Spatiotemporal Analysis of Fire Hotspots and PM2.5 in Riau, Jambi, and South Sumatra

Abstract

Forest and land fires in Indonesia significantly degrade air quality by increasing PM2.5 concentrations. This study examines the spatiotemporal patterns of fire hotspot distribution and estimated PM2.5 concentrations in Riau, Jambi, and South Sumatra Provinces during August–October 2023. MODIS fire hotspot data were analyzed using the ST-DBSCAN algorithm with defined spatial distance, temporal distance, and minimum point parameters to identify fire clusters. PM2.5 concentrations were estimated by converting MODIS Aerosol Optical Depth (AOD) using an empirical model. The results demonstrate that ST-DBSCAN effectively identifies fire hotspot clusters, with the highest cluster density observed in South Sumatra Province. The average estimated PM2.5 concentrations were 50.51 µg/m³ in Riau, 48.16 µg/m³ in Jambi, and 41.59 µg/m³ in South Sumatra. The highest PM2.5 levels occurred in Riau Province in October, exceeding the World Health Organization air quality guideline. These findings reveal a strong spatiotemporal association between fire activity and elevated particulate pollution and highlight the potential of this approach to support environmental and health risk assessments related to wildfire events.