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

บทคัดย่อ

In 2023, Thailand exhibited the greatest motorbike usage rate on a global scale, as reported by the World Atlas website. Specifically, over 87% of Thailand's population resorted to motorcycles as their primary mode of transportation. The Transportation Department of Thailand recorded a total of 22,540,765 registered motorcycles in 2023. Motorcycle enthusiasts in Thailand encounter the pervasive challenge of vehicular theft, alongside the predicaments above. This research focused on the stolen motorcycle crime statistics under the jurisdiction of Mueang Chonburi Police Station, utilizing a dataset spanning five years. The theft rate in 2023 demonstrates a notable upward trend in comparison to the preceding four years. To mitigate motorcycle theft in high-risk areas, it is recommended to employ Geographic Information Systems (GIS) and Photogrammetry approaches to analyze the areas associated with these criminal activities. The concept of crime prevention in areas characterized by high crime rates or elevated risk factors holds the capacity to reduce overall crime levels. This research recommends the implementation of diverse dimension methods that prioritize Crime Prevention through Environmental Design (CPTED) as a means to address this crime and achieve the goal of "Zero Tolerance" in high-risk areas.

The first objective of this study is to conduct crime analysis utilizing GIS-based methods. Using ArcGIS Pro software to analyze the risk areas related to motorbike theft. The risk zones are assessed using Global Moran's I approach of spatial autocorrelation and Getis-Ord Gi* statistics. The Inverse Distance Weight (IDW) method is used to improve the depiction of hot spots. Enhancing the understanding of crime-prone environments and facilitating the implementation of Crime Prevention through Environmental Design (CPTED) can be achieved by overlaying police red box checkpoints and land use with risk zones. The results of the two techniques indicate that from 2019 to 2023, Nong Mai Daeng is identified as the highest risk area with varying degrees of confidence: medium (with a 90% confidence level, Gi* = 1.65 -1.96), high (with a 95% confidence level, Gi* = 1.96-2.58), and very high (with a 99% confidence level, Gi* > 2.56). The land use of Khlong Tamru, which is adjacent to Nong Mai Daeng, has a significant impact on Nong Mai Daeng. This area is identified as the second highest risk by at least two methodologies annually. The predominant land use in Nong Mai Daeng and Khlong Tamru consists of industrial, village, and city-town-commercial areas. According to crime data from 2019 to 2023, the land use type of village exhibited the highest incidence of motorcycle theft, followed by city-town-commercial and institutional land.

The final aim is to address the issue of motorcycle theft by campaigning for the Thai government to publicly endorse and authorize the adoption of electric bicycles (e-bikes) as a viable substitute for traditional motorcycles to reduce stolen motorcycle crime in Thailand. The findings of the analysis are highly valuable and significant in providing help to many departments within the Royal Thai Police, particularly about the concept of crime prevention. Police stations can be utilized for operational planning. The allocation of patrollers to the local community. Patrol police must possess a comprehensive understanding of crime hot spots