Spatial Databases and Geographic Information Systems€¦ · Spatial Databases and Geographic...

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

29 1829 18

21 2221 22

4 74 7

– 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

• 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

<path id="SN4100_einzelsignaturNadelholz"d="M 130 0 L fill="none" strokestrokestroke

• 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

• Network of 32 sensor nodes

• 9 nodes in different breeding

• 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,

• [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,

• [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,

• [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,

• [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]

• [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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