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 Spatial Pattern Analysis in a GIS Environment

Description | Agenda |  Participants & Instructors  | Travel & Accommodations

Click for enlarged image.Introduction to Spatial Pattern Analysis
in a GIS Environment

Santa Barbara, CA
6-10 August 2001

Host institution
Center for Spatially Integrated Social Science (CSISS)
University of California
Santa Barbara, CA

Arthur Getis - Workshop Coordinator,
John R. Weeks, and John Kaiser (all of San Diego State University),
and Michael F. Goodchild (University of California, Santa Barbara)

The Workshop
Image of last year's workshop.This workshop focuses on applications of pattern analysis in a Geographic Information Systems environment. It features:

  1. a series of illustrated lectures on both GIS and spatial pattern analysis
  2. exercises demonstrating the principles outlined in the lectures
  3. data exploration based on current projects concerned with spatial patterns relating to various social, behavioral, and economic phenomena.

The workshop lectures will emphasize the fundamental principles and examples of the use of spatial pattern analysis for the help it gives toward the solution of important societal questions. Demonstrating concepts covered in the lectures, exercises will utilize a variety of software tools including ArcView, Point Pattern Analysis, and clustering software. The data exploration portion of the workshop will consist of GIS-based analyses of spatial data related to

  1. the incidences of various crimes within an urban environment
  2. the spread of infectious diseases in the tropics
  3. the diffusion of fertility decline in a third world setting
  4. variables selected by the participants prior to the workshop.

Participants will prepare a final report of their GIS-based analyses.

Workshop Leaders
Art Getis and participants at BBQ.Arthur Getis, Michael Goodchild, John Weeks, and John Kaiser will conduct the workshop.

Professor Getis, San Diego State University, has had a long association with spatial statistics, especially in the area of point pattern analysis. Perhaps his best known work is the collaborative effort in which he has been engaged with Professor J. Keith Ord (Georgetown University) on the development of a series of mainly locally based spatial association statistics.

Professor Goodchild is best known for his work in geographic information systems and digital libraries. He is Professor of Geography at UC Santa Barbara, Director of CSISS, and Associate Director of the Alexandria Digital Library.

Professor Weeks, San Diego State University, is a well-known demographer and author of the standard textbook in the field, now in its 7th edition. Currently he is chair of the Association of American Geographers specialty group on population geography. Professor Weeks has broad experience in the social sciences, having taught in both the Departments of Geography and Sociology at SDSU.

Mr. Kaiser coordinates the remote sensing research activities of the NASA-sponsored Affiliated Research Center program at SDSU and teaches geographic information systems. He has had considerable experience in managing complex environmental programs in the Federal and private sectors.

Pedagogical Goals
Image of last year's workshop.The workshop will be geared toward PhD candidates and young faculty members in the social sciences and health related disciplines. The purposes are not only to inform those new to spatial pattern analysis about its uses, but also to instill in them a fundamental understanding of the importance of spatial thinking and spatial concern. In the spirit of CSISS, we hope to "facilitate intensive cross-fertilization of research ideas…" among a diverse group from fields such as political science, criminal justice, epidemiology, sociology, and anthropology. The workshop will attempt to extend the analytical power of spatial analysis to social science. Participants will be encouraged to bring with them a georeferenced data set in which they have a particular interest. They will be informed beforehand of possible web sites where such data are available. Data will be made available to those without personal data sets. Participants will take part in the development and discussion of a report that they create on the use of spatial pattern analysis.


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