Spatial Analysis of Forest Fire Hotspots in Kalimantan Using Inhomogeneous Neyman-Scott Cluster Area

Forest and land fires in Kalimantan pose a serious environmental challenge with significant impacts on ecosystems, public health, and the achievement of the Sustainable Development Goals (SDGs). In recent years, fire intensity has increased due to the combined effects of human activities, peatland characteristics, and extreme climate conditions associated with El Niño. Spatial analysis shows that fire hotspots are unevenly distributed, with a strong concentration in peatland areas. This study applies the Inhomogeneous Neyman–Scott Cluster Process (NSCP) to model the spatial clustering of hotspots under heterogeneous conditions by incorporating covariate information. The objective is to identify hotspot distribution patterns in Kalimantan during 2022–2024 and to generate fire risk maps to support targeted mitigation and environmental management policies. Model comparison using the Akaike Information Criterion (AIC) indicates that the Thomas Cluster Process with distance to BPBD facilities as a covariate provides the best fit, with the lowest AIC value (-456,944.7). The results reveal a negative relationship between distance to BPBD facilities and hotspot intensity, indicating that fire occurrences decrease with increasing distance. These findings confirm that hotspot distribution in Kalimantan is not random and highlight the importance of spatially informed fire management strategies.