Forest and Land Fire Severity Analysis in 2022-2023 in Hulu Sungai Selatan Regency Using the NBR (Normalized Burn Ratio) Method

Authors

  • Desti Meirisa Putri Department of Geographic Information Science, Indonesia University of Education, Jalan Dr. Setiabudhi No. 229, Bandung 40154, Indonesia
  • Muhammad Refa Department of Geographic Information Science, Indonesia University of Education, Jalan Dr. Setiabudhi No. 229, Bandung 40154, Indonesia
  • Sheren Siti Salamah Department of Geographic Information Science, Indonesia University of Education, Jalan Dr. Setiabudhi No. 229, Bandung 40154, Indonesia
  • Tania Septi Anggraini Department of Geographic Information Science, Indonesia University of Education, Jalan Dr. Setiabudhi No. 229, Bandung 40154, Indonesia
  • Shafira Himayah Department of Geographic Information Science, Indonesia University of Education, Jalan Dr. Setiabudhi No. 229, Bandung 40154, Indonesia

DOI:

https://doi.org/10.34123/icdsos.v2025i1.626

Keywords:

dNBR (Differenced Normalized Burn Ratio), Forest and Land Fires, Hulu Sungai Selatan, Landsat, NBR (Normalized Burn Ratio)

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.

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Published

2025-12-22

How to Cite

Meirisa Putri, D., Refa, M., Siti Salamah, S., Septi Anggraini, T., & Himayah, S. (2025). Forest and Land Fire Severity Analysis in 2022-2023 in Hulu Sungai Selatan Regency Using the NBR (Normalized Burn Ratio) Method. Proceedings of The International Conference on Data Science and Official Statistics, 2025(1), 391–411. https://doi.org/10.34123/icdsos.v2025i1.626