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dc.contributor.authorGonzález Ferreiro, Eduardo Manuel
dc.contributor.authorArellano Pérez, Stéfano
dc.contributor.authorCastedo Dorado, Fernando
dc.contributor.authorHevia Cabal, Andrea
dc.contributor.authorVega, José Antonio
dc.contributor.authorVega-Nieva, Daniel Jose
dc.contributor.authorÁlvarez González, Juan Gabriel
dc.contributor.authorRuiz González, Ana Daría
dc.date.accessioned2017-07-06T12:48:53Z
dc.date.available2017-07-06T12:48:53Z
dc.date.issued2017-04-27
dc.identifier.citationGonzález-Ferreiro E, Arellano-Pérez S, Castedo-Dorado F, Hevia A, Vega JA, Vega-Nieva D, et al. (2017) Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data. PLoS ONE 12(4): e0176114. https://doi.org/10.1371/ journal.pone.0176114
dc.identifier.urihttp://hdl.handle.net/10347/15627
dc.description.abstractThe fuel complex variables canopy bulk density and canopy base height are often used to predict crown fire initiation and spread. Direct measurement of these variables is impractical, and they are usually estimated indirectly by modelling. Recent advances in predicting crown fire behaviour require accurate estimates of the complete vertical distribution of canopy fuels. The objectives of the present study were to model the vertical profile of available canopy fuel in pine stands by using data from the Spanish national forest inventory plus lowdensity airborne laser scanning (ALS) metrics. In a first step, the vertical distribution of the canopy fuel load was modelled using the Weibull probability density function. In a second step, two different systems of models were fitted to estimate the canopy variables defining the vertical distributions; the first system related these variables to stand variables obtained in a field inventory, and the second system related the canopy variables to airborne laser scanning metrics. The models of each system were fitted simultaneously to compensate the effects of the inherent cross-model correlation between the canopy variables. Heteroscedasticity was also analyzed, but no correction in the fitting process was necessary. The estimated canopy fuel load profiles from field variables explained 84% and 86% of the variation in canopy fuel load for maritime pine and radiata pine respectively; whereas the estimated canopy fuel load profiles from ALS metrics explained 52% and 49% of the variation for the same species. The proposed models can be used to assess the effectiveness of different forest management alternatives for reducing crown fire hazard
dc.description.sponsorshipWe are grateful to the Galician Government and European Social Fund (Official Journal of Galicia—DOG n° 52, 17/03/2014, p. 11343, exp: POS-A/2013/049) for financing the postdoctoral research stays of Dr Eduardo González-Ferreiro at different institutions. Copyright of LiDAR data, Instituto Geográfico Nacional-Xunta de Galicia
dc.language.isoeng
dc.publisherPublic Library of Science
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/633464
dc.rights© 2017 González-Ferreiro et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subject.classificationMaterias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310604 Ordenación de montes
dc.subject.classificationMaterias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310606 Protección
dc.subject.classificationMaterias::Investigación::31 Ciencias agrarias::3106 Ciencia forestal::310608 Silvicultura
dc.titleModelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data
dc.typeinfo:eu-repo/semantics/article
dc.identifier.DOI10.1371/journal.pone.0176114
dc.relation.publisherversionhttps://doi.org/10.1371/journal.pone.0176114
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.e-issn1932-6203
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Enxeñaría Agroforestal
dc.description.peerreviewedSI


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© 2017 González-Ferreiro et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Except where otherwise noted, this item's license is described as  © 2017 González-Ferreiro et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited





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