Using remote sensing data to derive built-form indexes to analyze the geography of residential burglary and street thefts
Creators: name: Ioannidis, Ioannis
name: Haining, Robert P.
name: Ceccato, Vania
name: Nascetti, Andrea
Publisher: name: Taylor & Francis
Year: 2024
Subjects: subject: Biotechnology
subject: Environmental Sciences not elsewhere classified
subject: Ecology
subject: FOS: Biological sciences
subject: Sociology
subject: FOS: Sociology
subject: Biological Sciences not elsewhere classified
subject: Inorganic Chemistry
subject: FOS: Chemical sciences
subject: Science Policy
subject: Plant Biology

description: By deploying remotely sensed data together with spatial statistical modeling, we use regression modeling to investigate the relationship between the density of the built environment and two types of crime. We show how the Global Human Settlement Layer (GHSL) data set, which is a measure of building density generated from Sentinel 2A satellite imagery, can be used to create different indexes to describe the built environment for the purpose of analyzing crime patterns for indoor crimes (residential burglary) and open space crimes (street theft). Analysis is at neighborhood level for Stockholm, Sweden. Modeling is then extended to incorporate six planning areas which represent different neighborhood types within the city. Modeling is further extended by adding selected social, economic, demographic and land use variables that have been found to be significant in explaining spatial variation in the two crime categories in Stockholm. Significant associations between the GHSL-based indexes and the two crime rates are observed but results indicate that allowance for differences in neighborhood type should be recognized. Average income and transport hubs were also significant variables in the investigated crime categories. The article provides a practical demonstration and assessment of the use of high-resolution satellite data to examine the association between urban density and two common types of crime and offers reflections about the use of satellite image data in crime analysis. Data Quality and Standardization: Encourage the testing and standardization of methods and measures using remote sensing data, in particular satellite imagery, as a basis for research on urban crime and practical use in urban safety interventions.Open Access to Data: Push for policies that promote open access to remote sensing data in research and practice, especially satellite imagery. This is of particular importance in resource-poor urban environments, especially in countries of the Global South where official statistics are not available or are not regularly updated. Open data, such as the one used in this study, provides evidence, fosters innovation, and is the basis for sustainable urban governance.Evidence-Based Resource Allocation: Highlight the importance of using remote sensing data and methodologies to inform resource allocation decisions in law enforcement agencies. Advocate for policies that prioritize data-driven strategies to address crime concentrations and allocate resources efficiently. Data Quality and Standardization: Encourage the testing and standardization of methods and measures using remote sensing data, in particular satellite imagery, as a basis for research on urban crime and practical use in urban safety interventions. Open Access to Data: Push for policies that promote open access to remote sensing data in research and practice, especially satellite imagery. This is of particular importance in resource-poor urban environments, especially in countries of the Global South where official statistics are not available or are not regularly updated. Open data, such as the one used in this study, provides evidence, fosters innovation, and is the basis for sustainable urban governance. Evidence-Based Resource Allocation: Highlight the importance of using remote sensing data and methodologies to inform resource allocation decisions in law enforcement agencies. Advocate for policies that prioritize data-driven strategies to address crime concentrations and allocate resources efficiently.