geoda (2006) - Geographical Analysis ISSN 0016-7363 GeoDa:...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
GeoDa : An Introduction to Spatial Data Analysis Luc Anselin 1 , Ibnu Syabri 2 , Youngihn Kho 1 1 Spatial Analysis Laboratory, Department of Geography, University of Illinois, Urbana, IL, 2 Laboratory for Spatial Computing and Analysis, Department of Regional and City Planning, Institut Teknologi, Bandung, Indonesia This article presents an overview of GeoDa TM , a free software program intended to serve as a user-friendly and graphical introduction to spatial analysis for non- geographic information systems (GIS) specialists. It includes functionality ranging from simple mapping to exploratory data analysis, the visualization of global and local spatial autocorrelation, and spatial regression. A key feature of GeoDa is an interactive environment that combines maps with statistical graphics, using the technology of dynamically linked windows. A brief review of the software design is given, as well as some illustrative examples that highlight distinctive features of the program in applications dealing with public health, economic development, real estate analysis, and criminology. Introduction The development of specialized software for spatial data analysis has seen rapid growth as the lack of such tools was lamented in the late 1980s by Haining (1989) and cited as a major impediment to the adoption and use of spatial statistics by geographic information systems (GIS) researchers. Initially, attention tended to focus on conceptual issues, such as how to integrate spatial statistical methods and a GIS environment (loosely versus tightly coupled, embedded versus modular, etc.), and which techniques would be most fruitfully included in such a framework. Familiar reviews of these issues are represented in, among others, Anselin and Getis (1992); Goodchild et al. (1992); Fischer and Nijkamp (1993); Fotheringham and Rogerson (1993, 1994); Fischer, Scholten, and Unwin (1996); and Fischer and Getis (1997). Today, the situation is quite different, and a fairly substantial collection of spatial data analysis software is readily available, ranging from niche programs, customized scripts and extensions for commercial statistical and GIS packages, to a Correspondence: Luc Anselin, Department of Geography, University of Illinois, Urbana- Champaign, Urbana, IL 61801 e-mail: [email protected] Submitted: January 1, 2004. Revised version accepted: March 10, 2005. Geographical Analysis 38 (2006) 5–22 r 2006 The Ohio State University 5 Geographical Analysis ISSN 0016-7363
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
burgeoning open-source effort using software environments such as R, Java, and Python. This is exemplified by the growing contents of the software tools clearing house maintained by the U.S.-based Center for Spatially Integrated Social Science (CSISS). 1
Background image of page 2
Image of page 3
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 02/15/2012 for the course GEO 6938 taught by Professor Staff during the Summer '08 term at University of Florida.

Page1 / 18

geoda (2006) - Geographical Analysis ISSN 0016-7363 GeoDa:...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online