ORIGINAL RESEARCH article
Front. For. Glob. Change
Sec. Fire and Forests
Volume 8 - 2025 | doi: 10.3389/ffgc.2025.1577612
This article is part of the Research TopicAdvancements in Fire Management Through Remote Sensing TechnologiesView all 3 articles
Multi-Index Remote Sensing for Post-Fire Damage Assessment: Accuracy, Carbon Loss, and Conservation Implications
Provisionally accepted
- 1National Chung Hsing University, Taichung, Taiwan
- 2Department of Forestry, National Chung Hsing University, Taichung, Taiwan
- 3National Sun Yat-sen University, Kaohsiung, Kaohsiung County, Taiwan
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This study advances environmental management practices by developing a comprehensive multi-index remote sensing methodology for rapid and accurate forest fire impact assessment in protected areas. Applied to the 2021 Yushan National Park fire in Taiwan, the approach integrates three complementary vegetation indices - Normalized Burn Ratio (NBR), Burned Area Index (BAI), and Normalized Difference Vegetation Index (NDVI) - to evaluate pre-fire and post-fire conditions across forest compartments No. 51 and No. 52. The methodology demonstrates significant advantages for protected area management where recreational activities intersect with conservation priorities. The NBR analysis identified 68.89 hectares of burned area with 97.1% accuracy compared to official reports, establishing the method's reliability for rapid damage assessment. NDVI and BAI analyses provided complementary insights, with NDVI effectively detecting 27.99 hectares of completely destroyed vegetation and BAI identifying 17.80 hectares of severely charred areas, both showing statistical significance when validated against ground observations. Through carbon storage analysis, we quantified a loss ranging from seven to eighteen thousand metric tons, demonstrating the approach's capability for environmental impact quantification. The multi-index methodology reveals varying degrees of burn severity across different forest compartments, enabling precise mapping of ecosystem damage patterns. This framework offers a cost-effective, reproducible approach for both immediate impact evaluation and long-term monitoring of forest recovery, supporting evidence-based management decisions in protected areas globally, though local calibration may be required for optimal performance.
Keywords: remote sensing, Forest Fire Impact Assessment, Burn severity mapping, Carbon Loss Estimation, protected areas
Received: 16 Feb 2025; Accepted: 21 May 2025.
Copyright: © 2025 Liu, Liu and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Wan-Yu Liu, National Chung Hsing University, Taichung, Taiwan
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