* Corresponding Author
Analyzing Burglary Dynamics through Land Use in Selangor, Kuala Lumpur, and Putrajaya: A Space-Time EHSA Approach
https://doi.org/10.22146/ijg.101678 Azizul Ahmad(1), Tarmiji Masron(2*), Syahrul Nizam Junaini(3), Mohd Azizul Hafiz Jamian(4), Mohamad Hardyman Barawi(5), Yoshinari Kimura(6), Norita Jubit(7), Ruslan Rainis(8)
(1) Centre for Spatially Integrated Digital Humanities (CSIDH), Faculty of Social Sciences & Humanities, Universiti Malaysia Sarawak (UNIMAS), 94300 Kota Samarahan, Sarawak, MALAYSIA. Agricultural and Environmental Statistics Division (BPPAS), Department of Statistics Malaysia (DOSM), Federal Government Administrative Centre, Block C6, 62514 Wilayah Persekutuan Putrajaya, MALAYSIA
(2) Centre for Spatially Integrated Digital Humanities (CSIDH), Faculty of Social Sciences & Humanities, Universiti Malaysia Sarawak (UNIMAS), 94300 Kota Samarahan, Sarawak, MALAYSIA
(3) Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, MALAYSIA
(4) Centre for Spatially Integrated Digital Humanities (CSIDH), Faculty of Social Sciences & Humanities, Universiti Malaysia Sarawak (UNIMAS), 94300 Kota Samarahan, Sarawak, MALAYSIA
(5) Faculty of Cognitive Science and Human Development, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, MALAYSIA
(6) Graduate School of Literature and Human Sciences, Osaka Metropolitan University, 3-3-138 Sugimoto, Sumiyoshi-Ku, Osaka 558-8585, JAPAN
(7) Borneo Institute for Indigenous Studies (BorIIS), Universiti Malaysia Sabah (UMS), 88400 Kota Kinabalu, Sabah, MALAYSIA
(8) Institute for Environment and Development (LESTARI), Universiti Kebangsaan Malaysia (UKM), 43600 UKM Bangi, Selangor, MALAYSIA
(*) Corresponding Author
Abstract
In response to the escalating incidence of burglary incidents in rapidly urbanizing metropolitan regions, this study innovatively integrates Emerging Hot Spot Analysis (EHSA) with Space-Time Pattern Mining (STPM) to examine the spatio-temporal dynamics of burglary across Selangor, Kuala Lumpur Federal Territory (KLFT) and Putrajaya Federal Territory (PFT) between 2015 and 2020. This paper aims to delineate the intricate interplay between urban land use configurations and the evolving patterns of burglary, thereby addressing critical research gaps in crime mapping and predictive resource allocation. The research employed robust methodological framework within the ArcGIS Pro 3.1 environment, the research stratifies crime data into four distinct temporal intervals to construct space-time netCDF cubes, applies the Getis-Ord Gi* statistic with False Discovery Rate (FDR) correction to identify statistically significant clusters, and utilizes the Mann-Kendall trend test to classify hotspots into eight categories (new, consecutive, intensifying, persistent, diminishing, sporadic, oscillating, and historical). The results reveal a nuanced spatial clustering of burglary incidents that is significantly influenced by varied land use types—ranging from residential and industrial zones to open spaces—thereby enhancing the granularity of hotspot detection and offering empirical insights into the temporal evolution of crime patterns. The study dinds that the integration of advanced geospatial analyses not only clarifies the complex dynamics between urban morphology and burglary occurrences but also provides a solid empirical basis for informed law enforcement and urban planning strategies. Moreover, these findings underscore the need for ongoing longitudinal investigations and the development of adaptive, data-driven models to refine predictive capabilities further and foster sustainable urban safety initiatives.
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DOI: https://doi.org/10.22146/ijg.101678
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