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A content analysis of web-based crime mapping in the world's top 100 highest GDP cities

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Crime Prevention and Community Safety Aims and scope

Abstract

The boom of internet technologies, particularly web-based geographic information system (GIS) technologies, is opening new opportunities for use of crime mapping to support crime prevention. The aim of this article is to review the adoption trend of web-based crime mapping in the world's top 100 highest GDP cities and access the current state of the art in the use of web-based crime mapping. We found that the functions provided in web-based crime mapping are less than in most traditional crime mapping software. We conclude that existing works of web-based crime mapping focus on supporting community policing rather than analytical functions such as pattern analysis and prediction. With the current descriptive study, we shed some light on the direction of web-based crime mapping studies. The findings in this article can be treated as a reference for developers, police officers and policymakers to develop, design and implement web-based crime mapping projects.

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Acknowledgements

We thank Rob Mawby, Ken Pease and all the referees of this journal for their helpful comments on an earlier draft of this article.

Author information

Authors and Affiliations

  1. School of Accounting and Finance, The Hong Kong Polytechnic University, Hong Kong

    Kelvin Leong

  2. Department of Computing, The Hong Kong Polytechnic University, Hong Kong

    Stephen C F Chan

Authors
  1. Kelvin Leong
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  2. Stephen C F Chan
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Corresponding author

Correspondence to Kelvin Leong.

Appendices

Appendix A

Table A1

Table A1 The world's top 100 highest GDP cities
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Appendix B

Table B1

Table B1 The 48 identified websites support web-based crime mapping and their links
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Appendix C

Table C1

Table C1 Summary of common geographic information selection approaches
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Appendix D

Table D1

Table D1 Summary of common time information selection approaches
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Appendix E

Table E1

Table E1 Summary of common crime type information selection approaches
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Appendix F

Table F1

Table F1 A summary of map display functions
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Leong, K., Chan, S. A content analysis of web-based crime mapping in the world's top 100 highest GDP cities. Crime Prev Community Saf 15, 1–22 (2013). https://doi.org/10.1057/cpcs.2012.11

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  • DOI: https://doi.org/10.1057/cpcs.2012.11

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