Geographic Information Systems and Crime Analysis

IGI Global
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Computerized crime mapping or GIS in law enforcement agencies has experienced rapid growth, particularly since the mid 1990s. There has also been increasing interests in GIS analysis of crime from various academic fields including criminology, geography, urban planning, information science and others. This book features a diverse array of GIS applications in crime analysis, from general issues such as GIS as a communication process and inter-jurisdictional data sharing to specific applications in tracking serial killers and predicting juvenile violence. Geographic Information Systems and Crime Analysis showcases a broad range of methods and techniques from typical GIS tasks such as geocoding and hotspot analysis to advanced technologies such as geographic profiling, agent-based modeling and web GIS. Contributors range from university professors, criminologists in research institutes to police chiefs, GIS analysts in police departments and consultants in criminal justice.
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Additional Information

Publisher
IGI Global
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Published on
Jan 1, 2005
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Pages
345
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ISBN
9781591404552
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Language
English
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Genres
Business & Economics / Business Ethics
Business & Economics / E-Commerce / General
Computers / Computer Graphics
Technology & Engineering / Remote Sensing & Geographic Information Systems
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Content Protection
This content is DRM protected.
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The second edition of a bestseller, Quantitative Methods and Socio-Economic Applications in GIS (previously titled Quantitative Methods and Applications in GIS) details applications of quantitative methods in social science, planning, and public policy with a focus on spatial perspectives. The book integrates GIS and quantitative (computational) methods and demonstrates them in various policy-relevant socio-economic applications with step-by-step instructions and datasets. The book demonstrates the diversity of issues where GIS can be used to enhance the studies related to socio-economic issues and public policy.

See What’s New in the Second Edition:

All project instructions are in ArcGIS 10.2 using geodatabase datasets New chapters on regionalization methods and Monte Carlo simulation Popular tasks automated as a convenient toolkit: Huff Model, 2SFCA accessibility measure, regionalization, Garin-Lowry model, and Monte Carlo based spatial simulation Advanced tasks now implemented in user-friendly programs or ArcGIS: centrality indices, wasteful commuting measure, p-median problem, and traffic simulation

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The book illustrates the range of computational methods and covers common tasks and major issues encountered in a spatial environment. It provides a platform for learning technical skills and quantitative methods in the context of addressing real-world problems, giving you instant access to the tools to resolve major socio-economic issues.

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The second edition of a bestseller, Quantitative Methods and Socio-Economic Applications in GIS (previously titled Quantitative Methods and Applications in GIS) details applications of quantitative methods in social science, planning, and public policy with a focus on spatial perspectives. The book integrates GIS and quantitative (computational) methods and demonstrates them in various policy-relevant socio-economic applications with step-by-step instructions and datasets. The book demonstrates the diversity of issues where GIS can be used to enhance the studies related to socio-economic issues and public policy.

See What’s New in the Second Edition:

All project instructions are in ArcGIS 10.2 using geodatabase datasets New chapters on regionalization methods and Monte Carlo simulation Popular tasks automated as a convenient toolkit: Huff Model, 2SFCA accessibility measure, regionalization, Garin-Lowry model, and Monte Carlo based spatial simulation Advanced tasks now implemented in user-friendly programs or ArcGIS: centrality indices, wasteful commuting measure, p-median problem, and traffic simulation

Each chapter has one subject theme and introduces the method (or a group of related methods) most relevant to the theme. While each method is illustrated in a special case of application, it can also be used to analyze different issues. For example, spatial regression is used to examine the relationship between job access and homicide patterns; systems of linear equations are analyzed to predict urban land use patterns; linear programming is introduced to solve the problem of wasteful commuting and allocate healthcare facilities; and Monte Carlo technique is illustrated in simulating urban traffic.

The book illustrates the range of computational methods and covers common tasks and major issues encountered in a spatial environment. It provides a platform for learning technical skills and quantitative methods in the context of addressing real-world problems, giving you instant access to the tools to resolve major socio-economic issues.

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