Nagarajan R, 2000, B ENG GEOL ENVIRON, V58, P275, DOI 10.1007/s100649900032 Nandi A., 2009, ENG GEOL, V110, P11 Nefeslioglu HA, 2008, ENG GEOL, V97, P171, DOI 10.1016/j.enggeo.2008.01.004 Neuhauser B, 2007, GEOMORPHOLOGY, V86, P12, DOI 10.1016/j.geomorph.2006.08.002 Oh HJ, 2011, J HYDROL, V399, P158, DOI 10.1016/j.jhydrol.2010.12.027 Oh HJ, 2010, ENG GEOL, V115, P36, DOI 10.1016/j.enggeo.2010.06.015 Oh HJ, 2010, ENVIRON EARTH SCI, V60, P1317, DOI 10.1007/s12665-009-0272-5 Ozdemir A, 2009, ENVIRON GEOL, V57, P1675, DOI 10.1007/s00254-008-1449-z Ozdemir A, 2011, NAT HAZARDS, V59, P1573, DOI 10.1007/s11069-011-9853-1 Poudyal CP, 2010, ENVIRON EARTH SCI, V61, P1049, DOI 10.1007/s12665-009-0426-5 Pradhan B, 2011, ENVIRON ECOL STAT, V18, P471, DOI 10.1007/s10651-010-0147-7 Pradhan B, 2010, ENVIRON EARTH SCI, V60, P1037, DOI 10.1007/s12665-009-0245-8 Radbruch-Hall, 1982, 1183 USGS Regmi NR, 2010, GEOMORPHOLOGY, V115, P172, DOI 10.1016/j.geomorph.2009.10.002 Remondo J, 2003, NAT HAZARDS, V30, P267, DOI 10.1023/B:NHAZ.0000007202.12543.3a Sidle R.C., 2006, WATER RESOURCES MONO, V18, P312, DOI DOI 10.1029/WM018 SPSS, 2004, SPSS 13 0 COMM SINT Tangestani H.M., 2004, AUST J EARTH SCI, V51, P439 Uromeihy A., 2000, B ENG GEOL ENVIRON, V58, P207, DOI 10.1007/s100640050076 den Eeckhaut M, 2006, GEOMORPHOLOGY, V76, P392, DOI 10.1016/j.geomorph.2005.12.003 Van Den Eeckhaut M, 2010, GEOMORPHOLOGY, V115, P141, DOI 10.1016/j.geomorph.2009.09.042 Van Westen CJ, 2003, NAT HAZARDS, V30, P399, DOI 10.1023/B:NHAZ.0000007097.42735.9e



Varnes D. J., 1984, NAT HAZARDS, V3, P63 Wilson J., 2000, TERRAIN ANAL PRINCIP Yalcin A, 2011, CATENA, V85, P274, DOI 10.1016/j.catena.2011.01.014 Yeon YK, 2010, ENG GEOL, V116, P274, DOI 10.1016/j.enggeo.2010.09.009 Yesilnacar E, 2005, ENG GEOL, V79, P251, DOI 10.1016/j.enggeo.2005.02.002 Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9 Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2007, ENG GEOL, V90, P89, DOI 10.1016/j.enggeo.2006.12.004 Yilmaz I, 2010, ENVIRON EARTH SCI, V60, P505, DOI 10.1007/s12665-009-0191-5 Zhu Lei, 2006, Journal of Zhejiang University (Science), V7, DOI 10.1631/jzus.2006.A2007Cited Reference Count: 69 Abstract: This study evaluated and compared landslide susceptibility maps produced with three different methods, frequency ratio, weights of evidence, and logistic regression, by using validation datasets. The field surveys performed as part of this investigation mapped the locations of 90 landslides that had been identified in the Sultan Mountains of south-western Turkey. The landslide influence parameters used for this study are geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transportation capacity index, distance to drainage, distance to fault, drainage density, fault density, and spring density maps. The relationships between landslide distributions and these parameters were analysed using the three methods, and the results of these methods were then used to calculate the landslide susceptibility of the entire study area. The accuracy of the final landslide susceptibility maps was evaluated based on the landslides observed during the fieldwork, and the accuracy of the models was evaluated by calculating each model's relative operating characteristic curve. The predictive capability of each model was determined from the area under the relative operating characteristic curve and the areas under the curves obtained using the frequency ratio, logistic regression, and weights of evidence methods are 0.976, 0.952, and 0.937, respectively. These results indicate that the frequency ratio and weights of evidence models are relatively good estimators of landslide susceptibility in the study area. Specifically, the results of the correlation analysis show a high correlation between the frequency ratio and weights of evidence results, and the frequency ratio and logistic regression methods exhibit correlation coefficients of 0.771 and 0.727, respectively. The frequency ratio model is simple, and its input, calculation and output processes are easily understood. The interpretations of the susceptibility map reveal that geology, slope steepness, slope aspect, and elevation played major roles in landslide occurrence and distribution in the Sultan Mountains. The landslide susceptibility maps produced from this study could therefore assist planners and engineers during development and land-use planning. (C) 2012 Elsevier Ltd. All rights reserved.Accession Number: WOS:000316706500015 Language: EnglishDocument Type: ArticleAuthor Keywords: Frequency ratio; Logistic regression; Weights of evidence; Landslide susceptibilityKeyWords Plus: ARTIFICIAL NEURAL-NETWORKS; CONDITIONAL-PROBABILITY; HAZARD ASSESSMENT; SAMPLING STRATEGIES; AREA; MODELS; GIS; VALIDATION; REGION; BASINAddresses: [Ozdemir, Adnan] Selcuk Univ, Dept Geol Engn, Konya, Turkey. [Altural, Tolga] Selcuk Univ, Grad Sch Nat & Appl Sci, Konya, Turkey. Reprint Address: Ozdemir, A (reprint author), Selcuk Univ, Dept Geol Engn, Konya, Turkey.E-mail Addresses: [email protected]: PERGAMON-ELSEVIER SCIENCE LTD Publisher Address: THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND Web of Science Categories: Geosciences, MultidisciplinaryResearch Areas: GeologyIDS Number: 113YV ISSN: 1367-9120 29-char Source Abbrev.: J ASIAN EARTH SCI ISO Source Abbrev.: J. Asian Earth Sci. Source Item Page Count: 18 Record 18 of 58Title: GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi-criteria evaluation models (North of Tehran, Iran) Author(s): Pourghasemi, HR (Pourghasemi, H. R.); Moradi, HR (Moradi, H. R.); Aghda, SMF (Aghda, S. M. Fatemi); Gokceoglu, C (Gokceoglu, C.); Pradhan, B (Pradhan, B.)Source: ARABIAN JOURNAL OF GEOSCIENCES Volume: 7 Issue: 5 Pages: 1857-1878 DOI: 10.1007/s12517-012-0825-x Published: MAY 2014 Times Cited in Web of Science Core Collection: 6 Total Times Cited: 6 Cited References: Akgun A, 2012, COMPUT GEOSCI-UK, V38, P23, DOI 10.1016/j.cageo.2011.04.012 Akgun A, 2012, LANDSLIDES, V9, P93, DOI 10.1007/s10346-011-0283-7 Akgun A, 2010, ENVIRON EARTH SCI, V61, P595, DOI 10.1007/s12665-009-0373-1 Aleotti P, 1999, B ENG ENV, V58, P21, DOI DOI 10.1007/S100640050066 Althuwaynee OF, 2012, COMPUT GEOSCI-UK, V44, P120, DOI 10.1016/j.cageo.2012.03.003 ANIYA M, 1985, ANN ASSOC AM GEOGR, V75, P102, DOI 10.1111/j.1467-8306.1985.tb00061.x Atkinson PM, 2011, GEOMORPHOLOGY, V130, P55, DOI 10.1016/j.geomorph.2011.02.001 Ayalew L, 2004, LANDSLIDES, V1, P73, DOI 10.1007/s10346-003-0006-9 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Ballabio C, 2012, MATH GEOSCI, V44, P47, DOI 10.1007/s11004-011-9379-9 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Beven K. 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Yeon YK, 2012, ENG GEOL, V116, P274 Yesilnacar E, 2005, ENG GEOL, V79, P251, DOI 10.1016/j.enggeo.2005.02.002 Yesilnacar EK, 2005, THESIS U MELBOURNE, P423 Yilmaz C, 2012, ENVIRON EARTH SCI, V65, P2161, DOI 10.1007/s12665-011-1196-4 Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9 Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P297, DOI 10.1007/s10064-009-0185-2 Zare M, 2013, ARAB J GEOSCI, V6, P2873, DOI 10.1007/s12517-012-0610-xCited Reference Count: 140 Abstract: The aim of this study is to produce landslide susceptibility mapping by probabilistic likelihood ratio (PLR) and spatial multi-criteria evaluation (SMCE) models based on geographic information system (GIS) in the north of Tehran metropolitan, Iran. The landslide locations in the study area were identified by interpretation of aerial photographs, satellite images, and field surveys. In order to generate the necessary factors for the SMCE approach, remote sensing and GIS integrated techniques were applied in the study area. Conditioning factors such as slope degree, slope aspect, altitude, plan curvature, profile curvature, surface area ratio, topographic position index, topographic wetness index, stream power index, slope length, lithology, land use, normalized difference vegetation index, distance from faults, distance from rivers, distance from roads, and drainage density are used for landslide susceptibility mapping. Of 528 landslide locations, 70 % were used in landslide susceptibility mapping, and the remaining 30 % were used for validation of the maps. Using the above conditioning factors, landslide susceptibility was calculated using SMCE and PLR models, and the results were plotted in ILWIS-GIS. Finally, the two landslide susceptibility maps were validated using receiver operating characteristic curves and seed cell area index methods. The validation results showed that area under the curve for SMCE and PLR models is 76.16 and 80.98 %, respectively. The results obtained in this study also showed that the probabilistic likelihood ratio model performed slightly better than the spatial multi-criteria evaluation. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose.Accession Number: WOS:000334686100015 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslide susceptibility; Spatial multi-criteria evaluation; Frequency ratio; GIS; Tehran metropolitanKeyWords Plus: ARTIFICIAL NEURAL-NETWORKS; ANALYTICAL HIERARCHY PROCESS; SUPPORT VECTOR MACHINE; LOGISTIC-REGRESSION; FREQUENCY RATIO; FUZZY-LOGIC; CONDITIONAL-PROBABILITY; DEMPSTER-SHAFER; INFORMATION-SYSTEM; MATRIX-METHODAddresses: [Pourghasemi, H. R.; Moradi, H. R.] Tarbiat Modares Univ, Coll Nat Resources & Marine Sci, Dept Watershed Management Engn, Noor, Mazandaran, Iran. [Aghda, S. M. Fatemi] Tarbiat Moallem Univ, Dept Engn Geol, Tehran, Iran. [Gokceoglu, C.] Hacettepe Univ, Fac Engn, Dept Geol Engn, Appl Geol Div, Ankara, Turkey. [Pradhan, B.] Univ Putra Malaysia, Dept Civil Engn, Fac Engn, Serdang 43400, Selangor, Malaysia. Reprint Address: Moradi, HR (reprint author), Tarbiat Modares Univ, Coll Nat Resources & Marine Sci, Dept Watershed Management Engn, Noor, Mazandaran, Iran.E-mail Addresses: [email protected]; [email protected]: SPRINGER HEIDELBERG Publisher Address: TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY Web of Science Categories: Geosciences, MultidisciplinaryResearch Areas: GeologyIDS Number: AF4ME ISSN: 1866-7511 eISSN: 1866-7538 29-char Source Abbrev.: ARAB J GEOSCI ISO Source Abbrev.: Arab. J. Geosci. Source Item Page Count: 22 Record 19 of 58Title: Creating infrastructure for seismic microzonation by Geographical Information Systems (GIS): A case study in the North Anatolian Fault Zone (NAFZ) Author(s): Turk, T (Turk, T.); Gumusay, U (Gumusay, U.); Tatar, O (Tatar, O.)Source: COMPUTERS & GEOSCIENCES Volume: 43 Pages: 167-176 DOI: 10.1016/j.cageo.2011.10.006 Published: JUN 2012 Times Cited in Web of Science Core Collection: 5 Total Times Cited: 5 Cited References: Aktimur H.T., 1989, 8894 GEN DIR MIN RES Aktimur H.T., 1992, GEN DIRECTORATE MINE, V114, P36 ALEXANDER DE, 1995, ADV NAT TECHNOL HAZ, V5, P1 Altan O., 2005, USE PHOTOGRAMMETRY R Anastasiadis A, 2001, PURE APPL GEOPHYS, V158, P2597, DOI 10.1007/PL00001188 Antoniou AA, 2008, NAT HAZARDS, V47, P369, DOI 10.1007/s11069-008-9226-6 Barka A., 1996, SEISMOL SOC AM B, V86, P1238 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 [Bogazici University Istanbul Technical University Middle East Technical University Yildiz Technical University], 2003, EARTHQ MAST PLAN IST Canik B., 2000, ERBAA TOKAT ZEMINLER Carniel R, 2006, SOIL DYN EARTHQ ENG, V26, P55, DOI 10.1016/j.soildyn.2005.08.005 Casson B, 2005, NAT HAZARD EARTH SYS, V5, P425 Erbaa Municipality, 2008, REP TURK ERB MUN Eyidogan H., 1991, MACROSEISMIC GUIDE L, P198 Galderisi A, 2008, NAT HAZARDS, V46, P221, DOI 10.1007/s11069-008-9224-8 [General Directorate of Disaster Affairs of Turkey (GDDA) World Institute for Disaster Risk Management (DRM)], 2004, MAN SEISM MICR MUN W General Directorate of State Hydraulic Works, 1971, ERB PLAIN HYDR INV R Grasso S, 2009, SOIL DYN EARTHQ ENG, V29, P953, DOI 10.1016/j.soildyn.2008.11.006 Hong Y, 2007, NAT HAZARDS, V43, P245, DOI 10.1007/s11069-006-9104-z Idriss I.M., 1968, J SOIL MECH FOUND DI, V94, P1003 Inel M., 2007, NAT HAZARDS, V46, P265 Jimenez MJ, 2000, SOIL DYN EARTHQ ENG, V19, P289, DOI 10.1016/S0267-7261(00)00007-5 Kienzle A, 2006, ENG GEOL, V87, P13, DOI 10.1016/j.enggeo.2006.05.008 Kilic H, 2006, ENG GEOL, V86, P238, DOI 10.1016/j.enggeo.2006.04.007 Kiremidjian A.S., 1997, GEOTECHNICAL SPECIAL, V67, P1 Kohler P, 2006, NAT HAZARD EARTH SYS, V6, P621 Kolat C, 2006, ENG GEOL, V87, P241, DOI 10.1016/j.enggeo.2006.07.005 Lantada N., 2007, NAT HAZARDS, V51, P501 Lee S, 2005, ENVIRON GEOL, V47, P982, DOI 10.1007/s00254-005-1228-z Li J., 2005, HIGH RESOLUTION SATE Mancini F, 2010, NAT HAZARD EARTH SYS, V10, P1851, DOI 10.5194/nhess-10-1851-2010 Mhaske Y.S., 2010, J APPL GEOPHYS, V70, P216 Nath SK, 2005, J ASIAN EARTH SCI, V25, P329, DOI 10.1016/j.jseaes.2004.03.002 Nichol JE, 2006, GEOMORPHOLOGY, V76, P68, DOI 10.1016/j.geomorph.2005.10.001 Pal I, 2007, NAT HAZARDS, V45, P333 Papadimitriou AG, 2008, COMPUT GEOTECH, V35, P505, DOI 10.1016/j.compgeo.2007.10.001 Sengor AMC, 2005, ANNU REV EARTH PL SC, V33, P37, DOI 10.1146/annurev.earth.32.101802.120415 Sun CG, 2008, COMPUT GEOTECH, V35, P436, DOI 10.1016/j.compgeo.2007.08.001 Tatar O., 2010, ACTIVE FAULT ZONE NA Thierry P., 2007, NAT HAZARDS, V45, P429 Tsai F, 2010, NAT HAZARD EARTH SYS, V10, P2179, DOI 10.5194/nhess-10-2179-2010



Turk T., 2004, THESIS YILDIZ TU IST Turk T., 2009, THESIS YILDIZ TU IST Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I., 1998, THESIS CUMHURIYET U Youd TL, 2001, J GEOTECH GEOENVIRON, V127, P817, DOI 10.1061/(ASCE)1090-0241(2001)127:10(817)Cited Reference Count: 46 Abstract: Although there are many studies for seismic microzonation in the literature, these studies have not covered the whole seismic microzonation processes. Moreover, they have not sufficiently focused on the important subjects, such as significance and use of aerial photos in seismic microzonation studies, data types used for seismic microzonation, and integrating these data by GIS. This study suggests a GIS-based model that can be used for all settlements that are at risk of natural disaster, with a view to taking necessary measures against such natural disasters (especially earthquakes). This model was applied so as to take the measures needed for the town of Erbaa located on the western part of the eastern segments of the North Anatolian Fault Zone (NAFZ), a settlement with earthquake risk on the NAFZ. During creation of the system, geological, geotechnical data and data produced from aerial photos were integrated and assessed on a GIS environment The infrastructure for seismic microzonation was created using this model. The potential areas for soil liquefaction were detected in the study area. Thus, the results were produced to assist in seismic microzonation. (C) 2011 Elsevier Ltd. All rights reserved.Accession Number: WOS:000305202500019 Language: EnglishDocument Type: ArticleAuthor Keywords: GIS; North Anatolian Fault Zone; Photogrammetry; Seismic microzonation; Spatiotemporal analysisKeyWords Plus: LANDSLIDE SUSCEPTIBILITY; EARTHQUAKE; HAZARD; TOOL; IMAGES; MODEL; RISKAddresses: [Turk, T.] Cumhuriyet Univ, Dept Geomat, Fac Engn, TR-58140 Sivas, Turkey. [Gumusay, U.] Yildiz Tekn Univ, Fac Civil Engn, Dept Geomat, TR-34220 Istanbul, Turkey. [Tatar, O.] Canakkale Onsekiz Mart Univ, Dept Geol, Fac Engn & Architecture, TR-17020 Canakkale, Turkey. Reprint Address: Turk, T (reprint author), Cumhuriyet Univ, Dept Geomat, Fac Engn, TR-58140 Sivas, Turkey.E-mail Addresses: [email protected] Identifiers:

Author ResearcherID Number ORCID NumberTurk, Tarik F-3151-2012 0000-0002-2671-7590 Publisher: PERGAMON-ELSEVIER SCIENCE LTD Publisher Address: THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND Web of Science Categories: Computer Science, Interdisciplinary Applications; Geosciences, MultidisciplinaryResearch Areas: Computer Science; GeologyIDS Number: 957YH ISSN: 0098-3004 29-char Source Abbrev.: COMPUT GEOSCI-UK ISO Source Abbrev.: Comput. Geosci. Source Item Page Count: 10

Funding:

Funding Agency Grant NumberTurkish State Planning Organization (DPT) Cumhuriyet University, Sivas DPT 2006K 120220 CUBAP M 338

The authors would like to thank Turkish State Planning Organization (DPT) and Cumhuriyet University, Sivas for financial support under Project number DPT 2006K 120220 and CUBAP project numbered M 338. In addition, they would like to thank the reviewers for their valuable contributions.

Record 20 of 58Title: Landslide susceptibility mapping by binary logistic regression, analytical hierarchy process, and statistical index models and assessment of their performances Author(s): Pourghasemi, HR (Pourghasemi, H. R.); Moradi, HR (Moradi, H. R.); Aghda, SMF (Aghda, S. M. Fatemi)Source: NATURAL HAZARDS Volume: 69 Issue: 1 Pages: 749-779 DOI: 10.1007/s11069-013-0728-5 Published: OCT 2013 Times Cited in Web of Science Core Collection: 4 Total Times Cited: 4 Cited References: Akgun A, 2012, COMPUT GEOSCI-UK, V38, P23, DOI 10.1016/j.cageo.2011.04.012 Akgun A, 2010, ENVIRON EARTH SCI, V61, P595, DOI 10.1007/s12665-009-0373-1 Aleotti P, 1999, B ENG ENV, V58, P21, DOI DOI 10.1007/S100640050066 Atkinson PM, 1998, COMPUT GEOSCI-UK, V24, P373, DOI 10.1016/S0098-3004(97)00117-9 Ayalew L, 2005, ENG GEOL, V81, P432, DOI 10.1016/j.enggeo.2005.08.004 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Bai SB, 2010, GEOMORPHOLOGY, V115, P23, DOI 10.1016/j.geomorph.2009.09.025 Ballabio C, 2012, MATH GEOSCI, V44, P47, DOI 10.1007/s11004-011-9379-9 Barredo J.I., 2000, INT J APPL EARTH OBS, V2, P9, DOI DOI 10.1016/S0303-2434(00)85022-9 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Bijukchhen SM, 2013, ARAB J GEOSCI, V6, P2727, DOI 10.1007/s12517-012-0569-7 Bui DT, 2011, COMPUT GEOSCI, DOI [10.1016/j.cageo.2011.10.031, DOI 10.1016/J.CAGE0.2011.10.031] Bui DT, 2011, NAT HAZARDS, V59, P1413, DOI 10.1007/s11069-011-9844-2 CARRARA A, 1995, ADV NAT TECHNOL HAZ, V5, P135 Cevik E, 2003, ENVIRON GEOL, V44, P949, DOI 10.1007/s00254-003-0838-6 Chen Y, 2009, P 18 WORLD IMACS MOD Constantin M, 2011, ENVIRON EARTH SCI, V63, P397, DOI 10.1007/s12665-010-0724-y Dahal RK, 2008, ENVIRON GEOL, V54, P311, DOI 10.1007/s00254-007-0818-3 Demir G, 2013, NAT HAZARDS, V65, P1481, DOI 10.1007/s11069-012-0418-8 Devkota KC, 2013, NAT HAZARDS, V65, P135, DOI 10.1007/s11069-012-0347-6 ECInc (Expert Choice Inc.), 1995, DEC SUPP SOFTW TUT E Egan JP, 1975, NY ACAD, V195, P266 Ercanoglu M, 2004, ENG GEOL, V75, P229, DOI 10.1016/j.enggeo.2004.06.001 Ercanoglu M, 2011, ENVIRON EARTH SCI, V64, P949, DOI 10.1007/s12665-011-0912-4 Erner A, 2010, LANDSLIDES, V7, P55 Erner A, 2012, ENVIRON EARTH SCI, V66, P859 Esmali Ouri A, 2009, INT C ACRS 2009 BEIJ Falaschi F, 2009, NAT HAZARDS, V50, P551, DOI 10.1007/s11069-009-9356-5 Feizizadeh B, 2013, J ENVIRON PLANN MAN, V56, P1, DOI 10.1080/09640568.2011.646964 Feizizadeh B, 2013, NAT HAZARDS, V65, P2105, DOI 10.1007/s11069-012-0463-3 Garcia-Rodriguez MJ, 2008, GEOMORPHOLOGY, V95, P172, DOI 10.1016/j.geomorph.2007.06.001 Ghosh S, 2011, THESIS U TWENTE, P214 Guzzetti F, 1999, GEOMORPHOLOGY, V31, P81 Guzzetti F., 2005, THESIS RHEINISCHEN F Guzzetti F, 2000, ENVIRON MANAGE, V25, P247, DOI 10.1007/s002679910020 HALL FG, 1995, REMOTE SENS ENVIRON, V51, P138, DOI 10.1016/0034-4257(94)00071-T



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The study area covers the north of Tehran metropolitan, Iran. When conducting the study, in the first stage, a landslide inventory map with a total of 528 landslide locations was compiled from various sources such as aerial photographs, satellite images, and field surveys. Then, the landslide inventory was randomly split into a testing dataset 70 % (370 landslide locations) for training the models, and the remaining 30 % (158 landslides locations) was used for validation purpose. Twelve landslide conditioning factors such as slope degree, slope aspect, altitude, plan curvature, normalized difference vegetation index, land use,



lithology, distance from rivers, distance from roads, distance from faults, stream power index, and slope-length were considered during the present study. Subsequently, landslide susceptibility maps were produced using binary logistic regression (BLR), analytical hierarchy process (AHP), and statistical index (SI) models in ArcGIS. The validation dataset, which was not used in the modeling process, was considered to validate the landslide susceptibility maps using the receiver operating characteristic curves and frequency ratio plot. The validation results showed that the area under the curve (AUC) for three mentioned models vary from 0.7570 to 0.8520 . Also, plot of the frequency ratio for the four landslide susceptibility classes of the three landslide susceptibility models was validated our results. Hence, it is concluded that the binary logistic regression model employed in this study showed reasonably good accuracy in predicting the landslide susceptibility of study area. Meanwhile, the results obtained in this study also showed that the statistical index model can be used as a simple tool in the assessment of landslide susceptibility when a sufficient number of data are obtained.Accession Number: WOS:000325101100040 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslide susceptibility mapping; Binary logistic regression; AHP; Statistical index; North of Tehran; IranKeyWords Plus: SUPPORT VECTOR MACHINE; ARTIFICIAL NEURAL-NETWORKS; CONDITIONAL-PROBABILITY; FREQUENCY RATIO; FUZZY-LOGIC; GOLESTAN PROVINCE; HAZARD ZONATION; NATURAL SLOPES; GIS; TURKEYAddresses: [Pourghasemi, H. R.; Moradi, H. R.] Tarbiat Modares Univ, Dept Watershed Management Engn, Coll Nat Resources & Marine Sci, Noor, Mazandaran, Iran. [Aghda, S. M. Fatemi] Kharazmi Univ, Tarbiat Moallem Univ, Dept Geol Engn, Tehran, Iran. [Aghda, S. M. Fatemi] Minist Rd & Urban Dev, Rd Housing & Urban Dev Res Ctr, Tehran, Iran. Reprint Address: Moradi, HR (reprint author), Tarbiat Modares Univ, Dept Watershed Management Engn, Coll Nat Resources & Marine Sci, Noor, Mazandaran, Iran.E-mail Addresses: [email protected]; [email protected]: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences; Water ResourcesResearch Areas: Geology; Meteorology & Atmospheric Sciences; Water ResourcesIDS Number: 227GW ISSN: 0921-030X eISSN: 1573-0840 29-char Source Abbrev.: NAT HAZARDS ISO Source Abbrev.: Nat. Hazards Source Item Page Count: 31 Record 21 of 58Title: Evaluation of environmental parameters in logistic regression models for landslide susceptibility mapping Author(s): Suzen, ML (Suzen, Mehmet Lutfi); Kaya, BS (Kaya, Basak Sener)Source: INTERNATIONAL JOURNAL OF DIGITAL EARTH Volume: 5 Issue: 4 Pages: 338-355 DOI: 10.1080/17538947.2011.586443 Published: 2012 Times Cited in Web of Science Core Collection: 4 Total Times Cited: 4 Cited References: Afifi A.A., 1998, COMPUTER AIDED MULTI Akgun A, 2007, ENVIRON GEOL, V51, P1377, DOI 10.1007/s00254-006-0435-6 Akgun A, 2008, ENVIRON GEOL, V54, P1127, DOI 10.1007/s00254-007-0882-8 Atkinson PM, 1998, COMPUT GEOSCI-UK, V24, P373, DOI 10.1016/S0098-3004(97)00117-9 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Aydan O, 2002, ENVIRON GEOL, V42, P621, DOI 10.1007/s00254-002-0565-4 Bai SB, 2010, GEOMORPHOLOGY, V115, P23, DOI 10.1016/j.geomorph.2009.09.025 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Can T, 2005, GEOMORPHOLOGY, V72, P250, DOI 10.1016/j.geomorph.2005.05.011 CARRARA A, 1991, EARTH SURF PROCESSES, V16, P427, DOI 10.1002/esp.3290160505 Chauhan S, 2010, LANDSLIDES, V7, P411, DOI 10.1007/s10346-010-0202-3 Chen ZH, 2007, NAT HAZARDS, V42, P75, DOI 10.1007/s11069-006-9061-6 Dai FC, 2003, EARTH SURF PROC LAND, V28, P527, DOI 10.1002/esp.456 Das I, 2010, GEOMORPHOLOGY, V114, P627, DOI 10.1016/j.geomorph.2009.09.023 Davis JC, 2006, COMPUT GEOSCI-UK, V32, P1120, DOI 10.1016/j.cageo.2006.02.006 Demirtas R., 1996, SEISMOTECTONICS TURK Duman TY, 2006, ENVIRON GEOL, V51, P241, DOI 10.1007/s00254-006-0322-1 Ercanoglu M., 2003, THESIS HACETTEPE U Ercanoglu M, 2002, ENVIRON GEOL, V41, P720, DOI 10.1007/s00254-001-0454-2 Ercanoglu M, 2004, NAT HAZARDS, V32, P1, DOI 10.1023/B:NHAZ.0000026786.85589.4a Gorum T, 2008, NAT HAZARDS, V46, P323, DOI 10.1007/s11069-007-9190-6 Greco R, 2007, ENG GEOL, V89, P47, DOI 10.1016/j.enggeo.2006.09.006 Guzzetti F, 2006, GEOMORPHOLOGY, V81, P166, DOI 10.1016/j.geomorph.2006.04.007 Guzzetti F, 2005, GEOMORPHOLOGY, V72, P272, DOI 10.1016/j.geomorph.2005.06.002 Hosmer DW, 2000, APPL LOGISTIC REGRES Kleinbaum D.G., 1991, LOGISTIC REGRESSION Lee S, 2001, ENVIRON GEOL, V40, P1095, DOI 10.1007/s002540100310 Mancini F, 2010, NAT HAZARD EARTH SYS, V10, P1851, DOI 10.5194/nhess-10-1851-2010 Mathew J, 2009, LANDSLIDES, V6, P17, DOI 10.1007/s10346-008-0138-z MOORE ID, 1991, HYDROL PROCESS, V5, P1, DOI 10.1002/hyp.3360050102 MOORE ID, 1986, SOIL SCI SOC AM J, V50, P1294 MOORE ID, 1993, SOIL SCI SOC AM J, V57, P443 Muratoglu B., 2009, THESIS MIDDLE E TU Nandi A., 2009, ENG GEOL, V110, P11 Nefeslioglu HA, 2008, ENG GEOL, V97, P171, DOI 10.1016/j.enggeo.2008.01.004 Nefeslioglu HA, 2008, GEOMORPHOLOGY, V94, P401, DOI 10.1016/j.geomorph.2006.10.036 Ohlmacher GC, 2003, ENG GEOL, V69, P331, DOI 10.1016/S0013-7952(03)00069-3 Santacana, 2003, NAT HAZARDS, V30, P281 Sengor AMC, 1985, SEPM SPECIAL PUBLICA, V37, P227, DOI DOI 10.2110/PEC.85.37.0227 Soeters R, 1996, 247 TRANSP RES BOARD, P129 Suzen ML, 2004, ENG GEOL, V71, P303, DOI 10.1016/S0013-7952(03)00143-1 Suzen ML, 2004, ENVIRON GEOL, V45, P665, DOI 10.1007/s00254-003-0917-8 Suzen M.L., 2002, THESIS MIDDLE E TU Wang HB, 2005, ENVIRON GEOL, V47, P956, DOI 10.1007/s00254-005-1225-2 Wilson J., 2000, TERRAIN ANAL PRINCIP Yesilnacar E, 2006, INT J REMOTE SENS, V27, P253, DOI 10.1080/0143116050030042 Yesilnacar E, 2005, ENG GEOL, V79, P251, DOI 10.1016/j.enggeo.2005.02.002 Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2010, ENVIRON EARTH SCI, V60, P505, DOI 10.1007/s12665-009-0191-5Cited Reference Count: 49 Abstract: The aim of this study was to determine how well the landslide susceptibility parameters, obtained by data-dependent statistical models, matched with the parameters used in the literature. In order to achieve this goal, 20 different environmental parameters were mapped in a well-studied landslide-prone area, the Asarsuyu catchment in northwest Turkey. A total of 4400 seed cells were generated from 47 different landslides and merged with different attributes of 20 different environmental causative variables into a database. In order to run a series of logistic regression models, different random landslide-free sample sets were produced and combined with seed cells. Different susceptibility maps were created with an average success rate of nearly 80%. The coherence among the models showed spatial correlations greater than 90%.



Models converged in the parameter selection peculiarly, in that the same nine of 20 were chosen by different logistic regression models. Among these nine parameters, lithology, geological structure (distance/density), landcover-landuse, and slope angle were common parameters selected by both the regression models and literature. Accuracy assessment of the logistic models was assessed by absolute methods. All models were field checked with the landslides resulting from the 12 November 1999, Kaynasli Earthquake (Ms = 7.2).Accession Number: WOS:000304826400004 Language: EnglishDocument Type: ArticleAuthor Keywords: landslide susceptibility; geographical information systems (GIS); logistic regression; Asarsuyu; TurkeyKeyWords Plus: NW TURKEY; STATISTICAL-ANALYSIS; NEURAL-NETWORKS; GIS; AREA; HAZARD; REGION; NORTH; MULTIVARIATE; BIVARIATEAddresses: [Suzen, Mehmet Lutfi] Middle E Tech Univ, Geol Engn Dept, TR-06531 Ankara, Turkey. [Kaya, Basak Sener] Colorado Sch Mines, Div Engn, Golden, CO 80401 USA. Reprint Address: Suzen, ML (reprint author), Middle E Tech Univ, Geol Engn Dept, TR-06531 Ankara, Turkey.E-mail Addresses: [email protected]: TAYLOR & FRANCIS LTD Publisher Address: 4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND Web of Science Categories: Geography, Physical; Remote SensingResearch Areas: Physical Geography; Remote SensingIDS Number: 952WT ISSN: 1753-8947 29-char Source Abbrev.: INT J DIGIT EARTH ISO Source Abbrev.: Int. J. Digit. Earth Source Item Page Count: 18 Record 22 of 58Title: Foundation Slab in Interaction with Subsoil Author(s): Cajka, R (Cajka, Radim); Burkovic, K (Burkovic, Kamil); Buchta, V (Buchta, Vojtech)Edited by: Zhang X; Zhang B; Jiang L; Xie MSource: CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING, PTS 1-4 Book Series: Advanced Materials Research Volume: 838-841 Pages: 375-380 DOI: 10.4028/www.scientific.net/AMR.838-841.375 Published: 2014 Times Cited in Web of Science Core Collection: 3 Total Times Cited: 3 Cited References: CAJKA R, 2011, 17 INT C ENG MECH 20, P95 Cajka R., 2003, INT S SHALL FDN FOND Cajka R, 2012, APPL MECH MATER, V188, P247, DOI 10.4028/www.scientific.net/AMM.188.247 Cajka R., 2011, P 13 INT C CIV STRUC, DOI [10.4203/ccp.96.208, DOI 10.4203/CCP.96.208] Cajka R., 2008, 11 E AS PAC C STRUCT, P718 Cajka R, 2005, IABSE Conference New Delhi, India 2005, P551 Cajka R., 2005, COST 12 FIN C P 20 2 Cajka R., 2011, CONSTRUCTION SERIES, VXI, P1, DOI [10.2478/v10160-011-0002-2, DOI 10.2478/V10160-011-0002-2] Cajka R., 2012, P 18 INT C ENG COMP, DOI [10.4203/ccp.100.114, DOI 10.4203/CCP.100.114] Cajka R., 2013, ADV MAT RES IN PRESS, V818 Cajka R, 2013, APPL MECH MATER, V300-301, P1127, DOI 10.4028/www.scientific.net/AMM.300-301.1127 Cajka R., 2012, P 3 INT S LIF CYCL C, p[399, 1955] Cajka R., 2013, CONSTRUCTION SERIES, VXIL, P26, DOI [10.2478/v10160-012-0014-6, DOI 10.2478/V10160-012-0014-6] Cajka R., 2007, P 11 INT C CIV STRUC, DOI [10.4203/ccp.86.18, DOI 10.4203/CCP.86.18] Fajman P, 2007, COMPUT STRUCT, V85, P1514, DOI 10.1016/j.compstruc.2007.01.024 Halvonik J., 2013, CONCRETE CO IN PRESS Kolar V., 1989, MODELING SOIL STRUCT Konecky P., 2010, P 1 INT C PAR DISTR Kralik J, 2013, ADV MATER RES-SWITZ, V712-715, P929, DOI 10.4028/www.scientific.net/AMR.712-715.929 Kralik J., 1993, INT C GEOM 93 STRAT, P233 Krejsa M, 2013, APPL MECH MATER, V300-301, P860, DOI 10.4028/www.scientific.net/AMM.300-301.860 Krejsa M, 2013, SCI WORLD J, DOI 10.1155/2013/267593 Kuldik P., ENG STRUCTURES, V33, P1195 Petrik T, 2012, ACTA GEODYN GEOMATER, V9, P165 PINKA M., 2012, CONSTRUCTION SERIES, VXI, p[1, 1804], DOI [10.2478/v10160-012-0006-6, DOI 10.2478/V10160-012-0006-6] Pukl R, 2006, COMPUTATIONAL MODELLING OF CONCRETE STRUCTURES, P891 Sekanina D., 2008, CONSTRUCTION SERIES, VIX, P17 Sucharda O., 2009, P 12 INT C CIV STRUC, DOI [10.4203/ccp.91.121, DOI 10.4203/CCP.91.121]Cited Reference Count: 28 Abstract: In the paper the experiment results of deformation in foundation slab segment in interaction with subsoil are presented. Pilot measurement is carried out on original subsoil with characteristics which were tested in cooperation with geotechnics specialists. Concrete precast slab with square dimensions 500 mm and with thickness 48 mm made of plain concrete is exposed to vertical load. The tests results are compared with bending moments and deformations analysed according to subsoil models given in Eurocodes using FEM analysis.Accession Number: WOS:000339531700069 Language: EnglishDocument Type: Proceedings PaperConference Title: 2nd Global Conference on Civil, Structural and Environmental Engineering (GCCSEE 2013) Conference Date: SEP 28-29, 2013 Conference Location: Shenzhen, PEOPLES R CHINA Conference Sponsors: Liaoning Tech UnivAuthor Keywords: Soil-structure interaction; foundation slab; deformation; stress; FEM analysisAddresses: [Cajka, Radim; Buchta, Vojtech] VSB TU Ostrava, Ostrava 70833, Czech Republic. Reprint Address: Cajka, R (reprint author), VSB TU Ostrava, L Podeste 1875-17, Ostrava 70833, Czech Republic.E-mail Addresses: [email protected]; [email protected]; [email protected] Identifiers:

Author ResearcherID Number ORCID NumberCajka, Radim F-2889-2010 0000-0002-2346-062X Publisher: TRANS TECH PUBLICATIONS LTD Publisher Address: LAUBLSRUTISTR 24, CH-8717 STAFA-ZURICH, SWITZERLAND Web of Science Categories: Engineering, MultidisciplinaryResearch Areas: EngineeringIDS Number: BA9LS ISSN: 1022-6680 ISBN: 978-3-03785-926-129-char Source Abbrev.: ADV MATER RES-SWITZ



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Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P459, DOI 10.1007/s10064-009-0188-z Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P297, DOI 10.1007/s10064-009-0185-2Cited Reference Count: 86 Abstract: The main purpose of this paper is to present the use of multi-resource remote sensing data, an incomplete landslide inventory, GIS technique and logistic regression model for landslide susceptibility mapping related to the May 12, 2008 Wenchuan earthquake of China. Landslide location polygons were delineated from visual interpretation of aerial photographs, satellite images in high resolutions, and verified by selecting field investigations. Eight factors, including slope angle, slope aspect, elevation, distance from drainages, distance from roads, distance from main faults, seismic intensity and lithology were selected as controlling factors for earthquake-triggered landslide susceptibility mapping. Qualitative susceptibility analyses were carried out using the map overlaying techniques in GIS platform. The validation result showed a success rate of 82.751 % between the susceptibility probability index map and the location of the initial landslide inventory. The predictive rate of 86.930 % was obtained by comparing the additional landslide polygons and the landslide susceptibility probability index map. Both the success rate and the predictive rate show sufficient agreement between the landslide susceptibility map and the existing landslide data, and good predictive power for spatial prediction of the earthquake-triggered landslides.Accession Number: WOS:000322727300035 Language: EnglishDocument Type: ArticleAuthor Keywords: The 2008 Wenchuan earthquake; Landslides; Landslide susceptibility mapping; Logistic regression; Success rate; Predictive rateKeyWords Plus: ARTIFICIAL NEURAL-NETWORKS; SPATIAL PREDICTION MODELS; SUPPORT VECTOR MACHINE; BHAGIRATHI GANGA VALLEY; ROCK SLOPE STABILITY; WEIGHTS-OF-EVIDENCE; HOA BINH PROVINCE; HAZARD ZONATION; TRIGGERED LANDSLIDES; CONDITIONAL-PROBABILITYAddresses: [Xu, Chong; Xu, Xiwei; He, Honglin; Shi, Feng; Wu, Xiyan] China Earthquake Adm, Inst Geol, Key Lab Act Tecton & Volcano, Beijing 100029, Peoples R China. [Xu, Chong; Dai, Fuchu] Chinese Acad Sci, Inst Geol & Geophys, Beijing 100029, Peoples R China. [Wu, Zhide] PetroChina, Langfang Branch, Res Inst Petr Explorat & Dev, Langfang 065007, Peoples R China. [Xu, Suning] China Inst Geoenvironm Monitoring, Beijing 100081, Peoples R China. Reprint Address: Xu, C (reprint author), China Earthquake Adm, Inst Geol, Key Lab Act Tecton & Volcano, POB 9803, Beijing 100029, Peoples R China.E-mail Addresses: [email protected] Identifiers:

Author ResearcherID Number ORCID NumberXu, Chong B-6460-2012 0000-0002-3956-4925 Dai, FC E-5660-2012 0000-0002-6290-0587 Publisher: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences; Water ResourcesResearch Areas: Geology; Meteorology & Atmospheric Sciences; Water ResourcesIDS Number: 195TU ISSN: 0921-030X 29-char Source Abbrev.: NAT HAZARDS ISO Source Abbrev.: Nat. Hazards Source Item Page Count: 18

Funding:


This research is supported by the National Science Foundation of China (grant No. 41202235). We thank Drs. Cees J. van Westen and Tolga Gorum for their help in providing ALOS and ASTER images for compiling the inventory of landslides triggered by the 2008 Wenchuan earthquake.

Record 24 of 58Title: Stability assessment of an ancient landslide crossed by two coal mine tunnels Author(s): Jiao, YY (Jiao, Yu-Yong); Wang, ZH (Wang, Zi-Hao); Wang, XZ (Wang, Xin-Zhi); Adoko, AC (Adoko, Amoussou Coffi); Yang, ZX (Yang, Zhen-Xing) Source: ENGINEERING GEOLOGY Volume: 159 Pages: 36-44 DOI: 10.1016/j.enggeo.2013.03.021 Published: JUN 12 2013 Times Cited in Web of Science Core Collection: 3 Total Times Cited: 3 Cited References: Alejano LR, 2011, INT J ROCK MECH MIN, V48, P16, DOI 10.1016/j.ijrmms.2010.06.013 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Brooks SM, 2012, GEOMORPHOLOGY, V153, P48, DOI 10.1016/j.geomorph.2012.02.007 Coggan J, 2012, INT J COAL GEOL, V90, P100, DOI 10.1016/j.coal.2011.11.003 Corkum AG, 2004, INT J ROCK MECH MIN, V41, P1109, DOI 10.1016/j.ijrmms.2004.04.008 Fujii Y, 2011, INT J ROCK MECH MIN, V48, P585, DOI 10.1016/j.ijrmms.2011.04.012 GEO-SLOPE International Ltd, 2007, SLOP W US GUID SLOP He MC, 2011, ENG GEOL, V121, P165, DOI 10.1016/j.enggeo.2010.12.001 ITASCA Consulting Group Inc., 2002, FLAC3D FAST LAGR AN Jia N, 2012, COMPUT GEOTECH, V45, P1, DOI 10.1016/j.compgeo.2012.04.007 Jiao YY, 2012, J ENG MECH-ASCE, V138, P199, DOI 10.1061/(ASCE)EM.1943-7889.0000319 Jiao YY, 2007, INT J ROCK MECH MIN, V44, P1070, DOI 10.1016/j.ijrmms.2007.03.001 Kaynia AM, 2008, ENG GEOL, V101, P33, DOI 10.1016/j.enggeo.2008.03.008 Korup O, 2005, GEOMORPHOLOGY, V66, P167, DOI 10.1016/j.geomorph.2004.09.013 Li LC, 2009, COMPUT GEOTECH, V36, P1246, DOI 10.1016/j.compgeo.2009.06.004 Maffei A, 2005, ENG GEOL, V78, P215, DOI 10.1016/j.enggeo.2004.12.009 Marcato G, 2012, ENG GEOL, V128, P95, DOI 10.1016/j.enggeo.2011.09.014 Perez-Ruiz M, 2012, BIOSYST ENG, V111, P64, DOI 10.1016/j.biosystemseng.2011.10.009 Shabanimashcool M, 2012, INT J ROCK MECH MIN, V51, P24, DOI 10.1016/j.ijrmms.2012.02.002 Song B, 2009, INT J MIN MET MATER, V16, P359 Tang CA, 1997, INT J ROCK MECH MIN, V34, P249, DOI 10.1016/S0148-9062(96)00039-3 Torano J, 2002, COMPUT GEOTECH, V29, P411, DOI 10.1016/S0266-352X(02)00006-X Wang X, 2012, TUNN UNDERGR SP TECH, V32, P98, DOI 10.1016/j.tust.2012.06.003 Wei ZA, 2006, ENG GEOL, V84, P1, DOI 10.1016/j.enggeo.2005.09.019 Wu Q, 2012, COMPUT GEOTECH, V46, P48, DOI 10.1016/j.compgeo.2012.05.013 Zhang CQ, 2012, INT J ROCK MECH MIN, V52, P139, DOI 10.1016/j.ijrmms.2012.03.016Cited Reference Count: 26 Abstract: In 2005, when two main tunnels were excavated in Faer Coal Mine, Guizhou Province, China, an unknown ancient landslide, subsequently named Dazhai landslide, was encountered. Roof caving, large convergence and severe support damage in the tunnels, as well as several ground subsidence occurred. The two tunnels have been kept stable after an inner supporting treatment in 2008. However, since a heavy rainfall in July 2010, some transverse cracks were observed at the landslide toe, determining significant additional costs over the normal administration of the mine. Invited by the owner, we performed a comprehensive investigation to evaluate the stability of Dazhai landslide crossed by two main tunnels. Firstly, field surveys and mappings were completed to obtain a preliminary delineation of the landslide surface, and a geological drilling along the central landslide axis was accomplished to depict the sliding surface. After that, a monitoring system containing a GPS-RTK network and six observation sections in one tunnel were established and a 12-month monitoring was conducted. Moreover, to obtain an overall comprehension, numerical simulations were carried out by using GeoStudio and FLAC(3D) software. The results from site drilling, monitoring and simulations indicate that the Dazhai landslide is stable as a whole, and



only local shallow landslides might occur. The local instability of Dazhai landslide has limited impact on the safety of the two main tunnels. This conclusion has led to a budget savings of over RMB 40 million. (C) 2013 Elsevier B.V. All rights reserved.Accession Number: WOS:000319852500004 Language: EnglishDocument Type: ArticleAuthor Keywords: Ancient landslide; Coal mine tunnel; Stability assessment; Geological exploration; GPS-RTK; Numerical simulationsKeyWords Plus: SLOPE STABILITY; STRESS-ANALYSES; ROCK; DISCONTINUUM; CONTINUUM; ROADWAYS; MODEL; DDAAddresses: [Jiao, Yu-Yong; Wang, Zi-Hao; Wang, Xin-Zhi; Adoko, Amoussou Coffi; Yang, Zhen-Xing] Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Peoples R China. Reprint Address: Jiao, YY (reprint author), Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Peoples R China.E-mail Addresses: [email protected]: ELSEVIER SCIENCE BV Publisher Address: PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS Web of Science Categories: Engineering, Geological; Geosciences, MultidisciplinaryResearch Areas: Engineering; GeologyIDS Number: 156VR ISSN: 0013-7952 29-char Source Abbrev.: ENG GEOL ISO Source Abbrev.: Eng. Geol. Source Item Page Count: 9

Funding:

Funding Agency Grant NumberNational Basic Research Program of China (973 Program) 2011CB710602 Key Research Program of the Chinese Academy of Sciences KZZD-EW-05-03 China National Natural Science Foundation 40972201

51139004

This study is financially supported by the National Basic Research Program of China (973 Program) (2011CB710602), the Key Research Program of the Chinese Academy of Sciences (KZZD-EW-05-03) and the China National Natural Science Foundation (40972201, 51139004). The authors also highly appreciate the two anonymous reviewers for their critical and helpful comments.

Record 25 of 58Title: Remote Sensing Data Derived Parameters and Its Use in Landslide Susceptibility Assessment using Shannon's Entropy and GIS Author(s): Pourghasemi, HR (Pourghasemi, Hamid Reza); Pradhan, B (Pradhan, Biswajeet); Gokceoglu, C (Gokceoglu, Candan)Edited by: Varatharajoo R; Abdullah EJ; Majid DL; Romli FI; Rafie ASM; Ahmad KASource: AEROTECH IV: RECENT ADVANCES IN AEROSPACE TECHNOLOGIES Book Series: Applied Mechanics and Materials Volume: 225 Pages: 486-491 DOI: 10.4028/www.scientific.net/AMM.225.486 Published: 2012 Times Cited in Web of Science Core Collection: 3 Total Times Cited: 3 Cited References: Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Bui D.T., COMPUTER GEOSCIENCE, DOI [10.1016/j.cageo.2011.10.031, DOI 10.1016/J] CHUNG CJF, 1995, ADV NAT TECHNOL HAZ, V5, P107 Constantin M, 2011, ENVIRON EARTH SCI, V63, P397, DOI 10.1007/s12665-010-0724-y Crozier M.J., 2005, LANDSLIDE HAZARD RIS, P1 Guzzetti F, 1999, GEOMORPHOLOGY, V31, P181, DOI 10.1016/S0169-555X(99)00078-1 Marjanovic M, 2011, ENG GEOL, V123, P225, DOI 10.1016/j.enggeo.2011.09.006 Pourghasemi H, 2013, GEOMAT NAT HAZ RISK, V4, P93, DOI 10.1080/19475705.2012.662915 Pourghasemi H., 2012, TERRIGENOUS MASS MOV, P23, DOI DOI 10.1007/978-3-642-25495-6-2 Pourghasemi HR, 2012, NAT HAZARDS, V63, P965, DOI 10.1007/s11069-012-0217-2 Pourghasemi HR, 2013, ARAB J GEOSCI, V6, P2351, DOI 10.1007/s12517-012-0532-7 Pourghasemi H.R., CATENA, DOI [10.1016/j.catena.2012.05.005, DOI 10.1016/J] Pradhan B, 2012, GEOMORPHOLOGY, DOI [10.1016/j.geomorph.2012.04.023, DOI 10.1016/J.GE0M0RPH.2012.04.023] Pradhan B, 2010, INT J COMPUT INT SYS, V3, P370 Pradhan B, 2010, J INDIAN SOC REMOT, V38, P301, DOI 10.1007/s12524-010-0020-z Pradhan B, 2011, ENVIRON ECOL STAT, V18, P471, DOI 10.1007/s10651-010-0147-7 Pradhan B., ENV ENG GEOSCIENCE, V16, P107 Song KY, 2012, ADV SPACE RES, V49, P978, DOI 10.1016/j.asr.2011.11.035 Vahidnia MH, 2010, COMPUT GEOSCI-UK, V36, P1101, DOI 10.1016/j.cageo.2010.04.004 Van Westen C. J., 2008, ENG GEOLOGY Yang Z., 2010, P 2010 7 INT C FUZZ, V3, P1336 Yesilnacar EK, 2005, THESIS U MELBOURNE, P423 Yufeng S., 2009, 2009 INT C ENV SCI I, P83, DOI 10.1109/ESIAT.2009.258Cited Reference Count: 23 Abstract: In recent years, the growth of urban populations in hazardous areas has increased the impact of natural disasters in both developed and developing countries. The purpose of the current study is to assess the landslide susceptibility in Kalaleh township of Golestan province, Iran. In this study the Shannon's entropy approach was applied. A total of 82 landslide locations were identified primarily from aerial photographs and field surveys. Then eighteen landslides conditioning factors were prepared in GIS. These landslide conditioning factors are: slope degree, slope aspect, altitude, plan curvature, profile curvature, tangential curvature, surface area ratio (SAR), lithology, land use, soil texture, distance from faults, distance from rivers, distance from roads, fault density, road density, topographic wetness index (TWI), stream power index (SPI), and sediment transport index (STI). Using these conditioning factors, landslide susceptibility index was calculated using Shannon's entropy. For model validation, the results of the analyses were then compared with the field-verified landslide locations. Additionally, the receiver operating characteristics (ROC) curves for landslide susceptibility maps were drawn and the area under curve values was calculated. Verification results showed 82.15% accuracy. According to the results of the AUC (area under curve) evaluation, the map produced exhibits satisfactory properties.Accession Number: WOS:000316578100079 Language: EnglishDocument Type: Proceedings PaperConference Title: AEROTECH 4 - Conference on Recent Advances in Aerospace Technologies Conference Date: NOV 21-22, 2012 Conference Location: Kuala Lumpur, MALAYSIA Conference Sponsors: Univ Putra Malaysia, Univ Kuala Lumpur, Malaysia Convent & Exhibit Bur, Tourism Malaysia, UNIKL MIATAuthor Keywords: landslide; susceptibility; Shannon's entropy; GIS; remote sensing; IranKeyWords Plus: FUZZY-LOGICAddresses: [Pourghasemi, Hamid Reza] Tarbiat Modares Univ TMU, Coll Nat Resources & Marine Sci, Dept Watershed Management Engn, Tehran, Iran. Reprint Address: Pourghasemi, HR (reprint author), Tarbiat Modares Univ TMU, Coll Nat Resources & Marine Sci, Dept Watershed Management Engn, Tehran, Iran. E-mail Addresses: [email protected]; [email protected]; [email protected] Identifiers:

Author ResearcherID Number ORCID Number



Pradhan, Biswajeet E-8226-2010 0000-0001-9863-2054 Publisher: TRANS TECH PUBLICATIONS LTD Publisher Address: LAUBLSRUTISTR 24, CH-8717 STAFA-ZURICH, SWITZERLAND Web of Science Categories: Engineering, AerospaceResearch Areas: EngineeringIDS Number: BEH34 ISSN: 1660-9336 ISBN: 978-3-03785-506-529-char Source Abbrev.: APPL MECH MATER Source Item Page Count: 6 Record 26 of 58Title: Probabilistic reliability assessment of steel structures exposed to fatigue Author(s): Krejsa, M (Krejsa, M.)Edited by: Steenbergen RDJM; VanGelder PHAJM; Miraglia S; Vrouwenvelder ACWMTSource: SAFETY, RELIABILITY AND RISK ANALYSIS: BEYOND THE HORIZON Pages: 2671-2679 DOI: 10.1201/b15938-404 Published: 2014 Times Cited in Web of Science Core Collection: 2 Total Times Cited: 2 Cited References: Anderson TL, 2005, FRACTURE MECH FUNDAM Bensi M, 2013, RELIAB ENG SYST SAFE, V112, P200, DOI 10.1016/j.ress.2012.11.017 Bris R, 2010, RELIABILITY, RISK AND SAFETY: THEORY AND APPLICATIONS VOLS 1-3, P635 Gocal J, 2010, PROCEDIA ENGINEER, V2, P1761, DOI 10.1016/j.proeng.2010.03.189 Gottvald J, 2012, J CIV ENG MANAG, V18, P609, DOI 10.3846/13923730.2012.719836 Holicky M, 2010, RELIABILITY, RISK AND SAFETY: THEORY AND APPLICATIONS VOLS 1-3, P1377 Janas P., 2012, T VSB TU OSTRAVA CON, V12, P1, DOI [10.2478/v10160-012-0017-3, DOI 10.2478/V10160-012-0017-3] Janas P., 2012, P 12 INT C CIV STRUC, DOI [10.4203/ccp.91.72, DOI 10.4203/CCP.91.72] Janas P, 2010, RELIABILITY, RISK AND SAFETY: THEORY AND APPLICATIONS VOLS 1-3, P1467 Kala Z, 2012, J CIV ENG MANAG, V18, P81, DOI 10.3846/13923730.2012.655306 Konecny P, 2009, CIVIL COMP PROCEED, P542 Kotes P, 2012, PROCEDIA ENGINEER, V40, P211, DOI 10.1016/j.proeng.2012.07.082 Kralik J, 2010, RELIABILITY, RISK AND SAFETY: THEORY AND APPLICATIONS VOLS 1-3, P1369 Krejsa M., 2012, P 11 INT C COMP STRU, DOI [10.4203/ccp.99.113., DOI 10.4203/CCP.99.113] Krejsa M, 1999, STABILITY AND DUCTILITY OF STEEL STRUCTURES, P19, DOI 10.1016/B978-008043016-4/50003-9 Krejsa M, 2013, APPL MECH MATER, V300-301, P860, DOI 10.4028/www.scientific.net/AMM.300-301.860 Krejsa M., 2012, RECENT ADV SYSTEMS S, P216 Krejsa M, 2012, P 18 INT C ENG MECH, P745 Krejsa M., 2011, T VSB TU OSTRAVA CON, V11, P1, DOI [10.2478/v10160-011-0007-x, DOI 10.2478/V10160-011-0007-X] Krejsa M., 2012, RECENT ADV MECH ENG, P104 Krejsa M., 2012, T VSB TU OSTRAVA CON, V12, P1, DOI [10.2478/v10160-012-0003-9, DOI 10.2478/V10160-012-0003-9] Krivy V, 2011, ENGINEERING MECHANICS 2011, P335 Moan T, 2005, STRUCT INFRASTRUCT E, V1, P33, DOI 10.1080/15732470412331289314 Paris P. C., 1963, J BASIC ENG, V85, P528 Praks P, 2010, RELIABILITY, RISK AND SAFETY: THEORY AND APPLICATIONS VOLS 1-3, P2199 Routil L, 2012, KEY ENG MATER, V488-489, P533, DOI 10.4028/www.scientific.net/KEM.488-489.533 Sadovsky Z, 2010, RELIABILITY, RISK AND SAFETY: THEORY AND APPLICATIONS VOLS 1-3, P1373 Seitl S, 2012, APPL MECH MATER, V121-126, P2726, DOI 10.4028/www.scientific.net/AMM.121-126.2726 Tesar A, 2008, INT J NUMER METH ENG, V74, P1670, DOI 10.1002/nme.2224 van der Weide JAM, 2010, RELIABILITY, RISK AND SAFETY: THEORY AND APPLICATIONS VOLS 1-3, P535 Vavrusova K, 2012, APPL MECH MATER, V188, P242, DOI 10.4028/www.scientific.net/AMM.188.242 Vorechovsky M, 2009, PROBABILIST ENG MECH, V24, P452, DOI 10.1016/j.probengmech.2009.01.004 Yilmaz I, 2012, NEURAL COMPUT APPL, V21, P957, DOI 10.1007/s00521-011-0535-4Cited Reference Count: 33 Abstract: The paper describes methods used for probabilistic assessment of reliability of steel structures and bridges that are exposed to cyclic loads. Propagation of fatigue cracks from surface and edges is taken into account, the maximum permitted dimension being of particular attention. The model is based on a linear fracture mechanics. Conditional probability is the basis when designing a regular system of inspections for the structure. A new method, which is still under development, has been used for probabilistic modeling of fatigue damage. Direct Optimized Probabilistic Calculation-DOProC-appears to be a very efficient for the computation of probabilities. DOProC provides the solution with only a numerical error and an error resulting from input and output quantities discretizing.Accession Number: WOS:000339427104020 Language: EnglishDocument Type: Proceedings PaperConference Title: 22nd Annual Conference on European Safety and Reliability (ESREL) Conference Date: SEP 29-OCT 02, 2013 Conference Location: Amsterdam, NETHERLANDS Conference Sponsors: Netherlands Org Appl Sci Res, Delft Univ Technol, Dutch Soc Risk Management & Reliabil Anal, European Safety & Reliabil Assoc Addresses: Tech Univ Ostrava, VSB, Ostrava, Czech Republic. Reprint Address: Krejsa, M (reprint author), Tech Univ Ostrava, VSB, Ostrava, Czech Republic.Author Identifiers:

Author ResearcherID Number ORCID NumberKrejsa, Martin D-2107-2011 0000-0003-0571-2616 Publisher: CRC PRESS-TAYLOR & FRANCIS GROUP Publisher Address: 6000 BROKEN SOUND PARKWAY NW, STE 300, BOCA RATON, FL 33487-2742 USA Web of Science Categories: Engineering, ManufacturingResearch Areas: EngineeringIDS Number: BA9IA ISBN: 978-1-315-81559-6; 978-1-138-00123-7Source Item Page Count: 9 Record 27 of 58Title: Application of Generalized Regression Neural Networks in Predicting the Unconfined Compressive Strength of Carbonate Rocks Author(s): Ceryan, N (Ceryan, Nurcihan); Okkan, U (Okkan, Umut); Kesimal, A (Kesimal, Ayhan)Source: ROCK MECHANICS AND ROCK ENGINEERING Volume: 45 Issue: 6 Pages: 1055-1072 DOI: 10.1007/s00603-012-0239-9 Published: NOV 2012 Times Cited in Web of Science Core Collection: 2 Total Times Cited: 2 Cited References: Altindag R, 2004, INT J ROCK MECH MIN, V41, P1023, DOI 10.1016/j.ijrmms.2004.03.005 Barton N, 2007, J SEISM EXPLOR, V16, P115 Baykasoglu A, 2008, EXPERT SYST APPL, V35, P111, DOI 10.1016/j.eswa.2007.06.006 BELL FG, 1978, ENG GEOL, V12, P1, DOI 10.1016/0013-7952(78)90002-9



BROOK N, 1985, INT J ROCK MECH MIN, V22, P61, DOI 10.1016/0148-9062(85)92328-9 Brown E. T., 1981, ROCK CHARACTERIZATIO, P211 Canakci H, 2007, ENG GEOL, V94, P10, DOI 10.1016/j.enggeo.2007.06.009 Ceryan S, 2008, ENVIRON GEOL, V55, P1319, DOI 10.1007/s00254-007-1080-4 Cevik A, 2011, APPL SOFT COMPUT, V11, P2587, DOI 10.1016/j.asoc.2010.10.008 Chang CD, 2006, J PETROL SCI ENG, V51, P223, DOI 10.1016/j.petrol.2006.01.003 Cigizoglu HK, 2005, CIV ENG ENVIRON SYST, V22, P71, DOI 10.1080/10286600500126256 Cobanoglu I, 2008, B ENG GEOL ENVIRON, V67, P491, DOI 10.1007/s10064-008-0158-x DOBEREINER L, 1986, GEOTECHNIQUE, V36, P79 Fahy M.P., 1979, B ASS ENG GEOLOGISTS, V16, P467 FRANKLIN JA, 1972, INT J ROCK MECH MIN, V9, P325, DOI 10.1016/0148-9062(72)90001-0 Gokceoglu C, 2002, ENG GEOL, V66, P39, DOI 10.1016/S0013-7952(02)00023-6 Gokceoglu C, 2004, ENG APPL ARTIF INTEL, V17, P61, DOI 10.1016/j.engappai.2003.11.006 Gokceoglu C, 2009, MATER CHARACT, V60, P1317, DOI 10.1016/j.matchar.2009.06.006 Grima MA, 1999, INT J ROCK MECH MIN, V36, P339 Gundogdu N, 1982, THESIS HU ENG FACULT, p368s Hack H, 2002, P 9 C INT ASS ENG GE Hawkins A, 1990, 7 INT C ROCK MECH AA, P257 Ji T, 2006, CEMENT CONCRETE RES, V36, P1399, DOI 10.1016/j.cemconres.2006.01.009 Kahraman S, 2001, INT J ROCK MECH MIN, V38, P981, DOI 10.1016/S1365-1609(01)00039-9 Kahraman S, 2010, EXPERT SYST APPL, V37, P8750, DOI 10.1016/j.eswa.2010.06.039 Kahraman S, 2009, EXPERT SYST APPL, V36, P6874, DOI 10.1016/j.eswa.2008.08.002 Kahraman S, 2006, INT J ROCK MECH MIN, V43, P1277, DOI 10.1016/j.ijrmms.2006.03.017 Kayabali K, 2010, INT J ROCK MECH MIN, V47, P265, DOI 10.1016/j.ijrmms.2009.09.010 McQuarrie A. D., 1998, REGRESSION TIME SERI Meulenkamp F, 1999, INT J ROCK MECH MIN, V36, P29, DOI 10.1016/S0148-9062(98)00173-9 Meulenkamp F., 1997, MEMOIRS CTR ENG GEOL, V162, P127 Moller M. F., 1993, NEURAL NETWORKS, V6, P523 Neter J., 1996, APPL LINEAR STAT MOD Okkan U, 2011, FRESEN ENVIRON BULL, V20, P3110 Oyler DC, 2010, INT J COAL GEOL, V83, P484, DOI 10.1016/j.coal.2010.07.002 Romana M., 1999, 9 ISRM C BALK PAR, V1, P673 Sarkar K, 2010, B ENG GEOL ENVIRON, V69, P599, DOI 10.1007/s10064-010-0301-3 Serbes ZA, 2011, 5 UL SU MUH S BILD K, P537 Shakoor A, 1991, B ASS ENG GEOLOGISTS, VXXVIII, P55 Sharma S., 1996, APPL MULTIVARIATE TE SINGH A, 1985, INT J REMOTE SENS, V6, P883 Singh TN, 2000, J SCI IND RES INDIA, V59, P482 Singh VK, 2001, INT J ROCK MECH MIN, V38, P269, DOI 10.1016/S1365-1609(00)00078-2 Sonmez H, 2004, INT J ROCK MECH MIN, V41, P717, DOI 10.1016/j.ijrmms.2004.01.011 SPECHT DF, 1991, IEEE T NEURAL NETWOR, V2, P568, DOI 10.1109/72.97934 Temel A, 1996, MINER DEPOSITA, V31, P539, DOI 10.1007/BF00196134 Ulusay R, 1994, ENG GEOL, V37, P135 Ulusay R, 2001, INT J ROCK MECH MIN, V38, P1113, DOI 10.1016/S1365-1609(01)00078-8 Ulusay R., 2007, SUGGESTED METHODS PR, P628 Yagiz S., 2011, INT J NUMER ANAL MET Yilmaz I, 2009, INT J ROCK MECH MIN, V46, P803, DOI 10.1016/j.ijrmms.2008.09.002 Yilmaz I, 2012, NEURAL COMPUT APPL, V21, P957, DOI 10.1007/s00521-011-0535-4 Yilmaz I, 2008, ROCK MECH ROCK ENG, V41, P781, DOI 10.1007/s00603-007-0138-7 Yilmaz I, 2010, INT J ROCK MECH MIN, V47, P845, DOI 10.1016/j.ijrmms.2010.03.003 Zorlu K, 2008, ENG GEOL, V96, P141, DOI 10.1016/j.enggeo.2007.10.009Cited Reference Count: 55 Abstract: Measuring unconfined compressive strength (UCS) using standard laboratory tests is a difficult, expensive, and time-consuming task, especially with highly fractured, highly porous, weak rock. This study aims to establish predictive models for the UCS of carbonate rocks formed in various facies and exposed in Tasonu Quarry, northeast Turkey. The objective is to effectively select the explanatory variables from among a subset of the dataset containing total porosity, effective porosity, slake durability index, and P-wave velocity in dry samples and in the solid part of samples. This was based on the adjusted determination coefficient and root-mean-square error values of different linear regression analysis combinations using all possible regression methods. A prediction model for UCS was prepared using generalized regression neural networks (GRNNs). GRNNs were preferred over feed-forward back-propagation algorithm-based neural networks because there is no problem of local minimums in GRNNs. In this study, as a result of all possible regression analyses, alternative combinations involving one, two, and three inputs were used. Through comparison of GRNN performance with that of feed-forward back-propagation algorithm-based neural networks, it is demonstrated that GRNN is a good potential candidate for prediction of the unconfined compressive strength of carbonate rocks. From an examination of other applications of UCS prediction models, it is apparent that the GRNN technique has not been used thus far in this field. This study provides a clear and practical summary of the possible impact of alternative neural network types in UCS prediction.Accession Number: WOS:000310227300015 Language: EnglishDocument Type: ArticleAuthor Keywords: Unconfined compressive strength; Prediction; Porosity; Wave velocity; Generalized regression neural networks; All possible regression methodsKeyWords Plus: TENSILE-STRENGTH; FUZZY MODEL; P-WAVE; SANDSTONES; MODULUS; ELASTICITY; VELOCITY; HARDNESS; TURKEY; INDEXAddresses: [Ceryan, Nurcihan] Balikesir Univ, Dept Geol Engn, Balikesir, Turkey. [Okkan, Umut] Balikesir Univ, Dept Civil Engn, Balikesir, Turkey. [Kesimal, Ayhan] Karadeniz Tech Univ, Dept Min Engn, Trabzon, Turkey. Reprint Address: Ceryan, N (reprint author), Balikesir Univ, Dept Geol Engn, Balikesir, Turkey.E-mail Addresses: [email protected]; [email protected]; [email protected]: SPRINGER WIEN Publisher Address: SACHSENPLATZ 4-6, PO BOX 89, A-1201 WIEN, AUSTRIA Web of Science Categories: Engineering, Geological; Geosciences, MultidisciplinaryResearch Areas: Engineering; GeologyIDS Number: 025WL ISSN: 0723-2632 29-char Source Abbrev.: ROCK MECH ROCK ENG ISO Source Abbrev.: Rock Mech. Rock Eng. Source Item Page Count: 18 Record 28 of 58Title: IMPACT OF MINING-INDUCED SURFACE DEFORMATIONS ON REINFORCEMENT OF STRUCTURAL EMBANKMENTS Author(s): Kalisz, P (Kalisz, Piotr)Source: ARCHIVES OF MINING SCIENCES Volume: 54 Issue: 4 Pages: 657-670 Published: 2009 Times Cited in Web of Science Core Collection: 2 Total Times Cited: 2 Cited References: AJDUKIEWICZ J, 2004, PROJEKTOWANIE GEOSYN CALA M, 2000, ANALIZA STATECZNOSCI Cala M, 2007, ARCH MIN SCI, V52, P75



DOMANSKA D, 2006, ARCH MIN SCI, V51, P503 GLINKO H, 1987, PRZEBIEG PROCESU ROZ GLINKO H, 2002, WYBRANE PROBLEMY GEO Gustkicwicz J., 2003, ARCH MIN SCI, V48, P197 KLOSEK K, 2008, MAT 7 K NAUK TECHN O, P101 KLOSEK K, 2006, NAWIERZCHNIA BUDOWLE, P123 KOWALCZYK A, 2003, OCENA STATECZNOSCI S KOWALSKI M, 2006, ZSMGIG, V29, P657 KRAZELEWSKI J, 2004, WYBRANE WLASCIWOSCI Kwiatek J., 1997, OCHRONA OBIEKTOW BUD Kwiatek J., 2007, OBIEKTY BUDOWLANE TE Leshchinsky D, 1997, GEOSYNTH INT, V4, P463 LITWINOWICZ L, 1982, PLYW ROZLUZNIENIA NA Marschalko M, 2008, ARCH MIN SCI, V53, P397 MIKA W, 1996, WPLYM POZIOMYCH ODKS Moraci N, 2006, GEOTEXT GEOMEMBRANES, V24, P116, DOI 10.1016/j.geotexmem.2005.11.001 Sawicki A., 1998, GEOTEXT GEOMEMBRANES, V16, P365, DOI 10.1016/S0266-1144(98)00020-X Shinoda M, 2004, GEOTEXT GEOMEMBRANES, V22, P205, DOI 10.1016/j.geotexmem.2004.03.003 SOBOLEWSKI J, 2006, UWAGI ZASAD PROJEKTO SOBOLEWSKI J, 1998, MAT 8 MIEDZ S GEOT 9 WILUN Z, 1987, ZARYS GEOTECHNIKICited Reference Count: 24 Abstract: In this paper issues concerning the impact of mining exploitation on embankments reinforced with geogrids have been discussed, with particular consideration of road embankments. Mining deformations cause loosening of subsoil as well as supplementary deformation and geogrids strain, which are built inside embankment structure. Moreover, loosening causes changes of subsoil and embankment properties.Accession Number: WOS:000274869500004 Language: EnglishDocument Type: ArticleAuthor Keywords: mining areas; civil engineering; embankments; geogridsKeyWords Plus: GEOGRIDSAddresses: Cent Min Inst, Dept Surface & Struct Protect, PL-40166 Katowice, Poland. Reprint Address: Kalisz, P (reprint author), Cent Min Inst, Dept Surface & Struct Protect, Pl Gwarkow 1, PL-40166 Katowice, Poland.Publisher: POLISH ACAD SCIENCES, STRATA MECHANICS RES INST Publisher Address: UL REYMONTA 27, KRAKOW, 30-059, POLAND Web of Science Categories: Mining & Mineral ProcessingResearch Areas: Mining & Mineral ProcessingIDS Number: 559YU ISSN: 0860-7001 29-char Source Abbrev.: ARCH MIN SCI ISO Source Abbrev.: Arch. Min. Sci. Source Item Page Count: 14 Record 29 of 58Title: GIS-based frequency ratio and index of entropy models for landslide susceptibility assessment in the Caspian forest, northern Iran Author(s): Jaafari, A (Jaafari, A.); Najafi, A (Najafi, A.); Pourghasemi, HR (Pourghasemi, H. R.); Rezaeian, J (Rezaeian, J.); Sattarian, A (Sattarian, A.)Source: INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY Volume: 11 Issue: 4 Pages: 909-926 DOI: 10.1007/s13762-013- 0464-0 Published: MAY 2014 Times Cited in Web of Science Core Collection: 1 Total Times Cited: 1 Cited References: Abdi E, 2010, ECOL ENG, V36, P1409, DOI 10.1016/j.ecoleng.2010.06.020 Akgun A, 2012, COMPUT GEOSCI-UK, V38, P23, DOI 10.1016/j.cageo.2011.04.012 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Bagnold R. A., 1966, APPROACH SEDIMENT TR Bednarik M, 2012, NAT HAZARDS, V64, P547, DOI 10.1007/s11069-012-0257-7 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Bell F.G., 1998, ENV GEOLOGY PRINCIPL Beven K. J., 1979, HYDROL SCI B, V24, P43, DOI [10.1080/02626667909491834, DOI 10.1080/02626667909491834] Constantin M, 2011, ENVIRON EARTH SCI, V63, P397, DOI 10.1007/s12665-010-0724-y Dai FC, 2001, ENVIRON GEOL, V40, P381, DOI 10.1007/s002540000163 Das I, 2012, GEOMORPHOLOGY, V179, P116, DOI 10.1016/j.geomorph.2012.08.004 Devkota KC, 2013, NAT HAZARDS, V65, P1 Didham RK, 2004, ENCY FOREST SCI, P68 Ercanoglu M, 2002, ENVIRON GEOL, V41, P720, DOI 10.1007/s00254-001-0454-2 Feizizadeh B, 2013, NAT HAZARDS, V65, P2105, DOI 10.1007/s11069-012-0463-3 Fernandes NF, 2004, CATENA, V55, P163, DOI 10.1016/S0341-8162(03)00115-2 Ghajar I, 2012, CROAT J FOR ENG, V33, P313 Ghimire M, 2011, NAT HAZARDS, V56, P299, DOI 10.1007/s11069-010-9569-7 Gokceoglu C, 2005, ENG GEOL, V81, P65, DOI 10.1016/j.enggeo.2005.07.011 Guzzetti F, 1999, GEOMORPHOLOGY, V31, P181, DOI 10.1016/S0169-555X(99)00078-1 HALL FG, 1995, REMOTE SENS ENVIRON, V51, P138, DOI 10.1016/0034-4257(94)00071-T Iranian Plan and Budget Organization (IPBO), 2000, GUID DES EX US FOR R Kamp U, 2008, GEOMORPHOLOGY, V101, P631, DOI 10.1016/j.geomorph.2008.03.003 Khanh NQ, 2009, LANDSLIDE HAZARD ASS Larsen MC, 1997, EARTH SURF PROC LAND, V22, P835 Lee S, 2007, LANDSLIDES, V4, P33, DOI 10.1007/s10346-006-0047-y Mohammady M, 2012, J ASIAN EARTH SCI, V61, P221, DOI 10.1016/j.jseaes.2012.10.005 MOORE ID, 1986, SOIL SCI SOC AM J, V50, P1294 MOORE ID, 1991, HYDROL PROCESS, V5, P3, DOI 10.1002/hyp.3360050103 Oh HJ, 2011, COMPUT GEOSCI-UK, V37, P1264, DOI 10.1016/j.cageo.2010.10.012 Ozdemir A, 2013, J ASIAN EARTH SCI, V64, P180, DOI 10.1016/j.jseaes.2012.12.014 PACHAURI AK, 1992, ENG GEOL, V32, P81, DOI 10.1016/0013-7952(92)90020-Y Papathanassiou G, 2013, LANDSLIDES, V10, P771, DOI 10.1007/s10346-012-0357-1 Pourghasemi H., 2012, TERRIGENOUS MASS MOV, P23, DOI DOI 10.1007/978-3-642-25495-6-2 Pourghasemi HR, 2014, ARAB J GEOSCI, V7, P1857, DOI 10.1007/s12517-012-0825-x Pourghasemi HR, 2012, NAT HAZARDS, V63, P965, DOI 10.1007/s11069-012-0217-2 Pourghasemi HR, 2012, CATENA, V97, P71, DOI 10.1016/j.catena.2012.05.005 Pradhan B, 2013, COMPUT GEOSCI-UK, V51, P350, DOI 10.1016/j.cageo.2012.08.023 Regmi AD, 2014, ARAB J GEOSCI, V7, P725, DOI 10.1007/s12517-012-0807-z Sefidi K, 2011, FLORA, V206, P418, DOI 10.1016/j.flora.2010.11.005 Sharma LP, 2010, ARAB J GEOSCI, V5, P421 Tien Bui D., 2012, CATENA, V96, P28



Vorpahl P, 2012, ECOL MODEL, V239, P27, DOI 10.1016/j.ecolmodel.2011.12.007 Yalcin A, 2011, CATENA, V85, P274, DOI 10.1016/j.catena.2011.01.014 Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P459, DOI 10.1007/s10064-009-0188-z Yufeng S, 2009, INT C ENV SCI INF AP, V2, P83Cited Reference Count: 47 Abstract: This study presents a landslide susceptibility assessment for the Caspian forest using frequency ratio and index of entropy models within geographical information system. First, the landslide locations were identified in the study area from interpretation of aerial photographs and multiple field surveys. 72 cases (70 %) out of 103 detected landslides were randomly selected for modeling, and the remaining 31 (30 %) cases were used for the model validation. The landslide-conditioning factors, including slope degree, slope aspect, altitude, lithology, rainfall, distance to faults, distance to streams, plan curvature, topographic wetness index, stream power index, sediment transport index, normalized difference vegetation index (NDVI), forest plant community, crown density, and timber volume, were extracted from the spatial database. Using these factors, landslide susceptibility and weights of each factor were analyzed by frequency ratio and index of entropy models. Results showed that the high and very high susceptibility classes cover nearly 50 % of the study area. For verification, the receiver operating characteristic (ROC) curves were drawn and the areas under the curve (AUC) calculated. The verification results revealed that the index of entropy model (AUC = 75.59 %) is slightly better in prediction than frequency ratio model (AUC = 72.68 %). The interpretation of the susceptibility map indicated that NDVI, altitude, and rainfall play major roles in landslide occurrence and distribution in the study area. The landslide susceptibility maps produced from this study could assist planners and engineers for reorganizing and planning of future road construction and timber harvesting operations.Accession Number: WOS:000334172200005 Language: EnglishDocument Type: ArticleAuthor Keywords: Forest road construction; Mountainous terrain; Slope stability; Susceptibility modelingKeyWords Plus: LOGISTIC-REGRESSION MODELS; HAZARD; TURKEY; ROAD; MOUNTAINS; WEIGHTS; TERRAIN; BASIN; AREAAddresses: [Jaafari, A.; Najafi, A.] Tarbiat Modares Univ, Fac Nat Resources, Dept Forestry, Noor, Mazandaran, Iran. [Pourghasemi, H. R.] Tarbiat Modares Univ, Fac Nat Resources, Dept Watershed Management Engn, Noor, Iran. [Rezaeian, J.] Mazandaran Univ Sci & Technol, Dept Ind Engn, Babol Sar, Iran. [Sattarian, A.] Gonbad Kavous Univ, Fac Agr & Nat Resources, Dept Forestry, Gonbad Kavous, Iran. Reprint Address: Najafi, A (reprint author), Tarbiat Modares Univ, Fac Nat Resources, Dept Forestry, POB 64414-356, Noor, Mazandaran, Iran.E-mail Addresses: [email protected]: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Environmental SciencesResearch Areas: Environmental Sciences & EcologyIDS Number: AE7IY ISSN: 1735-1472 eISSN: 1735-2630 29-char Source Abbrev.: INT J ENVIRON SCI TE ISO Source Abbrev.: Int. J. Environ. Sci. Technol. Source Item Page Count: 18

Funding:

Funding Agency Grant NumberTarbiat Modares University

This work was supported by the Tarbiat Modares University. Abdullah Abbasi, Sattar Ezzati, Hamed Asadi, and Mostafa Adib are thanked for their assistance in field surveys. The authors also express their sincere appreciation to the anonymous reviewers for their helpful and valuable detailed comments and suggestions.

Record 30 of 58Title: Landslide susceptibility mapping at central Zab basin, Iran: A comparison between analytical hierarchy process, frequency ratio and logistic regression models Author(s): Shahabi, H (Shahabi, Himan); Khezri, S (Khezri, Saeed); Bin Ahmad, B (Bin Ahmad, Baharin); Hashim, M (Hashim, Mazlan)Source: CATENA Volume: 115 Pages: 55-70 DOI: 10.1016/j.catena.2013.11.014 Published: APR 2014 Times Cited in Web of Science Core Collection: 1 Total Times Cited: 1 Cited References: Akgun A, 2007, ENVIRON GEOL, V51, P1377, DOI 10.1007/s00254-006-0435-6 Akgun A, 2008, ENVIRON GEOL, V54, P1127, DOI 10.1007/s00254-007-0882-8 Akgun A, 2012, ENVIRON MONIT ASSESS, V184, P5453, DOI 10.1007/s10661-011-2352-8 Akinci H., 2011, International Journal of Physical Sciences, V6, P1015 Ayalew L, 2004, LANDSLIDES, V1, P73, DOI 10.1007/s10346-003-0006-9 Ayalew L, 2005, ENG GEOL, V81, P432, DOI 10.1016/j.enggeo.2005.08.004 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Baeza C, 2001, EARTH SURF PROC LAND, V26, P1251, DOI 10.1002/esp.263 Bai SB, 2010, GEOMORPHOLOGY, V115, P23, DOI 10.1016/j.geomorph.2009.09.025 Bednarik M, 2012, NAT HAZARDS, V64, P547, DOI 10.1007/s11069-012-0257-7 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Bui DT, 2011, NAT HAZARDS, V59, P1413, DOI 10.1007/s11069-011-9844-2 Che VB, 2011, NAT HAZARDS, V59, P47, DOI 10.1007/s11069-011-9738-3 Clark W.A., 1986, STAT METHODS GEOGRAP Clerici A, 2002, GEOMORPHOLOGY, V48, P349, DOI 10.1016/S0169-555X(02)00079-X Cruden D.M., 1996, LANDSLIDES INVESTIGA, P36, DOI DOI 10.1007/BF02590167 Dai FC, 2002, GEOMORPHOLOGY, V42, P213, DOI 10.1016/S0169-555X(01)00087-3 Das I, 2010, GEOMORPHOLOGY, V114, P627, DOI 10.1016/j.geomorph.2009.09.023 Dymond JR, 2006, GEOMORPHOLOGY, V74, P70, DOI 10.1016/j.geomorph.2005.08.005 Feizizadeh B, 2013, INT J ENVIRON RES, V7, P319 Iranian Landslide Working Party (ILWP), 2007, IR LANDSL LIST FOR Kaab A, 2008, PERMAFROST PERIGLAC, V19, P107, DOI 10.1002/ppp.619 Kayastha P, 2013, J GEOL SOC INDIA, V81, P219, DOI 10.1007/s12594-013-0025-7 Khezri S., 2013, J BASIC APPL SCI RES, V3, P765 Khezri S., 2013, J BASIC APPL SCI RES, V3, P924 Kleinbaum D.G., 2010, MAXIMUM LIKELIHOOD T Komac M, 2006, GEOMORPHOLOGY, V74, P17, DOI 10.1016/j.geomorph.2005.07.005 Lee S, 2005, INT J REMOTE SENS, V26, P1477, DOI 10.1080/01431160412331331012 Lee S, 2005, GEOSCI J, V9, P63, DOI 10.1007/BF02910555 Lee S, 2007, LANDSLIDES, V4, P33, DOI 10.1007/s10346-006-0047-y Lee S, 2013, CATENA, V100, P15, DOI 10.1016/j.catena.2012.07.014 Lee S, 2006, ENVIRON GEOL, V50, P847, DOI 10.1007/s00254-006-0256-7 Mathew J, 2007, INT J REMOTE SENS, V28, P2257, DOI 10.1080/01431160600928583 Mohammady M, 2012, J ASIAN EARTH SCI, V61, P221, DOI 10.1016/j.jseaes.2012.10.005 Nefeslioglu HA, 2008, ENG GEOL, V97, P171, DOI 10.1016/j.enggeo.2008.01.004 Ozdemir A., 2012, J ASIAN EARTH SCI, V5, P180 Pourghasemi HR, 2012, CATENA, V97, P71, DOI 10.1016/j.catena.2012.05.005



Pradhan B, 2012, ENVIRON MONIT ASSESS, V184, P715, DOI 10.1007/s10661-011-1996-8 Pradhan B, 2010, ENVIRON EARTH SCI, V60, P1037, DOI 10.1007/s12665-009-0245-8 Saaty T. L, 1980, ANAL HIERARCHY PROCE SAATY TL, 1977, J MATH PSYCHOL, V15, P234, DOI 10.1016/0022-2496(77)90033-5 SAATY T. L., 1991, PREDICTION PROJECTIO SAATY TL, 1984, J MATH PSYCHOL, V28, P205, DOI 10.1016/0022-2496(84)90027-0 Sahnoun H, 2012, ENVIRON EARTH SCI, V66, P2477, DOI 10.1007/s12665-011-1471-4 Shahabi H, 2012, INT J ADV ENG TECHNO, V4, P103 Shahabi H., 2012, INT J COMPUT SCI ISS, V9, P108 Shahabi H., 2012, ARAB J GEOSCI, V6, P3885 den Eeckhaut M, 2006, GEOMORPHOLOGY, V76, P392, DOI 10.1016/j.geomorph.2005.12.003 Van Westen CJ, 2003, NAT HAZARDS, V30, P399, DOI 10.1023/B:NHAZ.0000007097.42735.9e Varnes D. J., 1984, LANDSLIDE HAZARD ZON Voogd H, 1983, MULTICRITERIA EVALUA Wan S, 2010, NAT HAZARDS, V52, P211, DOI 10.1007/s11069-009-9366-3 Wan SA, 2009, KNOWL-BASED SYST, V22, P580, DOI 10.1016/j.knosys.2009.07.008 Wang LJ, 2013, COMPUT GEOSCI-UK, V57, P81, DOI 10.1016/j.cageo.2013.04.006 Yalcin A, 2011, CATENA, V85, P274, DOI 10.1016/j.catena.2011.01.014 Yalcin A, 2008, CATENA, V72, P1, DOI 10.1016/j.catena.2007.01.003 Yesilnacar E, 2005, ENG GEOL, V79, P251, DOI 10.1016/j.enggeo.2005.02.002Cited Reference Count: 57 Abstract: The purpose of this study is to compare the landslide susceptibility mapping models of logistic regression (LR), analytical hierarchy process (AHP) and frequency ratio (FR) applied in the central Zab basin (West Azerbaijan Iran). Eight factors were used for landslide susceptibility mapping including slope, aspect, land cover, precipitation, lithology and the distance to roads, drainage, and faults that affect the occurrence of landslides. To get more precision, speed and facility in our analysis, all descriptive and spatial information was entered into GIS system. Satellite images (Landsat ETM+ and SPOT 5) are also used to prepare for land use and landslide-inventory mapping respectively. Landslide events as used as dependant variable and data layers as independent variable, making use of the correlation between these two variables in landslide susceptibility. The three models are validated using the relative landslide density index (R-index) and the receiver operating characteristic (ROC) curves. The predictive capability of each model was determined from the area under the relative operating characteristic curve and the areas under the curves obtained using the LR, AHP, and FR methods are 0.8941, 0.8115, and 0.8634, respectively. These results indicate that the LR and FR models are relatively good estimators of landslide susceptibility in the study area. The interpretations of the susceptibility map reveal that precipitation, lithology and slope played major roles in landslide occurrence and distribution in the central Zab basin. In general, all three models were reasonably accurate. The resultant maps would be useful for regional spatial planning as well as for land cover planning. (C) 2013 Elsevier B.V. All rights reserved.Accession Number: WOS:000331346400007 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslide; GIS; Central Zab basin; Remote sensingKeyWords Plus: WEIGHTED LINEAR COMBINATION; REMOTE-SENSING DATA; NEURAL-NETWORKS; RISK-ASSESSMENT; GIS; AREA; TURKEY; VALIDATION; REGION; JAPANAddresses: [Shahabi, Himan; Bin Ahmad, Baharin; Hashim, Mazlan] UTM, Inst Geospatial Sci & Technol INSTeG, Skudai 81310, Johor Bahru, Malaysia. [Khezri, Saeed] Univ Kurdistan, Fac Nat Resources, Dept Phys Geog, Kurdistan, Iran. Reprint Address: Shahabi, H (reprint author), UTM, Fac Geoinformat & Real Estate, Dept Geoinformat, Skudai 81310, Johor Bahru, Malaysia.E-mail Addresses: [email protected]: ELSEVIER SCIENCE BV Publisher Address: PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS Web of Science Categories: Geosciences, Multidisciplinary; Soil Science; Water ResourcesResearch Areas: Geology; Agriculture; Water ResourcesIDS Number: AA8LG ISSN: 0341-8162 eISSN: 1872-6887 29-char Source Abbrev.: CATENA ISO Source Abbrev.: Catena Source Item Page Count: 16 Record 31 of 58Title: Rainfall event-based landslide susceptibility zonation mapping Author(s): Bhandary, NP (Bhandary, Netra Prakash); Dahal, RK (Dahal, Ranjan Kumar); Timilsina, M (Timilsina, Manita); Yatabe, R (Yatabe, Ryuichi) Source: NATURAL HAZARDS Volume: 69 Issue: 1 Pages: 365-388 DOI: 10.1007/s11069-013-0715-x Published: OCT 2013 Times Cited in Web of Science Core Collection: 1 Total Times Cited: 1 Cited References: Akgun A, 2007, ENVIRON GEOL, V51, P1377, DOI 10.1007/s00254-006-0435-6 Atkinson PM, 1998, COMPUT GEOSCI-UK, V24, P373, DOI 10.1016/S0098-3004(97)00117-9 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Bai SB, 2010, GEOMORPHOLOGY, V115, P23, DOI 10.1016/j.geomorph.2009.09.025 Bednarik M, 2012, NAT HAZARDS, V64, P547, DOI 10.1007/s11069-012-0257-7 Bui DT, 2011, NAT HAZARDS, V59, P1413, DOI 10.1007/s11069-011-9844-2 Carrara A, 1983, PREDICTION PERCEPTIO, P101 Cascini L, 2008, ENG GEOL, V102, P164, DOI 10.1016/j.enggeo.2008.03.016 Cevik E, 2003, ENVIRON GEOL, V44, P949, DOI 10.1007/s00254-003-0838-6 Chang KT, 2007, GEOMORPHOLOGY, V89, P335, DOI 10.1016/j.geomorph.2006.12.011 Chauhan S, 2010, LANDSLIDES, V7, P411, DOI 10.1007/s10346-010-0202-3 Chen ZH, 2007, NAT HAZARDS, V42, P75, DOI 10.1007/s11069-006-9061-6 Chung CJF, 2003, NAT HAZARDS, V30, P451, DOI 10.1023/B:NHAZ.0000007172.62651.2b Dahal RK, 2008, GEOMORPHOLOGY, V102, P496, DOI 10.1016/j.geomorph.2008.05.041 Dahal RK, 2009, ENVIRON GEOL, V56, P1295, DOI 10.1007/s00254-008-1228-x Dahal RK, 2012, GEOMAT NAT HAZ RISK, V3, P161, DOI 10.1080/19475705.2011.629007 Dahal RK, 2008, ENVIRON GEOL, V54, P311, DOI 10.1007/s00254-007-0818-3 Dahal RK, 2006, P 10 INT C IAEG GEOL, P1 Dahal RK, 2010, IAEG 2010 C GEOL ACT, P1053 Dahal RK, 2011, J NEPAL GEOL SOC, V42, P127 Dai FC, 2002, GEOMORPHOLOGY, V42, P213, DOI 10.1016/S0169-555X(01)00087-3 Dai FC, 2001, ENVIRON GEOL, V40, P381, DOI 10.1007/s002540000163 Das I, 2010, GEOMORPHOLOGY, V114, P627, DOI 10.1016/j.geomorph.2009.09.023 Ermini L, 2005, GEOMORPHOLOGY, V66, P327, DOI 10.1016/j.geomorph.2004.09.025 Fell R, 2008, ENG GEOL, V102, P85, DOI 10.1016/j.enggeo.2008.03.022 Frattini P, 2010, ENG GEOL, V111, P62, DOI 10.1016/j.enggeo.2009.12.004 Geological Survey of Japan, 2002, COMP GRAPH GEOL JAP Ghimire M, 2011, NAT HAZARDS, V56, P299, DOI 10.1007/s11069-010-9569-7 Ghosh S, 2012, ENG GEOL, V128, P49, DOI 10.1016/j.enggeo.2011.03.016 Gomez H, 2005, ENG GEOL, V78, P11, DOI 10.1016/j.enggeo.2004.10.004 Guzzetti F, 1999, GEOMORPHOLOGY, V31, P181, DOI 10.1016/S0169-555X(99)00078-1



Guzzetti F, 2006, GEOMORPHOLOGY, V81, P166, DOI 10.1016/j.geomorph.2006.04.007 Guzzetti F, 2005, THESIS R FRIEDRICHWI, P373 Hiura H, 2005, Landslides and Avalanches: ICFL 2005 Norway, P157 Hosmer D. W., 2000, APPL LOGISTIC REGRES, DOI [10.1002/0471722146, DOI 10.1002/0471722146] Jade S, 1993, ENG GEOL, V36, P71 Kayastha P, 2012, NAT HAZARDS, DOI [10.1007/s11069-012-0163-z., DOI 10.1007/S11069-012-0163-Z.0NLINE] Lee S, 2005, INT J REMOTE SENS, V26, P1477, DOI 10.1080/01431160412331331012 Lee S, 2004, INT J GEOGR INF SCI, V18, P789, DOI 10.1080/13658810410001702003 Lee S, 2007, LANDSLIDES, V4, P33, DOI 10.1007/s10346-006-0047-y Lee S, 2006, ENVIRON GEOL, V50, P847, DOI 10.1007/s00254-006-0256-7 Lee S, 2003, EARTH SURF PROC LAND, V28, P1361, DOI 10.1002/esp.593 Melchiorre C, 2008, GEOMORPHOLOGY, V94, P379, DOI 10.1016/j.geomorph.2006.10.035 Miyahisa M, 1976, SUBSURFACE GEOLOGICA Nandi A., 2009, ENG GEOL, V110, P11 Ohlmacher GC, 2003, ENG GEOL, V69, P331, DOI 10.1016/S0013-7952(03)00069-3 Ozdemir A, 2011, NAT HAZARDS, V59, P1573, DOI 10.1007/s11069-011-9853-1 Oztekin B, 2005, ENVIRON GEOL, V49, P124, DOI 10.1007/s00254-005-0071-6 Pantha BR, 2008, EPISODES, V31, P384 Poudyal CP, 2010, ENVIRON EARTH SCI, V61, P1049, DOI 10.1007/s12665-009-0426-5 Pourghasemi HR, 2012, NAT HAZARDS, V63, P965, DOI 10.1007/s11069-012-0217-2 Ramani SE, 2011, J MT SCI-ENGL, V8, P505, DOI 10.1007/s11629-011-2157-9 Regmi NR, 2010, GEOMORPHOLOGY, V115, P172, DOI 10.1016/j.geomorph.2009.10.002 Saha AK, 2005, LANDSLIDES, V2, P61, DOI 10.1007/s10346-004-0039-8 Schicker R, 2012, GEOMORPHOLOGY, V161-162, P10 SIDDLE HJ, 1991, SLOPE STABILITY ENGINEERING, P137 Simizu T, 1976, SOIL MAP NIHAMA AREA Suzen ML, 2004, ENVIRON GEOL, V45, P665, DOI 10.1007/s00254-003-0917-8 den Eeckhaut M, 2006, GEOMORPHOLOGY, V76, P392, DOI 10.1016/j.geomorph.2005.12.003 Van Westen CJ, 1997, STAT LANDSLIDE HAZAR, P73 Van Den Eeckhaut M, 2010, GEOMORPHOLOGY, V115, P141, DOI 10.1016/j.geomorph.2009.09.042 Van Westen CJ, 2003, NAT HAZARDS, V30, P399, DOI 10.1023/B:NHAZ.0000007097.42735.9e Varnes DJ, 1984, INT ASS ENG GEOLOGY WU WM, 1995, WATER RESOUR RES, V31, P2097, DOI 10.1029/95WR01136 Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9 Yin KL, 1988, LANDSLIDES, V2, P1269 Zhu L, 2006, ZHEJIANG U SCI A, V7, P2007Cited Reference Count: 67 Abstract: Landslide susceptibility assessment is a major research topic in geo-disaster management. In recent days, various landslide susceptibility and landslide hazard assessment methodologies have been introduced with diverse thoughts of assessment and validation method. Fundamentally, in landslide susceptibility zonation mapping, the susceptibility predictions are generally made in terms of likelihoods and probabilities. An overview of landslide susceptibility zoning practices in the last few years reveals that susceptibility maps have been prepared to have different accuracies and reliabilities. To address this issue, the work in this paper focuses on extreme event-based landslide susceptibility zonation mapping and its evaluation. An ideal terrain of northern Shikoku, Japan, was selected in this study for modeling and event-based landslide susceptibility mapping. Both bivariate and multivariate approaches were considered for the zonation mapping. Two event-based landslide databases were used for the susceptibility analysis, while a relatively new third event landslide database was used in validation. Different event-based susceptibility zonation maps were merged and rectified to prepare a final susceptibility zonation map, which was found to have an accuracy of more than 77 %. The multivariate approach was ascertained to yield a better prediction rate. From this study, it is understood that rectification of susceptibility zonation map is appropriate and reliable when multiple event-based landslide database is available for the same area. The analytical results lead to a significant understanding of improvement in bivariate and multivariate approaches as well as the success rate and prediction rate of the susceptibility maps.Accession Number: WOS:000325101100021 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslide susceptibility; Event-based landslide; Susceptibility zonationKeyWords Plus: ARTIFICIAL NEURAL-NETWORKS; LOGISTIC-REGRESSION MODELS; WEIGHTS-OF-EVIDENCE; FREQUENCY RATIO; LANTAU-ISLAND; HONG-KONG; GIS; HAZARD; TURKEY; SLOPEAddresses: [Bhandary, Netra Prakash; Dahal, Ranjan Kumar; Timilsina, Manita; Yatabe, Ryuichi] Ehime Univ, Grad Sch Sci & Engn, Dept Civil & Environm Engn, Matsuyama, Ehime 7908577, Japan. [Dahal, Ranjan Kumar] Tribhvuan Univ, Dept Geol, Kathmandu, Nepal. Reprint Address: Bhandary, NP (reprint author), Ehime Univ, Grad Sch Sci & Engn, Dept Civil & Environm Engn, 3 Bunkyo, Matsuyama, Ehime 7908577, Japan.E-mail Addresses: [email protected]; [email protected]; [email protected]; [email protected]: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences; Water ResourcesResearch Areas: Geology; Meteorology & Atmospheric Sciences; Water ResourcesIDS Number: 227GW ISSN: 0921-030X eISSN: 1573-0840 29-char Source Abbrev.: NAT HAZARDS ISO Source Abbrev.: Nat. Hazards Source Item Page Count: 24 Record 32 of 58Title: Landslide susceptibility mapping based on frequency ratio and logistic regression models Author(s): Solaimani, K (Solaimani, K.); Mousavi, SZ (Mousavi, Seyedeh Zohreh); Kavian, A (Kavian, Ataollah)Source: ARABIAN JOURNAL OF GEOSCIENCES Volume: 6 Issue: 7 Pages: 2557-2569 DOI: 10.1007/s12517-012-0526-5 Published: JUL 2013 Times Cited in Web of Science Core Collection: 1 Total Times Cited: 1 Cited References: Abolmasov B, 1997, ENGINEERING GEOLOGY AND THE ENVIRONMENT, VOLS 1-3, P471 ANBALAGAN R, 1992, ENG GEOL, V32, P269, DOI 10.1016/0013-7952(92)90053-2 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Baeza C, 2001, EARTH SURF PROC LAND, V26, P1251, DOI 10.1002/esp.263 Barredol JI, 2000, JAG, V2, P9 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Binaghi E, 1998, NAT HAZARDS, V17, P77, DOI 10.1023/A:1008001724538 Bonham-Carter GF, 1994, GEOGRAPHIC INFORM SY, P398 Brabb E.E., 1984, P 4 INT S LANDSL TOR, V1, P307 Can T, 2005, GEOMORPHOLOGY, V72, P250, DOI 10.1016/j.geomorph.2005.05.011 Carrara A, 2003, EARTH SURF PROC LAND, V28, P1125, DOI 10.1002/esp.545 Carrara A, 1995, GEOGRAPHICAL INFORM, P173 Cascini L, 1991, P 16 INT LANDSL C BA, P899 Cevik E, 2003, ENVIRON GEOL, V44, P949, DOI 10.1007/s00254-003-0838-6



Chau KT, 2004, COMPUT GEOSCI-UK, V30, P429, DOI 10.1016/j.cageo.2003.08.013 Chau KT, 2005, LANDSLIDES, V2, P280, DOI 10.1007/s10346-005-0024-x Chen ZH, 2007, NAT HAZARDS, V42, P75, DOI 10.1007/s11069-006-9061-6 Clerici A, 2002, GEOMORPHOLOGY, V48, P349, DOI 10.1016/S0169-555X(02)00079-X Dai FC, 2002, GEOMORPHOLOGY, V42, P213, DOI 10.1016/S0169-555X(01)00087-3 Dai FC, 2001, ENVIRON GEOL, V40, P381, DOI 10.1007/s002540000163 Dai FC, 2004, J B ENG GEOL ENV, V63, P315 Davis JC, 2006, COMPUT GEOSCI-UK, V32, P1120, DOI 10.1016/j.cageo.2006.02.006 Dominguez-Cuesta M, 2007, J GEOMORPHOL, V89, P1 Duman TY, 2006, ENVIRON GEOL, V51, P241, DOI 10.1007/s00254-006-0322-1 Ercanoglu M, 2004, ENG GEOL, V75, P229, DOI 10.1016/j.enggeo.2004.06.001 Gokceoglu C, 1996, ENG GEOL, V44, P147, DOI 10.1016/S0013-7952(97)81260-4 Gomez H, 2005, ENG GEOL, V78, P11, DOI 10.1016/j.enggeo.2004.10.004 Gorseveski PV, 2000, 14 INT C INT GIS ENV Greco R, 2007, ENG GEOL, V89, P47, DOI 10.1016/j.enggeo.2006.09.006 Guzzetti F, 1999, GEOMORPHOLOGY, V31, P181, DOI 10.1016/S0169-555X(99)00078-1 Guzzetti F, 2005, GEOMORPHOLOGY, V72, P272, DOI 10.1016/j.geomorph.2005.06.002 Hosmer DW, 2000, APPL LOGISTIC REGRES JADE S, 1993, ENG GEOL, V36, P91, DOI 10.1016/0013-7952(93)90021-4 Jibson WR, 2000, J ENG GEOL, V58, P271 Jimg-feng H, 2006, U SCI, V12, P2007 JUANG CH, 1992, J GEOTECH ENG-ASCE, V118, P475, DOI 10.1061/(ASCE)0733-9410(1992)118:3(475) Kanungo DP, 2006, ENG GEOL, V85, P347, DOI 10.1016/j.enggeo.2006.03.004 Kelarestaghi A, 2007, GEOGRAPHICAL RES, V62, P81 Kelarestaghi A, 2009, ARAB J GEOSCI, V2, P95, DOI 10.1007/s12517-008-0022-0 Kelarestaghi A, 2007, GEOGRAPHICAL RES, V87, P49 Larsen MC, 1997, EARTH SURF PROC LAND, V22, P835 Lee S, 2005, ENVIRON GEOL, V47, P982, DOI 10.1007/s00254-005-1228-z Lee S, 2007, LANDSLIDES, V4, P33, DOI 10.1007/s10346-006-0047-y Lee S, 2001, ENVIRON GEOL, V40, P1095, DOI 10.1007/s002540100310 Lee S, 2006, ENVIRON GEOL, V50, P847, DOI 10.1007/s00254-006-0256-7 Lee S, 2004, INT J REMOTE SENS, V25, P2037, DOI 10.1080/01431160310001618734 Luzi L, 2000, ENG GEOL, V58, P313, DOI 10.1016/S0013-7952(00)00041-7 Mirsaneee A, 1999, 1 C GEOL ENG LIV ENV, P83 Mousavi Khatir SZ, 2009, J WATER SOIL CONSERV, V16, P85 Mousavi SZ, 2011, GEOMAT NAT HAZ RISK, V2, P33, DOI 10.1080/19475705.2010.532975 Nefeslioglu HA, 2008, ENG GEOL, V97, P171, DOI 10.1016/j.enggeo.2008.01.004 Ohlamcher GC, 2003, ENG GEOL, V69, P331 Peart MR, 2005, J ASIAN EARTH SCI, V25, P821, DOI 10.1016/j.jseaes.2004.08.004 Pradhan B, 2010, ADV SPACE RES, V45, P1244, DOI 10.1016/j.asr.2010.01.006 Pradhan B., 2008, J APPL REMOTE SENS, V2, P1, DOI DOI 10.1117/12.821511 Pradhan B, 2010, ENVIRON EARTH SCI, V60, P1037, DOI 10.1007/s12665-009-0245-8 Pradhan B, 2009, J APPL GEOMATICS, V1, P3 Pradhan B, 2010, PHOTOGRAMM FERNERKUN, P17, DOI 10.1127/1432-8364/2010/0037 Rengers N, 1998, CHAPTER APP IN PRESS Saha AK, 2002, INT J REMOTE SENS, V23, P357, DOI 10.1080/01431160010014260 Soeters R, 1996, LANDSLIDES INVESTIGA, V247, P129 Suzen ML, 2004, ENG GEOL, V71, P303, DOI 10.1016/S0013-7952(03)00143-1 Suzen ML, 2004, ENVIRON GEOL, V45, P665, DOI 10.1007/s00254-003-0917-8 Tangestani MH, 2009, J ASIAN EARTH SCI, V35, P66, DOI 10.1016/j.jseaes.2009.01.002 Temesgen B, 2001, PHYS CHEM EARTH PT C, V26, P665, DOI 10.1016/S1464-1917(01)00065-4 Wieczorek GF, 1996, P 7 INT S LANDSL TRO Yaclin A, 2008, J CATENA, V72, P1 Yesilnacar E, 2005, ENG GEOL, V79, P251, DOI 10.1016/j.enggeo.2005.02.002 Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9 Yilmaz I, 2009, J COMPUT GEOSCI, V35, P1125 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P297, DOI 10.1007/s10064-009-0185-2 Zhou G, 2003, ENG GEOL, V68, P373, DOI 10.1016/S0013-7952(02)00241-7Cited Reference Count: 72 Abstract: The aim of this study is to apply and compare a probability model, frequency ratio and statistical model, and a logistic regression to Sajaroud area, Northern Iran using geographic information system. Landslide locations of the study area were detected from interpretation of aerial photographs and field surveys. Landslide-related factors such as elevation, slope gradient, slope aspect, slope curvature, rainfall, distance to fault, distance to drainage, distance to road, land use, and geology were calculated from the topographic and geology map and LANDSAT ETM satellite imagery. The spatial relationships between the landslide location and each landslide-related factor were analyzed and then landslide susceptibility maps were produced using the frequency ratio and forward stepwise logistic regression methods. Finally, the maps were tested and compared using known landslide locations, and success rates were calculated. Predicted accuracy values for frequency ratio (79.48%) and logistic regression models showed that the map obtained from frequency ratio model is more accurate than the logistic regression (77.4%) model. The models used in this study have shown a great deal of importance for watershed management and land use planning.Accession Number: WOS:000320662000028 Language: EnglishDocument Type: ArticleAuthor Keywords: Susceptibility mapping; Frequency ratio; Logistic regression; Northern IranKeyWords Plus: ARTIFICIAL NEURAL-NETWORKS; HONG-KONG; INFORMATION-SYSTEMS; HAZARD EVALUATION; DEMPSTER-SHAFER; LANTAU-ISLAND; REGION TURKEY; GIS; ZONATION; FUZZYAddresses: [Solaimani, K.] Sari Univ Agr Sci & Nat Resources, GIS Ctr, Sari, Iran. [Mousavi, Seyedeh Zohreh; Kavian, Ataollah] Sari Univ Agr Sci & Nat Resources, Sari, Iran. Reprint Address: Solaimani, K (reprint author), Sari Univ Agr Sci & Nat Resources, GIS Ctr, Sari, Iran.E-mail Addresses: [email protected]: SPRINGER HEIDELBERG Publisher Address: TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY Web of Science Categories: Geosciences, MultidisciplinaryResearch Areas: GeologyIDS Number: 167UZ ISSN: 1866-7511 eISSN: 1866-7538 29-char Source Abbrev.: ARAB J GEOSCI ISO Source Abbrev.: Arab. J. Geosci. Source Item Page Count: 13 Record 33 of 58Title: Mechanism of mining-induced slope movement for gullies overlaying shallow coal seams Author(s): Wang, XF (Wang Xu-feng); Zhang, DS (Zhang Dong-sheng); Zhang, CG (Zhang Cheng-guo); Fan, GW (Fan Gang-wei)



Source: JOURNAL OF MOUNTAIN SCIENCE Volume: 10 Issue: 3 Pages: 388-397 DOI: 10.1007/s11629-013-2455-5 Published: JUN 2013 Times Cited in Web of Science Core Collection: 1 Total Times Cited: 1 Cited References: Altun AO, 2010, SCI RES ESSAYS, V5, P3206 Chen YL, 2012, INT J MINING SCI TEC, V22, P487 Cui F, 2011, COAL SCI TECHNOLOGY, V39, P10 Erginal AE, 2008, GEOGR ANN A, V90A, P109, DOI 10.1111/j.1468-0459.2008.00159.x Fan Gang-wei, 2009, Journal of Coal Science and Engineering (China), V15, DOI 10.1007/s12404-009-0402-4 Fan KG, 2010, ADV INTEL SYS RES, V12, P76 He MC, 2008, INT J ROCK MECH MIN, V45, P289, DOI 10.1016/j.ijrmms.2007.05.007 Ji H, 2012, COAL ENG, P69 [蒋泽泉 JIANG Zequan], 2011, [中国地质灾害与防治学报, The Chinese Journal of Geological Hazard and Control], V22, P87 [康建荣 KANG Jianrong], 2008, [岩石力学与工程学报, Chinese Journal of Rock Mechanics and Engineering], V27, P59 Li WX, 2006, INT J ROCK MECH MIN, V43, P503, DOI 10.1016/j.ijrmms.2005.09.008 Lin SZ, 1989, J XIAN COLL GEOLOGY, V11, p[70, 112] Malgot J, 1986, B INT ASS ENG GEOLOG, V33, P57, DOI 10.1007/BF02594706 Marschalko M, 2009, ACTA MONTAN SLOVACA, V14, P232 Marschalko M, 2008, ACTA MONTAN SLOVACA, V13, P58 Peng XZ, 2008, J MINING SAFETY ENG, V25, P301 Singh R, 2008, INT J ROCK MECH MIN, V45, P29, DOI 10.1016/j.ijrmms.2007.03.006 Singh VK, 2006, J SCI IND RES INDIA, V65, P47 [缪协兴 MIAO Xie-xing], 2009, [岩石力学与工程学报, Chinese Journal of Rock Mechanics and Engineering], V28, P217 Tang Fu-quan, 2009, Journal of Coal Science and Engineering (China), V15, DOI 10.1007/s12404-009-0403-3 Wang JA, 2010, J MT SCI-ENGL, V7, P282, DOI 10.1007/s11629-010-2020-4 [王双明 WANG Shuang-ming], 2010, [煤炭学报, Journal of China Coal Society], V35, P7 Wang XF, 2011, MINING SCI TECHNOLOG, V21, P23 Wang XF, 2009, THESIS CHINA U MININ Yang JH, 2010, THESIS XIAN U SCI TE [尹光志 Yin Guangzhi], 2012, [北京科技大学学报, Journal of University Science and Technology Beijing], V34, P231 Yuan T, 2011, THESIS XIAN U SCI TE Zhang DS, 2012, INT J MINING SCI TEC, V22, P47 Zhang ZQ, 2012, INT J MINING SCI TEC, V22, P51 Zhong XC, 2007, THESIS CHINA U MININCited Reference Count: 30 Abstract: This paper provides an improved understanding of the movement mechanisms of both bed-rock gully and sandy soil gully when underground mining occurs underneath, followed by systematic analysis of the contributing factors such as mining advance direction, gully slope angle, gully erosion coefficient and mining height. This paper presents the results from monitoring, theoretical analyses and up to date modeling based on the geological features in the gully affected area, and the implications of these results to the success of roof support trial. It was observed that when mining occurred towards the gully, sliding of slope block along the fracture surface occurred, which resulted in unstable roof condition; when mining progressed away from the gully, polygon blocks developed in the gully slope and rotated in reversed direction forming hinged structure; within the bed-rock slope, the hinged structure was unstable due to shear failure of the polygon block; however, within the sandy soil slope, the structure was relatively stable due to the gradual rotating and subsiding of the polygon block. The increase of the value of slope angle and mining height lead to a faster and more intensive fracture development within the gully slope, which had a pronounced effect on gully slope stability and underground pressure. Various remediation approaches are hence proposed in this paper including introducing more powerful support and reasonable mining height, setting up working face along or away from gullies, using room and pillar, strip mining and backfill instead of longwall mining.Accession Number: WOS:000319418700006 Language: EnglishDocument Type: ArticleAuthor Keywords: Coal mine; Shallow coal seam; Gully slope; Movement mechanism; Roof control; Mining methodKeyWords Plus: STRATA MOVEMENT; STABILITY; LANDSLIDE; DESIGNAddresses: [Wang Xu-feng; Zhang Dong-sheng; Fan Gang-wei] China Univ Min & Technol, Sch Mines, Xuzhou 221116, Peoples R China. [Wang Xu-feng; Zhang Dong-sheng; Fan Gang-wei] State Key Lab Coal Resource & Mine Safety, Xuzhou 221116, Peoples R China. [Wang Xu-feng; Zhang Dong-sheng; Fan Gang-wei] Minist Educ China, Key Lab Deep Coal Resource Min, Xuzhou 221116, Peoples R China. [Zhang Cheng-guo] Univ New S Wales, Sydney, NSW 2052, Australia. Reprint Address: Zhang, DS (reprint author), China Univ Min & Technol, Sch Mines, Xuzhou 221116, Peoples R China.E-mail Addresses: [email protected]; [email protected]: SCIENCE PRESS Publisher Address: 16 DONGHUANGCHENGGEN NORTH ST, BEIJING 100717, PEOPLES R CHINA Web of Science Categories: Environmental SciencesResearch Areas: Environmental Sciences & EcologyIDS Number: 150VE ISSN: 1672-6316 29-char Source Abbrev.: J MT SCI-ENGL ISO Source Abbrev.: J Mt. Sci. Source Item Page Count: 10

Funding:

Funding Agency Grant NumberNational Natural Science Foundation of China 51004101

51264035 Science Foundation for Young Scholars of China University of Mining Technology 2009A001 Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) Fundamental Research Funds for the Central Universities 2012QNA35

We acknowledge the financial support for this work, provided by the National Natural Science Foundation of China (Grant No. 51004101, No. 51264035), the Science Foundation for Young Scholars of China University of Mining & Technology (Grant No. 2009A001), the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), the Fundamental Research Funds for the Central Universities (2012QNA35). The Program for Introduction of Talents of China University of Mining & Technology is also gratefully acknowledged.

Record 34 of 58Title: Hazards of heavy metal contamination at Lubietova Cu-deposit (Slovakia) Author(s): Andras, P (Andras, Peter); Turisova, I (Turisova, Ingrid); Krnac, J (Krnac, Jozef); Dirner, V (Dirner, Vojtech); Volekova-Lalinska, B (Volekova-Lalinska, Bronislava); Buccheri, G (Buccheri, Giuseppe); Jelen, S (Jelen, Stanislav)Edited by: PatruStupariu I; Patroescu M; Ioja CI; Rozylowicz LSource: 2011 INTERNATIONAL CONFERENCE OF ENVIRONMENT-LANDSCAPE-EUROPEAN IDENTITY Book Series: Procedia Environmental Sciences Volume: 14 Pages: 3-21 DOI: 10.1016/j.proenv.2012.03.002 Published: 2012 Times Cited in Web of Science Core Collection: 1 Total Times Cited: 1 Cited References: Achal V, 2011, ECOL ENG, V37, P1601, DOI 10.1016/j.ecoleng.2011.06.008 Andras P., 2009, ADV TECHNOLOGIES, P163 Andras P, 2007, ACTA FACULTATIS ECOL, V16, P147



BAKER AJM, 1981, J PLANT NUTR, V3, P643, DOI 10.1080/01904168109362867 Baker AJM, 1990, HEAVY METAL TOLERANC, P156 Bartzas G, 2006, MINER ENG, V19, P505, DOI 10.1016/j.mineng.2005.09.032 Bergfest A, 1951, BANICTVO V LUBIETOVE Bethke C, 2000, GEOCHEMISTS WORKBENC Bigham JM, 1996, GEOCHIM COSMOCHIM AC, V60, P2111, DOI 10.1016/0016-7037(96)00091-9 Bowen HJM, 1979, KOMPOSTOVANI ODPADU, P83 CATALDO DA, 1978, ENVIRON HEALTH PERSP, V27, P149, DOI 10.2307/3428874 Derakhshani R., 2010, Research Journal of Environmental Sciences, V4, P250 FERGUSON JF, 1972, WATER RES, V6, P1259, DOI 10.1016/0043-1354(72)90052-8 Greenwood N. N., 1990, CHEM ELEMENTE Hintikka V, 2001, GEOLOGICAL SURVEY FI, V32, P151 Ilavsky J, 1994, LUBIETOVA STRUKTURNO Jornanov HJ, 2007, DESALINATION, V213, P65 Keeney DR, 1972, SOILS MANAGEMENT ORG, P142 KISHK FM, 1973, PLANT SOIL, V39, P497 Kodera M, 1990, TOPOGRAFICKA MINERAL Kozac J, 1996, GEOVESTNIK, V28, P5 Lin Z, 2000, ENVIRON GEOL, V39, P753 Lintnerova O, 2005, MINERALIA SLOVACA, V37, P517 Manning BA, 1997, ENVIRON SCI TECHNOL, V31, P2005, DOI 10.1021/es9608104 Marschalko M, 2011, ENG GEOL, V122, P169, DOI 10.1016/j.enggeo.2011.05.008 Missana T., 2008, PHYS CHEM EARTH S1, V33, P156 Monterroso C, 1998, SCI TOTAL ENVIRON, V216, P121, DOI 10.1016/S0048-9697(98)00149-1 Morin KA., 1997, ENV GEOCHEMISTRY MIN Varsha Mudgal, 2010, Agriculture and Biology Journal of North America, V1, P40 Pilon-Smits EAH, 2009, CURR OPIN PLANT BIOL, V12, P267, DOI 10.1016/j.pbi.2009.04.009 Rosado L, 2008, MINERAL MAG, V72, P489, DOI 10.1180/minmag.2008.072.1.489 Routson RC, 1969, CHEM ENG PROGR S SER, V65, P19 Rybicka E. H., 1995, Applied Clay Science, V9, P369 Ryu JH, 2002, GEOCHIM COSMOCHIM AC, V66, P2981, DOI 10.1016/S0016-7037(02)00897-9 Sobek AA, 1978, 600278054 EPA IND EN Stuben D, 2001, ENVIRON MONIT ASSESS, V70, P181, DOI 10.1023/A:1010663631647 Vink BW, 1996, CHEM GEOL, V130, P21, DOI 10.1016/0009-2541(95)00183-2 Wahba M., 2007, J APPL SCI RES, V3, P421 Wang X, 2008, CHEMOSPHERE, V72, P1260, DOI 10.1016/j.chemosphere.2008.05.001 Younger PL, 2002, MINE WATER HYDROLOGYCited Reference Count: 40 Abstract: The dump-fields Podlipa and Reiner at Lubietova abandoned Cu-(Ag) deposit is situated at the boundary of the village settlement. The heavy metal contamination of the technogenous sediments and soils at the investigated dump-field show irregular planar distribution. Also the heavy metal content in the surface water, drainage water and in the groundwater was studied both in the dry as well as during the rainy periods. The speciation of As and Sb showed that there are present both As3+, Sb3+ as well as the less toxic As5+ and Sb5+ species. In the sediments prevail As5+ and Sb5+ species while in the water is dominant the As3+ and Sb3+ form. The article also presents results of the plant tissue degradation study in heavy metal contaminated conditions and compares them with those from reference sites. The cementation process causes substitution of iron by copper. The technogenous sediments and the contaminated soil of the dump show only very limited acidification potential. The installation of the Fe-0-barrier seems to an acceptable solution for cleaning of the underground water. (c) 2011 Published by Elsevier B.V. Selection and/or peer review under responsibility of University of Bucharest, Faculty of Geography, Department of Regional Geography and Environment, Centre for Environmental Research and Impact Studies.Accession Number: WOS:000312370500001 Language: EnglishDocument Type: Proceedings PaperConference Title: International Conference of Environment, Landscape, European Identity / Annual Scientific Meeting of the Faculty-of-Geography Conference Date: NOV 04-06, 2011 Conference Location: Bucharest, ROMANIA Conference Sponsors: Univ Bucharest, Fac Geog, Dept Reg Geog & Environm, Natl Author Sci Res, Natl Univ Res Council, Intergraph Comp ServAuthor Keywords: contamination; dump-field; heavy metals; sediment; soil; acid potential; neutralisation potential; plant contaminationKeyWords Plus: CLAY-MINERALS; DESORPTION; STABILITY; WATERS; PLANTS; ACCUMULATION; ADSORPTION; OXIDATION; SORPTION; COPPERAddresses: [Andras, Peter; Turisova, Ingrid; Krnac, Jozef] Matej Bel Univ, Fac Nat Sci, Banska Bystrica 97401, Slovakia. Reprint Address: Andras, P (reprint author), Matej Bel Univ, Fac Nat Sci, Tajovskeho 40, Banska Bystrica 97401, Slovakia.E-mail Addresses: [email protected]: ELSEVIER SCIENCE BV Publisher Address: SARA BURGERHARTSTRAAT 25, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS Web of Science Categories: Environmental SciencesResearch Areas: Environmental Sciences & EcologyIDS Number: BDA73 ISSN: 1878-0296 29-char Source Abbrev.: PROCEDIA ENVIRON SCI Source Item Page Count: 19 Record 35 of 58Title: On the Use of Conventional and Soft Computing Models for Prediction of Gross Calorific Value (GCV) of Coal Author(s): Erik, NY (Erik, Nazan Yalcin); Yilmaz, I (Yilmaz, Isik)Source: INTERNATIONAL JOURNAL OF COAL PREPARATION AND UTILIZATION Volume: 31 Issue: 1 Pages: 32-59 Article Number: DOI: 10.1080/19392699.2010.534683 Published: 2011 Times Cited in Web of Science Core Collection: 1 Total Times Cited: 1 Cited References: Alvarez GM, 1999, INT J ROCK MECH MIN, V36, P339 [Anonymous], 2005, SOFTW TECHN COMP MOD ASTM, 2004, 2004 ANN BOOK ASTM S, V04.08 Channiwala SA, 2002, FUEL, V81, P1051, DOI 10.1016/S0016-2361(01)00131-4 Cordero T, 2001, FUEL, V80, P1567, DOI 10.1016/S0016-2361(01)00034-5 Demirbas A, 1997, FUEL, V76, P431, DOI 10.1016/S0016-2361(97)85520-2 Finol J, 2001, J PETROL SCI ENG, V29, P97, DOI 10.1016/S0920-4105(00)00096-6 GIVEN PH, 1986, FUEL, V65, P849, DOI 10.1016/0016-2361(86)90080-3 JANG JSR, 1993, IEEE T SYST MAN CYB, V23, P665, DOI 10.1109/21.256541 JANG JSR, 1995, P IEEE, V83, P378, DOI 10.1109/5.364486 Jin Y., 1999, FUZZY THEORY SYSTEMS Kaynar O, 2011, ENER EDUC SCI TECH-A, V26, P221 KUCUKBAYRAK S, 1991, FUEL, V70, P979, DOI 10.1016/0016-2361(91)90054-E LEE CC, 1990, IEEE T SYST MAN CYB, V20, P404, DOI 10.1109/21.52551 LEE CC, 1990, IEEE T SYST MAN CYB, V20, P419, DOI 10.1109/21.52552 Loukas YL, 2001, J MED CHEM, V44, P2772, DOI 10.1021/jm000226c



Majumder AK, 2008, FUEL, V87, P3077, DOI 10.1016/j.fuel.2008.04.008 Marschalko M, 2009, ACTA MONTAN SLOVACA, V14, P232 Marschalko M, 2008, ACTA MONTAN SLOVACA, V13, P58 MASON DM, 1983, FUEL PROCESS TECHNOL, V7, P11, DOI 10.1016/0378-3820(83)90022-X Mazumdar B. K., 1954, J SCI IND RES B PH S, V13B, P857 Mazumdar BK, 2000, FUEL, V79, P1413, DOI 10.1016/S0016-2361(99)00272-0 Mesroghli S, 2009, INT J COAL GEOL, V79, P49, DOI 10.1016/j.coal.2009.04.002 Parikh J, 2005, FUEL, V84, P487, DOI 10.1016/j.fuel.2004.10.010 Patel SU, 2007, FUEL, V86, P334, DOI 10.1016/j.fuel.2006.07.036 Rumelhart D. E., 1986, PARALLEL DISTRIBUTED, V1 Rumelhart DE, 1986, PARALLEL DISTRIBUTED Schuster VF, 1951, BRENNST CHEM, V32, P19 Simpson PK, 1990, ARTIFICIAL NEURAL SY Singh TN, 2003, MIN ENG J, V5, P12 Spooner C. E., 1951, FUEL, V30, P193 *SPSS INC, 1999, STAT AN SOFTW STAND Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2009, INT J ROCK MECH MIN, V46, P803, DOI 10.1016/j.ijrmms.2008.09.002 Yilmaz I, 2006, ENG GEOL, V85, P295, DOI 10.1016/j.enggeo.2006.02.005 Yilmaz I, 2008, ROCK MECH ROCK ENG, V41, P781, DOI 10.1007/s00603-007-0138-7Cited Reference Count: 36 Abstract: Gross calorific value (GCV) is an important characteristic of coal and organic shale; the determination of GCV, however, is difficult, time-consuming, and expensive and is also a destructive analysis. In this article, the use of some soft computing techniques such as ANNs (artificial neural networks) and ANFIS (adaptive neuro-fuzzy inference system) for predicting GCV (gross calorific value) of coals is described and compared with the traditional statistical model of MR (multiple regression). This article shows that the constructed ANFIS models exhibit high performance for predicting GCV. The use of soft computing techniques will provide new approaches and methodologies in prediction of some parameters in investigations about the fuel.Accession Number: WOS:000287085600004 Language: EnglishDocument Type: ArticleAuthor Keywords: ANFIS; ANN; Coal; Gross calorific value; Multiple regression; Soft computingKeyWords Plus: FUZZY-LOGIC CONTROLLER; PROXIMATE ANALYSIS; INFERENCE SYSTEM; ROCK PARAMETERS; HEATING VALUES; NEURAL-NETWORK; FUELS; LIQUID; HHVAddresses: [Erik, Nazan Yalcin; Yilmaz, Isik] Cumhuriyet Univ, Dept Geol Engn, Fac Engn, TR-58140 Sivas, Turkey. Reprint Address: Erik, NY (reprint author), Cumhuriyet Univ, Dept Geol Engn, Fac Engn, TR-58140 Sivas, Turkey.E-mail Addresses: [email protected]: TAYLOR & FRANCIS INC Publisher Address: 325 CHESTNUT ST, SUITE 800, PHILADELPHIA, PA 19106 USA Web of Science Categories: Energy & Fuels; Mining & Mineral ProcessingResearch Areas: Energy & Fuels; Mining & Mineral ProcessingIDS Number: 717YQ ISSN: 1939-2699 29-char Source Abbrev.: INT J COAL PREP UTIL ISO Source Abbrev.: Int. J. Coal Prep. Util. Source Item Page Count: 28 Record 36 of 58Title: HEAVY METAL CONTAMINATION AND ITS IMPACT ON PLANTS AT CAPORCIANO Cu-MINE (MONTECATINI VAL DI CECINA, ITALY) Author(s): Buccheri, G (Buccheri, Giuseppe); Andras, P (Andras, Peter, Jr.); Andras, P (Andras, Peter); Dadova, J (Dadova, Jana); Kupka, J (Kupka, Jiri)Source: CARPATHIAN JOURNAL OF EARTH AND ENVIRONMENTAL SCIENCES Volume: 9 Issue: 4 Pages: 73-81 Published: NOV 2014 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Andras P., 2014, REMNANTS OLD ACTIVIT Andras P, 2007, CARPATH J EARTH ENV, V2, P5 Andras P., 2012, PROCEDIA ENV SCI, P3 Aschenbrenner S., 2011, ACTA U MATTHIAE B EM, V13/2, P48 BAKER AJM, 1981, J PLANT NUTR, V3, P643, DOI 10.1080/01904168109362867 Banasova V, 2006, BIOLOGIA, V61, P433, DOI 10.2478/s11756-006-0073-1 Beck R, 1905, NATURE ORE DEPOSITS, P45 Bertolani M., 1973, B SOC GEOL ITAL, VXCII, P635 Curlik J, 2003, MAP SOIL CONTAMINATI De Michele V., 1987, MINERAL PROCESSING M, P1 Fuleky G., 2008, CARPATH J EARTH ENV, V3, p[2, 93] Hemond H.F., 2000, CHEM FATE TRANSPORT Horn HA, 2012, CARPATH J EARTH ENV, V7, P211 Kempa T, 2013, ENG GEOL, V154, P42, DOI 10.1016/j.enggeo.2012.12.008 Kisku GC, 2000, WATER AIR SOIL POLL, V120, P121, DOI 10.1023/A:1005202304584 Klemm D.D., 1982, COPPER DEPOSIT OPHIO, V7, P331 Lotti B, 1884, B R COMIT GEOLOGICO, VXV, P359 Marrucci A, 2000, RASSEGNA VOLTERRANA, VLXXVII, P80 Marschalko M, 2012, B ENG GEOL ENVIRON, V71, P105, DOI 10.1007/s10064-011-0401-8 Mazzuoli L, 1883, R COMITATO GEOLOGICO, V9, P44 McNeill D. J., 1992, SOIL SCI SOC AM SPEC, V30 Mehes-Smith M., 2013, American Journal of Environmental Sciences, V9, P483 Pitter P, 2009, HYDROGEOCHEMISTRY Richter R., 2003, USTAV ZEMEDELSKYCH P Riparbelli A., 1980, HIST MONTECATINI VC Schneider A., 1890, COPPER MINE MONTECAT Sobek A.A., 1978, 600278054 EPA ENV PR Strba T., 2013, MODERN PHYTOMORPHOLO, V2/4, P13 Terenzi A., 1988, RIV MINERALOGICA ITA, V12, P19 Tomaskin J, 2012, CARPATH J EARTH ENV, V7, P71 Turisova I, 2013, B ENVIRON CONTAM TOX, V91, P469, DOI 10.1007/s00128-013-1074-8Cited Reference Count: 31 Abstract: This article reports an environmental study concerning the abandoned Caporciano copper mine in Montecatini Val di Cecina. The environmental matrices (water, soil, dump sediments, plants) of the studied mining sites were investigated in order to evaluate its environmental status. The heavy metals mobilization can cause contamination of country components. Our attention was focused on heavy metal content in the studied environmental matrices. Concentration values which we found out by laboratory analyses were also compared with concentration limits provided by Italian law (L.D. 152/06) as far as soil and water are concerned. Acidification potential of dump sediments and soils from the dump was also studied. The acidification risk seems to be negligible. The bioconcentration factor (BIF <1) and translocation factor (TF in average 4.063 for Pinus sp. and 3.340 for Quercus sp.) of the heavy metals in the studied plants indicate that the plants are excluders. Also the enrichment factor (EF) is not



very high. The highest EF value was calculated for Cd in Pinus sp. (in average 42.59), while for Mn, Pb and Cu in Quercus sp. (EF = 8.10, 8,00, 8.23 in average). The lowest EF shows Cd in Quercus sp. (1.19 in average).Accession Number: WOS:000344580900007 Language: EnglishDocument Type: ArticleAuthor Keywords: contamination; dump-field; heavy metals; soil; plants; biocaccumulation factor; translocation factor; enrichment factorKeyWords Plus: CENTRAL SLOVAKIA; SITES; SOILAddresses: [Buccheri, Giuseppe; Andras, Peter] Matej Bel Univ, Fac Sci, Banska Bystrica 97401, Slovakia. [Andras, Peter, Jr.; Andras, Peter; Dadova, Jana; Kupka, Jiri] VSB Techn Univ Ostrava, Fac Min & Geol, Ostrava 70833, Czech Republic. [Andras, Peter, Jr.] State Nat Conservancy Slovak Republ, Banska Bystrica 97401, Slovakia. Reprint Address: Buccheri, G (reprint author), Matej Bel Univ, Fac Sci, Tajovskeho 40, Banska Bystrica 97401, Slovakia.E-mail Addresses: [email protected]; [email protected]: NORTH UNIV BAIA MARE Publisher Address: FACULTY MINERAL RESOURCES & ENVIRONMENT, DR VICTOR BABES 62-A,, BAIA MARE, 430083, ROMANIA Web of Science Categories: Environmental SciencesResearch Areas: Environmental Sciences & EcologyIDS Number: AS9SD ISSN: 1842-4090 eISSN: 1844-489X 29-char Source Abbrev.: CARPATH J EARTH ENV ISO Source Abbrev.: Carpath. J. Earth Environ. Sci. Source Item Page Count: 9

Funding:

Funding Agency Grant NumberSlovak Research and Development Agency APVV-0663-10

This work was supported by the Slovak Research and Development Agency under the contract APVV-0663-10 Contamination of mining country by toxic elements at selected Cu-deposits and possibilities of its remediation. The authors thank also to Dr. Jozef Krnac for technical works.

Record 37 of 58Title: Predictive models for pot-hole depth in underground coal mining-some Indian experiences Author(s): Lokhande, RD (Lokhande, R. D.); Murthy, VMSR (Murthy, V. M. S. R.); Singh, KB (Singh, K. B.)Source: ARABIAN JOURNAL OF GEOSCIENCES Volume: 7 Issue: 11 Pages: 4697-4705 DOI: 10.1007/s12517-013-1077-0 Published: NOV 2014 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Abdulla WA, 1996, J GEOTECH ENG-ASCE, V122, P998, DOI 10.1061/(ASCE)0733-9410(1996)122:12(998) Abdullah WA, 1996, J GEOTEC ENG, V122, P79 Altun AO, 2010, SCI RES ESSAYS, V5, P3206 Atkinson JH, 1975, TUNNELS TUNNELING, V7, P7 BRADY BGH, 1993, ROCK MECH UNDERGROUN BROWN ET, 1979, T I MIN METALL A, V88, pA92 Choobbasti AJ, 2009, ARAB J GEOSCI, V2, P311, DOI 10.1007/s12517-009-0035-3 CRAIG WH, 1990, CAN GEOTECH J, V27, P355 DAVIS EH, 1980, GEOTECHNIQUE, V30, P397 Dunrud CR, 1984, REV ENG GEOLOGY, V6, P151 Dyne LA, 1998, THESIS BLACKSBURG, P5 GEMAN S, 1992, NEURAL COMPUT, V4, P1, DOI 10.1162/neco.1992.4.1.1 Goyal P, 2006, ATMOS ENVIRON, V40, P2068, DOI 10.1016/j.atmosenv.2005.11.041 Hoek E, 1974, T I MIN METALL A, V83A, P133 LECA E, 1990, GEOTECHNIQUE, V40, P581 Lokhande R. D., 2013, Geotechnical and Geological Engineering, V31, DOI 10.1007/s10706-012-9598-y Lokhande RD, 2005, J SCI IND RES INDIA, V64, P323 Marschalko M, 2012, ENG GEOL, V147, P37, DOI 10.1016/j.enggeo.2012.07.014 Monjezi M, 2011, ARAB J GEOSCI, V4, P845, DOI 10.1007/s12517-009-0101-x Montgomery DC, 2003, INTRO LINEAR REGRESS MUHLHAUS HB, 1985, ROCK MECH ROCK ENG, V18, P37, DOI 10.1007/BF01020414 Palchik V, 2002, ENVIRON GEOL, V42, P92, DOI 10.1007/s00254-002-0542-y Piggott RI, 1978, P 1 INT C LARG GROUN, P749 Price DG, 1969, J ENG GEOL, V1, P271 Reza M, 2013, ARAB J GEOSCI, V6, P115 Roy S., 2011, Journal of Environmental Science and Technology, V4, P284 Singh KB, 2007, ENG GEOL, V89, P88, DOI 10.1016/j.enggeo.2006.09.011 Tharp TM, 1999, ENG GEOL, V52, P22 Vaziri HH, 2001, INT J SOLIDS STRUCT, V38, P3735, DOI 10.1016/S0020-7683(00)00239-0 Whittaker BN, 1989, SUBSIDENCE OCCURRENCCited Reference Count: 30 Abstract: Ground subsidence induced by extraction of coal seam belowground brings about changes in territorial environment. This occurs in two forms, namely, trough and pothole subsidence. Pot-hole subsidence is extremely hazardous as it does not give any prior indication before its occurrence. Several pot-holes have occurred in the recent past in the coal mines of South Eastern Coalfields Limited and called for a specific study to develop an in-depth understanding of various parameters influencing the pot-hole occurrence for formulating the basis of different predictive models. These critical parameters have been compiled and analysed for seven mines located in different areas of SECL, a subsidiary of Coal India Limited. Multiple regression and artificial neural network (ANN) techniques were used for the preparation of the predictive models to calculate pot-hole depth under different conditions. Different conditions considered in the study are development and depillaring, presence and absence of faults and water bodies. This paper presents the results of the studies carried out in Indian mines representing different geo-mining conditions along with the pot-hole depth prediction models developed. The developed models were validated for a few new cases with the model results matching (within 10 % error in the case of ANN model) with the actual pot-hole depth measured. More varied data sets can fine tune the developed models further.Accession Number: WOS:000344476700017 Language: EnglishDocument Type: ArticleAuthor Keywords: Coal mine; Subsidence; Pot-hole depth; Multiple regression model; Artificial neural networkKeyWords Plus: LOWER-BOUND SOLUTIONS; CIRCULAR TUNNELS; STABILITY; SUBSIDENCE; MINESAddresses: [Lokhande, R. D.] Natl Inst Technol Raipur, Raipur, Chhattisgarh, India. [Murthy, V. M. S. R.] Indian Sch Mines, Dhanbad, Jharkhand, India. [Singh, K. B.] Cent Inst Min & Fuel Res, Dhanbad, Jharkhand, India. Reprint Address: Lokhande, RD (reprint author), Natl Inst Technol Raipur, Raipur, Chhattisgarh, India.E-mail Addresses: [email protected]: SPRINGER HEIDELBERG Publisher Address: TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY Web of Science Categories: Geosciences, Multidisciplinary



Research Areas: GeologyIDS Number: AS8CA ISSN: 1866-7511 eISSN: 1866-7538 29-char Source Abbrev.: ARAB J GEOSCI ISO Source Abbrev.: Arab. J. Geosci. Source Item Page Count: 9 Record 38 of 58Title: A computational modeling of student cognitive processes in science education Author(s): Lamb, RL (Lamb, Richard L.); Vallett, DB (Vallett, David B.); Akmal, T (Akmal, Tariq); Baldwin, K (Baldwin, Kathryn)Source: COMPUTERS & EDUCATION Volume: 79 Pages: 116-125 DOI: 10.1016/j.compedu.2014.07.014 Published: OCT 2014 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Ajwani D, 2013, J PARALLEL DISTR COM, V73, P1362, DOI 10.1016/j.jpdc.2013.06.002 Albus JS, 2010, INFORM SCIENCES, V180, P1519, DOI 10.1016/j.ins.2009.12.031 Annetta LA, 2008, THEOR PRACT, V47, P229, DOI 10.1080/00405840802153940 Arciniegas D. 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M., 2013, COGNITIVE PSYCHOL OU Ghosh-Dastidar S, 2009, NEURAL NETWORKS, V22, P1419, DOI 10.1016/j.neunet.2009.04.003 Goldstein H., 2011, MULTILEVEL STAT MODE, V922 Gupta AK, 2010, INT J PROD RES, V48, P763, DOI 10.1080/00207540802452132 Hanrahan G., 2011, ARTIFICIAL NEURAL NE Hanrahan G, 2010, ANAL CHEM, V82, P4307, DOI 10.1021/ac902636q Holizinger K., 2014, LECT NOTES COMPUTER, P35 Holzinger A, 2009, COMPUT EDUC, V52, P292, DOI 10.1016/j.compedu.2008.08.008 Huff K, 2007, COGNITIVE DIAGNOSTIC ASSESSMENT FOR EDUCATION: THEORY AND APPLICATIONS, P19, DOI 10.1017/CBO9780511611186.002 Institute of Education Sciences, 2003, ID IMPL ED PRACT SUP Kalyuga S, 2011, EDUC PSYCHOL REV, V23, P1, DOI 10.1007/s10648-010-9150-7 Lachaux JP, 2012, PROG NEUROBIOL, V98, P279, DOI 10.1016/j.pneurobio.2012.06.008 Lamb R., 2012, MERIDIAN, V13 Lamb R., 2009, J VIRGINIA SCI ED, V3, P34 Lamb R., 2011, INT J SCI MATH EDUC, V10, P643 Lamb R., COMPUTERS HUMAN BEHA, V39, P224 Lamb R., 2012, J SCI EDUC TECHNOL, V22, P603 Lamb R. L., 2013, THESIS GEORGE MASON Lamb RL, 2014, COMPUT EDUC, V70, P92, DOI 10.1016/j.compedu.2013.08.008 Neymotin SA, 2011, J COMPUT NEUROSCI, V30, P69, DOI 10.1007/s10827-010-0253-4 Piaget J., 1970, STRUCTURALISM Pons AJ, 2010, NEUROIMAGE, V52, P848, DOI 10.1016/j.neuroimage.2009.12.105 Raykov T, 2010, STRUCT EQU MODELING, V17, P265, DOI 10.1080/10705511003659417 Raykov T, 2009, MEAS EVAL COUNS DEV, V42, P223, DOI 10.1177/0748175609344096 Roberts M., 2010, ED MEASUREMENT ISSUE, V29, P25 Soares TM, 2009, J EDUC BEHAV STAT, V34, P348, DOI 10.3102/1076998609332752 Tatsuoka K., 1983, J EDUC MEAS, V20, P35 Thomas M. S., 2013, COMPUTATIONAL MODELI Wallach W, 2010, TOP COGN SCI, V2, P454, DOI 10.1111/j.1756-8765.2010.01095.x Wallander L, 2009, SOC SCI RES, V38, P505, DOI 10.1016/j.ssresearch.2009.03.004 Yilmaz I, 2011, EXPERT SYST APPL, V38, P5958, DOI 10.1016/j.eswa.2010.11.027 Yilmaz I, 2012, NEURAL COMPUT APPL, V21, P957, DOI 10.1007/s00521-011-0535-4 Zangeneh M., 2012, SPAN J AGRIC RES, V9, P661 Zylberberg A, 2010, PLOS COMPUT BIOL, V6, DOI 10.1371/journal.pcbi.1000765Cited Reference Count: 51 Abstract: The purpose of this paper is to explain and document the creation of a computational model in the form of an Artificial Neural Network (ANN) capable of simulating student cognition. Specifically, the model simulates students' cognition as they complete activities within a science classroom. This study also seeks to examine the effects, as evidenced in the ANN, of an intervention designed to develop increased levels of critical thinking related to science skills. This model is based on the identification of cognitive attributes and integration of two advanced measurement frameworks: cognitive diagnostics and Item Response Theory. Both frameworks examine student response patterns, providing initial inputs for the ANN portion of the model. Once initial task response patterns are identified, they are parameterized and presented to the ANN. The ANN within this study is the foundational component of a computational model based upon the interaction of multiple, connected, adaptive processing elements know as cognitive attributes. These cognitive attributes process student responses to cognitive tasks within science tasks. Using the Student Task and Cognition Model (STAC-M), the study authors simulated a cognitive training intervention using a randomized control trial design of 100,000 students. Results of the simulation suggest that it is possible to increase levels of student success using a targeted cognitive attribute approach and that computational modeling provides a means to test educational theory for future education research. The paper also discusses limitations of the use of this computational model within education and the possible future directions for educators and researchers. (C) 2014 Elsevier Ltd. All rights reserved.Accession Number: WOS:000342880100009 Language: EnglishDocument Type: ArticleAuthor Keywords: Computational modeling; Cognitive processing; Science education; Critical reasoning; Serious educational gamesKeyWords Plus: SCALE RELIABILITY; BRAIN; BINARYAddresses: [Lamb, Richard L.; Akmal, Tariq; Baldwin, Kathryn] Washington State Univ, Pullman, WA 99164 USA. [Vallett, David B.] Univ Nevada Las Vegas, Las Vegas, NV USA. Reprint Address: Lamb, RL (reprint author), Washington State Univ, Pullman, WA 99164 USA.E-mail Addresses: [email protected]; [email protected]; [email protected]; [email protected]: PERGAMON-ELSEVIER SCIENCE LTD Publisher Address: THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND Web of Science Categories: Computer Science, Interdisciplinary Applications; Education & Educational Research



Research Areas: Computer Science; Education & Educational ResearchIDS Number: AQ5WU ISSN: 0360-1315 eISSN: 1873-782X 29-char Source Abbrev.: COMPUT EDUC ISO Source Abbrev.: Comput. Educ. Source Item Page Count: 10 Record 39 of 58Title: Landslide hazard zonation mapping in ghat road section of Kolli hills, India Author(s): Anbazhagan, S (Anbazhagan, Siddan); Ramesh, V (Ramesh, Veerappan)Source: JOURNAL OF MOUNTAIN SCIENCE Volume: 11 Issue: 5 Pages: 1308-1325 DOI: 10.1007/s11629-012-2618-9 Published: SEP 2014 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: AGS, 2007, AUSTR GEOMECHANICS, V42, P13 Ahmad M, 2013, GEOMATERIALS, V3, P15 Aleotti P, 1999, B ENG ENV, V58, P21, DOI DOI 10.1007/S100640050066 ANBALAGAN R, 1992, ENG GEOL, V32, P269, DOI 10.1016/0013-7952(92)90053-2 Anbalagan R, 2008, J SCI IND RES INDIA, V67, P486 Anbazhagan S, 2008, J GEOL SOC INDIA, V72, P348 Anderson MG, 2013, COMMUNITY-BASED LANDSLIDE RISK REDUCTION: MANAGING DISASTERS IN SMALL STEPS, P1, DOI 10.1596/978-0-8213-9456-4 [Anonymous], 2006, GEOL MIN RES STAT 4 Arora MK, 2004, INT J REMOTE SENS, V25, P559, DOI 10.1080/0143116031000156819 Ayalew L, 2004, LANDSLIDES, V1, P73, DOI 10.1007/s10346-003-0006-9 Bhandari RK, 1987, J IGE, V17, P1 Brabb E.E., 1984, P 4 INT S LANDSL TOR, V1, P307 Bureau of Indian Standard, 1998, IS14496 2 CARRARA A, 1991, EARTH SURF PROCESSES, V16, P427, DOI 10.1002/esp.3290160505 Chung CJF, 1999, PHOTOGRAMM ENG REM S, V65, P1389 Dai FC, 2002, ENG GEOL, V64, P65, DOI 10.1016/S0013-7952(01)00093-X Das I, 2011, LANDSLIDES, V8, P293, DOI 10.1007/s10346-011-0257-9 Devoli G, 2007, LANDSLIDES, V4, P5, DOI 10.1007/s10346-006-0048-x Dhakal AS, 2000, PHOTOGRAMM ENG REM S, V66, P981 Xavier TF, 2011, INDIAN J TRADIT KNOW, V10, P559 Ghosh S, 2011, THESIS U TWENTE NETH, P13 GUPTA RP, 1990, ENG GEOL, V28, P119, DOI 10.1016/0013-7952(90)90037-2 Guzzetti F, 1999, GEOMORPHOLOGY, V31, P181, DOI 10.1016/S0169-555X(99)00078-1 Hansen A, 1984, SLOPE INSTABILITY, P523 Kannan M, 2011, J INDIAN SOC REMOTE, V39, P485, DOI 10.1007/s12524-011-0112-4 Kanungo DP, 2009, J S ASIA DISASTER ST, V2, P81 Kanungo DP, 2006, ENG GEOL, V85, P347, DOI 10.1016/j.enggeo.2006.03.004 KIENHOLZ H, 1984, MT RES DEV, V4, P247, DOI 10.2307/3673145 Kumar K, 2012, INT J GEOMATICS GEOS, V2, P878 Lee S, 2007, ENVIRON GEOL, V52, P615, DOI 10.1007/s00254-006-0491-y Lee S, 2002, ENVIRON GEOL, V43, P120, DOI 10.1007/s00254-002-0616-x MARK RK, 1995, ADV NAT TECHNOL HAZ, V5, P93 MCKEAN J, 1991, PHOTOGRAMM ENG REM S, V57, P1185 Mostyn GR, 1997, QUANTITATIVE SEMIQUA, P297 Naranjo JL, 1994, ITC J, V3 National Disaster Management Guidelines, 2009, PUBL NAT DIS MAN AUT Okimura T, 1986, INT GEOMORPHOLOGY, P121 Okimura T, 1982, SHIN SABO, V35, P9 PACHAURI AK, 1992, ENG GEOL, V32, P81, DOI 10.1016/0013-7952(92)90020-Y Saranathan E, 2012, DISASTER ADV, V5, P42 Saranathan E, 2010, INDIAN LANDSLIDES, V3, P9 SARKAR S, 1995, MT RES DEV, V15, P301, DOI 10.2307/3673806 Sarkar S, 2008, J MT SCI-ENGL, V5, P232, DOI 10.1007/s11629-008-0172-2 Sharma RK, 2012, NAT HAZARDS, V60, P671, DOI 10.1007/s11069-011-0041-0 Sharma VK, 2008, J GEOL SOC INDIA, V71, P425 Singh R, 2012, GEOMAT NAT HAZ RISK, V4, P13 Skempton AW, 1957, P 4 INT C SOIL MECH, V4, P379 Srivastava V, 2010, GEOMAT NAT HAZ RISK, V1, P225, DOI 10.1080/19475705.2010.490103 van Westen CJ, 2000, INT J APPL EARTH OBS, V2, P51, DOI 10.1016/S0303-2434(00)85026-6 Varnes DJ, 1981, SLOPE STABILITY PROB, P489 Varnes D.J., 1984, LANDSLIDE HAZARD ZON, P1 Verstappen HT, 1983, APPL GEOMORPHOLOGY G, P437 WANG SQ, 1992, INT J GEOGR INF SYST, V6, P391 Wieczorek G.F., 1984, B ASS ENG GEOLOGISTS, V21, P337 Yasilnacar E, 2006, INT J REMOTE SENS, V27, P253, DOI [10.1080/0143116050030042, DOI 10.1080/0143116050030042] Yilmaz I, 2012, B ENG GEOL ENVIRON, V71, P803, DOI 10.1007/s10064-011-0406-3 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P297, DOI 10.1007/s10064-009-0185-2 Yin K. J, 1988, P 5 INT S LANDSL LAU, V2, P1269 Zika P, 1988, P 5 INT S LANDSL LAU, P1273Cited Reference Count: 59 Abstract: Landslides are the most common natural disaster in hilly terrain which causes changes in landscape and damage to life and property. The main objective of the present study was to carry out landslide hazard zonation mapping on 1:50,000 scale along ghat road section of Kolli hills using a Landslide Hazard Evaluation Factor (LHEF) rating scheme. The landslide hazard zonation map has been prepared by overlaying the terrain evaluation maps with facet map of the study area. The terrain evaluation maps include lithology, structure, slope morphometry, relative relief, land use and land cover and hydrogeological condition. The LHEF rating scheme and the Total Estimated Hazard (TEHD) were calculated as per the Bureau of Indian Standard (BIS) guidelines (IS: 14496 (Part-2) 1998) for the purpose of preparation of Landslide Hazard Zonation (LHZ) map in mountainous terrains. The correction due to triggering factors such as seismicity, rainfall and anthropogenic activities were also incorporated with Total Estimated Hazard to get final corrected TEHD. The landslide hazard zonation map was classified as the high, moderate and low hazard zones along the ghat road section based on corrected TEHD.Accession Number: WOS:000342223500018 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslide hazard zonation (LHZ); Kolli Hills; Mountainous terrain; LHEF rating scheme; Bureau of Indian Standard (BIS); TEHDKeyWords Plus: TAMIL-NADU; SUSCEPTIBILITY ZONATION; MOUNTAINOUS TERRAIN; HIMACHAL-PRADESH; MACRO-ZONATION; GIS; HIMALAYAS; FUZZY; RIVER; VERIFICATIONAddresses: [Anbazhagan, Siddan; Ramesh, Veerappan] Periyar Univ, Dept Geol, Ctr Geoinformat & Planetary Studies, Salem 636011, Tamil Nadu, India. Reprint Address: Anbazhagan, S (reprint author), Periyar Univ, Dept Geol, Ctr Geoinformat & Planetary Studies, Salem 636011, Tamil Nadu, India.E-mail Addresses: [email protected]; [email protected]



Publisher: SCIENCE PRESS Publisher Address: 16 DONGHUANGCHENGGEN NORTH ST, BEIJING 100717, PEOPLES R CHINA Web of Science Categories: Environmental SciencesResearch Areas: Environmental Sciences & EcologyIDS Number: AP6YC ISSN: 1672-6316 eISSN: 1993-0321 29-char Source Abbrev.: J MT SCI-ENGL ISO Source Abbrev.: J Mt. Sci. Source Item Page Count: 18

Funding:

Funding Agency Grant NumberNatural Resources Data Management System (NRDMS), Department of Science and Technology, New Delhi

The authors acknowledge the Natural Resources Data Management System (NRDMS), Department of Science and Technology, New Delhi, to sponsor the project. The authors also thank the State Highways and Horticulture departments for providing landslide event and rainfall data. The authors thank anonymous reviewers for their comments and suggestions to improve the quality of the research article.

Record 40 of 58Title: Land subsidence susceptibility mapping at Kinta Valley (Malaysia) using the evidential belief function model in GIS Author(s): Pradhan, B (Pradhan, Biswajeet); Abokharima, MH (Abokharima, Mohammed Hasan); Jebur, MN (Jebur, Mustafa Neamah); Tehrany, MS (Tehrany, Mahyat Shafapour)Source: NATURAL HAZARDS Volume: 73 Issue: 2 Pages: 1019-1042 DOI: 10.1007/s11069-014-1128-1 Published: SEP 2014 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Alon N, 2004, PROBABILISTIC METHOD Althuwaynee OF, 2012, COMPUT GEOSCI-UK, V44, P120, DOI 10.1016/j.cageo.2012.03.003 An P., 1994, NONRENEWABLE RESOURC, V3, P60, DOI DOI 10.1007/BF02261716 Aurit MD, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0053832 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Bui DT, 2012, CATENA, V96, P28, DOI 10.1016/j.catena.2012.04.001 Calderhead AI, 2011, ADV WATER RESOUR, V34, P83, DOI 10.1016/j.advwatres.2010.09.017 Caniani D, 2008, NAT HAZARDS, V45, P55, DOI 10.1007/s11069-007-9169-3 Carranza EJM, 2008, INT J APPL EARTH OBS, V10, P374, DOI 10.1016/j.jag.2008.02.008 Carranza E.J.M., 2005, NATURAL RESOURCES RE, V14, P47, DOI DOI 10.1007/S11053-005-4678-9 Carranza EJM, 2003, ORE GEOL REV, V22, P117, DOI 10.1016/S0169-1368(02)00111-7 Chang Z, 2004, P IEEE INT GEOSC REM, V1, P20 Chaussard E, 2014, REMOTE SENS ENVIRON, V140, P94, DOI 10.1016/j.rse.2013.08.038 Choi JK, 2010, ENVIRON EARTH SCI, V59, P1009, DOI 10.1007/s12665-009-0093-6 Clerici A, 2002, GEOMORPHOLOGY, V48, P349, DOI 10.1016/S0169-555X(02)00079-X Demir G, 2013, NAT HAZARDS, V65, P1481, DOI 10.1007/s11069-012-0418-8 DEMPSTER AP, 1967, BIOMETRIKA, V54, P515, DOI 10.2307/2335042 DEMPSTER AP, 1967, ANN MATH STAT, V38, P325, DOI 10.1214/aoms/1177698950 Ding XL, 2004, PHOTOGRAMM ENG REM S, V70, P1151 Galve JP, 2009, EARTH SURF PROC LAND, V34, P437, DOI 10.1002/esp.1753 Galve JP, 2008, ENG GEOL, V99, P185, DOI 10.1016/j.enggeo.2007.11.011 Ghafari A. 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Wang WD, 2009, ENVIRON GEOL, V58, P33, DOI 10.1007/s00254-008-1488-5 Wang Y, 2004, P SOC PHOTO-OPT INS, V5574, P323, DOI 10.1117/12.565518 Wu X, 2009, ENVIRON EARTH SCI, V59, P803, DOI 10.1007/s12665-009-0076-7 Yang T, 2006, EARTH PLANET SC LETT, V250, P11, DOI 10.1016/j.epsl.2006.07.031 Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2013, J EARTH SYST SCI, V122, P371, DOI 10.1007/s12040-013-0281-3 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P297, DOI 10.1007/s10064-009-0185-2 Youssef AM, 2011, ENVIRON EARTH SCI, V62, P611, DOI 10.1007/s12665-010-0551-1 Zhou GY, 2003, ENVIRON GEOL, V44, P665, DOI 10.1007/s00254-003-0806-1 Ziaie A., 2009, Research Journal of Environmental Sciences, V3, P486, DOI 10.3923/rjes.2009.486.496Cited Reference Count: 76 Abstract: Land subsidence is one of the frequent geological hazards worldwide. Urban areas and agricultural industries are the entities most affected by the consequences of land subsidence. The main objective of this study was to estimate the land subsidence (sinkhole) hazards at the Kinta Valley of Perak, Malaysia, using geographic information system and remote sensing techniques. To start, land subsidence locations were observed by surveying measurements using GPS and using the tabular data, which were produced as coordinates of each sinkhole incident. Various land subsidence conditioning factors were used such as altitude, slope, aspect, lithology, distance from the fault, distance from the river, normalized difference vegetation index, soil type, stream power index, topographic wetness index, and land use/cover. In this article, a data-driven technique of an evidential belief function (EBF), which is in the category of multivariate statistical analysis, was used to map the land subsidence-prone areas. The frequency ratio (FR) was performed as an efficient bivariate statistical analysis method in order compare it with the acquired results from the EBF analysis. The probability maps were acquired and the results of the analysis validated by the area under the (ROC) curve using the testing land subsidence locations. The results indicated that the FR model could produce a 71.16 % prediction rate, while the EBF showed better prediction accuracy with a rate of 73.63 %. Furthermore, the success rate was measured and accuracies of 75.30 and 79.45 % achieved for FR and EBF, respectively. These results can produce an understanding of the nature of land subsidence as well as promulgate public awareness of such geo-hazards to decrease human and economic losses.Accession Number: WOS:000340490100048 Language: EnglishDocument Type: ArticleAuthor Keywords: Land subsidence; Frequency ratio model; Evidential belief function; Remote sensing; GIS; Kinta Valley; MalaysiaKeyWords Plus: ARTIFICIAL NEURAL-NETWORKS; LANDSLIDE SUSCEPTIBILITY; GROUND SUBSIDENCE; LOGISTIC-REGRESSION; SPATIAL PREDICTION; HAZARD ASSESSMENT; FREQUENCY RATIO; DECISION TREE; FUZZY-LOGIC; URBAN AREAAddresses: [Pradhan, Biswajeet; Abokharima, Mohammed Hasan; Jebur, Mustafa Neamah; Tehrany, Mahyat Shafapour] Univ Putra Malaysia, Dept Civil Engn, GISRC, Fac Engn, Serdang 43400, Selangor, Malaysia. Reprint Address: Pradhan, B (reprint author), Univ Putra Malaysia, Dept Civil Engn, GISRC, Fac Engn, Serdang 43400, Selangor, Malaysia.E-mail Addresses: [email protected]: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences; Water ResourcesResearch Areas: Geology; Meteorology & Atmospheric Sciences; Water ResourcesIDS Number: AN3LR ISSN: 0921-030X eISSN: 1573-0840 29-char Source Abbrev.: NAT HAZARDS ISO Source Abbrev.: Nat. Hazards Source Item Page Count: 24 Record 41 of 58Title: Regional-scale landslide activity and landslide susceptibility zonation in the Nepal Himalaya Author(s): Dahal, RK (Dahal, Ranjan Kumar)Source: ENVIRONMENTAL EARTH SCIENCES Volume: 71 Issue: 12 Pages: 5145-5164 DOI: 10.1007/s12665-013-2917-7 Published: JUN 2014 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Akgun A, 2007, ENVIRON GEOL, V51, P1377, DOI 10.1007/s00254-006-0435-6 Atkinson PM, 1998, COMPUT GEOSCI-UK, V24, P373, DOI 10.1016/S0098-3004(97)00117-9 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Bai SB, 2011, ENVIRON EARTH SCI, V62, P139, DOI 10.1007/s12665-010-0509-3 Bednarik M, 2012, NAT HAZARDS, V64, P547, DOI 10.1007/s11069-012-0257-7 Beven K. 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Huang HP, 2013, ENVIRON EARTH SCI, V69, P2151, DOI 10.1007/s12665-012-2044-x Ives JD, 1981, MOUNTAIN RES DEV, V1, P223, DOI 10.2307/3673059 Jaiswal P, 2010, NAT HAZARD EARTH SYS, V10, P1253, DOI 10.5194/nhess-10-1253-2010 Kayastha P, 2012, NAT HAZARDS, V63, P479, DOI 10.1007/s11069-012-0163-z KIENHOLZ H, 1984, MT RES DEV, V4, P247, DOI 10.2307/3673145 Lee S, 2005, INT J REMOTE SENS, V26, P1477, DOI 10.1080/01431160412331331012 Lee S, 2004, INT J GEOGR INF SCI, V18, P789, DOI 10.1080/13658810410001702003 Lee S, 2006, ENVIRON GEOL, V50, P847, DOI 10.1007/s00254-006-0256-7 Lee S, 2003, EARTH SURF PROC LAND, V28, P1361, DOI 10.1002/esp.593 Magliulo P, 2012, ENVIRON EARTH SCI, V67, P1801, DOI 10.1007/s12665-012-1634-y Melchiorre C, 2008, GEOMORPHOLOGY, V94, P379, DOI 10.1016/j.geomorph.2006.10.035 Mihalic S, 1998, GEOL CROAT, V51, P195 Nefeslioglu HA, 2011, MATH PROBL ENG, DOI 10.1155/2011/280431 Nefeslioglu HA, 2008, ENG GEOL, V97, P171, DOI 10.1016/j.enggeo.2008.01.004 Ohlmacher GC, 2003, ENG GEOL, V69, P331, DOI 10.1016/S0013-7952(03)00069-3 Ozdemir A, 2011, NAT HAZARDS, V59, P1573, DOI 10.1007/s11069-011-9853-1 Oztekin B, 2005, ENVIRON GEOL, V49, P124, DOI 10.1007/s00254-005-0071-6 PACHAURI AK, 1992, ENG GEOL, V32, P81, DOI 10.1016/0013-7952(92)90020-Y Park S, 2013, ENVIRON EARTH SCI, V68, P1443, DOI 10.1007/s12665-012-1842-5 Poudyal CP, 2010, ENVIRON EARTH SCI, V61, P1049, DOI 10.1007/s12665-009-0426-5 Pourghasemi HR, 2012, NAT HAZARDS, V63, P965, DOI 10.1007/s11069-012-0217-2 Ramani SE, 2011, J MT SCI-ENGL, V8, P505, DOI 10.1007/s11629-011-2157-9 Regmi NR, 2010, GEOMORPHOLOGY, V115, P172, DOI 10.1016/j.geomorph.2009.10.002 Roering JJ, 2005, GEOL SOC AM BULL, V117, P654, DOI 10.1130/B25567.1 Ruff M, 2008, GEOMORPHOLOGY, V94, P314, DOI 10.1016/j.geomorph.2006.10.032 RUPKE J, 1988, ENG GEOL, V26, P33, DOI 10.1016/0013-7952(88)90005-1 Schicker R, 2012, GEOMORPHOLOGY, V161-162, P10 Schmidt Frank, 2003, Precision Agriculture, V4, P179, DOI 10.1023/A:1024509322709 Sharma LP, 2011, GEOCARTO INT, V26, P491, DOI 10.1080/10106049.2011.598951 Stocklin J, 1978, TECHNICAL REPORT Suzen ML, 2004, ENVIRON GEOL, V45, P665, DOI 10.1007/s00254-003-0917-8 Uchida T, 2004, STUDY METHODOLOGY AS, P91 van Westen CJ, 2008, ENG GEOL, V102, P112, DOI 10.1016/j.enggeo.2008.03.010 Van Westen CJ, 2003, NAT HAZARDS, V30, P399, DOI 10.1023/B:NHAZ.0000007097.42735.9e Van Westen CJ, 2000, SURV GEOPHYS, V21, P241, DOI 10.1023/A:1006794127521 Varnes DJ, 1984, INT ASS ENG GEOLOGY Wilson JP, 2000, TERRAIN ANAL Xie MW, 2004, ENVIRON GEOL, V46, P840, DOI 10.1007/s00254-004-1069-1 Yesilnacar E, 2005, ENG GEOL, V79, P251, DOI 10.1016/j.enggeo.2005.02.002 Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9 Zhu Lei, 2006, Journal of Zhejiang University (Science), V7, DOI 10.1631/jzus.2006.A2007Cited Reference Count: 82 Abstract: Landslide susceptibility zonation mapping is a fundamental procedure for geo-disaster management in tropical and sub-tropical regions. Recently, various landslide susceptibility zonation models have been introduced in Nepal with diverse approaches of assessment. However, validation is still a problem. Additionally, the role of various predisposing causative parameters for landslide activity is still not well understood in the Nepal Himalaya. To address these issues of susceptibility zonation and landslide activity, about 4,000 km(2) area of central Nepal was selected for regional-scale assessment of landslide activity and susceptibility zonation mapping. In total, 655 new landslides and 9,229 old landslides were identified with the study area with the help of satellite images, aerial photographs, field data and available reports. The old landslide inventory was "blind landslide database" and could not explain the particular rainfall event responsible for the particular landslide. But considering size of the landslide, blind landslide inventory was reclassified into two databases: short-duration high-intensity rainfall-induced landslide inventory and long-duration low-intensity rainfall-induced landslide inventory. These landslide inventory maps were considered as proxy maps of multiple rainfall event-based landslide inventories. Similarly, all 9,884 landslides were considered for the activity assessment of predisposing causative parameters. For the Nepal Himalaya, slope, slope aspect, geology and road construction activity (anthropogenic cause) were identified as most affective predisposing causative parameters for landslide activity. For susceptibility zonation, multivariate approach was considered and two proxy rainfall event-based landslide databases were used for the logistic regression modelling, while a relatively recent landslide database was used in validation. Two event-based susceptibility zonation maps were merged and rectified to prepare the final susceptibility zonation map and its prediction rate was found to be more than 82 %. From this work, it is concluded that rectification of susceptibility zonation map is very appropriate and reliable. The results of this research contribute to a significant improvement in landslide inventory preparation procedure, susceptibility zonation mapping approaches as well as role of various predisposing causative parameters for the landslide activity.Accession Number: WOS:000336397100017 Language: EnglishDocument Type: ArticleAuthor Keywords: Event-based landslide; Geo-disasters; Susceptibility zonation maps; The Nepal Himalaya; Blind landslide inventory; Landslide activity; Validation of susceptibility mapsKeyWords Plus: ARTIFICIAL NEURAL-NETWORKS; LOGISTIC-REGRESSION MODEL; VULNERABILITY ASSESSMENT; HIERARCHY PROCESS; LESSER HIMALAYA; FREQUENCY RATIO; SLOPE STABILITY; LANTAU-ISLAND; OF-EVIDENCE; HONG-KONGAddresses: Tribhuvan Univ, Dept Geol, Kathmandu, Nepal. Reprint Address: Dahal, RK (reprint author), Tribhuvan Univ, Dept Geol, Tri Chandra Campus, Kathmandu, Nepal.E-mail Addresses: [email protected]: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Environmental Sciences; Geosciences, Multidisciplinary; Water ResourcesResearch Areas: Environmental Sciences & Ecology; Geology; Water ResourcesIDS Number: AH8OJ ISSN: 1866-6280 eISSN: 1866-6299 29-char Source Abbrev.: ENVIRON EARTH SCI ISO Source Abbrev.: Environ. Earth Sci. Source Item Page Count: 20

Funding:

Funding Agency Grant NumberJapan Society for Promotion of Science (JSPS)

The author is thankful to Prof. Ryuichi Yatabe for providing opportunity to perform this research in Geo-disaster Laboratory, Ehime University, under the financial support of Japan Society for Promotion of Science (JSPS). Dr. Netra Prakash Bhadary, Dr. Manita Timilsina and Mr. Anjan Kumar Dahal are sincerely acknowledged for their technical support during preparation of this paper. This research is partly supported by Japan Society for Promotion of Science (JSPS).Record 42 of 58Title: Relative effect method of landslide susceptibility zonation in weathered granite soil: a case study in Deokjeok-ri Creek, South Korea Author(s): Pradhan, AMS (Pradhan, Ananta Man Singh); Kim, YT (Kim, Yun-Tae)Source: NATURAL HAZARDS Volume: 72 Issue: 2 Pages: 1189-1217 DOI: 10.1007/s11069-014-1065-z Published: JUN 2014



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A., 2001, INT J APPL EARTH OBS, V3, P43, DOI 10.1016/S0303-2434(01)85020-0Cited Reference Count: 77 Abstract: The objective of this study was to produce and evaluate a landslide susceptibility map for weathered granite soils in Deokjeok-ri Creek, South Korea. The relative effect (RE) method was used to determine the relationship between landslide causative factors (CFs) and landslide occurrence. To determine the effect of CFs on landslides, data layers of aspect, elevation, slope, internal relief, curvature, distance to drainage, drainage density, stream power index, sediment transport index, topographic wetness index, soil drainage character, soil type, soil depth, forest type, timber age, and geology were analyzed in a geographical information system (GIS) environment. A GIS-based landslide inventory map of 748 landslide locations was prepared using data from previous reports, aerial photographic interpretation, and extensive field work. A RE model was generated from a training set consisting of 673 randomly selected landslides in the inventory map, with the remaining 75 landslides used for validation of the susceptibility map. The results of the analysis were verified using the landslide location data. According to the analysis, the RE model had a success rate of 86.3 % and a predictive accuracy of 88.6 %. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations. The results of this study can therefore be used to mitigate landslide-induced hazards and to plan land use.Accession Number: WOS:000335827100050 Language: EnglishDocument Type: Article



Author Keywords: Deokjeok-ri Creek; GIS; Landslide susceptibility; Relative effect; Weathered granite soilKeyWords Plus: SPATIAL PREDICTION MODELS; NEURAL-NETWORK MODEL; FREQUENCY RATIO; DECISION-TREE; LOSS EQUATION; FUZZY-LOGIC; TURKEY; SLOPE; MOUNTAINS; STABILITYAddresses: [Pradhan, Ananta Man Singh; Kim, Yun-Tae] Pukyong Natl Univ, Dept Ocean Engn, Geosyst Engn Lab, Pusan 608737, South Korea. Reprint Address: Kim, YT (reprint author), Pukyong Natl Univ, Dept Ocean Engn, Geosyst Engn Lab, 559-1,Daeyeon3 Dong, Pusan 608737, South Korea.E-mail Addresses: [email protected]; [email protected]: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences; Water ResourcesResearch Areas: Geology; Meteorology & Atmospheric Sciences; Water ResourcesIDS Number: AH0RE ISSN: 0921-030X eISSN: 1573-0840 29-char Source Abbrev.: NAT HAZARDS ISO Source Abbrev.: Nat. Hazards Source Item Page Count: 29

Funding:

Funding Agency Grant NumberPublic Welfare and Safety Research Program through the National Research Foundation of Korea (NRF) - Ministry of Science, ICT, and Future Planning

2012M3A2A1050977

Brain Korea 21 Plus (BK21Plus)

The authors are thankful to anonymous reviewers for their valuable comments that were very useful in bringing the manuscript into its present form. Dr. Saro Lee, Principal Researcher in KIGAM, Mr. Hyo-Sub Kang, and Mr. Ji-Sung Lee are sincerely acknowledged for their great help during the field work and in writing this manuscript. This research was supported by the Public Welfare and Safety Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT, and Future Planning (Grant No. 2012M3A2A1050977) and the Brain Korea 21 Plus (BK21Plus).

Record 43 of 58Title: The use of neural networks for the prediction of the settlement of one-way footings on cohesionless soils based on standard penetration test Author(s): Erzin, Y (Erzin, Yusuf); Gul, T (Gul, T. Oktay)Source: NEURAL COMPUTING & APPLICATIONS Volume: 24 Issue: 3-4 Pages: 891-900 DOI: 10.1007/s00521-012-1302-x Published: MAR 2014 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Burbidge MC, 1982, THESIS U LONDON LOND BURLAND JB, 1985, P I CIVIL ENG PT 1, V78, P1325 Choobbasti AJ, 2009, ARAB J GEOSCI, V2, P311, DOI 10.1007/s12517-009-0035-3 Coduto DP, 1994, FDN DESIGN PRINCIPLE Demuth H., 2006, NEURAL NETWORK TOOLB Erzin Yusuf, 2011, Mathematical & Computational Applications, V16 Erzin Y, 2012, B ENG GEOL ENVIRON, V71, P529, DOI 10.1007/s10064-012-0424-9 Erzin Y, 2009, CAN GEOTECH J, V46, P955, DOI 10.1139/T09-035 Erzin Y, 2010, INT J THERM SCI, V49, P118, DOI 10.1016/j.ijthermalsci.2009.06.008 Erzin Y, 2012, COMPUT GEOSCI, DOI [10.1016/j.cageo.2012. 09.003, DOI 10.1016/J.CAGE0.2012.09.003] Erzin Y, 2007, CAN GEOTECH J, V44, P1215, DOI 10.1139/T07-052 Erzin Y, 2012, SCI IRAN, V19, P188, DOI 10.1016/j.scient.2012.02.008 Erzin Y, 2008, INT J THERM SCI, V47, P1347, DOI 10.1016/j.ijthermalsci.2007.11.001 FLOOD I, 1994, J COMPUT CIVIL ENG, V8, P131, DOI 10.1061/(ASCE)0887-3801(1994)8:2(131) Garson G.D., 1991, AI EXPERT, V6, P47 Gul TO, 2011, THESIS CELAL BAYAR U HORNIK K, 1989, NEURAL NETWORKS, V2, P359, DOI 10.1016/0893-6080(89)90020-8 Kanibir A, 2006, IAEG 2006 Kaynar O, 2011, ENER EDUC SCI TECH-A, V26, P221 Maugeri M, 1998, J GEOTECH GEOENVIRON, V124, P595, DOI 10.1061/(ASCE)1090-0241(1998)124:7(595) Meyerhof G.G, 1965, J SOIL MECH FDN DIV, V91, P21 Parry RHG, 1971, P S INTERACTION STRU, P29 Peck R. B., 1974, FDN ENG Rumelhart D.E., 1986, PARALLEL DISTRIBUTED, V1, P318 Schmertmann JH, 1970, J SOIL MECH FDN ASCE, V96, P1032 Shahin M. A., 2001, AUSTR GEOMECH, V36, P49 Shahin MA, 2002, J GEOTECH GEOENVIRON, V128, P785, DOI 10.1061/(ASCE)1090-0241(2002)128:9(785) Shahin MA, 2004, J COMPUT CIVIL ENG, V18, P105, DOI DOI 10.1061/(ASCE)0887-3801(2004)18:2(105) Sivakugan N, 1998, AUSTR CIVIL ENG T, VCE40, P49 Smith M, 1993, NEURAL NETWORKS MODE Sowers G. B., 1970, INTRO SOIL MECH FDN STONE M, 1974, J R STAT SOC B, V36, P111 Terzaghi K, 1967, SOIL MECH FDN ENG PR Terzaghi K, 1996, SOIL MECH ENG PRACTI Twomey M, 1997, ARTIFICIAL NEURAL NE, P44 Yilmaz I, 2009, INT J ROCK MECH MIN, V46, P803, DOI 10.1016/j.ijrmms.2008.09.002 Yilmaz I, 2011, EXPERT SYST APPL, V38, P5958, DOI 10.1016/j.eswa.2010.11.027 Yilmaz I, 2012, NEURAL COMPUT APPL, V21, P957, DOI 10.1007/s00521-011-0535-4 Yilmaz I, 2008, ROCK MECH ROCK ENG, V41, P781, DOI 10.1007/s00603-007-0138-7Cited Reference Count: 39 Abstract: In this study, artificial neural networks (ANNs) were used to predict the settlement of one-way footings, without a need to perform any manual work such as using tables or charts. To achieve this, a computer programme was developed in the Matlab programming environment for calculating the settlement of one-way footings from five traditional settlement prediction methods. The footing geometry (length and width), the footing embedment depth, the bulk unit weight of the cohesionless soil, the footing applied pressure, and corrected standard penetration test varied during the settlement analyses, and the settlement value of each one-way footing was calculated for each traditional method by using the written programme. Then, an ANN model was developed for each method to predict the settlement by using the results of the analyses. The settlement values predicted from each ANN model developed were compared with the settlement values calculated from the traditional method. The predicted values were found to be quite close to the calculated values. Additionally, several performance indices such as determination coefficient, variance account for, mean absolute error, root mean square error, and scaled percent error were computed to check the prediction capacity of the ANN models developed. The constructed ANN models have shown high prediction performance based on the performance indices calculated. The results demonstrated that the ANN models developed can be used at the preliminary stage of designing one-way footing on cohesionless soils without a need to perform any manual work such as using tables or charts.Accession Number: WOS:000331638400039 Language: EnglishDocument Type: ArticleAuthor Keywords: Artificial neural networks; Cohesionless soils; One-way footing; Settlement; Standard penetration testKeyWords Plus: SHALLOW FOUNDATIONS; MODELS; SANDAddresses: [Erzin, Yusuf; Gul, T. Oktay] Celal Bayar Univ, Fac Engn, Dept Civil Engn, Manisa 45140, Turkey.



Reprint Address: Erzin, Y (reprint author), Celal Bayar Univ, Fac Engn, Dept Civil Engn, Manisa 45140, Turkey.E-mail Addresses: [email protected]: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Computer Science, Artificial IntelligenceResearch Areas: Computer ScienceIDS Number: AB2QY ISSN: 0941-0643 eISSN: 1433-3058 29-char Source Abbrev.: NEURAL COMPUT APPL ISO Source Abbrev.: Neural Comput. Appl. Source Item Page Count: 10 Record 44 of 58Title: Landslide susceptibility mapping at Zonouz Plain, Iran using genetic programming and comparison with frequency ratio, logistic regression, and artificial neural network models Author(s): Nourani, V (Nourani, Vahid); Pradhan, B (Pradhan, Biswajeet); Ghaffari, H (Ghaffari, Hamid); Sharifi, SS (Sharifi, Seyed Saber)Source: NATURAL HAZARDS Volume: 71 Issue: 1 Pages: 523-547 DOI: 10.1007/s11069-013-0932-3 Published: MAR 2014 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Akgun A, 2011, ENVIRON MONIT ASSESS, V184, P5453 Akgun A, 2012, COMPUT GEOSCI-UK, V38, P23, DOI 10.1016/j.cageo.2011.04.012 Althuwaynee OF, 2012, COMPUT GEOSCI-UK, V44, P120, DOI 10.1016/j.cageo.2012.03.003 Atkinson PM, 1998, COMPUT GEOSCI-UK, V24, P373, DOI 10.1016/S0098-3004(97)00117-9 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Aytek A, 2008, J HYDROL, V351, P288, DOI 10.1016/j.jhydrol.2007.12.005 Bednarik M, 2012, NAT HAZARDS, V64, P547, DOI 10.1007/s11069-012-0257-7 Begueria S, 2006, GEOMORPHOLOGY, V74, P196, DOI 10.1016/j.geomorph.2005.07.018 Biggerstaff BJ, 2000, STAT MED, V19, P649, DOI 10.1002/(SICI)1097-0258(20000315)19:5<649::AID-SIM371>3.0.CO;2-H Bui DT, 2012, CATENA, V96, P28, DOI 10.1016/j.catena.2012.04.001 Bui DT, 2012, GEOMORPHOLOGY, V171, P12, DOI 10.1016/j.geomorph.2012.04.023 BUI DT, 2013, VIETNAM NAT HAZARDS, V66, P707, DOI DOI 10.1007/S11069-012-0510-0 Caniani D, 2008, NAT HAZARDS, V45, P55, DOI 10.1007/s11069-007-9169-3 Cevik E, 2003, ENVIRON GEOL, V44, P949, DOI 10.1007/s00254-003-0838-6 Dahal RK, 2008, ENVIRON GEOL, V54, P311, DOI 10.1007/s00254-007-0818-3 Dai FC, 2001, ENVIRON GEOL, V40, P381, DOI 10.1007/s002540000163 Ermini L, 2005, GEOMORPHOLOGY, V66, P327, DOI 10.1016/j.geomorph.2004.09.025 Gorum T, 2008, NAT HAZARDS, V46, P323, DOI 10.1007/s11069-007-9190-6 Hagen M T, 1994, IEEE T NEURAL NETWOR, V5, p989~993 Hakimzadeh H., 2013, J HYDROL ENG HORNIK K, 1989, NEURAL NETWORKS, V2, P359, DOI 10.1016/0893-6080(89)90020-8 Kawabata D, 2009, GEOMORPHOLOGY, V113, P97, DOI 10.1016/j.geomorph.2009.06.006 Kayastha P, 2013, COMPUT GEOSCI-UK, V52, P398, DOI 10.1016/j.cageo.2012.11.003 Koza JR, 1992, GENETIC PROGRAMMING Lamelas MT, 2008, ENVIRON GEOL, V54, P963, DOI 10.1007/s00254-007-0895-3 Lan HX, 2004, ENG GEOL, V76, P109, DOI 10.1016/j.enggeo.2004.06.009 Lee S, 2006, NAT HAZARD EARTH SYS, V6, P687 Lee S, 2007, LANDSLIDES, V4, P33, DOI 10.1007/s10346-006-0047-y Lee S, 2001, ENVIRON GEOL, V40, P1095, DOI 10.1007/s002540100310 Lee S, 2006, ENVIRON GEOL, V50, P847, DOI 10.1007/s00254-006-0256-7 Melchiorre C, 2008, GEOMORPHOLOGY, V94, P379, DOI 10.1016/j.geomorph.2006.10.035 Mohammady M, 2012, J ASIAN EARTH SCI, V61, P221, DOI 10.1016/j.jseaes.2012.10.005 Niefeslioglu HA, 2008, ENG GEOL, V97, P171 Nourani V, 2012, J HYDROL ENG, V17, P724, DOI 10.1061/(ASCE)HE.1943-5584.0000506 Nourani V., 2012, INT J SOFT COMPUT EN, V2, P464 Nourani V, 2013, J HYDROL, V476, P228, DOI 10.1016/j.jhydrol.2012.10.054 Nourani V, 2012, J HYDROL ENG, V17, P1368, DOI 10.1061/(ASCE)HE.1943-5584.0000587 Nourani V, 2013, J HYDROINFORM, V15, P427, DOI 10.2166/hydro.2012.113 Oh HJ, 2011, COMPUT GEOSCI-UK, V37, P1264, DOI 10.1016/j.cageo.2010.10.012 Pourghasemi H. 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N., 2008, INTRO GENETIC ALGORI Slide RC, 2006, LANDSLIDE PROCESSES, P312 Sung DG, 2001, LANDSCAPE URBAN PLAN, V56, P75, DOI 10.1016/S0169-2046(01)00174-8 Suzen ML, 2004, ENG GEOL, V71, P303, DOI 10.1016/S0013-7952(03)00143-1 Bui DT, 2012, MATH PROBL ENG, DOI 10.1155/2012/974638 Bui DT, 2012, COMPUT GEOSCI-UK, V45, P199, DOI 10.1016/j.cageo.2011.10.031 Tunusluoglu MC, 2008, ENVIRON GEOL, V54, P9, DOI 10.1007/s00254-007-0788-5 Vahidnia MH, 2010, COMPUT GEOSCI-UK, V36, P1101, DOI 10.1016/j.cageo.2010.04.004 Yalcin A, 2011, CATENA, V85, P274, DOI 10.1016/j.catena.2011.01.014 Yalcin A, 2008, CATENA, V72, P1, DOI 10.1016/j.catena.2007.01.003 Yao X, 2008, GEOMORPHOLOGY, V101, P572, DOI 10.1016/j.geomorph.2008.02.011 Yesilnacar E, 2005, ENG GEOL, V79, P251, DOI 10.1016/j.enggeo.2005.02.002 Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9



Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007 Yilmaz I, 2011, NEURAL COMPUT APPL, V21, P957 Yilmaz I, 2010, ENVIRON EARTH SCI, V60, P505, DOI 10.1007/s12665-009-0191-5 Zare M, 2013, ARAB J GEOSCI, V6, P2873, DOI 10.1007/s12517-012-0610-xCited Reference Count: 76 Abstract: Without a doubt, landslide is one of the most disastrous natural hazards and landslide susceptibility maps (LSMs) in regional scale are the useful guide to future development planning. Therefore, the importance of generating LSMs through different methods is popular in the international literature. The goal of this study was to evaluate the susceptibility of the occurrence of landslides in Zonouz Plain, located in North-West of Iran. For this purpose, a landslide inventory map was constructed using field survey, air photo/satellite image interpretation, and literature search for historical landslide records. Then, seven landslide-conditioning factors such as lithology, slope, aspect, elevation, land cover, distance to stream, and distance to road were utilized for generation LSMs by various models: frequency ratio (FR), logistic regression (LR), artificial neural network (ANN), and genetic programming (GP) methods in geographic information system (GIS). Finally, total four LSMs were obtained by using these four methods. For verification, the results of LSM analyses were confirmed using the landslide inventory map containing 190 active landslide zones. The validation process showed that the prediction accuracy of LSMs, produced by the FR, LR, ANN, and GP, was 87.57, 89.42, 92.37, and 93.27 %, respectively. The obtained results indicated that the use of GP for generating LSMs provides more accurate prediction in comparison with FR, LR, and ANN. Furthermore; GP model is superior to the ANN model because it can present an explicit formulation instead of weights and biases matrices.Accession Number: WOS:000331395900024 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslide; GIS; Genetic programming; Remote sensing; Artificial neural network; Zonouz PlainKeyWords Plus: ANALYTICAL HIERARCHY PROCESS; SUPPORT VECTOR MACHINE; HOA BINH PROVINCE; CONDITIONAL-PROBABILITY; HAZARD ZONATION; FUZZY-LOGIC; PROCESS AHP; HONG-KONG; GIS; TURKEYAddresses: [Nourani, Vahid] Univ Tabriz, Dept Water Resources Engn, Fac Civil Engn, Tabriz, Iran. [Pradhan, Biswajeet] Univ Putra Malaysia, Dept Civil Engn, Fac Engn, Serdang 43400, Selangor, Malaysia. [Ghaffari, Hamid] Islamic Azad Univ, Dept Water Resources Engn, Fac Civil Engn, Mahabad Branch, Mahabad, Iran. [Sharifi, Seyed Saber] Univ Tabriz, Dept Water Engn, Fac Agr, Tabriz, Iran. Reprint Address: Nourani, V (reprint author), Univ Tabriz, Dept Water Resources Engn, Fac Civil Engn, 29 Bahman Ave, Tabriz, Iran.E-mail Addresses: [email protected]; [email protected]; [email protected]; [email protected] Identifiers:

Author ResearcherID Number ORCID NumberYanmin, Song D-8314-2014 Publisher: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences; Water ResourcesResearch Areas: Geology; Meteorology & Atmospheric Sciences; Water ResourcesIDS Number: AA9EF ISSN: 0921-030X eISSN: 1573-0840 29-char Source Abbrev.: NAT HAZARDS ISO Source Abbrev.: Nat. Hazards Source Item Page Count: 25 Record 45 of 58Title: Assessing landslide susceptibility using Bayesian probability-based weight of evidence model Author(s): Sujatha, ER (Sujatha, Evangelin Ramani); Kumaravel, P (Kumaravel, P.); Rajamanickam, GV (Rajamanickam, G. Victor)Source: BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT Volume: 73 Issue: 1 Pages: 147-161 DOI: 10.1007/s10064-013-0537-9 Published: FEB 2014 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Agterberg FP, 1993, COMPUTERS GEOLOGY 25, P13 ANBALAGAN R, 1992, ENG GEOL, V32, P269, DOI 10.1016/0013-7952(92)90053-2 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Bai SB, 2011, ENVIRON EARTH SCI, V62, P139, DOI 10.1007/s12665-010-0509-3 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Binaghi E, 1998, NAT HAZARDS, V17, P77, DOI 10.1023/A:1008001724538 Bonham-Carter GF, 1994, GEOGRAPHIC INFORMATI, P267 Bonham-Carter G.F., 1989, STAT APPL EARTH SCI, V89, P171 BONHAMCARTER GF, 1988, PHOTOGRAMM ENG REM S, V54, P1585 Can T, 2005, GEOMORPHOLOGY, V72, P250, DOI 10.1016/j.geomorph.2005.05.011 Chung CJ, 2006, COMPUT GEOSCI-UK, V32, P1052, DOI 10.1016/j.cageo.2006.02.003 Chung CJF, 1999, PHOTOGRAMM ENG REM S, V65, P1389 Dahal RK, 2008, ENVIRON GEOL, V54, P311, DOI 10.1007/s00254-007-0818-3 Dai FC, 2002, GEOMORPHOLOGY, V42, P213, DOI 10.1016/S0169-555X(01)00087-3 Duman TY, 2006, ENVIRON GEOL, V51, P241, DOI 10.1007/s00254-006-0322-1 Ercanoglu M, 2002, ENVIRON GEOL, V41, P720, DOI 10.1007/s00254-001-0454-2 Fell R, 2008, ENG GEOL, V102, P85, DOI 10.1016/j.enggeo.2008.03.022 Gokceoglu C, 2005, ENG GEOL, V81, P65, DOI 10.1016/j.enggeo.2005.07.011 Gokeceoglu C, 1996, ENG GEOL, V44, P147 Gomez H, 2005, ENG GEOL, V78, P11, DOI 10.1016/j.enggeo.2004.10.004 Gorsevski PV, 2006, CONTROL CYBERN, V35, P121 Guzzetti F, 1999, GEOMORPHOLOGY, V31, P181, DOI 10.1016/S0169-555X(99)00078-1 Keefer DK, 2007, SCIENCE, V316, P1136, DOI 10.1126/science.1143308 Lee S, 2006, NAT HAZARD EARTH SYS, V6, P687 Lee S, 2005, ENVIRON GEOL, V47, P982, DOI 10.1007/s00254-005-1228-z Lee S, 2007, LANDSLIDES, V4, P33, DOI 10.1007/s10346-006-0047-y Lee S, 2007, ENVIRON GEOL, V52, P615, DOI 10.1007/s00254-006-0491-y Lee S, 2002, ENVIRON GEOL, V43, P120, DOI 10.1007/s00254-002-0616-x Magliulo P, 2008, NAT HAZARDS, V47, P411, DOI 10.1007/s11069-008-9230-x Mathew J, 2007, CURR SCI INDIA, V92, P628 Nefeslioglu HA, 2010, MATH PROBL ENG, DOI 10.1155/2010/901095 Oh HJ, 2011, ENVIRON EARTH SCI, V62, P935, DOI 10.1007/s12665-010-0579-2 Poli S., 2007, NAT RESOUR RES, V16, P121, DOI DOI 10.1007/S11053-007-9043-8 Pradhan B, 2010, COMPUT ENVIRON URBAN, V34, P216, DOI 10.1016/j.compenvurbsys.2009.12.004 Pradhan B, 2011, ENVIRON ECOL STAT, V18, P471, DOI 10.1007/s10651-010-0147-7 Pradhan B, 2010, ENVIRON EARTH SCI, V60, P1037, DOI 10.1007/s12665-009-0245-8 Sujatha ER, 2013, ARAB J GEOSCI, V6, P429, DOI 10.1007/s12517-011-0356-x Sujatha ER, 2011, J MT SCI-ENGL, V8, P505 Sujatha ER, 2011, NAT HAZARDS, V59, P401, DOI 10.1007/s11069-011-9763-2 van Westen CJ, 2006, B ENG GEOL ENVIRON, V65, P167, DOI 10.1007/s10064-005-0023-0



Yilmaz I, 2010, ENVIRON EARTH SCI, V61, P821, DOI 10.1007/s12665-009-0394-9 Yilmaz I, 2009, B ENG GEOL ENVIRON, V68, P297, DOI 10.1007/s10064-009-0185-2Cited Reference Count: 42 Abstract: This study aims to demonstrate the application of a Bayesian probability-based weight of evidence model to map landslide susceptibility in the Tevankarai stream watershed, Kodaikkanal, India. Slope gradient, relief, aspect, curvature, land use, soil, lineament density, flow accumulation and proximity to roads were the landslide conditioning factors we considered in order to assess susceptibility. The weight of evidence model uses the prior probability of occurrence of a landslide event to identify areas prone to landslides based on the relative contributions of landslide conditioning factors. A pair-wise test of conditional independence was performed for the above factors, allowing the combination of conditioning factors to be analyzed. The contrast (difference of W (+) and W (-)) was used as weight for each factor's type. The best observed combination consisted of the relief, slope, curvature, land use and distance to road factors, showing an accuracy of 86.1 %, while the accuracy of the map with all factors was 83.9 %.Accession Number: WOS:000330952100013 Language: EnglishDocument Type: ArticleAuthor Keywords: Landslide; Susceptibility; Weight of evidence; Contrast; Conditional independenceKeyWords Plus: ARTIFICIAL NEURAL-NETWORKS; LOGISTIC-REGRESSION; CONDITIONAL-PROBABILITY; HAZARD EVALUATION; TURKEY; ZONATION; GIS; VERIFICATION; KOYULHISAR; CATCHMENTSAddresses: [Sujatha, Evangelin Ramani] SASTRA Univ, Sch Civil Engn, Thanjavur, Tamil Nadu, India. [Kumaravel, P.] Indian Inst Astrophys, Kodaikkanal, Tamil Nadu, India. [Rajamanickam, G. Victor] Sairam Grp Inst, Madras, Tamil Nadu, India. Reprint Address: Sujatha, ER (reprint author), SASTRA Univ, Sch Civil Engn, Thanjavur, Tamil Nadu, India.E-mail Addresses: [email protected]; [email protected]; [email protected]: SPRINGER HEIDELBERG Publisher Address: TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY Web of Science Categories: Engineering, Environmental; Engineering, Geological; Geosciences, MultidisciplinaryResearch Areas: Engineering; GeologyIDS Number: AA2VK ISSN: 1435-9529 eISSN: 1435-9537 29-char Source Abbrev.: B ENG GEOL ENVIRON ISO Source Abbrev.: Bull. Eng. Geol. Environ. Source Item Page Count: 15 Record 46 of 58Title: Highway construction across heavily mined ground and steep topography in southern China Author(s): Tong, LY (Tong, Liyuan); Liu, L (Liu, Lian); Yu, Q (Yu, Qiu)Source: BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT Volume: 73 Issue: 1 Pages: 43-60 DOI: 10.1007/s10064-013-0503-6 Published: FEB 2014 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Aissaoui K, 1999, THESIS NANCY SCH MIN, P230 Al Heib M, 2005, RESIDUAL SUBSIDENCE, P1 Almasmoum A, 1996, GEOTECH GEOL ENG, V14, P21, DOI 10.1007/BF00431232 Altun AO, 2010, SCI RES ESSAYS, V5, P3206 [Anonymous], 1947, REPORT SPECIAL COMMI, P80 Beadman D.R., 2002, MIN TECHNOL, V111, P99 Bell F.G., 1999, B ENG GEOL ENVIRON, V57, P225, DOI 10.1007/s100640050040 Bell FG, 2006, MINING ITS IMPACT EN, P560 Biswas K, 1999, P 2 INT WORKSH COAL, P5 Brauner G, 1973, 8572 US BUR MIN, P53 Bruhn RW, 1978, AM SOC CIV ENG SPRIN, V3293, P26 Cai HB, 2010, J CENT S U SCI TECHN, V41, P1528 Collins BJ, 1977, P C U WAL I SCI TECH, P3 Culshaw M.G., 2000, MIN TECHNOL, V109, P132 Ding CJ, 2009, STUDY CHARACTER FORE Donnelly LJ, 2007, Q J ENG GEOL HYDROGE, V41, P301 Drumm EC, 1988, MINE INDUC SUBSID EF, V19, P168 Fernando DA, 1988, GEOTECH SPECIAL PUBL, V19, P189 Flaschentrager H, 1957, P EUR C GROUND MOV L [高磊 GAO Lei], 2009, [防灾减灾工程学报, Journal of Disaster Prevention and Mitigation Engineering], V29, P387 Goulty NR, 1996, Q J ENG GEOL, V29, P83, DOI 10.1144/GSL.QJEGH.1996.029.P1.06 Grard C, 1969, REV IND MIN, V51, P35 Gray RE, 1978, STUDY ANAL SURFACE S, P362 Gray RR, 1977, STUDY ANAL SURFACE S, P155 Guo GL, 2001, MECH DEFORMATION BUI Hari Pokharel, 2012, AUSTR STRUCT ENG C 2 He GQ, 1994, MINE SUBSIDENCE Hegazy YA, 2011, TIME DEPENDENT GROUN Hood M, 1981, P WORKSH SURF SUBS U, P100 Hunt SR, 1978, P ILL MIN I, P50 Jones CJFP, 1988, GEOTECH SPECIAL PUBL, V19, P107 Jones CJFP, 2004, INT TECHN GROUP AB U Jones DB, 1991, P 7 ISRM INT C ROCK, P898 Kapp WA, 1973, P 4 S AUSTR I MIN ME Kempton G.T., 1998, P 6 INT C GEOS ATL U, V2, P767 Kratzsch H, 1983, MINING SUBSIDENCE EN, P543 Li TF, 2012, CHIN J ROCK MECH S2, V31, P3803 Li X.H., 2005, CHIN J ROCK SOIL MEC, V26, P910 LOW BK, 1994, J GEOTECH ENG-ASCE, V120, P1917, DOI 10.1061/(ASCE)0733-9410(1994)120:11(1917) Marino GG, 1988, GEOTECH SPECIAL PUBL, V19, P87 Marschalko M, 2012, ENG GEOL, V147, P37, DOI 10.1016/j.enggeo.2012.07.014 Ministry of Transport of PRC, 2011, D31032011 JTGT MIN T Orchard RJ, 1956, T I MIN E 1, V116, P942 Orchard RJ, 1974, P INT S MIN ENV, P643 Orchard RJ, 1956, T I MIN E 2, V116, P941 Pasamehmetoglu AG, 1972, THESIS U NOTTINGHAM, P190 Peng SS, 1989, MINING SCI TECHNOLOG, V8, P89, DOI 10.1016/S0167-9031(89)90493-3 Peng S.S., 1992, SURFACE SUBSIDENCE E Piggott RJ, 1978, GROUND MOVEMENTS ARI, P749 Rodriguez R, 2010, TUNN UNDERGR SP TECH, V25, P456, DOI 10.1016/j.tust.2010.02.010 Sargand Shad M, 1988, GEOTECH SPECIAL PUBL, V19, P18



Shadrin AG, 1977, FIZIKOTEKHNICHESKIE, V6, P21 Singh MM, 1992, MINING ENG HDB, P938 Sun SG, 2008, GEOSYNTHETICS IN CIVIL AND ENVIRONMENTAL ENGINEERING, P839 Tang Fu-quan, 2009, Journal of Coal Science and Engineering (China), V15, DOI 10.1007/s12404-009-0403-3 Tong LY, 2006, ASSESSMENT HIGHWAY D Triplett TL, 1986, P 27 US S ROCK MECH, P283 Tsang P, 1996, MIN ENG J, V48, P55 VANDERMERWE JN, 1993, J S AFR I MIN METALL, V93, P71 Wang ZS, 2011, STUDY NONLINEAR PRED Whittaker BN, 1989, SUBSIDENCE OCCURRENC, P528 Wu JG, 2012, ADV MAT RES, V524-527, P330 YAO XL, 1994, Q J ENG GEOL, V27, P15, DOI 10.1144/GSL.QJEGH.1994.027.P1.04 Zhao MH, 2004, CHIN J ROCK SOIL MEC, V25, P64 Zhu YQ, 2009, CHIN J ENG GEOL, V17, P394Cited Reference Count: 65 Abstract: Due to rapid expansion of the highway network in southern China in recent years, abandoned mine areas have been increasingly considered for highway construction. It is particularly challenging to carry out the assessment and remediation of mining subsidence effects on highway infrastructures, including high-filling embankments, deep-cutting slopes, and bridges. This article describes the subsidence mechanisms of abandoned mines with longwall workings and room-and-pillar systems, and also the potential geohazards and risks associated with abandoned mines. A hazard zonation criterion adopted for highway design and construction in China is introduced, as well as the possible remedial measures that can be carried out for various highway infrastructures. In the case study, grouting was used to fill cavities and stabilize the voids, and a two-layered geogrid was incorporated in the sub-base and embankment to avoid subsidence or sudden collapse of the ground. The remedial measures applied to deep-cutting slopes involved grouting, an anchor, or grid beam, employed either alone or in combination. In addition, a reinforced soil-piled embankment was utilized to reduce differential settlement at the transition zone between a bridge abutment and embankment. Based on the experiences gained, recommendations for future projects are given.Accession Number: WOS:000330952100005 Language: EnglishDocument Type: ArticleAuthor Keywords: Highway construction; Hilly ground; Abandoned mine workings; Damage; Protection measuresKeyWords Plus: SUBSIDENCE; COALAddresses: [Tong, Liyuan] Southeast Univ, Transportat Coll, Nanjing 210096, Jiangsu, Peoples R China. [Liu, Lian] Mott MacDonald Grp, Croydon CR0 2EE, Surrey, England. [Yu, Qiu] Guangdong Rd & Bridge Construct Co Ltd, Guangzhou 510635, Guangdong, Peoples R China. Reprint Address: Tong, LY (reprint author), Southeast Univ, Transportat Coll, Nanjing 210096, Jiangsu, Peoples R China.E-mail Addresses: [email protected]: SPRINGER HEIDELBERG Publisher Address: TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY Web of Science Categories: Engineering, Environmental; Engineering, Geological; Geosciences, MultidisciplinaryResearch Areas: Engineering; GeologyIDS Number: AA2VK ISSN: 1435-9529 eISSN: 1435-9537 29-char Source Abbrev.: B ENG GEOL ENVIRON ISO Source Abbrev.: Bull. Eng. Geol. Environ. Source Item Page Count: 18 Record 47 of 58Title: Measured Data Processing in Civil Structure Using the DOProC Method Author(s): Cajka, R (Cajka, Radim); Krejsa, M (Krejsa, Martin)Edited by: Zhang H; Jin D; Zhao XJSource: ADVANCED RESEARCH ON CIVIL ENGINEERING, MATERIALS ENGINEERING AND APPLIED TECHNOLOGY Book Series: Advanced Materials Research Volume: 859 Pages: 114-121 DOI: 10.4028/www.scientific.net/AMR.859.114 Published: 2014 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Cajka R., 2012, RECENT RES ENV GEOLO, P447 Cajka R., 2011, T VSB TU OSTRAVA CON, V11, P1, DOI DOI 10.2478/V10160-011-0021-Z Cajka R., 2013, PROCEDIA ENG, V65, P230, DOI [10.1016/j.proeng.2013.09.035, DOI 10.1016/J.PROENG.2013.09.035] Janas P., 2010, T VSB TU OSTRAVA COS, V10, P1, DOI [10.2478/v10160-010-0010-7, DOI 10.2478/V10160-010-0010-7] Janas P., 2012, T VSB TU OSTRAVA CON, V12, P1, DOI [10.2478/v10160-012-0017-3, DOI 10.2478/V10160-012-0017-3] Janas P, 2010, RELIABILITY, RISK AND SAFETY: THEORY AND APPLICATIONS VOLS 1-3, P1467 Janas P., 2012, P 12 INT C CIV STRUC Kala Z, 2012, AIP CONF PROC, V1479, P2070, DOI 10.1063/1.4756597 Kralik J, 2013, ADV MATER RES-SWITZ, V712-715, P929, DOI 10.4028/www.scientific.net/AMR.712-715.929 Krejsa M., 2012, P 11 INT C COMP STRU, DOI [10.4203/ccp.99.113., DOI 10.4203/CCP.99.113] Krejsa M, 2013, APPL MECH MATER, V300-301, P860, DOI 10.4028/www.scientific.net/AMM.300-301.860 Krejsa M., 2012, RECENT ADV SYSTEMS S, P216 Krejsa M, 2012, P 18 INT C ENG MECH, P745 Krejsa M, 2013, SCI WORLD J, DOI 10.1155/2013/267593 Krejsa M., 2012, RECENT ADV MECH ENG, P104 Krejsa M, 2014, KEY ENG MATER, V577-578, P101, DOI 10.4028/www.scientific.net/KEM.577-578.101 Krejsa M, 2014, SAFETY, RELIABILITY AND RISK ANALYSIS: BEYOND THE HORIZON, P2671, DOI 10.1201/b15938-404 Krejsa M., 2013, P 11 INT PROB WORKSH, P203 Krivy V, 2012, APPL MECH MATER, V188, P177, DOI 10.4028/www.scientific.net/AMM.188.177 Lokaj A, 2012, APPL MECH MATER, V137, P95, DOI 10.4028/www.scientific.net/AMM.137.95 Marschalko M, 2008, ARCH MIN SCI, V53, P397 Mikolasek D, 2013, APPL MECH MATER, V351-352, P254, DOI 10.4028/www.scientific.net/AMM.351-352.254 Novak D, 2014, ADV ENG SOFTW, V72, P179, DOI 10.1016/j.advengsoft.2013.06.011 Stara M., 2013, PROCEDIA ENG, V65, P411, DOI [10.1016/j.proeng.2013.09.064, DOI 10.1016/J.PROENG.2013.09.064] Sykora M, 2013, ENG STRUCT, V56, P1419, DOI 10.1016/j.engstruct.2013.07.015 Vavrusova K, 2013, APPL MECH MATER, V351-352, P1710, DOI 10.4028/www.scientific.net/AMM.351-352.1710 Vorechovska D, 2010, J PERFORM CONSTR FAC, V24, P571, DOI 10.1061/(ASCE)CF.1943-5509.0000130Cited Reference Count: 27 Abstract: This paper describes the use of measured values in the probabilistic tasks by means of the new method which is under development now - Direct Optimized Probabilistic. Calculation (DOProC). This method has been used to solve a number of probabilistic tasks. DOProC has been applied in ProbCalc a part of this software is a module for entering and assessing the measured data. The software can read values saved in a text file and can create histograms with non-parametric (empirical) distribution of the probabilities. In case of the parametric distribution, it is possible to make selection from among 24 defined types and specify the best choice, using the coefficient of determination. This approach has been used, for instance, for modelling and experimental validation of reliability of an additionally prestressed masonry construction.Accession Number: WOS:000338596900024 Language: EnglishDocument Type: Proceedings Paper



Conference Title: 2nd International Conference on Civil Engineering and Material Engineering (CEME 2013) Conference Date: DEC 21-22, 2013 Conference Location: Wuhan, PEOPLES R CHINA Conference Sponsors: Int Sci & Educ Researcher Assoc, Beijing Gireida Educ Res Ctr, VIP Informat Conf CtrAuthor Keywords: Direct Optimized Probabilistic Calculation; DOProC Method; HistAn; ProbCalc; Bounded Histogram; Probability DistributionAddresses: [Cajka, Radim] Tech Univ Ostrava, Dept Struct, Fac Civil Engn, Ostrava 70833, Czech Republic. Reprint Address: Cajka, R (reprint author), Tech Univ Ostrava, Dept Struct, Fac Civil Engn, Ludvika Podeste 1875-17, Ostrava 70833, Czech Republic.E-mail Addresses: [email protected]; [email protected] Identifiers:

Author ResearcherID Number ORCID NumberKrejsa, Martin D-2107-2011 0000-0003-0571-2616 Cajka, Radim F-2889-2010 0000-0002-2346-062X Publisher: TRANS TECH PUBLICATIONS LTD Publisher Address: LAUBLSRUTISTR 24, CH-8717 STAFA-ZURICH, SWITZERLAND Web of Science Categories: Computer Science, Interdisciplinary Applications; Engineering, Civil; Engineering, Mechanical; Materials Science, MultidisciplinaryResearch Areas: Computer Science; Engineering; Materials ScienceIDS Number: BA8TC ISSN: 1022-6680 ISBN: 978-3-03785-979-729-char Source Abbrev.: ADV MATER RES-SWITZ Source Item Page Count: 8 Record 48 of 58Title: Validating a computational model of a rooflight steel structure by means of a load test Author(s): Cajka, R (Cajka, Radim); Krejsa, M (Krejsa, Martin)Edited by: Huang YSource: ADVANCES IN CIVIL AND STRUCTURAL ENGINEERING III, PTS 1-4 Book Series: Applied Mechanics and Materials Volume: 501-504 Pages: 592- 598 DOI: 10.4028/www.scientific.net/AMM.501-504.592 Published: 2014 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Cajka R., 2012, 3 INT S LIF CYCL CIV, P1955 Cajka R., 2010, J STRUCTURAL FIRE EN, V1, P243, DOI [10.1260/2040-2317.1.4.243, DOI 10.1260/2040-2317.1.4.243] Cajka R, 2005, IABSE Conference New Delhi, India 2005, P551 Cajka R., 2005, P OF FINAL C COST AC Cajka R., 2011, T VSB TECHNICAL U OS, VXI, DOI [10.2478/v10160-011-0037-4, DOI 10.2478/V10160-011-0037-4] Janas P., 2012, P 12 INT C CIV STRUC, DOI [10.4203/ccp.91.72, DOI 10.4203/CCP.91.72] Janas P, 2010, RELIABILITY, RISK AND SAFETY: THEORY AND APPLICATIONS VOLS 1-3, P1467 Kala J, 2012, J VIBROENG, V14, P1151 Kala Z, 2012, J CIV ENG MANAG, V18, P81, DOI 10.3846/13923730.2012.655306 Kralik Juraj, 2013, Applied Mechanics and Materials, V390, DOI 10.4028/www.scientific.net/AMM.390.172 Krejsa M, 2013, APPL MECH MATER, V300-301, P860, DOI 10.4028/www.scientific.net/AMM.300-301.860 Krejsa M, 2013, SCI WORLD J, DOI 10.1155/2013/267593 Krejsa M, 2014, SAFETY, RELIABILITY AND RISK ANALYSIS: BEYOND THE HORIZON, P2671, DOI 10.1201/b15938-404 Krivy V, 2012, APPL MECH MATER, V188, P177, DOI 10.4028/www.scientific.net/AMM.188.177 Krivy V, 2011, ENGINEERING MECHANICS 2011, P335 Lokaj A, 2012, APPL MECH MATER, V137, P95, DOI 10.4028/www.scientific.net/AMM.137.95 Mikolasek D, 2013, APPL MECH MATER, V351-352, P254, DOI 10.4028/www.scientific.net/AMM.351-352.254 Naprstek J, 2012, J WIND ENG IND AEROD, V111, P1, DOI 10.1016/j.jweia.2012.08.002 Pustka D., 2008, P 11 E AS PAC C STRU, P334 Sykora M, 2013, ENG STRUCT, V56, P1419, DOI 10.1016/j.engstruct.2013.07.015 Tesar A, 2008, INT J NUMER METH ENG, V74, P1670, DOI 10.1002/nme.2224 Vavrusova K, 2013, APPL MECH MATER, V351-352, P1710, DOI 10.4028/www.scientific.net/AMM.351-352.1710 Vican J., 2013, KOMUNIKACIE, V15, P112Cited Reference Count: 23 Abstract: During erection of a rooflight steel structure excessive deformation started appearing in the steel structure designed for a rooflight. After repairing the load-carrying system it was necessary to check whether the structure was free of permanent deformations. The situation was consulted with the investor and it was proposed to carry out a load test which should prove that the real structure was in accordance with the computational model.Accession Number: WOS:000339031500118 Language: EnglishDocument Type: Proceedings PaperConference Title: 3rd International Conference on Civil Engineering and Transportation (ICCET 2013) Conference Date: DEC 14-15, 2013 Conference Location: Kunming, PEOPLES R CHINA Conference Sponsors: Guizhou UnivAuthor Keywords: steel structure; computational model; load test; permanent deformationAddresses: [Cajka, Radim] Tech Univ Ostrava, Dept Struct, Fac Civil Engn, Ostrava 70833, Czech Republic. Reprint Address: Cajka, R (reprint author), Tech Univ Ostrava, Dept Struct, Fac Civil Engn, LudvikaPodeste 1875-17, Ostrava 70833, Czech Republic.E-mail Addresses: [email protected]; [email protected] Identifiers:

Author ResearcherID Number ORCID NumberKrejsa, Martin D-2107-2011 0000-0003-0571-2616 Cajka, Radim F-2889-2010 0000-0002-2346-062X Publisher: TRANS TECH PUBLICATIONS LTD Publisher Address: LAUBLSRUTISTR 24, CH-8717 STAFA-ZURICH, SWITZERLAND Web of Science Categories: Construction & Building Technology; Engineering, Civil; Engineering, Mechanical; Engineering, GeologicalResearch Areas: Construction & Building Technology; EngineeringIDS Number: BA8YQ ISSN: 1660-9336 ISBN: 978-3-03835-005-729-char Source Abbrev.: APPL MECH MATER Source Item Page Count: 7



Author(s): Eker, R (Eker, Remzi); Aydin, A (Aydin, Abdurrahim)Source: TURKISH JOURNAL OF AGRICULTURE AND FORESTRY Volume: 38 Issue: 2 Pages: 281-290 DOI: 10.3906/tar-1303-12 Published: 2014 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Akgun A, 2011, LANDSLIDES, V9, P93 Aleotti P, 1999, B ENG ENV, V58, P21, DOI DOI 10.1007/S100640050066 Allison C, 2004, ENVIRON MANAGE, V33, P173, DOI 10.1007/s00267-003-0142-y Aricak B, 2010, FORMEC 2010 FOR ENG Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Bai SB, 2008, FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 4, PROCEEDINGS, P647, DOI 10.1109/FSKD.2008.524 Clark WA, 1986, STAT METHODS GEOGRAP Coker R. J., 1993, Journal of Hydrology, New Zealand, V31, P65 Dhakal AS, 2003, EARTH SURF PROC LAND, V28, P853, DOI 10.1002/esp.499 Duman TY, 2005, ENG GEOL, V77, P99, DOI 10.1016/j.engeo.2004.08.005 Ercanoglu M, 2002, ENVIRON GEOL, V41, P720, DOI 10.1007/s00254-001-0454-2 Ercanoglu M, 2011, ENVIRON EARTH SCI, V64, P949, DOI 10.1007/s12665-011-0912-4 Erener A, 2010, LANDSLIDES, V7, P55, DOI 10.1007/s10346-009-0188-x Girvetz E, 2003, ENVIRON MANAGE, V32, P218, DOI 10.1007/s00267-003-2970-1 Gorcelioglu E, 2004, ORMAN YOLLARI EROZYO Gumus S, 2008, ENVIRON MONIT ASSESS, V142, P109, DOI 10.1007/s10661-007-9912-y Hasmadi MI, 2008, MODERN APP SCI, V2, P100 Heam G, 2007, LANDSLIDE IMPACTS RO Hosmer D. M., 2000, WILEY SERIES PROBABI Hosseini SA, 2012, J ENVIRON ENG LANDSC, V20, P58, DOI 10.3846/16486897.2012.662748 Jakob M, 2000, CATENA, V38, P279, DOI 10.1016/S0341-8162(99)00078-8 Jones JA, 2000, CONSERV BIOL, V14, P76, DOI 10.1046/j.1523-1739.2000.99083.x Kincal C, 2009, ENVIRON EARTH SCI, V59, P745, DOI 10.1007/s12665-009-0070-0 Lee S, 2005, INT J REMOTE SENS, V26, P1477, DOI 10.1080/01431160412331331012 Lee S, 2005, ENVIRON GEOL, V47, P982, DOI 10.1007/s00254-005-1228-z Malamud BD, 2004, EARTH SURF PROC LAND, V29, P687, DOI [10.1002/esp.1064, 10.1002/esq.1064] Marschalko M, 2009, ACTA MONTAN SLOVACA, V14, P232 Nefeslioglu HA, 2008, ENG GEOL, V97, P171, DOI 10.1016/j.enggeo.2008.01.004 Radfar I., 2011, 2011 2nd IEEE International Conference on Emergency Management and Management Sciences(ICEMMS), DOI 10.1109/ICEMMS.2011.6015739 Reichenbach P, 2002, P 4 EGS PLIN C HELD Sharpe C.F.S., 1938, LANDSLIDES RELATED P Sidle RC, 1985, WATER RESOURCES MONO, V11 Sorkhi A., 2012, African Journal of Environmental Science and Technology, V6, P43 Suzen ML, 2011, INT J DIGIT EARTH, V5, P1 SWANSON FJ, 1975, GEOLOGY, V3, P393, DOI 10.1130/0091-7613(1975)3<393:IOCARC>2.0.CO;2 Vahidnia MH, 2010, COMPUT GEOSCI-UK, V36, P1101, DOI 10.1016/j.cageo.2010.04.004 Van Den Eeckhaut M, 2010, GEOMORPHOLOGY, V115, P141, DOI 10.1016/j.geomorph.2009.09.042 Wachal D. J., 2000, GeoJournal, V51, P245, DOI 10.1023/A:1017524604463 Wemple BC, 2001, EARTH SURF PROC LAND, V26, P191, DOI 10.1002/1096-9837(200102)26:2<191::AID-ESP175>3.3.CO;2-L Yilmaz I, 2009, COMPUT GEOSCI-UK, V35, P1125, DOI 10.1016/j.cageo.2008.08.007Cited Reference Count: 40 Abstract: Forest roads are one of the biggest investments in forest management. Their possible adverse effect on the environment is becoming an important issue for administrators due to a recent increase in public awareness. Especially in the Black Sea Region of Turkey, road-related landslides are common in forested areas because the roads are located in hilly regions with steep slopes. In addition to their impact on forests, landslides can cause damage to roadbeds which requires immediate maintenance. Landslide-susceptibility maps are widely used for different purposes such as reducing the effects of landslides, decision making, and planning. These maps can easily be generated by utilizing the advanced features of Geographical Information Systems (GIS) and computer technologies. Logistic regression (LR) is a widely used technique for mapping landslide susceptibility; landslide conditioning parameters such as topography, lithology, land use, distance to streams and roads, and curvature can be mapped by GIS tools. In this study a fieldwork-generated inventory of 288 landslides was used to produce a landslide-susceptibility map for the Yigilca Forest Directorate (Turkey). This map was generated by applying a GIS-based LR method. Land use, lithology, elevation, slope, aspect, distance to streams, distance to roads, and plan curvature were considered as the landslide conditioning parameters. After the landslide-susceptibility map was divided into 5 classes of susceptibility (very low, low, moderate, high, and very high), it was overlapped with a road network map in order to evaluate forest road conditions in terms of landslide susceptibility. For a quantitative analysis of forest road-landslide interaction, 2 new parameters were determined: a landslide frequency index (divided into general and real) and a road-landslide index (divided into general and real). Real landslide frequency and general landslide frequency on the roads were found to be 0.42 and 0.18, respectively. The results showed that the real road-landslide index and the general road-landslide index in the area were 0.10 and 0.04, respectively.Accession Number: WOS:000329965800014 Language: EnglishDocument Type: ArticleAuthor Keywords: Forest road networks; landslide frequency; landslide susceptibility; logistic regression; road-landslide index; YigilcaKeyWords Plus: LOGISTIC-REGRESSION; CASCADE RANGE; IMPACT; GIS; NETWORKS; ANATOLIA; OREGONAddresses: [Eker, Remzi; Aydin, Abdurrahim] Duzce Univ, Fac Forestry, Duzce, Turkey. Reprint Address: Eker, R (reprint author), Duzce Univ, Fac Forestry, Duzce, Turkey.E-mail Addresses: [email protected]: TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY Publisher Address: ATATURK BULVARI NO 221, KAVAKLIDERE, ANKARA, 00000, TURKEY Web of Science Categories: Agriculture, Multidisciplinary; Agronomy; ForestryResearch Areas: Agriculture; ForestryIDS Number: 293IY ISSN: 1300-011X eISSN: 1303-6173 29-char Source Abbrev.: TURK J AGRIC FOR ISO Source Abbrev.: Turk. J. Agric. For. Source Item Page Count: 10



Record 49 of 58Title: Assessment of forest road conditions in terms of landslide susceptibility: a case study in Yigilca Forest Directorate (Turkey)

Kay D., 2006, COAL 2006 COAL OP C, P327 [乐琪浪 Le Qilang], 2011, [工程地质学报, Journal of Engineering Geology], V19, P823 [李媛 Li Yuan], 2004, [中国地质灾害与防治学报, The Chinese Journal of Geological Hazard and Control], V15, P29 Lollino P., 2013, GEOSYSTEM ENG, V16, P100 Marschalko M, 2012, ENVIRON MONIT ASSESS, V184, P6709, DOI 10.1007/s10661-011-2453-4 Palma B, 2012, NAT HAZARDS, V61, P187, DOI 10.1007/s11069-011-9899-0 Parise M, 2008, LANDSLIDES AND ENGINEERED SLOPES: FROM THE PAST TO THE FUTURE, VOLS 1 AND 2, P275, DOI 10.1201/9780203885284-c21 Parise M., 2010, SERIES GROUNDWATER I, V2, P155 Pells P. J. N., 2008, P 1 SO HEM INT ROCK, P39 Rainer P., 2005, J MT SCI-ENGL, V2, P211, DOI 10.1007/BF02973194 Ren Y. R., 2005, J GEOL HAZARD CONT, V16, P28 Rohn J., 2004, B ENG GEOL ENVIRON, V63, P71, DOI 10.1007/s10064-003-0201-x Ruff M, 2008, ENVIRON GEOL, V55, P441, DOI 10.1007/s00254-007-0990-5 Santo A, 2007, GEOL SOC SPEC PUBL, V279, P59, DOI 10.1144/SP279.6 Tang Fu-quan, 2009, Journal of Coal Science and Engineering (China), V15, DOI 10.1007/s12404-009-0403-3 von Poschinger A., 2002, CATASTROPHIC LANDSLI, V15, P237 White E., 1969, B NATL SPELEOL SOC, V31, P83 Zhang C. S., 2000, QUATERNARY SCI, V20, P559 Zhang Z. Y., 1994, PRINCIPLE ENG GEOLOG, P66Cited Reference Count: 25 Abstract: Calcareous mountainous areas are highly prone to geohazards, and rockslides play an important role in cliff retreat. This study presents three examples of failures of limestone cliffs with subhorizontal bedding in the southwestern calcareous area of China. Field observations and numerical modeling of Yudong Escarpment, Zengzi Cliff, and Wangxia Cliff showed that pre-existing vertical joints passing through thick limestone and the alternation of competent and incompetent layers are the most significant features for rockslides. A "hard-on-soft" cliff made of hard rocks superimposed on soft rocks is prone to rock slump, characterized by shearing through the underlying weak strata along a curved surface and backward tilting. When a slope contains weak interlayers rather than a soft basal, a rock collapse could occur from the compression fracture and tensile split of the rock mass near the interfaces. A rockslide might shear through a hard rock mass if no discontinuities are exposed in the cliff slope, and sliding may occur along a moderately inclined rupture plane. The "toe breakout" mechanism mainly depends on the strength characteristics of the rock mass.Accession Number: WOS:000343116800024 Language: EnglishDocument Type: ArticleAddresses: [Feng, Z.; Li, B.] Chinese Acad Geol Sci, Inst Geomech, Key Lab Neotecton Movement & Geohazard MLR, Beijing, Peoples R China. [Yin, Y. P.] China Inst Geoenvironm Monitoring, Beijing 100081, Peoples R China. [He, K.] Changan Univ, Xian 710054, Peoples R China. Reprint Address: Li, B (reprint author), Chinese Acad Geol Sci, Inst Geomech, Key Lab Neotecton Movement & Geohazard MLR, Beijing, Peoples R China.E-mail Addresses: [email protected]: COPERNICUS GESELLSCHAFT MBH Publisher Address: BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY Web of Science Categories: Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences; Water ResourcesResearch Areas: Geology; Meteorology & Atmospheric Sciences; Water ResourcesIDS Number: AQ8WB ISSN: 1561-8633 29-char Source Abbrev.: NAT HAZARD EARTH SYS ISO Source Abbrev.: Nat. Hazards Earth Syst. Sci. Source Item Page Count: 9 Funding:

Funding Agency Grant NumberChina Geological Survey 12120114079101 Ministry of Science and Technology of the People's Republic of China 2012BAK10B01 National Natural Science Foundation of China 41302246



Record 50 of 58Title: Rockslides on limestone cliffs with subhorizontal bedding in the southwestern calcareous area of China Author(s): Feng, Z (Feng, Z.); Li, B (Li, B.); Yin, YP (Yin, Y. P.); He, K (He, K.)Source: NATURAL HAZARDS AND EARTH SYSTEM SCIENCES Volume: 14 Issue: 9 Pages: 2627-2635 DOI: 10.5194/nhess-14-2627-2014 Published: 2014 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: ABELE G, 1994, MT RES DEV, V14, P315, DOI 10.2307/3673727 Altun AO, 2010, SCI RES ESSAYS, V5, P3206 Ding W. W, 1990, STABILITY ANAL RESER, P7 Embleton-Hamann C., 2007, GEOMORPHOLOGY FUTURE, P33 Geology Team of Sichuan Geology and Mineral Bureau, 1995, GEOL SURV REP BAUX D Huang R. Q., 2013, KEY NOT 6 NAT AC C G

Record 51 of 58Title: The slope aspect: A predisposing factor for landsliding? Author(s): Capitani, M (Capitani, Marco); Ribolini, A (Ribolini, Adriano); Bini, M (Bini, Monica)Source: COMPTES RENDUS GEOSCIENCE Volume: 345 Issue: 11-12 Pages: 427-438 DOI: 10.1016/j.crte.2013.11.002 Published: NOV-DEC 2013 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Alexander RW, 2008, GEOMORPHOLOGY, V100, P83, DOI 10.1016/j.geomorph.2007.10.025 Atkinson PM, 2011, GEOMORPHOLOGY, V130, P55, DOI 10.1016/j.geomorph.2011.02.001 Atkinson PM, 1998, COMPUT GEOSCI-UK, V24, P373, DOI 10.1016/S0098-3004(97)00117-9 Ayalew L, 2004, GEOMORPHOLOGY, V57, P95, DOI 10.1016/S0169-555X(03)00085-0 Ayalew L, 2005, GEOMORPHOLOGY, V65, P15, DOI 10.1016/j.geomorph.2004.06.010 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Blahut J, 2010, GEOMORPHOLOGY, V119, P36, DOI 10.1016/j.geomorph.2010.02.017 Buccianti A., 2003, METODI MATEMATICI ST, V3 Canton Y, 2001, J HYDROL, V252, P65, DOI 10.1016/S0022-1694(01)00450-4 Capitani M., 2013, GEOMORPHOLOGY, DOI DOI 10.1016/J.GE0-M0RPH.2013.06.014 CARMIGNANI L, 1994, TECTONOPHYSICS, V238, P295, DOI 10.1016/0040-1951(94)90061-2 CARRARA A, 1995, ADV NAT TECHNOL HAZ, V5, P135 Carrara A, 1999, NAT HAZARDS, V20, P117, DOI 10.1023/A:1008097111310 Cevik E, 2003, ENVIRON GEOL, V44, P949, DOI 10.1007/s00254-003-0838-6 Chung CJ, 2008, GEOMORPHOLOGY, V94, P438, DOI 10.1016/j.geomorph.2006.12.036 Chung CJF, 1999, PHOTOGRAMM ENG REM S, V65, P1389 Clerici A, 2010, NAT HAZARDS, V52, P1, DOI 10.1007/s11069-009-9349-4 Clerici A, 2006, ENVIRON GEOL, V50, P941, DOI 10.1007/s00254-006-0264-7 Cruden D.M., 1996, LANDSLIDES INVESTIGA, P36, DOI DOI 10.1007/BF02590167 Dai FC, 2002, ENG GEOL, V64, P65, DOI 10.1016/S0013-7952(01)00093-X Dai FC, 2001, ENVIRON GEOL, V40, P381, DOI 10.1007/s002540000163 Das I, 2010, GEOMORPHOLOGY, V114, P627, DOI 10.1016/j.geomorph.2009.09.023 De Rose RC, 2013, EARTH SURF PROC LAND, V38, P356, DOI 10.1002/esp.3283 Dewitte O, 2010, GEOMORPHOLOGY, V122, P153, DOI 10.1016/j.geomorph.2010.06.010 DRAMIS F, 1994, ENG GEOL, V38, P231, DOI 10.1016/0013-7952(94)90040-X Fabbris L., 1997, STAT MULTIVARIATA AN, P437 Fell R, 2008, ENG GEOL, V102, P85, DOI 10.1016/j.enggeo.2008.03.022 Fernandes NF, 2004, CATENA, V55, P163, DOI 10.1016/S0341-8162(03)00115-2 Gallart F., 2012, GEOMORPHOLOGY, DOI DOI 10.1016/J.GE0M0RPH.2012.05.028 Gallart F, 2013, CATENA, V106, P4, DOI 10.1016/j.catena.2012.02.008 Galli M, 2008, GEOMORPHOLOGY, V94, P268, DOI 10.1016/j.geomorph.2006.09.023 Gao J, 2010, GEOMORPHOLOGY, V114, P373, DOI 10.1016/j.geomorph.2009.08.002 Ghosh S, 2011, GEOMORPHOLOGY, V131, P35, DOI 10.1016/j.geomorph.2011.04.019 Giudici P., 2005, DATA MINING METODI I, P401 Guzzetti F, 1999, GEOMORPHOLOGY, V31, P181, DOI 10.1016/S0169-555X(99)00078-1 He SW, 2012, GEOMORPHOLOGY, V171, P30, DOI 10.1016/j.geomorph.2012.04.024 Jimenez-Peralvarez JD, 2009, NAT HAZARDS, V50, P571, DOI 10.1007/s11069-008-9305-8 Kanungo DP, 2009, J S ASIA DISASTER ST, V2, P81 Kendall M., 1979, ADV THEORY STAT, P748 Komac M, 2006, GEOMORPHOLOGY, V74, P17, DOI 10.1016/j.geomorph.2005.07.005 Lee S, 2005, INT J REMOTE SENS, V26, P1477, DOI 10.1080/01431160412331331012 Lulli L, 1973, FIRENZE, V4, P143 Luzi L, 1999, NAT HAZARDS, V20, P57, DOI 10.1023/A:1008162814578 Magliulo P, 2008, NAT HAZARDS, V47, P411, DOI 10.1007/s11069-008-9230-x Nefeslioglu HA, 2008, GEOMORPHOLOGY, V94, P401, DOI 10.1016/j.geomorph.2006.10.036 Neuhauser B, 2007, GEOMORPHOLOGY, V86, P12, DOI 10.1016/j.geomorph.2006.08.002 Ohlmacher C.G., 2003, ENG GEOL, V69, P331 Piacentini D, 2012, GEOMORPHOLOGY, V151, P196, DOI 10.1016/j.geomorph.2012.02.003 Pugh E.M., 1966, ANALYSIS PHYSICAL ME, P246 Regmi NR, 2010, GEOMORPHOLOGY, V115, P172, DOI 10.1016/j.geomorph.2009.10.002 Soeters R, 1996, LANDSLIDES INVESTIGA, V247, P129 Sterlacchini S, 2011, GEOMORPHOLOGY, V125, P51, DOI 10.1016/j.geomorph.2010.09.004 Strahler A.N., 1952, CR 19 INT GEOL C A 3, V13, P341 SUZEN ML, 2004, TURKEY ENG GEOL, V71, P303 Torn D., 1996, SOIL EROSION CONSERV, P77 den Eeckhaut M, 2006, GEOMORPHOLOGY, V76, P392, DOI 10.1016/j.geomorph.2005.12.003 Van Den Eeckhaut M, 2009, GEOMORPHOLOGY, V105, P239, DOI 10.1016/j.geomorph.2008.09.027 van Westen CJ, 2008, ENG GEOL, V102, P112, DOI 10.1016/j.enggeo.2008.03.010 Vergari F, 2011, NAT HAZARD EARTH SYS, V11, P1475, DOI 10.5194/nhess-11-1475-2011 Vittorini S., 1979, RIV GEOGRAFICA ITALI, V86, P338 Vittorini S., 1977, B SOC GEOGR ITAL, V6, P25 von Ruette J, 2011, GEOMORPHOLOGY, V133, P11, DOI 10.1016/j.geomorph.2011.06.010 Yalcin A, 2011, CATENA, V85, P274, DOI 10.1016/j.catena.2011.01.014 Yalcin A, 2007, NAT HAZARDS, V41, P201, DOI 10.1007/s11069-006-9030-0 Yalcin A, 2008, CATENA, V72, P1, DOI 10.1016/j.catena.2007.01.003Cited Reference Count: 65 Abstract: The influence of slope aspect on the distribution of landslides was studied in the Milia and Roglio basins in Tuscany, Italy. For each basin, the new Tuscany region landslide inventory that was initiated in 2010 was used. The landslides were split into separate datasets based on their prevailing movement typology. To assess the results that were obtained from the different slope aspect values, maps of the lithology, slope angle, distances to streams, and distances to tectonic lineaments were included in the bivariate statistical analysis as comparison terms. For each basin, all of the geo-environmental factor maps were compared with the different landslide typologies with GIS software. Pearson's Chi(2) (chi(2)) coefficient was used to test the degree of spatial association between each predictor variable and landslide type. In addition, Cramer's V test was used to quantify the strength of the degree of association. Next, a conditional analysis was applied to all of the possible combinations that occurred between the slope aspect and other landslide-predisposing factors. Overall, the slope aspect significantly affected the distribution of superficial landslide types, but apparently not that of other landslide types. (C) 2013 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.Accession Number: WOS:000333726900002 Language: EnglishDocument Type: ArticleAuthor Keywords: Bivariate and multifactor statistical analysis; Slope aspect; Landslide susceptibility; Central ItalyKeyWords Plus: ANALYTICAL HIERARCHY PROCESS; SUSCEPTIBILITY ASSESSMENT; LOGISTIC-REGRESSION; BIVARIATE STATISTICS; CONDITIONAL ANALYSIS; SHALLOW LANDSLIDES; NORTHERN APENNINES; SPATIAL DATA; SE SPAIN; GISAddresses: [Capitani, Marco; Ribolini, Adriano; Bini, Monica] Univ Pisa, Dept Earth Sci, I-56126 Pisa, Italy.



Reprint Address: Capitani, M (reprint author), Univ Pisa, Dept Earth Sci, 53 Via S Maria, I-56126 Pisa, Italy.E-mail Addresses: [email protected]; [email protected]: ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER Publisher Address: 23 RUE LINOIS, 75724 PARIS, FRANCE Web of Science Categories: Geosciences, MultidisciplinaryResearch Areas: GeologyIDS Number: AE1JZ ISSN: 1631-0713 eISSN: 1778-7025 29-char Source Abbrev.: CR GEOSCI ISO Source Abbrev.: C. R. Geosci. Source Item Page Count: 12

Funding:

Funding Agency Grant NumberTuscany Region Project CIPE/Regione Toscana: Carta Geologica Regione Toscana e geo-tematiche derivate Italian MIUR Project

This research was supported by the Tuscany Region Project CIPE/Regione Toscana: Carta Geologica Regione Toscana e geo-tematiche derivate (Leaders Prof. P.R. Federici, Prof. A. Puccinelli), and the Italian MIUR Project (PRIN 2010-11): "Response of morphoclimatic system dynamics to global changes and related geomorphological hazards" (national and local coordinator Prof. C. Baroni). The authors would like to thank Prof. Aldo Clerici and Prof. Birgit Terhorst for their comments, which improved the paper. We would also like to acknowledge the professional English editing services of the American Journal Experts.

Record 52 of 58Title: Roof instability mechanism of longwall coalface for sandy soil gullies overlaying shallow seams Author(s): Wang, XF (Wang, Xufeng); Zhang, DS (Zhang, Dongsheng); Xu, MT (Xu, Mengtang); Fan, GW (Fan, Gangwei); Yang, ZH (Yang, Zhenhao); Qin, DD (Qin, Dongdong)Source: DISASTER ADVANCES Volume: 6 Special Issue: 5 Pages: 260-267 Published: NOV 2013 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Donnelly LJ, 2002, Q J ENG GEOL HYDROGE, V35, P33 [范钢伟 Fan Gangwei], 2011, [中国矿业大学学报. 自然科学版, Journal of China University of Mining & Technology], V40, P196 [侯忠杰 Hou Zhongjie], 2003, [煤炭学报, Journal of China Coal Society], V28, P8 Hou Zhongjie, 1999, J CHINA COAL SOC, V24, P359 Huang QX, 2000, STUDY ROOF STRUCTURE Huang QX, 2009, J MINING SAFETY ENG, V26, P304 Li FY, 2005, GROUND PRESSURE STRA, V4, P78 Li FY, 2005, J CHIA COAL SOC, V4, P83 Li KG, 2012, DISASTER ADV, V5, P1547 Marschalko M, 2008, ACTA MONTAN SLOVACA, V13, P58 Nan SQ, 2012, DISASTER ADV, V5, P110 Peng SS, 1989, MINING SCI TECHNOLOG, V8, P89, DOI 10.1016/S0167-9031(89)90493-3 Qian MG, 1994, J CHINA COAL SOC, V19, P557 Saro L, 2010, DISASTER ADV, V3, P11 Shi PW, 1996, J XIAN MINING I, V16, P215 Shi PW, 1996, J XIAN MINING I, V6, P204 Tang JX, 2010, DISASTER ADV, V3, P424 Wang SR, 2013, DISASTER ADV, V6, P59 [王旭锋 Wang Xufeng], 2013, [煤炭学报, Journal of China Coal Society], V38, P194 Wang XF, 2013, J MT SCI-ENGL, V10, P388, DOI 10.1007/s11629-013-2455-5 Wang XF, 2010, COAL SCI TECHNOLOGY, V38, P18 Xue YA, 2012, DISASTER ADV, V5, P427 Xufeng Wang, 2009, STUDY MINING INDUCED [杨治林 YANG Zhi-lin], 2008, [煤炭学报, Journal of China Coal Society], V33, P1341Cited Reference Count: 24 Abstract: Based on the geological conditions of gullies overlaying shallow coal seams, this paper analyzes the characteristics of the first roof breaking with gully-away longwall mining method, thus establishing the mechanical model of roof structure during the first and periodic breaking. In addition, its sliding and rotating instability mechanism is revealed by systematically analyzing the unstable roof condition. The results show that the main roof firstly breaks into asymmetry blocks, and the nonuniform loads on roof structure take the main responsibility for sliding instability during the first and periodic weighting Given the instability load, the method of calculating support resistance for roof control is obtained by the interaction model of support-surrounding rock, and the practice proves its reliability.Accession Number: WOS:000326419800028 Language: EnglishDocument Type: ArticleAuthor Keywords: Mining engineering; Shallow seam; Mining-induced slope; Sliding Instability; Roof controlKeyWords Plus: STABILITY; MINEAddresses: [Wang, Xufeng; Zhang, Dongsheng; Xu, Mengtang; Fan, Gangwei; Yang, Zhenhao; Qin, Dongdong] China Univ Min & Technol, Sch Mines, Xuzhou 221116, Peoples R China. [Wang, Xufeng; Zhang, Dongsheng; Fan, Gangwei] China Univ Min & Technol, Key Lab Deep Coal Resource Min, Minist Educ China, Xuzhou 221116, Peoples R China. [Wang, Xufeng; Fan, Gangwei] China Univ Min & Technol, State Key Lab Coal Resources & Safe Min, Xuzhou 221116, Peoples R China. [Zhang, Dongsheng] Xinjiang Univ, Coll Geol & Explorat Engn, Urumqi 830046, Peoples R China. Reprint Address: Zhang, DS (reprint author), China Univ Min & Technol, Sch Mines, Xuzhou 221116, Peoples R China.E-mail Addresses: [email protected]: DISASTER ADVANCES Publisher Address: SECTOR AG-80, SCHEME NO 54, VIJAY NAGAR, A B RD, INDORE, 452010, INDIA Web of Science Categories: Geosciences, Multidisciplinary; Meteorology & Atmospheric Sciences; Water ResourcesResearch Areas: Geology; Meteorology & Atmospheric Sciences; Water ResourcesIDS Number: 244WB ISSN: 0974-262X eISSN: 2278-4543 29-char Source Abbrev.: DISASTER ADV ISO Source Abbrev.: Disaster Adv. Source Item Page Count: 8

Funding:

Funding Agency Grant NumberNational Natural Science Foundation of China 51004101

51264035 Science Foundation for Young Scholars of China University of Mining Technology 2009A001



Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) Fundamental Research Funds for the Central Universities 2012QNA35

We acknowledge the financial support for this work, provided by the National Natural Science Foundation of China (Grant No.51004101, No.51264035), the Science Foundation for Young Scholars of China University of Mining & Technology (Grant No.2009A001), the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), the Fundamental Research Funds for the Central Universities (2012QNA35). The Program for Introduction of Talents of China University of Mining & Technology is also gratefully acknowledged.Record 53 of 58Title: Assessment of data-driven modeling strategies for water delivery canals Author(s): Tavares, I (Tavares, Isaias); Borges, J (Borges, Jose); Mendes, MJGC (Mendes, Mario J. G. C.); Botto, MA (Botto, Miguel Ayala)Source: NEURAL COMPUTING & APPLICATIONS Volume: 23 Issue: 3-4 Special Issue: SI Pages: 625-633 DOI: 10.1007/s00521-013-1417-8 Published: SEP 2013 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Babuska R, 1998, FUZZY MODELING IDENT Babuska R, 1996, CONTROL ENG PRACT, V4, P1593, DOI 10.1016/0967-0661(96)00175-X Baume JP, 1998, IEEE SYS MAN CYBERN, P3856 Borges J, 2011, 18 IFAC WC MIL IT Borges J, 2004, 16 INT S MATH THEOR Borges J, 2005, 16 IFAC WORLD C PRAH Coron JM, 1999, P EUR CONTR C ECC 19 Corriga G, 1997, INT WORK REGULATION, P39 Dash NB, 2010, NEURAL COMPUT APPL, V19, P1251, DOI 10.1007/s00521-010-0360-1 Guo WW, 2012, NEURAL COMPUT APPL, V21, P109, DOI 10.1007/s00521-011-0636-0 Haykin S, 1999, NEURAL NETWORKS COMP KOSKO B, 1994, IEEE T COMPUT, V43, P1329, DOI 10.1109/12.324566 Lemos JM, 2009, NETW HETEROG MEDIA, V4, P303, DOI 10.3934/nhm.2009.4.303 Litrico X, 2005, CONTROL ENG PRACT, V13, P1425, DOI 10.1016/j.conengprac.2004.12.010 LIU FB, 1995, J IRRIG DRAIN E-ASCE, V121, P179, DOI 10.1061/(ASCE)0733-9437(1995)121:2(179) Malaterre PO, 1994, THESIS CNRS CEMAGREF Mandic D. P., 2001, RECURRENT NEURAL NET MATLAB, 2012, NEUR NETW TOOLB REL Murray-Smith R, 1997, MULTIPLE MODEL APPRO, P3 Roubos H, 2002, THESIS TUDELFT DELFT Saraswati S, 2010, NEURAL COMPUT APPL, V19, P919, DOI 10.1007/s00521-010-0419-z Siegelmann HT, 1997, IEEE T SYST MAN CY B, V27, P208, DOI 10.1109/3477.558801 TAKAGI T, 1985, IEEE T SYST MAN CYB, V15, P116 Verdult V, 2002, INT J CONTROL, V75, P1385, DOI 10.1080/0020717021000023807 VERHAEGEN M, 1994, AUTOMATICA, V30, P61, DOI 10.1016/0005-1098(94)90229-1 Voron B, 1997, INT WORKSH REG IRR C, P317 Yilmaz I, 2012, NEURAL COMPUT APPL, V21, P957, DOI 10.1007/s00521-011-0535-4 ZADEH LA, 1965, INFORM CONTROL, V8, P338, DOI 10.1016/S0019-9958(65)90241-XCited Reference Count: 28 Abstract: The aim of this paper is to develop models for experimental open-channel water delivery systems and assess the use of three data-driven modeling tools toward that end. Water delivery canals are nonlinear dynamical systems and thus should be modeled to meet given operational requirements while capturing all relevant dynamics, including transport delays. Typically, the derivation of first principle models for open-channel systems is based on the use of Saint-Venant equations for shallow water, which is a time-consuming task and demands for specific expertise. The present paper proposes and assesses the use of three data-driven modeling tools: artificial neural networks, composite local linear models and fuzzy systems. The canal from Hydraulics and Canal Control Nucleus (A parts per thousand vora University, Portugal) will be used as a benchmark: The models are identified using data collected from the experimental facility, and then their performances are assessed based on suitable validation criterion. The performance of all models is compared among each other and against the experimental data to show the effectiveness of such tools to capture all significant dynamics within the canal system and, therefore, provide accurate nonlinear models that can be used for simulation or control. The models are available upon request to the authors.Accession Number: WOS:000324794200008 Language: EnglishDocument Type: ArticleAuthor Keywords: Nonlinear modeling; Open-channel water delivery systems; Artificial neural networks; Composite local linear models; Fuzzy systemsKeyWords Plus: STATE-SPACE MODELS; IRRIGATION CHANNEL; IDENTIFICATION; SYSTEMSAddresses: [Tavares, Isaias; Botto, Miguel Ayala] Univ Tecn Lisboa, Inst Super Tecn, IDMEC, P-1049001 Lisbon, Portugal. [Borges, Jose] Portuguese Mil Acad, Acad Mil, P-1169203 Lisbon, Portugal. [Mendes, Mario J. G. C.] Polytech Inst Lisbon, Inst Super Engn Lisboa, P-1959007 Lisbon, Portugal. Reprint Address: Borges, J (reprint author), Portuguese Mil Acad, Acad Mil, Rua Gomes Freire, P-1169203 Lisbon, Portugal.E-mail Addresses: [email protected]; [email protected]; [email protected]; [email protected]: SPRINGER Publisher Address: 233 SPRING ST, NEW YORK, NY 10013 USA Web of Science Categories: Computer Science, Artificial IntelligenceResearch Areas: Computer ScienceIDS Number: 223HB ISSN: 0941-0643 29-char Source Abbrev.: NEURAL COMPUT APPL ISO Source Abbrev.: Neural Comput. Appl. Source Item Page Count: 9

Funding:

Funding Agency Grant Numberproject AQUANET-Decentralised and Reconfigurable Control for Water delivery Multipurpose Canal Systems FCT, Portugal Fundacao para a Ciencia e a Technologic, through IDMEC under LAETA

PTDC/EEACRO/102102/2008

Research for this paper was partially supported by project AQUANET-Decentralised and Reconfigurable Control for Water delivery Multipurpose Canal Systems, PTDC/EEACRO/102102/2008, FCT, Portugal, and Fundacao para a Ciencia e a Technologic, through IDMEC under LAETA.Record 54 of 58Title: Analytical derivation of friction parameters for FEM calculation of the state of stress in foundation structures on undermined territories Author(s): Cajka, R (Cajka, Radim)Source: ACTA MONTANISTICA SLOVACA Volume: 18 Issue: 4 Pages: 254-261 Published: 2013 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0



Cited References: [Anonymous], 730039 CSN Asadi A, 2004, J MIN SCI+, V40, P142, DOI 10.1023/B:JOMI.0000047856.91826.76 Balcarek V., 1982, POZEMNI STAVBY Bradac J., 1996, EFFECTS UNDERMINING Cajka R., 2000, MEZ K HORN PRIBR VED Cajka R., IABSE C NEW DELH IND, P551 Cajka R., 2008, 11 E AS PAC C STRUCT, P716 Cajka R., 2005, COST 12 FIN C P 20 2 Cajka Radim, 2013, Advanced Materials Research, V818, DOI 10.4028/www.scientific.net/AMR.818.178 Cajka R., 2013, 6 WSEAS INT C ENG ME Cajka R, 2013, APPL MECH MATER, V300-301, P1127, DOI 10.4028/www.scientific.net/AMM.300-301.1127 Cajka R., 2007, P 11 INT C CIV STRUC, DOI [10.4203/ccp.86.18, DOI 10.4203/CCP.86.18] Cajka Radim, 2013, Advanced Materials Research, V818, DOI 10.4028/www.scientific.net/AMR.818.197 Can E, 2012, ENVIRON EARTH SCI, V66, P2503, DOI 10.1007/s12665-011-1473-2 Chai HB, 2012, APPL MECH MATER, V166-169, P1967, DOI 10.4028/www.scientific.net/AMM.166-169.1967 Cheng G.M., 2014, APPL MECH MATER, V448-453, P3863, DOI [10.4028/www.scientific.net/AMM.448-453.3863, DOI 10.4028/www.scientific.net/AMM.448-453.3863] Cui XM, 2000, INT J ROCK MECH MIN, V37, P615, DOI 10.1016/S1365-1609(99)00125-2 Cui XM, 2013, INT J ROCK MECH MIN, V60, P246, DOI 10.1016/j.ijrmms.2012.12.036 Gayarre FL, 2010, ENG FAIL ANAL, V17, P270, DOI 10.1016/j.engfailanal.2009.06.008 Huayang D., 2002, INT J ROCK MECH MIN, V39, P115, DOI [10.1016/S1365-1609(02)00008-4, DOI 10.1016/S1365-1609(02)00008-4] Janda T, 2013, ADV ENG SOFTW, V62-63, P51, DOI 10.1016/j.advengsoft.2013.04.011 JANULIKOVA M, 2013, PROCEDIA ENG, V65, P284, DOI DOI 10.1016/J.PROENG.2013.09.044 Kalab Z, 2012, ACTA GEOPHYS, V60, P399, DOI 10.2478/s11600-011-0071-8 Marschalko M, 2009, ACTA MONTAN SLOVACA, V14, P232 Marschalko M, 2008, ACTA MONTAN SLOVACA, V13, P58 Mynarcik P., 2013, PROCEDIA ENG, V65, P107, DOI [10.1016/j.proeng.2013.09.019, DOI 10.1016/J.PROENG.2013.09.019] Qi XD, 2013, ADV MATER RES-SWITZ, V734-737, P290, DOI 10.4028/www.scientific.net/AMR.734-737.290 Ren G., 1989, MIN SCI TECHNOL, V8, P235, DOI 10.1016/S0167-9031(89)90393-9 Saeidi Ali, 2013, Geotechnical and Geological Engineering, V31, DOI 10.1007/s10706-013-9633-7 Swift G, 2014, B ENG GEOL ENVIRON, V73, P163, DOI 10.1007/s10064-013-0539-7 Unlu T, 2013, ENG GEOL, V166, P186, DOI 10.1016/j.enggeo.2013.07.014 Woo KS, 2012, INT J ROCK MECH MIN, V53, P166, DOI 10.1016/j.ijrmms.2012.05.008 Xia J.W., 2007, ZHONGGUO KUANGYE DAX, V36, P33Cited Reference Count: 33 Abstract: When calculating the state of stress in a structure caused by relative strain of landscape which is a result of undermining, the structure is often deformed in order to create the specific situation. Each part of the structure resists the strain in a difference way. This depends on places where the structure is in contact with soil environment. When calculating the 3D foundation structures by means of the Finite Element Method (FEM), it is necessary to determine the soil environment resistance. For that purpose, most FEM software applications enable now to enter the friction parameters Clx and CIy. Unlike CIz which resists the structure in the direction perpendicular to the element's plane, these parameters are applied in the central line plane of a slab and rod element.Accession Number: WOS:000343184100006 Language: EnglishDocument Type: ArticleAuthor Keywords: friction parameters; FEM calculation; foundation structuresKeyWords Plus: SURFACE SUBSIDENCE; MINING SUBSIDENCE; PREDICTION; DEFORMATION; INTEGRATION; BUILDINGSAddresses: Tech Univ Ostrava, Dept Struct, Fac Civil Engn, Ostrava 70833, Czech Republic. Reprint Address: Cajka, R (reprint author), Tech Univ Ostrava, Dept Struct, Fac Civil Engn, Ludvika Podeste 1875-17, Ostrava 70833, Czech Republic.E-mail Addresses: [email protected]: BERG FAC TECHNICAL UNIV KOSICE Publisher Address: PARK KOMENSKEHO 19, KOSICE, 043 84, SLOVAKIA Web of Science Categories: Geosciences, Multidisciplinary; Mining & Mineral ProcessingResearch Areas: Geology; Mining & Mineral ProcessingIDS Number: AQ9OC ISSN: 1335-1788 29-char Source Abbrev.: ACTA MONTAN SLOVACA ISO Source Abbrev.: Acta. Montan. Slovaca. Source Item Page Count: 8

Funding:

Funding Agency Grant NumberMinistry of Industry and Trade of the Czech Republic FR-T12/746

This paper has been prepared within the project which has been co-financed from the financial support of the Ministry of Industry and Trade of the Czech Republic, program TIP, project No. FR-T12/746 Rheological sliding joint with thermocontrolled viscoelastic properties.

Record 55 of 58Title: RESULTS FROM DEALING WITH ROCK AND GAS OUTBURST PREVENTION IN THE CZECH REPUBLIC Author(s): Hudecek, V (Hudecek, Vlastimil); Zapletal, P (Zapletal, Pavel); Stonis, M (Stonis, Milan); Sojka, R (Sojka, Radislav)Source: ARCHIVES OF MINING SCIENCES Volume: 58 Issue: 3 Pages: 779-787 DOI: 10.2478/amsc-2013-0054 Published: 2013 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Chlebowski D, 2009, ARCH MIN SCI, V54, P543 Hudecek V., 2010, J MINES METALS FUELS, p[212, 236] Hudecek V., 2010, ACTA MONTAN SLOVACA, V15, P241 Hudecek V., 2003, MINE PLANNING MINING, V2003, P121 Hudecek V., 2009, PROTECTION EMPLOYEES, P129 Hudecek V., 2008, J MIN SCI+, V44, P42 Marschalko M, 2008, ARCH MIN SCI, V53, P397 Prokop P, 2011, INT J MIN MET MATER, V18, P127, DOI [10.1007/s12613-011-0411-3, 10.1007/s12613-201-0411-8] Skoczylas N, 2012, ARCH MIN SCI, V57, P861, DOI 10.2478/v10267-012-0056-8 Wierzbicki M, 2013, ARCH MIN SCI, V58, P21, DOI 10.2478/amsc-2013-0002Cited Reference Count: 10 Abstract: In the Czech Republic, the prevention of rock and gas outbursts is carried out in the course of driving mine workings in seams and in sandstone and conglomerate beds classified into a category with the highest degree of rock and gas outburst hazard. It is a case of active methods that aim at prevention of rock and gas outbursts by creating a protection zone in front of and in sides of mine workings being driven and passive methods that mitigate the effects of outbursts (Hudecek et al., 2009, 2010). In this article, authors present recommendations and proposals for changes in rock and gas outburst prevention. These proposed changes should reflect in increased efficiency in coping with this anomalous geomechanical events.Accession Number: WOS:000327025500013 Language: EnglishDocument Type: Article



Author Keywords: Outburst prevention; coal; gas mixture; gas pressure; boreholesAddresses: [Hudecek, Vlastimil; Zapletal, Pavel] Tech Univ Ostrava, Ostrava 70833, Czech Republic. [Stonis, Milan; Sojka, Radislav] Green Gas DPB, Paskov 73921, Czech Republic. Reprint Address: Hudecek, V (reprint author), Tech Univ Ostrava, 17,Listopadu 15, Ostrava 70833, Czech Republic.Publisher: POLISH ACAD SCIENCES, STRATA MECHANICS RES INST Publisher Address: UL REYMONTA 27, KRAKOW, 30-059, POLAND Web of Science Categories: Mining & Mineral ProcessingResearch Areas: Mining & Mineral ProcessingIDS Number: 252QX ISSN: 0860-7001 29-char Source Abbrev.: ARCH MIN SCI ISO Source Abbrev.: Arch. Min. Sci. Source Item Page Count: 9

Funding:

Funding Agency Grant Numberscience-research project of the Czech Mining Authority 57/07

The article was prepared thanks to support provided by the science-research project of the Czech Mining Authority No. 57/07.

Record 56 of 58Title: MODIFIED STABILITY CHARTS FOR ROCK SLOPES BASED ON THE HOEK-BROWN FAILURE CRITERION Author(s): Nekouei, M (Nekouei, Mahdi); Ahangari, K (Ahangari, Kaveh)Source: ARCHIVES OF MINING SCIENCES Volume: 58 Issue: 3 Pages: 747-766 DOI: 10.2478/amsc-2013-0052 Published: 2013 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Cai M, 2004, INT J ROCK MECH MIN, V41, P3, DOI 10.1016/S1365-1609(03)00025-X COLLINS IF, 1988, INT J NUMER ANAL MET, V12, P533, DOI 10.1002/nag.1610120507 DRESCHER A, 1988, INT J NUMER ANAL MET, V12, P341, DOI 10.1002/nag.1610120307 Hoek E, 2006, PRACTICAL ROCK ENG Hoek E., 1998, B ENG GEOL ENVIRON, V57, P153 Hoek E., 2002, P N AM ROCK MECH S T Hoek E, 1981, ROCK SLOPE ENG Lia A.J., 2008, INT J ROCK MECH MIN, V45, P689 Marinos P., 2004, P RENG S Marinos P., 2004, B GEOLOGICAL SOC GRE, VXXXVI Marschalko M, 2008, ARCH MIN SCI, V53, P397 Rocscience, PHASE2 2D FIN EL SOF Rocscience, 2D LIM EQ AN SOFTW S Russo G, 2009, TUNN UNDERGR SP TECH, V24, P103, DOI 10.1016/j.tust.2008.03.002 Sonmez H, 1999, INT J ROCK MECH MIN, V36, P743, DOI 10.1016/S0148-9062(99)00043-1 SRK and Kani Kavan Shargh Consulting Engineers, 2006, REP PHAS 2 DES SLOP Taylor DW, 1937, J BOSTON SOC CIV ENG, V24, P197 Yang XL, 2004, GEOTECHNIQUE, V54, P543, DOI 10.1680/geot.54.8.543.52014 Yang XL, 2004, INT J NUMER ANAL MET, V28, P181, DOI 10.1002/nag.330 Yang XL, 2006, INT J ROCK MECH MIN, V43, P1146, DOI 10.1016/j.ijrmms.2006.03.010 Zanbak C., 1983, J GEOTECH ENG DIV AS, V190, P1039Cited Reference Count: 21 Abstract: Only an article rendered by Lia et al. in 2008 has represented charts based on Hoek-Brown criterion for rock slopes, however, these charts are not precise and efficient. Because of this problem, a modification is suggested for the mentioned charts in this study. The new charts are calculated according to four methods. Among the methods, one relates to finite element method using Phase2 software. The other three methods are Janbu, Bishop and Fellenius that belong to limit equilibrium method by using Slide software. For each slope angle, the method having high correlation coefficient is selected as the best one. Then, final charts are rendered according to the selected method and its specific equations. Among forty equations, twenty-five ones or 62.5% relate to numerical method and Phase2 software, six ones or 15% belong to Fellenius limit equilibrium, six ones or 15% relate to Bishop limit equilibrium, and three ones or 7.5% belong to Janbu limit equilibrium. In order to validate new charts, slope stability analysis is carried out for several sections of Chadormalu iron ore open pit mine, Iran. The error percentage of new charts in limit equilibrium method using Slide software and in Bishop method for slopes of Chadormalu iron ore mine are rendered and compared. The charts on a basis of Hoek-Brown failure criterion for rock slopes show less than +/- 4% error. This indicates that these charts are appropriate tools and their safety factor is optimal for rock slopes.Accession Number: WOS:000327025500011 Language: EnglishDocument Type: ArticleAuthor Keywords: Stability charts; Rock slopes; Hoek-Brown criterionKeyWords Plus: GSI; STRENGTHAddresses: [Nekouei, Mahdi; Ahangari, Kaveh] Islamic Azad Univ, Sci & Res Branch, Dept Min Engn, Tehran, Iran. Reprint Address: Ahangari, K (reprint author), Islamic Azad Univ, Sci & Res Branch, Dept Min Engn, Tehran, Iran.E-mail Addresses: [email protected]; [email protected]: POLISH ACAD SCIENCES, STRATA MECHANICS RES INST Publisher Address: UL REYMONTA 27, KRAKOW, 30-059, POLAND Web of Science Categories: Mining & Mineral ProcessingResearch Areas: Mining & Mineral ProcessingIDS Number: 252QX ISSN: 0860-7001 29-char Source Abbrev.: ARCH MIN SCI ISO Source Abbrev.: Arch. Min. Sci. Source Item Page Count: 20 Record 57 of 58Title: Prediction of Slope Failures Using Bivariate Statistical Based Index of Entropy Model Author(s): Althuwaynee, OF (Althuwaynee, Omar F.); Pradhan, B (Pradhan, Biswajeet); Mahmud, AR (Mahmud, Ahmad Rodzi); Yusoff, ZM (Yusoff, Zainuddin Md) Book Group Author(s): IEEESource: 2012 IEEE COLLOQUIUM ON HUMANITIES, SCIENCE & ENGINEERING RESEARCH (CHUSER 2012) Published: 2012 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: Alansi A. W., 2009, EUR J SCI RES, V31, P88 Althuwaynee OF, 2012, COMPUT GEOSCI-UK, V44, P120, DOI 10.1016/j.cageo.2012.03.003 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 Bui DT, 2012, CATENA, V96, P28, DOI 10.1016/j.catena.2012.04.001 Constantin M, 2011, ENVIRON EARTH SCI, V63, P397, DOI 10.1007/s12665-010-0724-y Guzzetti F, 2012, EARTH-SCI REV, V112, P42, DOI 10.1016/j.earscirev.2012.02.001 Kojima H., 2000, INT ARCH PHOTOGRA B7, V33, P701



Lee S, 2007, LANDSLIDES, V4, P33, DOI 10.1007/s10346-006-0047-y Oh H. J., 2011, COMPUTERS GEOSCIENCE Oh HJ, 2009, ENVIRON GEOL, V57, P641, DOI 10.1007/s00254-008-1342-9 Pradhan B, 2010, ENVIRON MODELL SOFTW, V25, P747, DOI 10.1016/j.envsoft.2009.10.016 Pradhan B, 2009, INT J PHYS SCI, V4, P1 Pradhan B, 2010, INT J COMPUT INT SYS, V3, P370 Pradhan B, 2010, COMPUT ENVIRON URBAN, V34, P216, DOI 10.1016/j.compenvurbsys.2009.12.004 Pradhan B, 2010, ARAB J GEOSCI, V3, P319, DOI 10.1007/s12517-009-0089-2 Pradhan B, 2010, LANDSLIDES, V7, P13, DOI 10.1007/s10346-009-0183-2 Pradhan B, 2010, ENVIRON ENG GEOSCI, V16, P107 Pradhan B, 2010, ENVIRON EARTH SCI, V60, P1037, DOI 10.1007/s12665-009-0245-8 Pradhan B, 2010, DISASTER ADV, V3, P26 Pradhan B, 2010, IEEE T GEOSCI REMOTE, V48, P4164, DOI 10.1109/TGRS.2010.2050328 Pradhan B, 2010, PHOTOGRAMM FERNERKUN, P17, DOI 10.1127/1432-8364/2010/0037 van Westen CJ, 2006, B ENG GEOL ENVIRON, V65, P167, DOI 10.1007/s10064-005-0023-0 Vlcko W. P., 1980, MINERALIA SLOVACA, V12, P275Cited Reference Count: 23 Abstract: The main objective of this research is to evaluate the spatial prediction of potential slope failures in Kuala Lumpur and surrounding areas using an index of entropy based statistical model. Based on potential information of entropy method (IoE), subjective weights were calculated for fourteen landslide conditioning factors used in this study such as, (slope, aspect, curvature, altitude, surface roughness, lithology, distance from faults, NDVI (normalized difference vegetation index), land cover, distance from drainage, distance from road, SPI (stream power index), soil type and precipitation). A landslide inventory map of the study area was produced using previous reports and aerial photographs interpretation aided with extensive field survey and total of 220 main scarps were identified. Out of this, 153 (70%) landslide locations were used to build the IoE model, while remaining 66 (30%) landslide locations were used for validation purpose. For validation, the area under the curve (AUC) was used to quantify the predictive performance of the employed IoE model. The validation results show that the prediction accuracy of the model is 0.80 (80%) and the success rate equals to 0.81 (81%) that consider fine indicator of the reliability of bivariate model based IoE model employed in this study.Accession Number: WOS:000319211300070 Language: EnglishDocument Type: Proceedings PaperConference Title: IEEE Colloquium on Humanities, Science and Engineering Research (CHUSER) Conference Date: DEC 03-04, 2012 Conference Location: Kota Kinabalu, MALAYSIA Conference Sponsors: IEEE, IEEE Malaysia, IEEE Malaysia Power Elect (PEL), Ind Elect (IE), Ind Applicat (IA) Joint Chapter, IEEE Malaysia Power & Energy ChapterAuthor Keywords: Landslides; Kuala Lumpur; Bivariate model; Index of Entropy; Geographic Information Systems (GIS); Remote SensingKeyWords Plus: NEURAL-NETWORK MODEL; LANDSLIDE SUSCEPTIBILITY ANALYSIS; MALAYSIA; HAZARD; AREA; MAPSAddresses: [Althuwaynee, Omar F.; Pradhan, Biswajeet; Mahmud, Ahmad Rodzi; Yusoff, Zainuddin Md] Univ Putra Malaysia, GISRC, Dept Civil Engn, Fac Engn, Serdang 43400, Selangor Darul, Malaysia. Reprint Address: Pradhan, B (reprint author), Univ Putra Malaysia, GISRC, Dept Civil Engn, Fac Engn, Serdang 43400, Selangor Darul, Malaysia.E-mail Addresses: [email protected]: IEEE Publisher Address: 345 E 47TH ST, NEW YORK, NY 10017 USA Web of Science Categories: Computer Science, Interdisciplinary Applications; Engineering, Electrical & ElectronicResearch Areas: Computer Science; EngineeringIDS Number: BFC85 ISBN: 978-1-4673-4617-7Source Item Page Count: 6 Record 58 of 58Title: ASSESSING THE NATURAL HAZARD OF GULLY EROSION THROUGH A GEOECOLOGICAL INFORMATION SYSTEM (GEIS): A CASE STUDY FROM THE WESTERN CARPATHIANS Author(s): Saksa, M (Saksa, Martin); Minar, J (Minar, Jozef)Source: GEOGRAFIE Volume: 117 Issue: 2 Pages: 152-169 Published: 2012 Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited References: BEDNARIK M., 2009, ENVIRON EARTH SCI, V61, P733 Bednarik M, 2010, PHYS CHEM EARTH, V35, P162, DOI 10.1016/j.pce.2009.12.002 CARRARA A., 1983, MATH GEOL, V5, P403 Carrara A, 1988, P WORKSH NAT DIS EUR, P205 Clerici A, 2002, GEOMORPHOLOGY, V48, P349, DOI 10.1016/S0169-555X(02)00079-X FALTAN V., 2009, MORAVIAN GEOGRAPHICA, V17, P44 Fulajtar E., 2001, VODNA EROZIA PODY PR HARVEY AM, 1987, GEOLOGY, V15, P689, DOI 10.1130/0091-7613(1987)15<689:ROQFST>2.0.CO;2 KLIMENT Z., 2003, GEOMORFOLOGICKY SBOR, V2, P95 LINEBACK M.G., 2001, GEOMORPHOLOGY, V37, P149, DOI 10.1016/S0169-555X(00)00068-4 Minar J, 2003, EKOL BRATISLAVA, V22, P141 MINAR J., 2006, STUDIA GEOMORPHOLOGI, VXL, P61 MINAR J., 1994, ACTA FAC RERUM NAT U, V35, P173 Minar J, 2008, GEOMORPHOLOGY, V95, P236, DOI 10.1016/j.geomorph.2007.06.003 MINAR J., 2009, LANDFORM ANAL, V10, P95 MINAR J., 2009, GEOGRAFICKY CASOPIS, V61, P179 Nachtergaele J, 2002, GEOMORPHOLOGY, V46, P223, DOI 10.1016/S0169-555X(02)00075-2 Nachtergaele J, 1999, EARTH SURF PROC LAND, V24, P693 NATHAN RJ, 1990, J HYDROL, V121, P217, DOI 10.1016/0022-1694(90)90233-N Ouarda TBMJ, 2001, J HYDROL, V254, P157, DOI 10.1016/S0022-1694(01)00488-7 PAUDITS P., 2005, MINERALIA SLOVACA, V37, P529 SAKSA M., 2005, GEOMORPHOLOGIA SLOVA, V2/2005, P30 Stankoviansky M, 2003, CATENA, V51, P223, DOI 10.1016/S0341-8162(02)00167-4 Stankoviansky M., 2003, GEOMORFOLOGICKA ODOZ Valentin C, 2005, CATENA, V63, P132, DOI 10.1016/j.catena.2005.06.001 ZACHAR D., 1960, EROZIA PODYCited Reference Count: 26 Abstract: SAKSA, M., MINAR, J. (2012): Assessing the natural hazard of gully erosion through a Geoecological Information System (GeIS): a case study from the Western Carpathians. Geografie, 117, No. 2, pp. 152-169 (2012). The development of gullies represents a specific type of fluvial erosion that is triggered when surface runoff becomes concentrated during extreme rainfall events. This study investigates a part of the Povazske Valley and Strazovske Mountains in Slovakia to assess the potential susceptibility and gully erosion hazard using a Geoecological Information System (GeIS). The landscape of the area was studied through primary field research and the analysis of secondary materials. The GeIS was then constructed in order to undertake specific multidimensional statistical methods. These were used to assess the potential susceptibly and gully erosion hazard. Those areas with the greatest potential susceptibility occur in Butkovska Furrow and the Podmaninska Hills whilst those with the least potential susceptibility occur in Butkovske Klippes and the Trencianska Upland. The greatest gully erosion hazard was identified on arable land in the Podmaninska Hills and on the river terraces in the Ilavska Basin. It is clear that the majority of the permanent gullies within the study area are controlled by the course of existing anthropogenic linear features such as unpaved field and forest roads and balks in arable land.Accession Number: WOS:000306154000002



Language: EnglishDocument Type: ArticleAuthor Keywords: natural hazard; gully erosion; abiocomplex; multidimensional statistical methods; Geoecological Information System; Western CarpathiansKeyWords Plus: EVOLUTION; LAND; SOILAddresses: [Saksa, Martin] SSCRI, Bratislava 8213 2, Slovakia. [Minar, Jozef] Comenius Univ, Fac Nat Sci, Dept Phys Geog & Geoecol, Bratislava 84215 4, Slovakia. [Minar, Jozef] Univ Ostrava, Fac Sci, Dept Phys Geog & Geoecol, Ostrava 71000, Czech Republic. Reprint Address: Saksa, M (reprint author), SSCRI, Gagarionova 10, Bratislava 8213 2, Slovakia.E-mail Addresses: [email protected]; [email protected]: CZECH GEOGRAPHIC SOC Publisher Address: CHARLES UNIV, DEPT SOC GEOGRAPHY & REGIONAL DEV, FAC SCIENCE, ALBERTOV 6, PRAGUE 2, 128 43, CZECH REPUBLIC Web of Science Categories: GeographyResearch Areas: GeographyIDS Number: 970TA ISSN: 1212-0014 29-char Source Abbrev.: GEOGRAFIE-PRAGUE ISO Source Abbrev.: Geografie Source Item Page Count: 18

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