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All Journal International Journal of Remote Sensing and Earth Sciences (IJReSES) Jurnal Penginderaan Jauh Indonesia
Rahmi, Khalifah Insan Nur
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Engineering Environmental Science

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Pemanfaatan Data Sentinel-2 untuk Analisis Indeks Area Terbakar (Burned Area) Rahmi, Khalifah Insan Nur; Febrianti, Nur
Jurnal Penginderaan Jauh Indonesia Vol 2 No 1 (2020)
Publisher : Masyarakat Ahli Penginderaan Jauh Indonesia (MAPIN) /Indonesian Society of Remote Sensing (ISRS)

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Abstract

The Use of Sentinel-2 Image to Analysis Burned Area Index Burned area mapping can be extracted from remote sensing imagery using burned area index. Various indices have been developed to identify burned areas including NBR, NBR2, MIRBI, and BAIS2. This study aims to determine the index that best distinguishes burning and non-burning areas in the detailed scale of small fires. Burned areas were identified from the delta index before and after the fire. Date of Sentinel-2 image before fires on May 1, 2019, after fires on September 8, 2019. The NBR index uses the comparison of SWIR and NIR band, the NBR2 and MIRBI indexes use the comparison of SWIRL and SWIRS band, while the BAIS2 index plays the red-edge spectral range, NIR, and SWIR. The result of the separability index analysis shows that the MIRBI index is good for distinguishing burned areas from bare land. The NBR index is good at distinguishing burned areas from vegetation and built-up land while the NBR2 index is good at distinguishing smoked burned areas from vegetation and built-up land.
HOTSPOT VALIDATION OF THE HIMAWARI-8 SATELLITE BASED ON MULTISOURCE DATA FOR CENTRAL KALIMANTAN Rahmi, Khalifah Insan Nur; Sulma, Sayidah; Prasasti, Indah
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 16, No 2 (2019)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1112.862 KB) | DOI: 10.30536/j.ijreses.2019.v16.a3293

Abstract

The Advanced Himawari Imager (AHI) is the sensor aboard the remote-sensing satellite Himawari-8 which records the Earth’s weather and land conditions every 10 minutes from a geostationary orbit. The imagery produced known as Himawari-8 has 16 bands which cover visible, near infrared, middle infrared and thermal infrared wavelength potentials to monitor forestry phenomena. One of these is forest/land fires, which frequently occur in Indonesia in the dry season. Himawari-8 can detect hotspots in thermal bands 5 and band 7 using absolute fire pixel (AFP) and possible fire pixel (PFP) algorithms. However, validation has not yet been conducted to assess the accuracy of this information. This study aims to validate hotspots identified from Himawari images based on information from Landsat 8 images, field surveys and burnout data. The methodology used to validate hotspots comprises AFP and PFP extraction, determining firespots from Landsat 8, buffering at 2 km from firespots, field surveys, burnout data, and calculation of accuracy. AFP and PFP hotspot validation of firespots from Landsat-8 is found to have higher accuracy than the other options. In using Himawari-8 hotspots to detect land/forest fires in Central Kalimantan, the AFP algorithm with 2km radius has accuracy of 51.33% while the PFP algorithm has accuracy of 27.62%.
Co-Authors Febrianti, Nur Indah Prasasti, Indah Sayidah Sulma, Sayidah