1. Identificação | |
Tipo de Referência | Artigo em Evento (Conference Proceedings) |
Site | mtc-m21c.sid.inpe.br |
Código do Detentor | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
Identificador | 8JMKD3MGP3W34R/42E95MB |
Repositório | sid.inpe.br/mtc-m21c/2020/05.04.12.06 |
Última Atualização | 2020:06.19.12.42.08 (UTC) simone |
Repositório de Metadados | sid.inpe.br/mtc-m21c/2020/05.04.12.06.44 |
Última Atualização dos Metadados | 2022:01.04.01.35.06 (UTC) administrator |
Chave Secundária | INPE--PRE/ |
Chave de Citação | BispoRZMCFBSARBPGRLBWSOB:2020:EsAbGr |
Título | Estimating the Above Ground Biomass of Brazilian Savanna using multi-sensor approach |
Ano | 2020 |
Data de Acesso | 20 abr. 2024 |
Tipo Secundário | PRE CI |
Número de Arquivos | 1 |
Tamanho | 294 KiB |
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2. Contextualização | |
Autor | 1 Bispo, Polyanna da Conceição 2 Rodriguez-Veiga, Pedro 3 Zimbres, Barbara 4 Miranda, Sabrina de Couto 5 Cezare, Cassio Henrique Giusti 6 Fleming, Sam 7 Baldacchino, Francesca 8 Shimbo, Julia Zanin 9 Alencar, Ane Auxiliadora Costa 10 Roitman, Iris 11 Bustamante, Mercedes 12 Pacheco-Pascagaza, Ana Maria 13 Gou, Yaqing 14 Roberts, John 15 Louis, Valentin 16 Barret, Kirsten 17 Woodhouse, Iain 18 Sousa Neto, Eráclito Rodrigues de 19 Ometto, Jean Pierre Henry Balbaud 20 Balzter, Heiko |
ORCID | 1 0000-0003-0247-8449 |
Grupo | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 COCST-COCST-INPE-MCTIC-GOV-BR 19 COCST-COCST-INPE-MCTIC-GOV-BR |
Afiliação | 1 University of Manchester 2 University of Leicester 3 Instituto de Pesquisa Ambiental da Amazônia (IPAM) 4 Universidade Estadual de Goiás (UEG) 5 Universidade Federal de Goiás (UFG) 6 Carbomap Ltd. 7 Carbomap Ltd. 8 Instituto de Pesquisa Ambiental da Amazônia (IPAM) 9 Instituto de Pesquisa Ambiental da Amazônia (IPAM) 10 Universidade de Brasília (UnB) 11 Universidade de Brasília (UnB) 12 University of Leicester 13 University of Leicester 14 University of Leicester 15 University of Leicester 16 University of Leicester 17 Carbomap Ltd 18 Instituto Nacional de Pesquisas Espaciais (INPE) 19 Instituto Nacional de Pesquisas Espaciais (INPE) 20 University of Leicester |
Endereço de e-Mail do Autor | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 eraclito.neto@inpe.br 19 jean.ometto@inpe.br |
Nome do Evento | EGU General Assembly |
Localização do Evento | Online |
Data | 04-08 may |
Histórico (UTC) | 2020-05-04 12:06:44 :: simone -> administrator :: 2020-05-04 15:25:04 :: administrator -> simone :: 2020 2020-06-19 12:42:08 :: simone -> administrator :: 2020 2022-01-04 01:35:06 :: administrator -> simone :: 2020 |
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3. Conteúdo e estrutura | |
É a matriz ou uma cópia? | é a matriz |
Estágio do Conteúdo | concluido |
Transferível | 1 |
Tipo do Conteúdo | External Contribution |
Tipo de Versão | publisher |
Resumo | The Brazilian Savanna, known as Cerrado (Cerrado sensu lato (s.l.)), is the second largest biome in South America. It comprises different physiognomies due to variations of soil, topography and human impacts. The gradients of tree density, tree height, above ground biomass (AGB) and wood species cover vary according to the Cerrado formation, ranging from different grassland formations (Campo limpo, campo sujo), savanna intermediary formations (Campo cerrado and Cerrado sensu stricto - s.s) and forest formations (Cerradão, Mata ciliar, Mata de galeria and Mata Seca). Although the carbon stock in Cerrado is lower than in the Brazilian Amazon, the conversion of this biome to other types of land use is occurring much faster. In the last ten years, the degradation of Cerrado forest was the second largest source of carbon emissions in Brazil. Therefore, effective methods for assessing and monitoring aboveground woody biomass and carbon stocks are needed. A multi-sensor Earth observation approach and machine learning techniques have shown potential for the large-scale characterization of Cerrado forest structure.The aim of this study is to present a method to estimate the AGB of an area of the Brazilian Cerrado using ALOS-PALSAR (L-band SAR), Landsat, LIDAR (LIght Detection And Ranging) and field datasets. Field data consisted of 15 plots of 1 ha area located in Rio Vermelho watershed in Goiás-State (Brazil). We used a 2-step AGB estimation (i) from the field AGB using LIDAR metrics and (ii) from LIDAR-AGB to satellite Earth Observation scales following a Random Forest regression algorithm. The methodology to estimate ABG of Cerrado Stricto Sensu vegetation is part of the Forests 2020 project which is the largest investment by the UK Space Agency, as part of the International Partnerships Programme (IPP), to support in the improvement of the forest monitoring in six partner countries through advanced uses of satellite data. |
Área | CST |
Arranjo | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > COCST > Estimating the Above... |
Conteúdo da Pasta doc | acessar |
Conteúdo da Pasta source | não têm arquivos |
Conteúdo da Pasta agreement | |
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4. Condições de acesso e uso | |
URL dos dados | http://urlib.net/ibi/8JMKD3MGP3W34R/42E95MB |
URL dos dados zipados | http://urlib.net/zip/8JMKD3MGP3W34R/42E95MB |
Arquivo Alvo | bispo_estimating.pdf |
Grupo de Usuários | simone |
Grupo de Leitores | administrator simone |
Visibilidade | shown |
Permissão de Atualização | não transferida |
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5. Fontes relacionadas | |
Unidades Imediatamente Superiores | 8JMKD3MGPCW/3F3T29H |
Lista de Itens Citando | sid.inpe.br/bibdigital/2013/10.19.20.40 1 |
Acervo Hospedeiro | urlib.net/www/2017/11.22.19.04 |
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6. Notas | |
Campos Vazios | archivingpolicy archivist booktitle callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress edition editor format isbn issn keywords label language lineage mark mirrorrepository nextedition notes numberofvolumes organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readpermission resumeid rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url volume |
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7. Controle da descrição | |
e-Mail (login) | simone |
atualizar | |
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