AG2414 Spatial Analysis

Course Description This course presents students with the fundamental concepts and advanced techniques of spatial analysis. GIS and statistical techniques are discussed for managing, analyzing and modeling spatial data.  Students will gain practical experience in publicly presenting spatial analysis topics.  This course also intends to prepare students for applying spatial analysis techniques to handle geospatial data in various fields and provide students opportunities to gain practical experience of undertaking GIS projects. The course covers the following topics: Cartographic modelling and Multi-Criteria Evaluation Spatial statistics, interpolation and geographic weighted regression Space syntax and urban morphology Cellular automata and agent-based modeling Exploratory spatial data analysis (ESDA): automated data mining Network and Small World Modeling

The course is composed of lectures, projects and seminars. Each new topic is introduced at a lecture. Associated with the topic is an exercise and a seminar. At the seminar students present relevant articles found in the literature. The students' perfomance during the seminar will be evaluated.

Prerequisites
AG2411 GIS Architecture, or equivalent

5B1501 Probability Theory and Statistics, or equivalent  

Requirements
- Written exam (TEN1; 3 ECTs)
- Approved exercise reports and completed Seminars (LAB1; 4.5 ECTs). 

Bonus points : If you can finish (submit and get approved) ALL the labs before the deadline, you will get 3 bonus points on the final exam. You can submit your report after the deadline, but you won't get any bonus points then. The grade of your seminar participation (3,4,5) are your bonus points.

___________________________________________________________________________ Lecture and Seminar schedule   (Schedule subject to change)
Time	Place	Content		Lecturer
100119 10-12	V33	Introduction to Spatial Analysis		Ban
100120 10-12	V21	Cartographic modelling and Multi-Criteria Evaluation (MCE)		Rangel
100126 10-12	V35	Seminar 1 : Cartographic modelling and MCE Presenters & Opponents (see BILDA)		Vu
100127 10-12	V35	Geostatistics, interpolation and geographic weighted regression		Vu
100209 10-12	V33	Seminar 2 : Geostatistics, interpolation and geographic weighted regression Presenters & Opponents (see BILDA)		Vu
100217 10-12	V21	Space syntax and its extension towards structuring urban street networks		Jiang
100217 13-15	GISlab	Cellular automata and agent-based modeling		Jiang
100223 10-12	V33	Seminar 3: Space syntax Presenters & Opponents (see BILDA)		Vu
100224 10-12	V33	Data Mining		Gidofalvi
100302 10-12	V01	Seminar 4: Cellular automata & agent-based modeling Presenters & Opponents (see BILDA)		Vu
100303 10-12	V21	Network and Small World Modelling (TBC)		Jiang
100309 10-12	V35	Seminar 5 : Data Mining Presenters & Opponents (see BILDA)		Vu
100319 14-18	E51, E52, E53	Exam

___________________________________________________________________________ Laboratory schedule   (Schedule subject to change)
Time	Place	Content	Assistant	Dued
100120 13-17	GISLab	Lab 1: Cartographic Modelling and MCE Using ArcGIS Lab 0: Introduction to Spatial Analysis and MCE Using Idrisi - for all students without prior MCE experience - Intro to Idrisi, Map-Algebra, MCE-Idrisi	Rangel	2010-02-03
100127 13-17	GISLab	Lab 1: Cartographic Modelling and MCE Using ArcGIS	Rangel	2010-02-10
100202 08-12	GISLab	Lab 1: Cartographic Modelling and MCE Using ArcGIS	Rangel	2010-02-10
100203 13-17	GISLab	Lab 2: Interpolation Methods	Rangel	2010-02-17
100210 13-17	GISLab	Lab 2: Interpolation Methods	Rangel	2010-02-17
100217 15-17	GISLab	Lab 3: Space syntax	Rangel	2010-02-24
100224 13-17	GISLab	Lab 4: Simulation using Cellular Automata	Rangel	2010-03-10
100303 13-17	GISLab	Lab 4: Simulation using Cellular Automata	Rangel	2010-03-10
100310 13-17	GISLab	Lab 5: Data Mining	Rangel	2010-03-17

The format for a Lab report is available here

Reading list for seminar 1

Eastman, R. J., Weigen J., Peter A. K., & Toledano, J., (1995). Raster Procedures for Multi-Criteria/Multi-Objective Decisions. Photogrammetric Engineering & Remote Sensing, Vol. 61, No 5. pp 539-547

Reading list for seminar 2

Burrough, P. A. (2001). GIS and Geostatistics: Essential partners for spatial analysis. Environmental and Ecological Statistics, Vol. 8. pp. 361 – 377.

Kriging http://uk.geocities.com/geoecosse/PG1979_pdf.html

Greographically Weighted Regression (GWR) http://ncg.nuim.ie/ncg/GWR/index.htm

Reading list for seminar 3

Batty M. (2001), Exploring isovist fields: Space and Shape in Architectural and Urban Morphology, Environment and Planning B: Planning and Design, 28, 123-150.
(to be emailed)

Jiang B. and Claramunt C. (2002), Integration of Space Syntax into GIS: New Perspectives for Urban Morphology, Transactions in GIS, Blackwell Publishers Ltd, 6(3), 295-309.
(http://www.hig.se/~bjg/Publications.htm)

Jiang B., Claramunt C. and Klarqvist B. (2000), An Integration of Space Syntax into GIS for Modelling Urban Spaces, International Journal of Applied Earth Observation and Geoinformation, 2, 161-171.
(http://www.hig.se/~bjg/Publications.htm)

Reading list for seminar 4

http://en.wikipedia.org/wiki/Cellular_automata

Jiang B. (1999), SimPed: Simulating Pedestrian Flows in a Virtual Urban Environment, Journal of Geographic Information and Decision Analysis, 3(1), 21 - 30.
(http://www.hig.se/~bjg/Publications.htm)

Jiang B. and Gimblett H. R. (2001), An Agent-Based Approach to Environmental and Urban Systems within Geographic Information Systems, in: Gimblett H. R. (ed.), Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Understanding Social and Ecological Processes, Oxford University Press, Oxford, 171 - 190.
(http://www.hig.se/~bjg/Publications.htm)

O'Sullivan, D., and Haklay, M., 2000, Agent-based models and individualism: is the world agent-based?, Environment and Planning A, 32(8), 1409-1425.

Reading list for seminar 5

Demsar, U. (2007), Knowledge Discovery in the Environmental Sciences: Visual and Automatic Data Mining for Randon Problems in Groundwater. Transactions in GIS, 11(2): 255-281.

Miller H. J. (2005), Geographic data mining and knowledge discovery, in: J.P. Wilsonand A. S. Fotheringham (eds.) Handbook of Geographic Information Science, Blackwell.