Material by Gilberto Câmara, General Director of Brazil’s National Institute for Space Research (INPE) from December 2005 to December 2009
Initial version given at International Postgraduate Course on Geoinformation, Universitat Jaume I, Castelló (Spain), June 2004.
Revised version given at English Semester Program 2005/2006, Institute for Geoinformation, University of Muenster, Germany, September 2005.
Reading Material
Spatial data analysis: a primer, by G. Câmara, A. Monteiro, S. Druck. M.Carvalho.
Spatial data analysis of areas, by G. Câmara, M.Carvalho.
Presentations
Course Outline.
Introduction to Spatial Data Analysis.
Areas I: Rate Smoothing and the MAUP.
Areas II: Exploratory Spatial Analysis.
Areas III: Regression.
Surfaces: Variogram and Kriging
Introduction to R statistical language
Geostatistics with gstat
Interfacing Spatial Statistics and GIS
Laboratory Exercises
Lab 1. Smoothing Rates with GeoDA
Use the GeoDa workbook, exercise 13 and 14.
Data for this exercise is Ohio lung cancer data.
Lab 2. Spatial Autocorrelation with GeoDA
Use the GeoDa spatial autocorrelation tutorial.
Data for this exercise is North Carolina SIDS data and the St Louis crime data.
Lab 3. Spatial Regression using GeoDA
Use the GeoDa workbook, exercises 22 and 24.
Data for these exercises is Columbus crime data and the US Southern county homicides 1960-1990.
Examinations
Exam 1. Spatial Analysis of Areas
Questions and the Rio infant mortality data set .
GIS Software for Spatial Analysis used in the course
GeoDa. Software for Exploratory Spatial Data Analysis (You need to create a username and a password to download GeoDa).
A good GeoDa tutorial can be found here.
R statistical tools R is an open source language and environment for statistical computing and graphics.
A good introduction to R can be found here.
TerraView. Open source software by INPE, includes tools for exploratory spatial data analysis.
See installations instructions here.
Free and Gratis GIS Software for Spatial Analysis
SPRING. Free GIS software by INPE, includes geostatistical tools and exploratory spatial data analysis.
Variowin. Software for variogram analysis and modeling by Yvan Pannatier, Switzerland.
CrimeStat. Spatial statistics program for the analysis of crime incident locations.
Additional References
Bailey, T.; Gatrell, A. “Interactive Spatial Data Analysis”. London, Longman Scientific and Technical, 1995.
(Very good reference book).
“Spatial point pattern analysis and its application in geographical epidemiology”.
AC Gatrell, T Bailey, P Diggle, B Rowlingson, Transactions Inst British Geographers, 21, 1996.
“A review of spatial statistical techniques for location studies”.
Roger Bivand, Norwegian School of Economics and Business Administration, 1988.
GIS and Geostatistics: Spatial Analysis of Chernobyl’s Consequences in Belarus.
Konstantin Krivoruchko, ESRI, USA.
Mapping Social Exclusion/Inclusion in Developing Countries: Social Dynamics of São Paulo in the 90′s.
G. Câmara, A. Monteiro, F. Ramos, A. Sposati, D. Koga.
In: D. Jonelle, M. Goodchild (eds.) Spatially-Enabled Social Science: Examples in Best Practice. Oxford University Press, 2004.
“GIS, Users, Developers, and Spatial Statistics: On Monarchs and Their Clothing”,
Konstantin Krivoruchko, Roger Bivand. StatGIS 2003, Portschach, Austria
