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Introduction to GIS, Thematic Mapping, and Spatial Analysis in Social Science: Research, Teaching and Outreach

Introduction to GIS, Thematic Mapping, and Spatial Analysis in Social Science: Research, Teaching and Outreach. Robert Nash Parker Presley Center for Crime and Justice Studies and Department of Sociology University of California Riverside . GIS: Transform and Enhance Social Research.

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Introduction to GIS, Thematic Mapping, and Spatial Analysis in Social Science: Research, Teaching and Outreach

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  1. Introduction to GIS, Thematic Mapping, and Spatial Analysis in Social Science: Research, Teaching and Outreach Robert Nash Parker Presley Center for Crime and Justice Studies and Department of Sociology University of California Riverside

  2. GIS: Transform and Enhance Social Research • Dissemination and Communication • Classroom; Policy; Scientific Communication • Facilitate Construction of more complex and useful research databases • Ability to link data to context • Combine traditional and Spatial Data • Construct more interesting hypotheses • Spatial Modeling Tools for hypothesis testing in Multivariate Frameworks

  3. Dissemination and Communication • Maps provide visually rich template for data dissemination and presentation • Complex analytical maps can convey multivariate information in a concise manner • Impact of information is enhanced for policy and scientific audiences • Classroom examples are powerful learning tools

  4. Dissemination Example #1: State Capitols • Data has traditionally been displayed in Tables

  5. Using A Map Instead has several advantages • Conveys the information in a visually attractive manner • Shows additional information concerning the spatial relationships that are not easily perceived in table form • Use of Color can enhance the dissemination of the information

  6. Example #1A: State Capitols

  7. Example #1A: State Capitols • Color used to display Census Regions • Map shows spatial relationship among the states • Use of Symbols can further enhance information content and transmission of another variable

  8. Example #2: Classifying Data • Maps can show dramatic differences depending on the classification and subclassification of data • Youth Contacts with Police versus Youth Gang Contacts

  9. Example #2: Classifying Youth Violence-All Youth Police Contacts

  10. Example #2a: Gang Youth Contacts

  11. Example #2a: Classification • Contrast is Sharp on Thematic Map Comparison • Spatial Patterns Immediately and Clearly evident • Additional Detail from Tabular presentation is harder to comprehend in Presentation setting

  12. Example 3: Impact in Presentation and Dissemination-Youth Violence in Riverside 2005

  13. Example 4: Multivariate Information Displayed on the Map: Youth Probation and Youth Violence

  14. Potential to Enhance Scientific Dissemination • Ability to display spatial statistical analyses • Powerful Tools such as animation and Three Dimensional mapping now accessible

  15. Example #5A: Two Dimensional Map of Inequality

  16. Example 5B: 3D Map of Inequality

  17. The Map is the Booby Prize of GIS (J. Dangermond?) • Database capabilities make GIS an effective tool for policy and research • Ability to use Geocoding to combine different data types with common spatial links is the key ability

  18. Example #6: Multiple Sources linked on a single map: City of New Orleans and Katrina Flood Waters

  19. Bringing Multiple Sources Together: Geocoding • Requirements • Address reference data • Events with recorded addresses • GIS software • Patience and Practice

  20. Example 7: Geocodable Events

  21. PIN MAPS MADE EASY

  22. WARS AND INTERNATIONAL RELATIONS

  23. USING SYMBOLS TO ENHANCE THE MAP

  24. COMBINING MAP TYPES FOR ADDED INSIGHT

  25. EXPLORING MULTIPLE DIMENSIONS

  26. Understanding and Testing for Spatial Impact • What are the consequences of Spatially Influenced data? • Variance of estimates is too small • Statistical Tests too large: False Positives • How can you tell if you have Spatially impacted Data? • Calculating Spatial Statistics • Moran’s I; Anselin’s Local Moran I; Getis-Ord Hotspots

  27. Multivariate Spatial Models for Hypothesis Testing • Such models are needed to support research applications of GIS • Database capabilities link different data sources and types to build more useful data and generate more interesting hypotheses and tests

  28. Example #8: Spatial Modeling

  29. Example #8: W or the Connection Matrix

  30. Conclusions • GIS currently used in about 10% of Social Research • A great deal of Enhancement to Social Research is possible with GIS • Dissemination, Class room use, and scientific communications will also be enhanced • Software should become more user friendly as capabilities recognized and demand increases

  31. IMAGES FROM: GIS and Spatial Analysis for the Social Sciences: Coding, Mapping, and Modeling ROBERT NASH PARKER EMILY K. ASENCIO Routledge Press, 2008

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