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All Journal PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Meirisa Putri, Desti
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Computer Science & IT

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Forest and Land Fire Severity Analysis in 2022-2023 in Hulu Sungai Selatan Regency Using the NBR (Normalized Burn Ratio) Method Meirisa Putri, Desti; Refa, Muhammad; Siti Salamah, Sheren; Septi Anggraini, Tania; Himayah, Shafira
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.626

Abstract

Forest and land fires are recurring disasters in Indonesia that cause environmental, health, and socio-economic losses. Hulu Sungai Selatan Regency, South Kalimantan, is among the affected regions, particularly during 2022–2023 when the El Niño phenomenon and flammable peatlands increased fire risk. This study analyzes the spatial extent and severity of fires and their potential impact on local communities by integrating remote sensing and demographic data. The Normalized Burn Ratio (NBR) and Difference Normalized Burn Ratio (dNBR) derived from Landsat 8 and 9 imagery (2021–2023) were used to map fire severity, supported by hotspot data from the Ministry of Environment and Forestry and settlement data from the Geospatial Information Agency. Population data from the Central Bureau of Statistics (BPS) were incorporated to develop a Fire Vulnerability Index (FVI) representing community exposure to fire-prone areas. The results show that burned areas in 2023 expanded compared to 2022, with increasing low to moderate severity classes. Subdistricts with dense populations, such as Kandangan and Angkinang, showed higher fire vulnerability values, indicating potential socio environmental risks. These findings emphasize the importance of integrating remote sensing and statistical data to support effective fire mitigation and risk reduction in vulnerable regions.
Co-Authors Anggraini, Tania Septi Himayah, Shafira Refa, Muhammad Siti Salamah, Sheren