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A method to produce a flexible and customized fuel models dataset

2023Journal article Open access
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dc.contributor.authorSá, A.C.L.
dc.contributor.authorBenali, A.
dc.contributor.authorAparicio, B.A.
dc.contributor.authorBruni, C.
dc.contributor.authorMota, C.
dc.contributor.authorPereira, J.M.C.
dc.contributor.authorFernandes, P.M.
dc.date.accessioned2023-11-06T10:03:39Z
dc.date.available2023-11-06T10:03:39Z
dc.date.issued2023
dc.description.abstractSimulation of vegetation fires very often resorts to fire-behavior models that need fuel models as input. The lack of fuel models is a common problem for researchers and fire managers because its quality depends on the quality/availability of data. In this study we present a method that combines expert- and research-based knowledge with several sources of data (e.g. satellite and fieldwork) to produce customized fuel models maps. Fuel model classes are assigned to land cover types to produce a basemap, which is then updated using empirical and user-defined rules. This method produces a map of surface fuel models as detailed as possible. It is reproducible, and its flexibility relies on juxtaposing independent spatial datasets, depending on their quality or availability. This method is developed in a ModelBuilder/ArcGis toolbox named FUMOD that integrates ten sub-models. FUMOD has been used to map the Portuguese annual fuel models grids since 2019, supporting regional fire risk assessments and suppression decisions. Datasets, models and supplementary files are available in a repository (https://github.com/anasa30/PT_ FuelModels).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationA.C.L. Sá, A. Benali, B.A. Aparicio, C. Bruni, C. Mota, J.M.C. Pereira, P.M. Fernandes, A method to produce a flexible and customized fuel models dataset, MethodsX, Volume 10, 2023, 102218pt_PT
dc.identifier.doi10.1016/j.mex.2023.102218pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.5/29300
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationFRISCO: managing Fire-induced RISks of water quality Contamination
dc.relation.publisherversionwww.elsevier.com/locate/mexpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectland coverpt_PT
dc.subjectfire-atlaspt_PT
dc.subjectburned areaspt_PT
dc.subjecttime since last firept_PT
dc.subjectspectral vegetation indexespt_PT
dc.subjectfuel modelspt_PT
dc.subjectexpert-based knowledgept_PT
dc.subjectflexible approachpt_PT
dc.subjectautomatic updatespt_PT
dc.titleA method to produce a flexible and customized fuel models datasetpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleFRISCO: managing Fire-induced RISks of water quality Contamination
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PCIF%2FMPG%2F0044%2F2018/PT
oaire.citation.startPage102218pt_PT
oaire.citation.titleMethodsXpt_PT
oaire.citation.volume10pt_PT
oaire.fundingStream3599-PPCDT
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isProjectOfPublicationbcf2aee4-085e-4a2d-9778-a1d579452d3f
relation.isProjectOfPublication.latestForDiscoverybcf2aee4-085e-4a2d-9778-a1d579452d3f

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