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Analysing Fire Propagation Models

2025-04-23Artigo científico Acesso aberto
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dc.contributor.authorMartins, Leonardo
dc.contributor.authorAlmeida, Rui Valente de
dc.contributor.authorMaia, António
dc.contributor.authorVieira, Pedro
dc.contributor.institutionDF – Departamento de Física
dc.contributor.pblMDPI - Multidisciplinary Digital Publishing Institute
dc.date.accessioned2025-07-30T21:20:14Z
dc.date.available2025-07-30T21:20:14Z
dc.date.issued2025-04-23
dc.descriptionFunding 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.
dc.description.abstractWith 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.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent26
dc.format.extent3285134
dc.identifier.doi10.3390/fire8050166
dc.identifier.issn2571-6255
dc.identifier.otherPURE: 123378970
dc.identifier.otherPURE UUID: c1edf05a-6af8-4dc0-9cb2-274b3a28a6f7
dc.identifier.otherScopus: 105006741129
dc.identifier.otherWOS: 001496085200001
dc.identifier.urihttp://hdl.handle.net/10362/185769
dc.identifier.urlhttps://www.scopus.com/pages/publications/105006741129
dc.identifier.urlhttps://www.webofscience.com/wos/woscc/full-record/WOS:001496085200001
dc.language.isoeng
dc.peerreviewedyes
dc.subjectFARSITE
dc.subjectReal-time fire detection
dc.subjectWildfires
dc.subjectForestry
dc.subjectBuilding and Construction
dc.subjectSafety, Risk, Reliability and Quality
dc.subjectEnvironmental Science (miscellaneous)
dc.subjectSafety Research
dc.subjectEarth and Planetary Sciences (miscellaneous)
dc.subjectSDG 13 - Climate Action
dc.titleAnalysing Fire Propagation Modelsen
dc.title.subtitleA Case Study on FARSITE for Prolonged Wildfiresen
dc.typejournal article
degois.publication.firstPage1
degois.publication.issue5
degois.publication.lastPage26
degois.publication.titleFire
degois.publication.volume8
dspace.entity.typePublication
rcaap.rightsopenAccess

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