Modelling aboveground biomass in forest remnants of the Brazilian Atlantic Forest using remote sensing, environmental and terrain-related data

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorSilveira, Eduarda Martiniano de Oliveira-
Autor(es): dc.creatorCunha, Luiza Imbroisi Ferraz-
Autor(es): dc.creatorGalvão, Lênio Soares-
Autor(es): dc.creatorWithey, Kieran Daniel-
Autor(es): dc.creatorAcerbi Júnior, Fausto Weimar-
Autor(es): dc.creatorScolforo, José Roberto Soares-
Data de aceite: dc.date.accessioned2026-02-09T12:37:48Z-
Data de disponibilização: dc.date.available2026-02-09T12:37:48Z-
Data de envio: dc.date.issued2020-04-15-
Data de envio: dc.date.issued2020-04-15-
Data de envio: dc.date.issued2019-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/40061-
Fonte completa do material: dc.identifierhttps://www.tandfonline.com/doi/abs/10.1080/10106049.2019.1594394?journalCode=tgei20-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1165149-
Descrição: dc.descriptionThe Brazilian Atlantic Forest, one of the most threatened tropical regions in the world, exhibits high levels of terrestrial aboveground biomass (AGB). We propose a random forest approach to model, map and assess whether public lands provide protection for AGB in the Rio Doce watershed, one of the most important watercourses of the Atlantic Forest biome. We used 188 field plots and individual and hybrid features from remote sensing, environmental and terrain-related data. The hybrid model improved the AGB prediction by reducing the root mean square error to 33.43 Mg/ha and increasing the coefficient of determination (R2) to 0.57. The total estimated AGB was 178,967,656.73 Mg, ranging from 20.40 to 167.72 Mg/ha following the seasonal precipitation pattern and anthropogenic disturbance effects. Only 5.76% of the total AGB was located on public protected lands, totalling 10,305,501 Mg, while most of the remaining AGB were located on private properties.-
Idioma: dc.languageen-
Publicador: dc.publisherTaylor & Francis Online-
Direitos: dc.rightsrestrictAccess-
???dc.source???: dc.sourceGeocarto International-
Palavras-chave: dc.subjectAboveground biomass-
Palavras-chave: dc.subjectRandom forest-
Palavras-chave: dc.subjectSpatial distribution-
Palavras-chave: dc.subjectRio Doce-
Título: dc.titleModelling aboveground biomass in forest remnants of the Brazilian Atlantic Forest using remote sensing, environmental and terrain-related data-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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