Introduction of Geoinformatic researches at Yunnan University of Finance and Economics (China)

Chunxue LIUSchool of Urban and Environment, Yunnan University of Finance and Economics, China

Research Introduction

1. Introduction of Yunnan University of Finance and EconomicsYunnan University of Finance and Economics (YUFE) was

founded in 1951, and designated as one of the key provincial

institutions of higher education by Yunnan Provincial

Government in 1995. YUFE is a multi-disciplinary university

which excels in economics and management and also, offers

high-quality programs in philosophy, law, liberal arts, natural

science and engineering. YUFE is located in the north of

Kunming, the province capital of Yunnan, China. Currently,

YUFE has established 19 schools and enrolls about 27 ,000

students in 61 bachelor’s programs, 10 master degrees in first-

class disciplines, 10 doctor degrees in first-class disciplines, and

1 postdoctoral research station (Fig.1) (http://en.ynufe.edu.cn/

index.htm).

Figure 1 . Photos of the main campus of Yunnan University of

Finance and Economics (YUFE) in Kunming City.

2. Geoinformatics Researches at School of Urban and EnvironmentResearches of Geoinformatics at YUFE are carried out in

several schools, covering many fields such as engineering,

management and economics. This article focuses only on the

main researches at School of Urban and Environment (SUE).

SUE, organized in 2007, is originated from the School of

Statistics and Information that was established in 1999. In 2018,

the teaching team of SUE was composed of over 70 faculty

members and the total number of undergraduate and graduate

students enrolled at SUE was around 1,000.

SUE has built virous cooperation with many research

institutions, universities and enterprises for faculty training and

researches. SUE also keeps close research connections with

aboard institutions in the US, Japan, France, Britain and so on.

These years, SUE has obtained research supports from

National Natural Science Foundation of China (NSFC),

local government and enterprises and accomplished many

Geoinformatic researches on natural resources including mineral,

water and land, environments and disasters.

Mineral resource, in particular nonferrous mineral resource,

roles importantly in the regional economic development.

Comprehensive geoinformation analyses and predications have

then developed significant economical mineral exploration

methods. For improving the prediction accuracy, spatial

distributions of ore bodies, lithology and magmatic rocks have

been regarded as comprehensive information sources for the

analyse. Because ore-controlling factors are different in various

mines, Geoinformatic researches should be different depending

on features of mine geology. For example, by considering spatial

changes in semivariogram of ore grade, high accuracy modelling

of ore grade was accomplished for the Yuanjiang gold mine and

Dachang tin mine (Liu et al., 1999; Qin et al., 2001). Another

example is 3D fracture distributions using GEOFRAC that

consists of ordinary kriging, sequential Gaussian simulation, and

principal component analysis to incorporate spatial correlation

structures of locations and directions of sample factures (Koike

et al., 2012 , 2015). GEOFRAC was used in the Gejiu tin

mine, situated in the southeast of Yunnan province (Liu et al.,

2013; Liu et al., 2019: see Figs. 2, 3 and 4). Comprehensive

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information analysis and prediction were mainly based on

information entropy theory to integrate orebody indicator

information and applied to the Gejiu tin mine (Liu et al., 2003).

Figure 2 . Bird view map (A) and stereogram (B) of simulated

fracture networks in the Gaosong field, Gejiu tin mine in

the southeast of Yunnan province, China (Liu et al., 2019).

Figure 3 . Relationship between the geometry of tin orebodies

and simulated continuous fractures that are composed of

160 facets or more (roughly longer than 2 km), coded as

SF1, SF2, SF3, SF4, SF5 and SF6. OX represents the tin

orebody. Dotted lines guide the control of steep fractures

on the vertical displacements of the orebody.

Figure 4 . Digital elevation model (left), large change portions of

slope gradient (middle) and interpreted fractures (right) in

the Gejiu tin mine.

Water resource is indispensable for economic and social

developments. Utilization, management and maintenance of

water resource affects sustainability of the developments. With

large change in water volume in time and space, water quality is

characterized by many factors. Then, Geoinformatic researches

on water resources have focused on space-time multivariate

ordinary cokriging (SPMOK). SPMOK consists of suitable

modeling of semivariograms and cross-semivariograms for

quantifying correlation structures among multivariate and an

extended standardized ordinary cokriging. In addition, a tensor

product cubic smoothing surface method was used for space-time

semivariogram modeling. SPMOK was applied to model the

water quality space-time distribution in Lake Dianchi, situated in

the southwest of Kunming City (Tan et al., 2012; Fig. 5).

Another research example is surface water storage modeling

Figure 5. Distribution map of water quality indicators (COD, TP

and TN) in Jan. 2010 with circles for sample location and

☆ for town.

Figure 6. Temporal change in distribution map of precipitation (mm/

year) in the Cangshan basin, Dali City.

Figure 7. Temporal change in normalized difference vegetation

index (NDVI) distribution in the Cangshan basin.

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using SWAT (Soil and Water Assessment Tool) combined with

geostatistics and remote sensing. SWAT was applied with the

data of precipitation, vegetation interception and soil infiltration

in the Cangshan basin in Dali City, located in the west of

Yunnan province (Liu et al., 2014: Figs. 6 and 7).

LULCC (land-use/land-cover change) greatly affects regional

ecosystem and environment. Modeling and prediction of LULCC

can support land use policy and coordinate sustainable urban

development and ecosystem protection, especially in plateau

lake basins. Remote sensing and GIS techniques have been used

to monitor the dynamics of land use patterns through fractal

dimension from 1974 to 2008 in the Dianchi lake watershed

(Zhang et al., 2013 : Fig. 8). SLEUTH (Slope, Land use,

Excluded, Urban, Transportation, and Hillshade) method was

used to forecast the LULCC pattern changes under six policies

for the urban development based on the LULCC data derived

from remote sensing images in the Dianchi lake watershed

(Zhao et al., 2010). LULCC was also simulated using a GIS

technique from 1990 to 2010 in the Dongchuan district in the

north of Kunming City (Li et al., 2017: Fig. 9). IDRISI software

was used to evaluate land ecological security in the Dali lake

for 16 natural, environmental and landscape indicators (Zhang

et al., 2017). In addition, satellite images of ALOS, SPOT

and Quickbird were applied to evaluate China’s alternative

cultivation policies for replacing poppy to anti-drug, substitution

planting of opium poppy in the north of Laos (Liu et al., 2010).

Natural disasters have widely occurred and destroyed the

economic and society developments in China. Geoinformatic

researches at SUE have also focused on monitoring and

predicting the disaster occurrence and reducing the influences.

RA (Rock Analyst) based dynamics-kinematic analysis under

the ArcGIS platform was built and applied to detect dangerous

zones in the Wenchuan earthquake area, Sichuan Province (Liu

et al., 2012: Fig. 10). Mountain hazard extraction model has

been constructed based on remote sensing data to predict the

hazard areas and applied in Yunnan province (Xu and Liu, 2018)

F ig u re 10 . Ro ck fa l l s i mu la t ion r esu l t fo r t he D uj ia ng ya n-

Wenchuan highway, Sichuan province.

　

Figure 11. Landsat ETM+ original image (left), density slice of

digital number (DN, middle) and extracted debris f low

gullies (right) in Dongchuan district in the north part of

Kunming City.

Figure 8 . Land use classification and its temporal change in the

Dianchi basin in the southwest par t of Kunming City.

Targeted years are 1974, 1988 , 1998 and 2008 from left

to right showing extension of urban area coloured by red.

Figure 9. Temporal change of land use in Dongchuan distr ict in

the north part of Kunming City. Targeted years are 1990,

2000 and 2010 from left to right.

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and the Wenchuan earthquake area (Su et al., 2008: Fig. 11).

Those introduced Geoinformatic researches are mainly

focused on modeling space-time distribution changes in natural

resources and influences from human activities. Since YUFE is

a university dominant at economics and management, all these

studies are aimed to enhance the space-time economics and

management researches and to support the natural resources

policy decisions and supervisions.

3. Concluding RemarksUnder the supports form cooperat ion ins t i tut ions ,

Geoinformatic researches at YUFE-SUE have concentrated to

simulate the space-time distribution changes in natural resources

and environments to support precisely the regional policy

decision and dynamic monitoring, especially in Yunnan province

in the southwest of China.

Towards more precise and comprehensive researches in

the future, Geoinformatic researches at YUFE-SUE will

concentrate furthermore on the process simulation and unified

modeling to support targeted and practical policy decision with

collaborations including faculty member exchanges. For this, to

build more strong connection with world research institutions

is an urgent issue. On the basis of long-term cooperation, more

advanced collaboration and joint researches of Geoinformatics

with Japanese universities are strongly expected.

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Reference Citeshttp://www.ynufe.edu.cn/index.htm

http://www.ynufe.edu.cn/pub/csyhjxy/

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