Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/103248
DC FieldValueLanguage
dc.contributor.authorSantos, Luís-
dc.contributor.authorLopes, Vasco-
dc.contributor.authorBaptista, Cecília-
dc.date.accessioned2022-10-26T10:29:18Z-
dc.date.available2022-10-26T10:29:18Z-
dc.date.issued2022-
dc.identifier.issn1999-4907pt
dc.identifier.urihttps://hdl.handle.net/10316/103248-
dc.description.abstractCountries unaccustomed to wildfires are currently experiencing wildfire as a new climatechange reality. Understanding how fire ignition and propagation are correlated with temperature, orography, humidity, wind, and the mixture and age of individual plants must be considered when designing prevention strategies. While wildfire prevention focuses on fire ignition avoidance, firefighting success depends on early ignition detection, meaning that, in either case, ignition plays a major role. The current case study considered three Portuguese municipalities that annually observe frequent fire ignitions (Tomar, Ourém, and Ferreira do Zêzere) as the testing ground for the Modernized Dynamic Ignition Risk (MDIR) strategy, thus evaluating the efficiency of MDIR and the efficacy of the variables used. This methodology uses geographic information systems technology sustained by open-source satellite imagery, along with the Habitat Risk Assessment model from the InVEST software package, as drivers for the MDIR application. The MDIR approach grants frequent update capabilities and fully open-sourced high ignition risk area identification, producing monthly ignition risk maps. The advantage of using this method is the ease of adaptation to any current monitoring strategy, awarding further efficiency and efficacy in reducing ignitions. The approach delivered adequate results in estimating ignitions for the three Portuguese municipalities, achieving, for several months, prediction accuracy percentages of over 70%. For the studied area, MDIR clearly identifies areas of high ignition risk and delivers an average of 62% success in predicting ignitions, thus showing potential for analyzing the impact of policy implementation and monitoring through the strategy design.pt
dc.language.isoengpt
dc.rightsopenAccesspt
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt
dc.subjectfire ignitionpt
dc.subjectfire hazardpt
dc.subjectQGISpt
dc.subjectInVESTpt
dc.subjectNDVIpt
dc.subjectS2 NDWIpt
dc.subjectriskpt
dc.titleMDIR Monthly Ignition Risk Maps, an Integrated Open-Source Strategy for Wildfire Preventionpt
dc.typearticle-
degois.publication.firstPage408pt
degois.publication.issue3pt
degois.publication.titleForestspt
dc.peerreviewedyespt
dc.identifier.doi10.3390/f13030408pt
degois.publication.volume13pt
dc.date.embargo2022-01-01*
uc.date.periodoEmbargo0pt
item.openairetypearticle-
item.fulltextCom Texto completo-
item.languageiso639-1en-
item.grantfulltextopen-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.researchunitCGEO - Geosciences Center-
crisitem.author.orcid0000-0003-1006-4131-
Appears in Collections:I&D CGUC - Artigos em Revistas Internacionais
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This item is licensed under a Creative Commons License Creative Commons