Exploring coarse- to fine-scale approaches for mapping and estimating forest volume from Brazilian National Forest Inventory data

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Autor(es): dc.contributorRural Fed Univ Amazonia-
Autor(es): dc.contributorMichigan State Univ-
Autor(es): dc.contributorUniv Fed Parana-
Autor(es): dc.contributorFed Univ South Bahia-
Autor(es): dc.contributorEmpresa Brasileira de Pesquisa Agropecuária (EMBRAPA)-
Autor(es): dc.contributorMato Grosso State Univ-
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorDavid, Hassan C.-
Autor(es): dc.creatorMacFarlane, David W.-
Autor(es): dc.creatorNetto, Sylvio Pellico-
Autor(es): dc.creatorDalla Corte, Ana Paula-
Autor(es): dc.creatorPiotto, Daniel-
Autor(es): dc.creatorOliveira, Yeda M. M. de-
Autor(es): dc.creatorMorais, Vinicius A.-
Autor(es): dc.creatorSanquetta, Carlos R.-
Autor(es): dc.creatorNeto, Rorai P. M. [UNESP]-
Data de aceite: dc.date.accessioned2022-02-22T00:09:42Z-
Data de disponibilização: dc.date.available2022-02-22T00:09:42Z-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2019-10-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1093/forestry/cpz030-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/196526-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/196526-
Descrição: dc.descriptionThe aim of this study was to explore methods to: (1) enhance coarse-scale estimates of wood volume from National Forest Inventories (NFIs) data and (2) map them at finer scales. The 'standard' coarse-scale estimation extrapolates wood volume from clusters to the grid cell they represent, using the cluster's represented forested area (RFA) to predict the cell's forested area. Data from a subset of Brazil's NFI clusters were combined with Landsat-8 imagery to explore a new coarse-scale method, where forested area derived from image classification (FADIC) is used instead of RFA. The RFA- and FADIC-derived estimates of total volume were, respectively, 197.4 million m(3) and 116.3 million m(3). For fine-scale methods, volume was estimated and mapped at pixel level using: (i) surface reflectance-based models (SRMs), and (ii) regression-kriging (RK) and a RK model (RKM) whose inputs were latitude and longitude of pixels. The SRM-based method captured the mean and the general spatial trend of the volume well. The RK-based method also estimated the mean well, but it failed to predict higher and lower volumes. The SRM- and RK-based estimates of total volume were 211.7 million m(3) and 203.3 million m(3), an overestimate of 7 per cent and 3 per cent, respectively, of the 'standard' NFI estimate (197.4 million m(3)), though both estimates were within the 95 per cent confidence interval, meaning that both fine-scale methods yield total volume statistically similar to the 'standard' coarse-scale method.-
Descrição: dc.descriptionRural Fed Univ Amazonia, Dept Forestry, Presidente Tancredo Neves Ave 2501, Belem, PA, Brazil-
Descrição: dc.descriptionMichigan State Univ, Dept Forestry, 480 Wilson Rd, E Lansing, MI 48824 USA-
Descrição: dc.descriptionUniv Fed Parana, Dept Forestry, Pref Lothario Meissner Ave 900, BR-80210170 Curitiba, PR, Brazil-
Descrição: dc.descriptionFed Univ South Bahia, Dept Sci & Agroforestry Technol, Highway 415,Km 22, BR-45653919 Ilheus, BA, Brazil-
Descrição: dc.descriptionEmbrapa Forests, Rd Ribeira,Km 111, BR-83411000 Colombo, PR, Brazil-
Descrição: dc.descriptionMato Grosso State Univ, Dept Forestry, Perimetral Deputado Rogerio Silva Ave, BR-78580000 Alta Floresta, MT, Brazil-
Descrição: dc.descriptionState Univ Sao Paulo, Dept Cartog, Roberto Simonsen St 305, BR-19060900 Presidente Prudente, SP, Brazil-
Descrição: dc.descriptionState Univ Sao Paulo, Dept Cartog, Roberto Simonsen St 305, BR-19060900 Presidente Prudente, SP, Brazil-
Formato: dc.format577-590-
Idioma: dc.languageen-
Publicador: dc.publisherOxford Univ Press-
Relação: dc.relationForestry-
???dc.source???: dc.sourceWeb of Science-
Título: dc.titleExploring coarse- to fine-scale approaches for mapping and estimating forest volume from Brazilian National Forest Inventory data-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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