1st Edition
GIS and Spatial Analysis for the Social Sciences Coding, Mapping, and Modeling
This is the first book to provide sociologists, criminologists, political scientists, and other social scientists with the methodological logic and techniques for doing spatial analysis in their chosen fields of inquiry.
The book contains a wealth of examples as to why these techniques are worth doing, over and above conventional statistical techniques using SPSS or other statistical packages.
GIS is a methodological and conceptual approach that allows for the linking together of spatial data, or data that is based on a physical space, with non-spatial data, which can be thought of as any data that contains no direct reference to physical locations.
Title Page
Table of Contents
Preface
Overview
Section I Introduction to Geocoding and Mapping
How to Make a Pin Map
Why Geocode?
The Basics of Geocoding
Ex: The Process of Geocoding
Ex: The Science and Art of
Interactive Geocoding
Ex: Exporting a Geocoded Map
Thematic Maps
Ex: Creating a Thematic Map from Sample Data
Ex: Racial Profiling Thematic Map
Ex: Juvenile Crime Thematic Map
Summary of Section I
Section II Mapping for Analysis, Policy, and Decision Making
Basic Multivariate Displays
Mapping Rates
Ex: Classification or World Armed Rivalries
Ex: Subsets of Youth Violence
Ex: Maps for School Planning
Ex: Tessellations and Youth Violence
Ex: Rates of Poverty Over Time in New Orleans
Ex: Patterns of Residency by Ethnicity
Ex: Diffusion of Innovation in the United States
(3D map)
Ex: Socioeconomic Conditions in 3D
Ex: Homicide Patterns
Ex: Alcohol Availability and Youth Violence
Ex: Hurricane Katrina’s Impact on Children and Schools
Ex: HIV and Armed National Rivalries
Ex: Immigration and Unemployment in the U.S.
Ex: California Education System
Summary of Section II
Section III Geospatial Modeling and G.I.S.
Why spatial modeling in this book?
Why spatial modeling at all?
The Meaning of Space in Causal Modeling
Measuring the Impact of Space and
Spatial Relationships
Statistical Issues in Spatial Modeling
The Impact of Spatial Autocorrelations and
Error Structures in Spatial Modeling
Statistical Modeling of Spatial Data
Types of Data Used in Spatial Models
Choosing Software to Estimate Spatial Models
Ex: A Cross Sectional Spatial Model: Gang Crime
And Alcohol Availability
Ex: Multi-Site Studies in Spatial Modeling
Ex: Pooled Cross Sectional and Time Series
Spatial Models
Ex: Spatial Models: Limitations, Issues,
And Emerging Developments
Conclusion
References
Appendix 1: GIS Data Sources
Biography
Robert Nash Parker (Ph.D., Duke University) is Co-Director of the Presley Center for Crime and Justice Studies at University of California, Riverside. He has long been interested in the useful application of methods originally pioneered outside of the social sciences (i.e. Structural Equation Modeling (psychology), HLM (education), logistic regression (Economics), ridge regression (chemistry) to the social sciences.
Emily Asencio (Ph.D., University of California, Riverside) is a Post-Doctoral Fellow at the Academic Center for Excellence on Youth Violence Prevention at the University of California, Riverside.
"This is a first-rate book on GIS and spatial analysis. The authors adopt a "learn-by-doing" approach and make it work by combining lucid explanations of concepts and procedures with rich examples. The book will be a valuable resource to students, teachers, and researchers interested in understanding the spatial dimension of social life." –Steven F. Messner, Distinguished Teaching Professor of Sociology, University at Albany, SUNY
"This book is an excellent introduction to the latest tools and techniques for using spatial analyses to study behavior. It is written in a clear and step-by-step fashion with ample illustrations and enables the reader to quickly engage the complex tools of GIS including details concerning appropriate statistical analyses which go well beyond plotting data on maps." –Harold D. Holder, Ph.D., Senior Research Scientist, Prevention Research