Spatial Databases and Geographic Information Systems€¦ · Spatial Databases and Geographic Information Systems ... element to model real world data in geographic information system

Spatial Databases and

Geographic Information

Systems

Karl Neumann

Sarah TauscherInstitut für Informationssysteme

Technische Universität Braunschweig

http://www.ifis.cs.tu-bs.de

1.1 Organizational Issues

1.2 Content and Overview

1.3 Literature

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

1 Introduction

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

• Lecture

– 29. 10.2010 - 11.02.2011

– 9:45 - 12:00

– Exercises and detours integrated into lecture

– URL:

www.ifis.cs.tu-bs.de/

teaching/ws-1011/gis

• Credits: 4 or 5

(depending on your

course of study)



• Exams

– Oral exam

– 14. -18. 02.2011

– Register at examination office

– Get an appointment

at the Ifis secretariat

→ Regine Dalkiran



• 2 Spatial Data Modelling

– 2.1 Introduction

– 2.2 Geometry

– 2.3 Conversion between Vector and Raster Models

– 2.4 Topology

– 2.5 Fields

– 2.6 AAA-Project

– 2.7 Operations

– 2.8 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

(“What’s so special about spatial?”):

• Geometry

• Topology



http://speedymole.com/Tubes/Paris/

– Vector: minimum distance between a point and a line

– Raster: Distance matrices for distance determination



http://worboys.duckham.org/

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

– 3.4 Label and Symbol

Placement

– 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

• Generalization of geometric and

thematic 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 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

– 4.4 Spatial Extension of the

Relational 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)

πid1(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

– 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

– 5.4 BSP tree

– 5.5 Grid file

– 5.6 Summary



15231523

13 2813 28

24 2824 28

26 1126 11

8 178

179

319

31

3 273

27

29 1829 18

17 5

17 5

21 2221 22

4 74 7

A

C

B

D

F

E

H

G

J

I

K

– 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



– 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

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

– 6.4 XSLT

– 6.5 SVG

– 6.6 Summary



– Example: a DTD of a city



<!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)>

<!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

• 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 fill="none" strokestrokestroke

<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

– 7.4 Processing of GML-

based Data

– 7.5 Functional Programming

with 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

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)

(point2 poly))

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

(+ (point-distance (point1 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

Systems

– 8.3 Clients and Servers

– 8.4 Web-based Spatial

Databases

– 8.5 Summary



[SX08]

– Architecture of GIS can be roughly classified

• File based

• Hybrid

• Layer-oriented

• Integrated



– Selection of some common GIS Servers

• ESRI

– ArcGIS

– ArcIMS

– ArcSDE

• GRASS

• Smallworld

• Oracle Spatial

• Postgres, PostGIS



• 9 Remote Sensing

– 9.1 Physical Basics

– 9.2 Recording Techniques

– 9.3 Image Processing

– 9.4 Thematic Classification

– 9.5 Summary



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

– System characteristics

• Recording techniques

– Radiometric resolution

– Geometric resolution

• 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

• 21. April 2005



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

• 10 Location Based Services

– 10.1 Positioning

– 10.2 Car Navigation

– 10.3 Map Matching

– 10.4 Privacy

– 10.5 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 alarm has been issued by the city you are in

You look for the nearest cinemain 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 shipmentshas 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)

• The transmitted signal describes

a circular sphere centered at the

satellite on whose surface the

signal is received at the same

time → circular baseline of

equal receiving times

on earth



http://www.uni-giessen.de/ilr/frede/lehrveranstaltungen/MP_51/2.6-GPS.pdf

• 11 Environmental Information Systems

– 11.1 Environmental Data

– 11.2 Collection of Environmental Data

– 11.3 Monitoring Networks

– 11.4 Laboratory Data

– 11.5 Example: EIS

Baden-Württemberg

– 11.6 Summary



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

– Applications

• Environmental documentation

• Recording, monitoring

• Biotope cadastre

• 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

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/

• 12 Review and Outlook

– 12.1 Review

– 12.2 Outlook



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

• [Al07] → Chap. 9Albertz, J.: Einführung in die Fernerkundung. 3. Aufl., Wissenschaftliche Buchgesellschaft, 2007.

• [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.


1.3 Literature - Books

• [BCKO08] Berg, M. de; Cheong, O.; Kreveld, M. van;

Overmars, M.: Computational Geometry –

Algorithms and Applications. 3. Ed. , Springer,

2008.

• [Be02] → Chap. 4, 5Bernhardsen, T.: Geographic Information Systems –

An Introduction. 3. Ed., Wiley, 2002.

• [Br08] Brinkhoff, T.: Geodatenbanksysteme in Theorie

und 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

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

Systems. Springer, 1998.

• [He06] → Chap. 2, 3, 4

Hennermann, K.: Kartographie und GIS – Eine

Einführung. Wissenschaftliche Buchgesellschaft,

2006.



• [HGM02] → Chap. 2.4, 3

Hake, G.; Grünreich, D.; Meng, L.: Kartographie.

8. Aufl., de Gruyter, 2002.

• [HK06] 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. 7.3Kothuri, 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 im

Internet. Wichmann, 2007.

• [La05] → Chap. 5.1, 5.2

Lange, N. de: Geoinformatik in Theorie und

Praxis. 2. Aufl., Springer, 2005.

• [LKC08] → Chap. 9

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] 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 –

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

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.



[WS06]

[WS06]

[WS06]

• [Ba08]

Baumann, P.: Konzeptuelle Modellierung von Geodiensten.

Informatik-Spektrum, Band 31, Nr. 5, 2008, pp. 435–450.

• [Br07]

Breunig, M.: Geodatenbankforschung: Rückblick und

Perspektiven aus Sicht der Informatik. Datenbank-Spektrum,

Band 21, Nr. 20, 2007, pp. 5–14.

• [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.


1.3 Literature - Articles

• [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-

gonen. Mitteilungen des Bundesamtes für Kartographie

und 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]Neumann, K.; Kupfer, A.;

Mathiak, B.: Umsetzung des

Signaturenkataloges SK25

bei der XML-basierten Erzeugung kartenähnlicher

Graphiken. 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. MdBKG, Band 41, 2008, pp. 83–92.

• [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 kartenähnlicher

Graphiken: XML-basierteVerdrängung und Platzierung

von Punktsignaturen. MdBKG, Band 36, 2006, pp. 89–98.

• [NSe01]Neumann, K.; Selke, M.: Elemente der

Programmiersprache Java vorgestellt an

einer Modifikation des

Douglas/Peucker-Algorithmus zur

Erhaltung rechter Winkel. MdBKG,

Band 20, 2001, pp. 87–97.



• [PP97]Petzold, I.; Plümer, L.: Platzierung der Beschriftung in

dynamisch erzeugten Bildschirmkarten. Nachrichten aus

dem Karten- und Vermessungswesen, (NaKaVerm),

Reihe I, Nr. 117, 1997, pp. 95–113.

• [Se00]Sester, M.: Automatische

Generalisierung mittels

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

• [TN10]

Tauscher, S.; Neumann, K.: Polygonverschneidung mit SQL. MdBKG, 2010.



• [Br09]Bruchno, S.: Realisierung einer Beispiel-Anwendung mit PostgreSQL, JDBC und geometrischen Datentypen. Studienarbeit, TU Braunschweig, 2009.

• [Bu10]Budgenhagen, B.: Automatische Visualisierung von Quadtrees mit XFig. Studienarbeit, TU Braunschweig, 2010.

• [La09]Latta, C.: Visualisierung der Z-Ordnung realistischer Punktmengen mit XFig. Studienarbeit, TU Braunschweig, 2009.


1.3 Literature – Student Works

• [Ra10]Rath, C.: Visualisierung von unregelmäßig verteilten Messpunkten durch Delaunay-Triangulation mit XFig, CGAL-Methoden und Java. Studienarbeit, TU Braunschweig, 2010.

• [Sp10]Spannknebel, J.: Visualisierung der Splitmöglichkeitenbeim R-Baum. Studienarbeit, TU Braunschweig, 2010.

• [St10]Stachowiak, N.: Greedy- und Delaunay-Triangulation von Polygonen im XFig-Format. Studienarbeit, TU Braunschweig, 2010.


1.3 Literature – Student Works

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Spatial Databases and Geographic Information Systems€¦ · Spatial Databases and Geographic Information Systems ... element to model real world data in geographic information system