Hotspot sebagai indikator dalam mitigasi kebakaran hutan dan lahan. Khusus pada kawasan gambut, risiko dan urgensi dinilai lebih besar dibanding kebakaran konvensional. Penelitian ini bertujuan untuk menganalisis variabilitas spasiotemporal hotspot, serta mengkaji hubungan antara pola sebaran hotspot dengan faktor alami yang mencakup unsur iklim dan tutupan lahan, serta faktor manusia di lahan gambut. Hotspot didapat dari FIRMS NASA selama periode 2015-2022. Data iklim secara kontinu harian diambil dari TerraClimate dengan resolusi 1/24°. Lalu untuk peta skala tahunan, citra TerraClimate untuk data curah hujan dan kelembaban tanah, MODIS untuk LST. Tutupan lahan didapat dari Kementrian Lingkungan Hidup dan Kehutanan yang kemudian diolah dengan proses reklasifikasi dan penerapan trasition matrix. Faktor manusia mencakup jarak hotspot terhadap jaringan parit, jaringan jalan, dan jaringan sungai dilakukan proses buffer untuk melihat tingkat hubungannya dengan hotspot. Metode Emerging Hotspot Analysis (EHA) diterapkan untuk mengidentifikasi pola dan perilaku kebakaran hutan dan lahan gambut. Hasil dari penelitian ini menunjukkan adanya korelasi negatif yang kuat antara hotspot dengan salah satu unsur iklim yaitu kelembaban tanah dan curah hujan, lalu tutupan lahan yang sensitif terhadap kemunculan hotspot paling banyak ada di area rawa dan agrikultur. Berdasarkan output dari EHA, didapat 5 pola, antara lain Sporadic Hotspot, Persistent Hotspot, Consecutive Coldspot, Oscillating Coldspot, dan New Coldspot yang berkaitan dengan keberadaan hotspot, peningkatan dan penurunan hotspot, serta seberapa lama suatu hotspot dan coldspot berada di suatu lokasi.

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Hotspot as an indicator in forest and land fire mitigation. Especially in peatland areas, the risk and urgency are considered greater than conventional fires. This research aims to analyze the spatiotemporal variability of hotspots and investigate the relationship between hotspot distribution patterns and natural factors including climate elements and land cover, as well as human factors in peatland areas. Hotspots were obtained from NASA’s FIRMS during the period 2015-2022. Daily continuous climate data was retrieved from TerraClimate at a resolution of 1/24°. For annual scale maps, TerraClimate imagery was used for rainfall and soil moisture data, MODIS for LST data. Land cover data were obtained from the Ministry of Environment and Forestry, which was then processed through reclassification and transition matrix. Human factors include hotspot distance to ditch networks, road networks, and river networks through the buffer process to assess their correlation with hotspots. The Emerging Hotspot Analysis (EHA) method was applied to identify patterns and behaviors of forest and peatland fires. The result of this study indicates a strong negative correlation between hotspots and one climate element, soil moisture and rainfall, with the most hotspot-sensitive land covers predominantly found in swamp and agricultural areas. Based on the EHA output, 5 patterns were identified, including Sporadic Hotspot, Persistent Hotspot, Consecutive Coldspot, Oscillating Coldspot, and New Coldspot related to hotspot presence, increase and decrease of hotspots, and how long a hotspot and coldspot stayed in a location.