GIS for Risk Areas Analysis of Stolen Motorcycles Crime, Mueang Chonburi Police Station, Thailand

Abstract

In 2023, Thailand exhibited the greatest motorbike usage rate on a global scale, as reported by the World Atlas website. The Department of Land Transport, Thailand recorded a total of 22,540,765 registered motorcycles in 2023. Motorcycle users in Thailand encounter the significant problem of vehicular theft. This research focused on the stolen motorcycle crime statistics under the jurisdiction of Mueang Chonburi Police Station, utilizing a dataset spanning five years from 2019 to 2023. This research recommends the implementation of Crime Prevention Through Environmental Design (CPTED) in high-risk areas. The concept of crime prevention in areas characterized by high crime rates or elevated risk factors has the potential to reduce overall crime levels. The objective of this study is to conduct crime analysis utilizing GIS-based methods, using ArcGIS Pro software version 3.0 to analyze the risk areas related to motorbike theft. The risk zones were assessed through spatial statistic analysis, including Global Moran's I approach of spatial autocorrelation and Getis-Ord Gi* statistics. The Inverse Distance Weight (IDW) method was applied to improve the visualization of hot spots. The results of these three techniques indicate that, from 2019 to 2023, Nong Mai Daeng was identified as the highest risk area, with varying degrees of confidence: medium (90% confidence level, Gi* = 1.65–1.96), high (95% confidence level, Gi* = 1.96–2.58), and very high (99% confidence level, Gi* > 2.56). The findings of the analysis are highly valuable and significant for supporting various departments within the Royal Thai Police. Police stations can utilize this information for operational planning and allocating patrollers to local communities.