Fire spot identification based on hotspot sequential pattern and burned area classification

Indonesia is a country with the world's largest tropical peatlands of about 14.9 million hectares that have important roles that support life. Unfortunately, there were many fires in peatlands. In Kalimantan, peatland fires which are characterized by hotspot occurrences reached an average of 25.1% in this decade. According to experts and field forest fire fighters, fire hotspots that appear in a sequence of two to three days at the same location has a high potential of becoming a forest fire. This study aims to determine the sequential patterns of hotspots occurrence, classify satellite image data and identify the fire spot. Fire spot identification was done using hotspots sequences patterns that were overlaid with burned area classification results. Sequential pattern mining using the Prefix Span algorithm was applied to identify sequences of hotspot occurrence. Meanwhile, classification using Maximum Likelihood method was applied to satellite image Landsat 7 to identify burned areas in Pulang Pisau and Palangkaraya Central Kalimantan and Pontianak in West Kalimantan. Furthermore, sequence patterns were overlaid with image classification results. The results show that in Pulang Pisau, 26.19% of sequences patterns are located in burned areas and 72.62% sequence patterns are in the buffer of burned area within a radius of one kilometer. As for Palangkaraya, there are 62.50% sequences patterns are located in burned areas and 87.50% sequence patterns are in the buffer of burned area with the radius of one kilometer. It is concluded that in Pulang Pisau and Palangkaraya there are respectively 72.62% and 87.50% fire hotspots which are strong indicators of peatland fires. © 2018, Seameo Biotrop.
  • Authors: Sitanggang, I.S., Istiqomah, N., Syaufina, L.
  • Author Affiliation: Bogor Agricultural University (IPB)
  • Subjects: peatlands, carbon sinks, forest fire, mapping, satellite imagery, remote sensing
  • Publication type: Journal Article
  • Source: BIOTROPIA-The Southeast Asian Journal of Tropical Biology 25(3): 147-155
  • Year: 2018
  • DOI:
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