spatial databases and geographic information systems · – douglas/peucker algorithm 1. given:...

Spatial Databases and Geographic Information SystemsSystems

Karl NeumannSarah TauscherInstitut für InformationssystemeTechnische Universität Braunschweighttp://www.ifis.cs.tu-bs.de

1.1 Organizational Issues

1.2 Content and Overview

1.3 Literature

1 Introduction

Spatial Databases and GIS – Karl Neumann, Sarah Tauscher– Ifis – TU Braunschweig 2

http://www.radcyberzine.com/xglobe/earth_2400.jpg

• Lecture

– 23. 10.2009 - 05.02.2010

– 9:45 - 12:00

– Exercises and detours integrated into lecture


Exercises and detours integrated into lecture

– URL: www.ifis.cs.tu-bs.de/ teaching/ws-0910/gis

• 4 Credits


• Exams

– Oral exam

– 08. - 12. 02.2010

– Register at examination office


Register at examination office

– Get an appointment at the Ifis secretariat → Regine Dalkiran


• 2 Spatial Data Modelling

– 2.1 Geometry

– 2.2 Conversion between Vector and Raster Models

– 2.3 Topology


2.3 Topology

– 2.4 Fields

– 2.5 AAA-Project

– 2.6 Operations

– 2.7 Summary


http://skagit.meas.ncsu.edu/~helena/gmslab/interp/F1a.gif

– Spatial object/Geoobject: element to model real world data in geographic information system

– Are described by spatial data (geodata)

– Spatial information: custom-designed spatial data

– Chief difference to “conventional” objects


– Chief difference to “conventional” objects (“What’s so special about spatial?”):

• Geometry

• Topology


– Vector: minimum distance between a point and a line


http://worboys.duckham.org/

– Raster: Distance matrices for distance determination


city block metric chessboard metric Euclidean distance

of cetres

• 3 Mapping of Spatial Data

– 3.1 Properties of Maps

– 3.2 Signatures, Text, Color

– 3.3 Geometric Generalization


3.3 Geometric Generalization

– 3.4 Label and SymbolPlacement

– 3.5 Summary


http://homepage.univie.ac.at/.../Janschitz_Text.pdf

– Challenges

• Projection of the 3D surface on two dimensions (paper, film, screen)

• Selection of the spatial objects and their attributes to be displayed


their attributes to be displayed

• Generalization of geometric andthematic properties (simplify, omit depending on scale)

• Exaggeration and displacement(e.g. river valley with roads and railway lines)


http://maps.google.de/

– Douglas/Peucker algorithm

1. given: polyline L, threshold g

2. determine line between the start and end point of L,

3. determine the point of L that is furthest


3. determine the point of L that is furthest from the line segment

4. if distance > g then the point is significant, repeat procedure for both sub-lines,

otherwise remove all the points between the start and end point of L


http://en.wiki.mcneel.com/

• 4 Spatial Queries

– 4.1 Development of SQL

– 4.2 Core SQL Queries

– 4.3 Spatial Queries and Core SQL


4.3 Spatial Queries and Core SQL

– 4.4 Spatial Extension of theRelational Algebra

– 4.5 Spatial Extensions of SQL

– 4.6 Evaluation of Spatial Queries

– 4.7 Summary


– Query 6: Ids of churches which are located no more than 2 km from a car park

Building(id: string, typeOfUse: String, groundPlan: Polygon)


Fid1(σDistance(Centroid(groundPlan1),

Centroid(groundPlan2))<2000

(σtypeOfUse1=′church′∧typeOfUse2=′car park′

(Building × Building)))


– Therefore evaluation of spatial queries in 2 steps

• Filter step

– Determination of possible hits by evaluation on spatial approximation (lower costs)

• Refinement step


• Refinement step

– Evaluation on accurate geometry only for objects of the filter step


• 5 Spatial Access Methods

– 5.1 Quadtree

– 5.2 R-tree

– 5.3 K-d tree


13

26

11

3

27

29

17

5

4

7

A

B

E

G

J

K5.3 K-d tree

– 5.4 BSP tree

– 5.5 Grid file

– 5.6 Summary


15

23

13

28

24

288

17

9

31

29

18

21

22

A

CD

F

H

G

I

– Problems

• Only suitable for points

• False positives, the solutions supplied by the index have to be verified

• Adequacy depends on the position of the query window


• Adequacy depends on the position of the query window


– Split at a data points or at an arbitrary points

– Choice of split dimension

• Alternating or dimension with the largest extent

– Choice of split position

• Median or average


• Median or average

1

2

2

3

3


12

23

3

12

3

4

56

1

2

34

2

3

• 6 Spatial Data and XML

– 6.1 Standards

– 6.2 XML

– 6.3 GML


6.3 GML

– 6.4 XSLT

– 6.5 SVG

– 6.6 Summary


– Example: a DTD of a city


<!ELEMENT city(name, inhabitants?, area)>


<!ELEMENT city(name, inhabitants?, area)><!ELEMENT name (#PCDATA)><!ELEMENT inhabitants(#PCDATA)><!ELEMENT area(polygon+)><!ELEMENT polygon (point, point, point,

point, point*)><!ELEMENT point(x, y)><!ELEMENT x (#PCDATA)><!ELEMENT y (#PCDATA)>

– Path instruction for complex shapes, lines and areas

• Element’s attributes include the attribute “d” for specifying the points of the path

• Attribute “d” contains further commands for the interpretation of the points


interpretation of the points

• E.g. a point may be the begin or the end of a curve or of a line


<path id="SN4100_einzelsignaturNadelholz"d="M 130 0 L -50 0 0 -180 50 0"fill="none" stroke-miterlimit="20"stroke-linejoin="miter"stroke-width="12" stroke="&baumgrün;"/>

• 7 Application Programming

– 7.1 Connecting SQL with Programming Languages

– 7.2 Postgres and JDBC

– 7.3 Oracle Spatial and JDBC


7.3 Oracle Spatial and JDBC

– 7.4 Processing of GML-based Data

– 7.5 Functional Programmingwith Polygons

– 7.6 Summary


[KGB04]

– For processing geometric attributes the special Java class "JGeometry" is offered

– JGeometry maps the SDO_GEOMETRY data type to a structure (STRUCT)

– Numerous basic methods for accessing spatial


– Numerous basic methods for accessing spatial information are offered, including

• createCircle, createPoint, createLinearPolygon, equals, getDimensions, getElemInfo, getFirstPoint, getJavaPoint, getJavaPoints, getLastPoint, getNumPoints, getOrdinatesArray, getSize, getType, isCircle, isPoint, isRectangle, load, setType, store, toString


– Perimeter of polygons


(define perimeter (lambda (poly)(if (not (null? (trunc-poly poly)))

(+ (point-distance (point1 poly)(point2 poly))

(perimeter (trunc-poly poly)))


(point2 poly))(perimeter (trunc-poly poly)))

0)))

• 8 Architecture of Geographic Information Systems

– 8.1 GIS Hardware and Software

– 8.2 Hybrid vs. Integrated


– 8.2 Hybrid vs. Integrated Systems

– 8.3 Client/Server Systems

– 8.4 Web-based SpatialDatabases

– 8.5 Summary


[SX08]

– Architecture of GIS can be roughly classified

• File based

• Hybrid

• Layer-oriented

• Integrated


• Integrated


– GetCapabilities

• Describes which WFS services are available

• Gives the names of the available feature types

– DescribeFeatureType

• Describes the schema of a feature type


• Describes the schema of a feature type

– GetFeature

• Delivers an instance of a feature

• Supports spatial andnon-spatial selections


<wfs:QuerytypeName="AX_Gebaeude"><ogc:Filter><ogc:PropertyIsEqualTo><ogc:PropertyName>

weitereGebaeudefunktion</ogc:PropertyName><ogc:Literal>1170</ogc:Literal>

</ogc:PropertyIsEqualTo></ogc:Filter>

</wfs:Query>

• 9 GIS Servers and Clients

– 9.1 Classification Characteristics

– 9.2 Servers

– 9.3 Clients


9.3 Clients

– 9.4 Summary


http://www.conterra.de/de/

– Selection of some common GIS Servers

• ESRI

– ArcGIS

– ArcIMS

– ArcSDE


ArcSDE

• GRASS

• Smallworld

• Oracle Spatial

• Postgres, PostGIS


– GIS clients are primarily visualisation tools (map viewer, gis viewer)

– Usually they display spatial data or maps via a web browser

– E.g. the OGC Web Map


– E.g. the OGC Web MapServices are realised

• OGC WMS Viewer company: Intergraph

• mapClient company: con terra

• ArcExplorer WebESRI


http://www.cardogis.com/

• 10 Remote Sensing

– 10.1 Physical Basics

– 10.2 Recording Techniques

– 10.3 Image Processing


10.3 Image Processing

– 10.4 Thematic Classification

– 10.5 Summary


http://saturn.unibe.ch/.../Fotogrammetrie-Bildflug.pdf

– System characteristics

• Recording techniques

– Radiometric resolution

– Geometric resolution

• Platform


• Platform

– Kind of platform

– Altitude

– Orbit

– Period

• Mission

– Temporal coverage

– Spatial coverage


www.atmos.albany.edu/deas/

atmclasses/atm335/history.pdf

www.irs.uni-stuttgart.de

– Example: aerial photo of Braunschweig

• Altitude approximately 1600 m

• Ground resolution 10 cm

• Color reversal film

• Central projection


• Central projection

• 21. April 2005


www.braunschweig.de/.../luftbilder.html

• 11 Location Based Services

– 11.1 Positioning

– 11.2 Car Navigation

– 11.3 Map Matching


11.3 Map Matching

– 11.4 Gazetteer

– 11.5 Privacy

– 11.6 Summary


http://de.wikipedia.org/

– Application examples


Push Services Pull Services

Person-

oriented

Communication A message is pushed to you

asking whether you allow a

friend to locate you

You request from a friend finder

application who is near you

Information You get an alert that a terror You look for the nearest cinema


Information You get an alert that a terror

alarm has been issued by the

city you are in

You look for the nearest cinema

in your area and navigation

instructions to get there

M-Commerce

and Advertising

A discount voucher is being

sent to you from a restaurant

in the area you are in

You look for events happening

in the area you are in

Device-

oriented

An alert is sent to you from

an asset-tracking application

that one of your shipments

has just deviated from its

foreseen route

You request information on

where your truck fleet currently

is located in the country

– Global Positioning System (GPS)

• Enables three dimensional positioning near the earth

• Measuring the runtime of signals between the satellite and the GPS-receiver, from which the distance and the position can be deduced (trilateration)


can be deduced (trilateration)

• The transmitted signal describesa circular sphere centered at thesatellite on whose surface thesignal is received at the sametime → circular baseline ofequal receiving timeson earth


http://www.uni-giessen.de/ilr/frede/

lehrveranstaltungen/MP_51/2.6-GPS.pdf

• 12 Environmental Information Systems

– 12.1 Environmental Data

– 12.2 Collection of Environmental Data

– 12.3 Monitoring Networks


12.3 Monitoring Networks

– 12.4 Laboratory Data

– 12.5 Example: EIS Baden-Württemberg

– 12.6 Summary


http://www.wuz-paderborn.de/

– Applications

• Environmental documentation

• Recording, monitoring

• Biotope cadastre

• Radiation detection


• Radiation detection

• Simulation of environmental

processes

• Environmental compatibility

assessment

• Informing the public


http://www.bec-kommunal.de/

http://www.e-c-o.at

– Example: sensor network on Great Duck Island

• For monitoring of the petrels' breeding in the U.S. state of Maine

• Network of 32 sensor nodes

• 9 nodes in different breeding


• 9 nodes in different breeding caves

• Temperature measurement in the nest (presence of the old birds)

• Additional nodes for measurement of air temperature and humidity and for message forwarding

• Example of peer-to-peer sensor network


http://www.wired.com/

• 13 Review and Outlook

– 13.1 Review

– 13.2 Outlook



http://www-kdd.isti.cnr.it/NWA

• [Al07] → Chap. 10Albertz, J.: Einführung in die Fernerkundung. 3. Aufl., Wissenschaftliche Buchgesellschaft, 2007.

• [Ba05] → Chap. 2, 3

1.3 Literature - Books

• [Ba05] → Chap. 2, 3Bartelme, N.: Geoinformatik – Modelle, Strukturen, Funktionen. 4. Aufl., Springer, 2005.

• [BCCF07] Belussi, A.; Catania, B.; Clementini, E.; Ferrari, E. (Eds.): Spatial Data on the Web – Modeling and Management. Springer, 2007.


• [BCKO08] Berg, M. de; Cheong, O.; Kreveld, M. van; Overmars, M.: Computational Geometry –Algorithms and Applications. 3. Ed. , Springer, 2008.


2008.

• [Be02] → Chap. 4, 5Bernhardsen, T.: Geographic Information Systems –An Introduction. 3. Ed., Wiley, 2002.

• [Br08] Brinkhoff, T.: Geodatenbanksysteme in Theorieund Praxis. 2. Aufl., Wichmann, 2008.


• [Da96] Dadam, P.: Verteilte Datenbanken und Client/Server-Systeme. Springer, 1996.

• [EE04] → Chap. 6.2

Eckstein, R.; Eckstein, S.: XML und


Eckstein, R.; Eckstein, S.: XML und Datenmodellierung. dpunkt.verlag, 2004.

• [Ei02] Eisenberg, J.D.: SVG Essentials. O’Reilly, 2002.


• [Fi05] Fischer-Stabel, P. (Hrsg.): Umwelt-informationssysteme. Wichmann, 2005.

• [Gü98] Günther, O.: Environmental Information


Günther, O.: Environmental Information Systems. Springer, 1998.

• [He06] → Chap. 2, 3, 4Hennermann, K.: Kartographie und GIS – EineEinführung. Wissenschaftliche Buchgesellschaft, 2006.


• [HGM02] → Chap. 2.3, 3

Hake, G.; Grünreich, D.; Meng, L.: Kartographie. 8. Aufl., de Gruyter, 2002.

• [HK06] Herter, M.; Koos, B.: Java und GIS. Wichmann,


Herter, M.; Koos, B.: Java und GIS. Wichmann, 2006.

• [Ka08] Kay, M.: XSLT 2.0 and XPath 2.0 –Programmer’s Reference. 4. Ed., Wrox, 2008.


• [KB01] Kraak, M.-J.; Brown, A. (Eds.): Web Cartography: Developments and Prospects. Taylor & Francis London, 2001.

• [KGB04] → Chap. 7.3


• [KGB04] → Chap. 7.3Kothuri, R.; Godfrind, A.; Beinat, E.: Pro Oracle Spatial. Apress, 2004.

• [KO03] Kraak, M.-J.; Ormeling, F.: Cartography –Visualization of Spatial Data. 2. Ed., Prentice Hall, 2003.


• [KZe07] Korduan, P.; Zehner, M. L.: Geoinformation imInternet. Wichmann, 2007.

• [La05] → Chap. 5.1, 5.2

Lange, N. de: Geoinformatik in Theorie und


Lange, N. de: Geoinformatik in Theorie und Praxis. 2. Aufl., Springer, 2005.

• [LKC08] → Chap. 10

Lillesand, T.; Kiefer, R.; Chipman, J.: Remote Sensing and Image Interpretation. 6. Ed., Wiley, 2008.


• [PA04] Plümer, L.; Asche, H. (Hrsg.): Geoinformation –Neue Medien für eine neue Disziplin. Wichmann, 2004.

• [RSV02]


• [RSV02] Rigaux, P.; Scholl, M.; Voisard, A.: Spatial Databases with Application to GIS. Morgan Kaufmann, 2002.

• [Sa06] → Chap. 5 Samet, H.: Foundations of Multidimensional and Metric Data Structures. Elsevier Science & Technology, 2006.


• [SaS03] → Chap. 7.1

Saake, G.; Sattler, K.-U.: Datenbanken & Java. 2. Aufl., dpunkt.Verlag, 2003.

• [SC03] Shashi, S.; Chawlanjay, C.: Spatial Databases –


Shashi, S.; Chawlanjay, C.: Spatial Databases –A Tour. Prentice Hall, 2003.

• [SV04] Schiller, J.; Voisard, A. (Eds.): Location-Based Services. Morgan Kaufmann, 2004.


• [SX08] Shekhar, S.; Xiong, H. (Eds.): Encyclopedia of GIS. Springer, 2008.

• [UW06] Ueberschär, N.; Winter, A.: Visualisieren von


Ueberschär, N.; Winter, A.: Visualisieren von Geodaten mit SVG im Internet. Wichmann, 2006.

• [WD04] → Chap. 3, 4

Worboys, M.; Duckham, M.: GIS: A Computing Perspective. 2. Ed., CRC Press, 2004.


• [WS06] Wade, T.; Sommer, S. (Eds.): A to Z GIS: An Illustrated Dictionary of Geographic Information Systems. 2. Ed., ESRI, 2006.

• [YB07]


• [YB07] Yeung, A. K.; Brent Hall, G.: Spatial Database Systems. Springer, 2007.


• [Ba08]Baumann, P.: Konzeptuelle Modellierung von Geodiensten. Informatik-Spektrum, Band 31, Nr. 5, 2008, pp. 435–450.

• [Br07]Brinkhoff, T.: Open-Source-Geodatenbanksysteme.

1.3 Literature - Articles

Brinkhoff, T.: Open-Source-Geodatenbanksysteme. Datenbank-Spektrum, Nr. 22, 2007, pp. 37–43.

• [DP73]Douglas, D.H.; Peucker, T.K.: Algorithms for the Reduction of the Number of Points required to represent a digitized Line or its Caricature. The Canadian Cartographer, Jhrg. 10, Heft 2, 1973, pp. 112–122.


• [Gü94]Güting, R.H.: An Introduction to Spatial Database Systems. VLDB Journal, Band 3, Nr. 4, 1994, pp. 357–399.

• [Ne02] → Chap. 7.5

Neumann, K.: Funktionales Programmieren mit Poly-


Neumann, K.: Funktionales Programmieren mit Poly-gonen. Mitteilungen des Bundesamtes für Kartographieund Geodäsie, (MdBKG), Band 22, 2002, pp. 125–136.

• [NE03] → Chap. 6.3

Neumann, K.; Eckstein, S.: Geography Markup Language (GML) – Eine Einführung aus Informatiksicht. MdBKG, Band 24, 2003, pp. 103–111.


• [NGNSW07]Neumann, K.; Grutza, M.; Nordmann, T.; Schlutow, F.; Wolf, C.: Metaautomation der Liegenschaftskarte. MdBKG, Band 39, 2007, pp. 15–29.

• [NKM05]


• [NKM05]Neumann, K.; Kupfer, A.; Mathiak, B.: Umsetzung des Signaturenkataloges SK25 bei der XML-basierten Erzeugung kartenähnlicherGraphiken. MdBKG, Band 34, 2005, pp. 107–118.


• [NKP08] → Chap. 7.4

Neumann, K.; Kupfer, A.; Panse, F.: Generierung von Gebäude-Präsentationsobjekten für NAS-Bestandsdaten-auszüge. In MdBKG, Band 41, 2008, pp. 83–92.

• [NMK04]


• [NMK04] Neumann, K.; Mathiak, B.; Kupfer, A.: Modellierung und kartographischeVisualisierung von Geodaten mit XML-basierten Sprachen. Proc. “Modellierung 2004”, B. Rumpe, W. Hesse (Hrsg.), LNI P-45, 2004, pp. 93–107.


• [NPW06] → Chap. 3.4

Neumann, K.; Petri, J.; Wolf, C.: Erzeugung kartenähnlicherGraphiken: XML-basierteVerdrängung und Platzierungvon Punktsignaturen. MdBKG, Band 36, 2006, pp. 89–98.

• [NSe01]


• [NSe01]Neumann, K.; Selke, M.: Elemente derProgrammiersprache Java vorgestellt an einer Modifikation des Douglas/Peucker-Algorithmus zurErhaltung rechterWinkel. MdBKG, Band 20, 2001, pp. 87–97.


• [PP97]Petzold, I.; Plümer, L.: Platzierung der Beschriftung in dynamisch erzeugten Bildschirmkarten. Nachrichten ausdem Karten- und Vermessungswesen, (NaKaVerm), Reihe I, Nr. 117, 1997, pp. 95–113.


Reihe I, Nr. 117, 1997, pp. 95–113.

• [Se00]Sester, M.: AutomatischeGeneralisierung mittelsAusgleichung. MdBKG, Band 17, 2000, pp. 105–113.


• [Se07]Sester, M.: Generierung von kartographischenPräsentationen im Maßstab 1:25.000 und 1:50.000 mitPUSH und TYPIFY. MdBKG, Band 39, 2007, pp. 93–101.

• [SH95]


• [SH95]Schoppmeyer, J.; Heisser, M.: Behandlung von Geometrie-typwechseln in GIS. NaKaVerm, Reihe I, Nr. 113,1995, pp. 209–224.


spatial databases and geographic information systems · – douglas/peucker algorithm 1. given:...

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