Applying Spatial Statistics Analysis to Crime Data in the Three Southern Border Provinces of Thailand
Abstract
The purpose of this study is to describe the criminal pattern and density in three southern provinces of Thailand (Yala, Pattani, and Narathiwat) using GIS and spatial analysis. Data on disorderly incidents received by reputable security authorities between 2017 and 2020, including shootings and bombings, arson, violence, and drugs were collected. This study's approach employed spatial statistics, particularly kernel density, to analyze crime patterns-hotspots, criminal periods, and criminal density. Second, the correlation coefficient and regression analysis were performed to determine the association between various factors and crime incidents. 1. The crime scenes were located in similar cluster patterns and repeated criminal areas or in areas close to previously criminal areas, according to the study. 2. According to the analysis of high-risk areas (hot spots), shooting and bombing cases was identified at the Yala Province, Arson and Violence was identified at Pattani and Drug was identified at Narathiwat. 3. In the multiple regression analysis for hypothesis testing, 5 independent variables could predict the number of crimes in Three southern border provinces at the statistical significance level of 0.05. These 5 independent variables were district area size, number of population, population density, number of drop-out students, and number of industrial establishment. When loading all these independent variables into a predictive equation, the multiple correlation coefficient (R) was 0.392 with predictive power (adjusted R square) at 0.362 (36.2%). This means that these 5 factors could predict the number of crimes in Three southern border provinces at 36.2%. The factors with effects of relationship of crime incidents were the number of population and the number of industrial establishments. The results of this study can be utilized for guidelines in criminal prevention and reduction, they are useful for police officers in planning for criminal prevention in Three southern border provinces in Thailand. Keywords : crime mapping ; criminal pattern; GIS; spatial analysis; Thailand's Three southern border provincesReferences
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Mayhew, H., & Binny, J. (2011). The criminal prisons of London: And scenes of prison life. Cambridge University Press.
Ninsri, S. (2014). Resurgence of violence in Southern Thailand. RUSAMILAE JOURNAL, 35(3), 23-36.
Soontorn, N., & HONG, S. (2020). THE KERNEL DENSITY ESTIMATION FOR CRIME ANALYSIS: A CASE STUDY IN THREE PROVINCES SOUTHERN OF THAILAND (master’s thesis). Chon Buri: Burapha University.
Tantiwutthipong, S., Meksangsouy, P., & Sithi, A. (2021). Application of Geographic Information System to Allocate Service Areas of the Rural Road Sub-district. Journal of Letters, 50(1), 136-156.
Tarde, G. (2010). Gabriel Tarde on communication and social influence: Selected papers. University of Chicago Press.
Yiampisan, M., & Srivanit, M. (2010). Using the Kernel Density Estimation surface for criminal pattern: A case study in Phranakhon district, Bangkok. Journal of Architectural/Planning Research and Studies (JARS), 7(1), 87-102.
Bourdieu P. (1984) Distinction: A Social Critique of the Judgement of Taste. London: Routledge & Kegan Paul
Breslin, P. (1999). Getting to know ArcView GIS: the geographic information system (GIS) for everyone.
ESRI, Inc.
Markovic, J. (2007). Book Review: Chainey, S., & Ratcliffe, J.(2005). GIS and Crime Mapping. London: Wiley.(422 pp., $60.00 paperback). Social Science Computer Review, 25(2), 279-282.
Maurizio, G., Paul, L., & Phil, A. (2007). Kernel density estimation and percent volume contours in general practice catchment area analysis in urban areas. GISRUK 2007: Proceedings of the Geographical Information Science Research UK 15th Annual Conference.
Mayhew, H., & Binny, J. (2011). The criminal prisons of London: And scenes of prison life. Cambridge University Press.
Ninsri, S. (2014). Resurgence of violence in Southern Thailand. RUSAMILAE JOURNAL, 35(3), 23-36.
Soontorn, N., & HONG, S. (2020). THE KERNEL DENSITY ESTIMATION FOR CRIME ANALYSIS: A CASE STUDY IN THREE PROVINCES SOUTHERN OF THAILAND (master’s thesis). Chon Buri: Burapha University.
Tantiwutthipong, S., Meksangsouy, P., & Sithi, A. (2021). Application of Geographic Information System to Allocate Service Areas of the Rural Road Sub-district. Journal of Letters, 50(1), 136-156.
Tarde, G. (2010). Gabriel Tarde on communication and social influence: Selected papers. University of Chicago Press.
Yiampisan, M., & Srivanit, M. (2010). Using the Kernel Density Estimation surface for criminal pattern: A case study in Phranakhon district, Bangkok. Journal of Architectural/Planning Research and Studies (JARS), 7(1), 87-102.
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Published
2023-05-24
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Research Article
