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Analysing Fire Propagation Models
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Orientador(es)
Resumo(s)
With increasing wildfire severity and duration driven by climate change, accurately predicting fire behavior over extended time frames is critical for effective management and mitigation of such wildfires. Fire propagation models play a pivotal role in these efforts, providing simulations that can be used to strategize and respond to active fires. This study examines the fire area simulator (FARSITE) model’s performance in simulating recent wildfire events that persisted over 24 h with limited firefighting intervention in mostly remote access areas across diverse ecosystems. Our findings reveal key insights into a prolonged wildfire scenarios potentially informing improvements in operational fire management and long-term predictive accuracy, as the area comparisons indexes showed reasonable results between the detected fires from the fire information for resource management systems (FIRMSs) in the first 24 h of the fire and the following days. A case study of a recent wildfire in Madeira Island highlights the integration of real-time weather predictions and post-event weather data analysis. This analysis underscores the potential of combining accurate forecasts with retrospective validation to improve predictive capabilities in dynamic fire environments, which guided the development of a software platform designed to analyse ongoing wildfire events in real-time, leveraging image satellite data and weather predictions.
Descrição
Funding Information: This research has been supported by project PRR New Space Portugal, funded by the European Union (NextGenerationEU). Ref: 02/C05-i01.01/2022.PC644936537-00000046. Publisher Copyright: © 2025 by the authors.
Palavras-chave
FARSITE Real-time fire detection Wildfires Forestry Building and Construction Safety, Risk, Reliability and Quality Environmental Science (miscellaneous) Safety Research Earth and Planetary Sciences (miscellaneous) SDG 13 - Climate Action