Explore multi-spatiotemporal patterns of burglary crimes in Chicago: 2000-2017

Authors: Jun Luo*, Missouri State University
Topics: Spatial Analysis & Modeling, Geographic Information Science and Systems
Keywords: Burglary crime; Spatiotemporal;GIS;Chicago
Session Type: Paper
Day: 4/7/2019
Start / End Time: 3:55 PM / 5:35 PM
Room: Wilson B, Marriott, Mezzanine Level
Presentation File: No File Uploaded


This research attempts to explore the patterns of burglary crimes at multi-spatiotemporal scales in Chicago between 2000 and 2017. Spatially, census block and police beat area are the two scales the crime occurrences are aggregated into. Each of two spatial scales is combined with three temporal scales: hourly scale with two-hour time step from 12:00am to the end of the day; daily scale with one-day step from Sunday to Saturday within a week; monthly scale with one-month step from January to December. A total of six types of spatiotemporal slices will be created as the base for the analysis. Burglary crimes are spatiotemporally aggregated to spatiotemporal slices based on where and when they occurred. For each type of spatiotemporal slices with burglary occurrences integrated, spatiotemporal neighborhood will be defined and managed in a spatiotemporal matrix. Hot-spot analysis will identify spatiotemporal clusters of each type of spatiotemporal slices. Spatiotemporal trend analysis is conducted to indicate how the clusters shift in space and time. A Web-based 3-D visualization platform will be created to visualize the analysis results. The analysis results will provide helpful information for better target policing and crime prevention policy such as police patrol scheduling regarding times and places covered.


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