Citation

Imran S, Khan MR, Hussain SE, Tahir MN, Karim S. J. Islam. Ctries. Soc. Stat. Sci. 2022; 8(1): 327-360.

Copyright

(Copyright © 2022, Islamic Countries Society of Statistical Sciences)

DOI

unavailable

PMID

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Abstract

After 9/11, terrorism, especially suicide attacks, became uncontrollable and drastically impacted the world. The capability to proactively react against a potential suicide attack remained a challenge for law enforcement agencies. There is a dire need to develop a geospatial model that can cope with this problem. The main objective of this study is to develop an automated geospatial model to analyze suicide attacks in any spatiotemporal environment. A geospatial model named as "Suicide Attack Assessment Model" (SAAM) was developed using Python Scripting and an ArcGIS environment. A user-friendly interface can be used under one platform without any prior knowledge of GIS and will be available for users and researchers. SAAM was applied to Pakistan as a case study. The results indicate that suicide attacks have partially spread across the country, particularly in Khyber Pakhtunkhwa (KPK) Province and Federally Administrated Tribal Areas (FATA). Moreover, SAAM predicted hotspots for suicide attacks on a more fine-grained geographical unit. Meanwhile, it shows that SAAM combined with geospatial techniques has excellent potential for simulating the risk of suicide attacks from simple spatial distribution to choropleth maps, raster analysis, complex statistical relationships development, and advanced geostatistical research in any space and time on a single click.

Language: en