Crime mapping and spatial data analysis using R
Author(s)
Bibliographic Information
Crime mapping and spatial data analysis using R
（Statistics in the social and behavioral sciences series）（A Chapman & Hall book）
CRC Press, 2023
1st ed
- : hbk
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Note
Includes bibliographical references (p. 407-420) and index
Description and Table of Contents
Description
Materials tested over three years with several cohorts of students at different levels (UG and PGT), based on experiences teaching these materials to professional crime analysts, and developed by researchers with over 20 year experience teaching crime mapping.
Very practical and embedded integration of criminological, spatial statistics, and cartographic concepts with the focus placed on lay understanding and development of intuition for 'professional/applied research' practice rather than in mathematical formulation and proof.
Moves away from heavy US focus of competing alternatives. Datasets and examples used come from a variety of national contexts (including the US) which should broaden its appeal.
Table of Contents
1. Producing your First Crime Map 2. Basic Geospatial Operations in R 3. Mapping Rates and Counts 4. Variations of Thematic Mapping 5. Basics of Cartographic Design: Elements of a Map 6. Time Matters 7. Spatial Point Patterns of Crime Events 8. Crime Along Spatial Networks 9. Spatial Dependence and Autocorrelation 10. Detecting Hot Spots and Repeats 11. Spatial Regression Models 12. Spatial Heterogeneity and Regression 13. Appendix: A Quick Intro to R and RStudio 14. Appendix B: Regression Analysis (A Refresher) 15. Appendix C: Sourcing Geographical Data for Crime Analysis
by "Nielsen BookData"