Pemodelan Distribusi Spasial Hotspot di Kabupaten Banjar Menggunakan Log-Gaussian Cox Process

Abstract

Forest and land fires are recurring ecological and socio-economic disasters in Banjar Regency, South Kalimantan Province, with complex triggers. A deep understanding of the spatial distribution of fire risk is crucial for effective mitigation efforts. This study aims to model the spatial intensity of hotspots as a proxy for forest and land fires events in Banjar Regency and produce a fire risk surface map. The data used in this study are hotspot data from the siPongi website in Banjar Regency for the period 2013–2024, along with elevation data analyzed using the Log-Gaussian Cox Process (LGCP) spatial statistical model. The analysis results show that elevation has a negative but statistically insignificant effect on hotspot intensity, where fire risk tends to be higher at lower elevations. The LGCP model proved effective in capturing the complex spatial patterns of hotspot occurrences, separating trends driven by covariates and residual spatial clustering. The resulting risk intensity map successfully identified high-risk clusters, particularly concentrated in western districts dominated by peatlands and agricultural activities.