Geospatial Clustering of Psychotropic Substances Crime Locations

The worldwide prevalence of drug overdose and the misconception on psychotropic substances lead to the increased incidents of drug use disorders, drug offences and environmental harms along with financial burden on local and federal government for drug control and prevention. As a small step to reduce drug-related offences, we analyze the data sets consisting of drug- or alcohol-related crime incidents to discover temporal and seasonal patterns of such crimes. More importantly, we employ a density-based clustering algorithm to find a natural grouping of the geographic locations of crime incidents based on their longitude and latitude information. By visualizing such clusters with major crime types for each cluster, we allow residents and public safety officers to easily identify hot spots of drug-related crimes and hence develop new prevention plans to cope with drug-related crimes.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-16
DOI
https://doi.org/10.5281/zenodo.16964388
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

Geospatial Clustering of Psychotropic Substances Crime Locations

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Geospatial Clustering of Psychotropic Substances Crime Locations

article en

Abstract

The worldwide prevalence of drug overdose and the misconception on psychotropic substances lead to the increased incidents of drug use disorders, drug offences and environmental harms along with financial burden on local and federal government for drug control and prevention. As a small step to reduce drug-related offences, we analyze the data sets consisting of drug- or alcohol-related crime incidents to discover temporal and seasonal patterns of such crimes. More importantly, we employ a density-based clustering algorithm to find a natural grouping of the geographic locations of crime incidents based on their longitude and latitude information. By visualizing such clusters with major crime types for each cluster, we allow residents and public safety officers to easily identify hot spots of drug-related crimes and hence develop new prevention plans to cope with drug-related crimes.

Zenodo (CERN European Organization for Nuclear Research)
Utah State University (US), Bridgend College (GB)
Good health and well-being
Openalex Percentile: Top 59%
Geochemistry and Geologic Mapping
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