Open AccessAnalyzing Rainfall and Greenness Vegetation Level on Forest/Land Fire Area in Jambi and Central Kalimantan Provinces using Remote Sensing Data
Author(s) -
Khalifah Insan Nur Rahmi,
Indah Prasasti,
Jalu Tejo Nugroho,
M. Rokhis Khomaruddin
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/893/1/012067
Subject(s) - hotspot (geology) , environmental science , normalized difference vegetation index , geography , vegetation (pathology) , physical geography , remote sensing , leaf area index , ecology , geology , medicine , biology , pathology , geophysics
El-Nino, which occurred in 2019 in Indonesia, caused longer dry conditions than usual. Low rainfall and vegetation drought cause widespread forest/land fires. This study aims to know the relationship between drought conditions and forest/land fires from the parameters of rainfall and vegetation greenness level. The study located in Jambi and Central Kalimantan Provinces during the peak months of fires which is September 2019. To see fluctuations in the peak of fires, eight daily data were taken for this period. Extraction of rainfall information is derived from the Himawari-8 infrared band L1 image into L2 rainfall rate data. Vegetation greenness level information is derived from Terra/Aqua MODIS red and near-infrared band images into L2 Enhance Vegetation Index (EVI) data. Hotspot data comes from the images of Terra, Aqua MODIS, SNPP VIIRS, and NOAA20. Fire data was extracted from hotspot data and delineation of MODIS RGB image smoke. Rainfall fluctuation affects the number of forest/land fire hotspots. The decrease in rainfall was followed by an increase of hotspot numbers and vice versa. In Jambi Province, rainfall decreased in first to second period i.e. 40 to 0 mm was followed by an increase of hotspot number which dominated by high confidence level. In Central Kalimantan rainfall increased from third to fourth period i.e. 0 to 100-400 mm followed by the decreasing of hotspot number which dominated by medium confidence level. Meanwhile, the TKV variable had little effect on the number of hotspots but related with rainfall data. In Central Kalimantan Province, the driest TKV (0.1) on September 14-21, 2019, was influenced by low rainfall in the previous period which also has highest number of fire hotspots. In Jambi Province, the driest TKV happened on third period which also the result of lowest rainfall and highest number of fire hotspot in the previous period.