Geographic Information System-Based Analysis to Identify the Spatiotemporal Patterns of Road Accidents in Sri Racha, Chon Buri, Thailand

The road accident rate has been growing in recent years; therefore, an analysis of the road accident hotspots is essential to reduce the number of accidents occurring in high-accident-density areas. Sri Racha district in Chon Buri province was selected as the study area for this research. The accident data of 2012-2017 was collected from the Road Accident Data Center (ThaiRSC). The spatiotemporal pattern of road accidents was clustered into various scales: accidents occurring on weekdays, weekends, daytime, nighttime and those involving fatality and injury. Spatial statistical methods, kernel density estimation (KDE), and Ripley’s K-function in geographic information system (GIS) were applied to identify patterns and the distribution of road accidents. The findings showed that a high density of road accidents was found in three main areas: Sri Racha municipality, Laem Chabang City municipality and Bowin subdistrict. The spatial distribution of all types of road accidents was clustered at various distances. Several agencies can use the results for planning and managing road accident reduction strategies. Furthermore, GIS and spatial statistical methods are effective tools that are quite widely used for accident analysis.

Keywords: Kernel density estimation; Ripley’s K-function; hotspot, spatial pattern; GIS