Understanding crime patterns using spatial data analysis
Case studies in Stockholm, Sweden
Time: Fri 2024-10-25 09.00
Location: Kollegiesalen, Brinellvägen 8, Stockholm
Video link: https://kth-se.zoom.us/s/66904913390
Language: English
Subject area: Planning and Decision Analysis, Urban and Regional Studies
Doctoral student: Ioannis Ioannidis , Urbana och regionala studier
Opponent: Professor Lin Liu, University of Cincinnati
Supervisor: Professor Vania Ceccato, Urbana och regionala studier; Associate Professor Andrea Nascetti, Geoinformatik
QC 241002
Abstract
Understanding the complex relationship between urban environments and crime is crucial for effective urban planning and crime prevention strategies. Spatial analytical methods have provided valuable knowledge into crime patterns, enabling the detection of crime-concentrated environments and informing law enforcement operations and urban planning interventions. The international literature highlights the increasing use of remote sensing in crime analysis, driven by improved data availability and accuracy. Given the potential of this approach, this thesis investigates the use of spatio-temporal data analyses, particularly the incorporation of remote sensing data along with traditional socio-demographic and land use indicators in understanding the dynamics of crime in urban environments. Four crime categories—cannabis-related crimes, street theft, residential burglaries, and sexual crimes—are investigated using Stockholm City in Sweden as a case study. Remote sensing data, particularly very high-resolution imagery, combined with machine learning algorithms, such as the Random Forest classifier, facilitate the prediction of crime risk areas and the identification of environmental factors associated with crime occurrences. While the thesis reflects upon the advantages and disadvantages of using remote sensing in crime analyses, findings offer practical insights for policymakers, urban planners, and law enforcement agencies, enabling the development of data-informed strategies to foster safer and more resilient urban environments.