Estimation of aboveground biomass stock in tropical savannas using photogrammetric imaging

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversity of Brasília, Department of Forestry-
Autor(es): dc.contributorBrazilian Agricultural Research Company (EMBRAPA), Agroforestry Research Center of Acre-
Autor(es): dc.contributorUniversity of Brasília, Department of Forestry-
Autor(es): dc.contributorUniversity of Brasília, Department of Forestry-
Autor(es): dc.creatorQueiroz, Roberta Franco Pereira de-
Autor(es): dc.creatorOliveira, Marcus Vinicio Neves d’-
Autor(es): dc.creatorRezende, Alba Valéria-
Autor(es): dc.creatorAlencar, Paola Aires Lócio de-
Data de aceite: dc.date.accessioned2025-03-18T17:14:24Z-
Data de disponibilização: dc.date.available2025-03-18T17:14:24Z-
Data de envio: dc.date.issued2024-07-10-
Data de envio: dc.date.issued2024-07-10-
Data de envio: dc.date.issued2023-07-27-
Fonte completa do material: dc.identifierhttp://repositorio.unb.br/handle/10482/48681-
Fonte completa do material: dc.identifierhttps://doi.org/10.3390/drones7080493-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/924438-
Descrição: dc.descriptionThe use of photogrammetry technology for aboveground biomass (AGB) stock estimation in tropical savannas is a challenging task and is still at a preliminary stage. This work aimed to use metrics derived from point clouds, constructed using photogrammetric imaging obtained by an RGB camera on board a remotely piloted aircraft (RPA), to generate a model for estimating AGB stock for the shrubby-woody stratum in savanna areas of Central Brazil (Cerrado). AGB stock was estimated using forest inventory data and an allometric equation. The photogrammetric digital terrain model (DTM) was validated with altimetric field data, demonstrating that the passive sensor can identify topographic variations in sites with discontinuous canopies. The inventory estimated an average AGB of 18.3 (±13.3) Mg ha−1 at the three sampled sites. The AGB model selected was composed of metrics used for height at the 10th and 95th percentile, with an adjusted R2 of 93% and a relative root mean squared error (RMSE) of 16%. AGB distribution maps were generated from the spatialization of the metrics selected for the model, optimizing the visualization and our understanding of the spatial distribution of forest AGB. The study represents a step forward in mapping biomass and carbon stocks in tropical savannas using low-cost remote sensing platforms.-
Descrição: dc.descriptionFaculdade de Tecnologia (FT)-
Descrição: dc.descriptionDepartamento de Engenharia Florestal (FT EFL)-
Descrição: dc.descriptionPrograma de Pós-Graduação em Ciências Florestais-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Publicador: dc.publisherMDPI-
Direitos: dc.rightsAcesso Aberto-
Direitos: dc.rights© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).-
Palavras-chave: dc.subjectSensoriamento remoto-
Palavras-chave: dc.subjectCerrados - vegetação-
Palavras-chave: dc.subjectMapeamento florestal-
Palavras-chave: dc.subjectEstoque de carbono-
Palavras-chave: dc.subjectMonitoramento ambiental-
Título: dc.titleEstimation of aboveground biomass stock in tropical savannas using photogrammetric imaging-
Tipo de arquivo: dc.typelivro digital-
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