FOREST FIRE DETECTION BASED ON GOOGLE EARTH ENGINE SEBANGAU NATIONAL PARK

Sebangau National Park, a peatland conservation area, is particularly vulnerable to forest fires. These conflagrations are most prevalent during the dry season. The objective of this research is to detect and analyze burned areas in Sebangau National Park using the Google Earth Engine (GEE) platform. The analysis will utilize Landsat 8 satellite imagery from 2015. The methods employed for detecting areas that have undergone combustion include the utilization of Normalized Burn Ratio (NBR) and Normalized Difference Vegetation Index (NDVI) indices. The analysis reveals that the burned area, as determined by the NBR index, encompasses 27,567.92 hectares. When assessed using NDVI, the burned area increases to 35,163.44 hectares. The accuracy assessment reveals that the NDVI index exhibits an Overall Accuracy (OA) value of 97.71% and Kappa Accuracy (KA) of 81.46%, which exceeds the NBR by 0.07% and 1.24%, respectively. This finding highlights the enhanced precision of NDVI in detecting vegetation changes resulting from fire events. Consequently, NDVI can serve as a crucial reference point in post-fire mitigation and rehabilitation efforts within peat conservation areas.

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Publication Details

Journal
Jurnal Belantara
Published
2025-08-14
DOI
https://doi.org/10.29303/jbl.v8i2.1143
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
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article

FOREST FIRE DETECTION BASED ON GOOGLE EARTH ENGINE SEBANGAU NATIONAL PARK

Beni Iskandar, Sari Marlina, Afifah Kiki Dwi Wulandari
Jurnal Belantara
Data Mining and Machine Learning Applications
article

FOREST FIRE DETECTION BASED ON GOOGLE EARTH ENGINE SEBANGAU NATIONAL PARK

Beni Iskandar, Sari Marlina, Afifah Kiki Dwi Wulandari
article en

Abstract

Sebangau National Park, a peatland conservation area, is particularly vulnerable to forest fires. These conflagrations are most prevalent during the dry season. The objective of this research is to detect and analyze burned areas in Sebangau National Park using the Google Earth Engine (GEE) platform. The analysis will utilize Landsat 8 satellite imagery from 2015. The methods employed for detecting areas that have undergone combustion include the utilization of Normalized Burn Ratio (NBR) and Normalized Difference Vegetation Index (NDVI) indices. The analysis reveals that the burned area, as determined by the NBR index, encompasses 27,567.92 hectares. When assessed using NDVI, the burned area increases to 35,163.44 hectares. The accuracy assessment reveals that the NDVI index exhibits an Overall Accuracy (OA) value of 97.71% and Kappa Accuracy (KA) of 81.46%, which exceeds the NBR by 0.07% and 1.24%, respectively. This finding highlights the enhanced precision of NDVI in detecting vegetation changes resulting from fire events. Consequently, NDVI can serve as a crucial reference point in post-fire mitigation and rehabilitation efforts within peat conservation areas.

Jurnal BelantaraVol. 8(2)
Universitas Muhammadiyah Palangkaraya (ID)
Openalex Percentile: Top 68%
Data Mining and Machine Learning Applications
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FOREST FIRE DETECTION BASED ON GOOGLE EARTH ENGINE SEBANGAU NATIONAL PARK — Beni Iskandar, Sari Marlina, et al. · Jurnal Belantara (2025) | TGRS Research Map | TGRS