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dc.contributor.authorCunill Camprubí, Àngel
dc.contributor.authorGonzález-Moreno, Pablo
dc.contributor.authorResco de Dios, Víctor
dc.date.accessioned2022-07-06T11:17:51Z
dc.date.available2022-07-06T11:17:51Z
dc.date.issued2022
dc.identifier.issn2072-4292
dc.identifier.urihttp://hdl.handle.net/10459.1/83606
dc.description.abstractRemotely sensed vegetation indices have been widely used to estimate live fuel moisture content (LFMC). However, marked differences in vegetation structure affect the relationship between field-measured LFMC and reflectance, which limits spatial extrapolation of these indices. To overcome this limitation, we explored the potential of random forests (RF) to estimate LFMC at the subcontinental scale in the Mediterranean basin wildland. We built RF models (LFMCRF) using a combination of MODIS spectral bands, vegetation indices, surface temperature, and the day of year as predictors. We used the Globe-LFMC and the Catalan LFMC monitoring program databases as ground-truth samples (10,374 samples). LFMCRF was calibrated with samples collected between 2000 and 2014 and validated with samples from 2015 to 2019, with overall root mean square errors (RMSE) of 19.9% and 16.4%, respectively, which were lower than current approaches based on radiative transfer models (RMSE ~74–78%). We used our approach to generate a public database with weekly LFMC maps across the Mediterranean basin.ca_ES
dc.description.sponsorshipThis study was funded by the MICINN (RTI2018-094691-B-C31), European Union’s Horizon 2020-Research and Innovation Framework Programme under grant agreement no. 101003890 project FirEUrisk, the National Natural Science Foundation of China (U20A20179, 31850410483), and the talent proposals in Sichuan Province (2020JDRC0065) from Southwest University of Science and Technology (18ZX7131)ca_ES
dc.language.isoengca_ES
dc.publisherMDPIca_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-094691-B-C31/ES/PAPEL DE LA EVOLUCION DE LOS FENOTIPOS INTEGRADOS EN LA RESILIENCIA DE LOS PINOS MEDITERRANEOS EN UN AMBIENTE CAMBIANTE/ca_ES
dc.relation.isformatofReproducció del document publicat a https://doi.org/10.3390/rs14133162ca_ES
dc.relation.ispartofRemote sensing, 2022, vol.14, núm. 13, p. 1-21ca_ES
dc.rightscc-by (c) Cunill et al., 2022ca_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectWildfireca_ES
dc.subjectMODISca_ES
dc.subjectSpectral indicesca_ES
dc.subjectLand surface temperatureca_ES
dc.subjectRandom forestsca_ES
dc.subjectLive fuel moisture contentca_ES
dc.subject.otherBoscos i silviculturaca_ES
dc.subject.otherBoscos i silvicultura -- Humitatca_ES
dc.titleLive fuel moisture Content mapping in the Mediterranean basin using random forests and combining MODIS spectral and thermal dataca_ES
dc.typeinfo:eu-repo/semantics/articleca_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_ES
dc.identifier.doihttps://doi.org/10.3390/rs14133162
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/101003890/EU/FirEUriskca_ES


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