Environmental indicators combined with risk analysis to evaluate potential wildfire incidence on the Dadu Plateau in Taiwan

Chao-Yuan Lin (), Pei-Ying Shieh, Shao-Wei Wu, Po-Cheng Wang and Yung-Chau Chen
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Chao-Yuan Lin: National Chung Hsing University
Pei-Ying Shieh: National Chung Hsing University
Shao-Wei Wu: National Chung Hsing University
Po-Cheng Wang: National Chung Hsing University
Yung-Chau Chen: National Chung Hsing University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 113, issue 1, No 12, 287-313

Abstract: Abstract Wildfire is a common disaster in the world, and it has a considerable impact on the safety of residents and ecological disturbance. Periodic wildfires are an urgent problem to be solved. This research uses big data from relevant departments to extract environmental indicators that affect wildfires, including satellite images, meteorological observations, and field surveys and establishes a risk model for the Spatio-temporal distribution of wildfires based on risk analysis. Previous studies using Differenced Normalized Burn Ratio (dNBR) to assess fire severity and distinguish wildfire ruins did not deal with the impact of atmospheric humidity on dNBR values. In this study, an adjustable fire threshold was developed to enable dNBR to improve the accuracy of identifying wildfire locations. Regarding the temporal distribution of wildfire risks, environmental vulnerability cannot specifically reflect the frequency of actual wildfires. If the hazard degree is introduced to calculate the wildfire risk, the coefficient of determination can be increased from 0.49 to 0.79. The verification of the village boundary zone depicts that the risk analysis can effectively show the temporal and spatial distribution of wildfire hotspots. On this basis, a village-level wildfire disaster prevention strategy can be formulated.

Keywords: Remote sensing; Principal component analysis; Fire hazard; Fire vulnerability; Normalized burn ratio (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11069-022-05300-3

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