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This book surveys the evolution, current state and future of crime mapping with geographic information systems technology. Covers methods from such areas as epidemiology and location-allocation analysis, and their application to spatial analysis of crime data.

eingereicht von Michael Leitner ; Literaturverzeichnis: Blatt 70-73 ; Diplomarbeit Paris-Lodron-Universität Salzburg 2021 ; Abstract/Zusammenfassung in deutscher und englischer Sprache

"This book provides an overview of why geography is important in the investigation of health, the importance of the main components of a GIS, how important neighborhood context is when using a GIS, and the general differences found between urban and rural health environments"--Provided by publisher

We examined published maps containing sensitive data, and the protection methods, if any, that were used. We investigated whether the many published warnings about disclosure risk have been effective in reducing privacy risk. During an 8-year period (2005-2012), 19 journals related to GIScience, geography, spatial crime analysis, and health geography were examined. We identified 41 articles that display actual confidential information and 16 articles where confidential information is protected by the use of a geographical mask. During the investigated time frame, the numbers of articles with unmasked confidential data increased, and in total more than 68,000 home addresses were disclosed. One of the more significant findings of this study is that efforts to instill sensitivity to location privacy and disclosure risk have been relatively unsuccessful.

As a Windows-based application, GeoDa 0.9.5-i is now much more user-friendly compared to its predecessor, the SpaceStat package and its Arc View Extension, DynESDA. GeoDa provides some very useful tools for doing exploratory spatial data analysis, including dynamically linked windows and data brushing. As a stand-alone program, it has a variety of options for data manipulation and transformation, mapping, exploratory spatial data analysis, spatial weights construction, descriptive statistics, spatial autocorrelation statistics, ordinary least squares (OLS) regression with spatial diagnostics, and spatial regression modeling.

This research proposes cartographic guidelines for presenting confidential point data on maps. Such guidelines do not currently exist, but are important for governmental agencies that disseminate personal data to the public because these agencies have to balance between the citizens' right to know, and preserving a citizen's right to privacy.In an experiment, participants compared an original point pattern of confidential crime locations with the same point pattern being geographically masked. Ten different masking methods were tested. The objective was to identify appropriate geographic masking methods that preserve both the confidentiality of individual locations, and the essential visual characteristics of the original point pattern. The empirical testing reported here is a novel approach for identifying various map design principles that would be useful for representing confidential point data on a map.The results of this research show that only two of the ten masking methods that were tested yield satisfactory solutions. The two masking methods include aggregating point locations at either (1) the midpoint of the street segment or (2) at the closest street intersection. The cartographic guidelines developed from this research suggest a combination of both masking strategies. Future research should focus on the refinement and further testing of these, and other alternative masking methods.