Open Access

ARTICLE

Forest Fire Severity Level Using dNBR Spectral Index

Nur Nabihah Ghazali¹, Noraain Mohamed Saraf^1,*, Abdul Rauf Abdul Rasam^1,*, Ainon Nisa Othman¹, Siti Aekbal Salleh¹, Nurhafiza Md Saad²

1 School of Geomatics Science and Natural Resources, College of Built Environment, Universiti Teknologi MARA, Shah Alam Campus, Shah Alam, 40450, Selangor, Malaysia
2 School of Geomatics Science and Natural Resources, College of Built Environment, Universiti Teknologi MARA, Arau Campus, Arau, 02600, Perlis, Malaysia

* Corresponding Authors: Noraain Mohamed Saraf. Email: ; Abdul Rauf Abdul Rasam. Email:

Revue Internationale de Géomatique 2025, 34, 89-101. https://doi.org/10.32604/rig.2025.057562

Received 21 August 2024; Accepted 24 January 2025; Issue published 24 February 2025

Abstract

Forest fires are contributing significantly to the acceleration of deforestation. Monitoring and mapping these fires are crucial, and remote sensing technology has proven effective for this purpose. This research employs remote sensing methods to evaluate the severity of a forest fire in Kampung Balai Besar, Dungun. The incident, covering a 23-hectare area, occurred on 15 June 2021. Initial data processing utilized Sentinel-2 satellite images from 14 June 2021 (pre-fire) and 19 June 2021 (post-fire). The extent and severity of the fire were assessed using the Normalized Burn Ratio (NBR) index derived from satellite images. Different levels of burn severity were classified based on the extracted NBR, and classes of the calculated index value were generated accordingly. The severity level and intensity of the burn were analyzed using the Difference Normalized Burn Ratio (dNBR) index. This spectral index aided in assessing the severity of the forest fire in Kampung Balai Besar. The findings revealed that 13.9% of the area experienced low severity burns, 47.2% had moderate to high severity burns, and 38.9% exhibited high severity burns. In summary, areas with moderate to high and high severity burns showed more significant damage, while unburned areas displayed higher vegetation productivity. The study successfully identified the burned area in Kampung Balai Besar, providing valuable information for early decision-making and effective forest management planning.

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Keywords

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