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Spatiotemporal Analysis of Nighttime Crimes in Vienna, Austria
Topics: Geographic Information Science and Systems
, Temporal GIS
, Europe
Keywords: Crime, GIS, spatiotemporal, Austria Session Type: Virtual Paper Abstract Day: Monday Session Start / End Time: 2/28/2022 02:00 PM (Eastern Time (US & Canada)) - 2/28/2022 03:20 PM (Eastern Time (US & Canada)) Room: Virtual 26
Authors:
Jiyoung Lee, Louisiana State University
Michael Leitner, Louisiana State University
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Abstract
Although many crime studies have considered a spatiotemporal period, few studies have conducted a time scope between daytime and nighttime. These studies used data that do not fully reflect the real world, such as simply using the real streetlight intensity or estimating the streetlight intensity through modeling. However, nighttime crimes are not only influenced by streetlights, but also by other socioeconomic factors, such as population, education, occupation, income, and the brightness of surrounding areas or shops. Thus, the detailed objectives of this study are to 1) analyze the correlation between nighttime crimes and brightness values of nighttime satellite image that include streetlights, power consumptions, 2) examines the correlation between socioeconomic indicators and nighttime crimes, and 3) predict crime hotspot using different algorithms: Geographically Weighted Regression (GWR) and Convolutional Neural Network (CNN) algorithms. Through this process, we found the nighttime criminal characteristics in Austria from 2014 to 2019.
Spatiotemporal Analysis of Nighttime Crimes in Vienna, Austria
