GIS-based analysis of spatio-temporal clustering of road traffic accidents in Bangkok Metropolitan Region (BMR), Thailand from 2012 to 2021

• Most of the deaths and injuries resulted from different patterns and clusters of Road Traffic Accidents (RTAs). • The spatio-temporal patterns of RTA hotspots can be identified using the Global Moran’s I index for spatial autocorrelation. • Data from 31,687 RTAs was analyzed across four temporal scales: time of day, week, month, and year (from 2012 to 2021). • Analyzing traffic accidents by severity level revealed a distinct spatial distribution of hotspots, primarily concentrated along highway networks, particularly at junctions and areas with high activity density. • Temporal analysis showed that different time periods affect the nature of RTAs in varying ways, especially during the day, night, and festive seasons. Most fatalities and injuries resulting from Road Traffic Accidents (RTAs) exhibit distinct spatial and temporal patterns which have adverse implications for both regional economies and demographic structures. This study aims to investigate the spatio-temporal distribution of RTA hotspots along the highway network. Using Global Moran’s I spatial autocorrelation, we examined the temporal dynamics of 31,687 RTA records from 2012 to 2021 across four temporal scales: time of day, day of the week, month, and year. The analysis of RTAs by severity levels (fatalities, serious injuries, and minor injuries) revealed clear spatial clustering of hotspot locations. The results demonstrated statistically significant clustering at the 95 % confidence level, indicating that RTAs are not randomly distributed but are concentrated in specific high-risk areas, particularly at highway junctions and in zones of high activity density. In contrast, other areas exhibited more dispersed or varied cluster patterns. Temporal analysis further revealed that accident patterns differ markedly by time period, with notable variations between daytime, nighttime, and festive seasons. These findings offer valuable insights for traffic safety authorities and policymakers in formulating targeted interventions and evidence-based strategies to mitigate road traffic accidents.