Volume IV-4/W2
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W2, 193-198, 2017
https://doi.org/10.5194/isprs-annals-IV-4-W2-193-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W2, 193-198, 2017
https://doi.org/10.5194/isprs-annals-IV-4-W2-193-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  20 Oct 2017

20 Oct 2017

MULTI-SPATIOTEMPORAL PATTERNS OF RESIDENTIAL BURGLARY CRIMES IN CHICAGO: 2006-2016

J. Luo J. Luo
  • Department of Geography, Geology and Planning Missouri State University, USA

Keywords: Spatiotemporal pattern, Spatiotemporal slice, Spatiotemporal weight, GIS, Getis-Ord Gi*, Burglary, Chicago

Abstract. This research attempts to explore the patterns of burglary crimes at multi-spatiotemporal scales in Chicago between 2006 and 2016. Two spatial scales are investigated that are census block and police beat area. At each spatial scale, three temporal scales are integrated to make spatiotemporal slices: 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. 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.