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Metadados

1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Sitemtc-m21d.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34T/4AC8LPB
Repositóriosid.inpe.br/mtc-m21d/2023/12.11.16.54
Repositório de Metadadossid.inpe.br/mtc-m21d/2023/12.11.16.54.33
Última Atualização dos Metadados2024:01.02.17.16.56 (UTC) administrator
Chave SecundáriaINPE--PRE/
Chave de CitaçãoDalagnolWYBOFTMGSAASG:2023:InCaEm
TítuloIncreasing Carbon Emissions from Amazonian Forest Degradation
Ano2023
Data de Acesso12 maio 2024
Tipo SecundárioPRE CI
2. Contextualização
Autor 1 Dalagnol, Ricardo
 2 Wagner, Fabien Hubert
 3 Yang, Yan
 4 Braga, Daniel
 5 Osborn, Fiona
 6 Favrichon, Samuel
 7 Takougoum, Le Bienfaiteur Sagang
 8 Mullissa, Adugna
 9 George, Stephanie
10 Silva Júnior, Celso Henrique Leite
11 Anderson, Liana O.
12 Aragão, Luiz Eduardo Oliveira e Cruz de
13 Saatchi, Sassan
14 Galvão, Lênio Soares
Identificador de Curriculo 1
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14 8JMKD3MGP5W/3C9JHLF
Grupo 1
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 4 DIOTG-CGCT-INPE-MCTI-GOV-BR
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10 SER-SRE-DIPGR-INPE-MCTI-GOV-BR
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12 DIOTG-CGCT-INPE-MCTI-GOV-BR
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14 DIOTG-CGCT-INPE-MCTI-GOV-BR
Afiliação 1 University of California Los Angeles
 2 University of California Los Angeles
 3 California Institute of Technology
 4 Instituto Nacional de Pesquisas Espaciais (INPE)
 5 CTrees.org
 6 JPL/NASA/Caltech
 7 University of California
 8 University of California Los Angeles
 9 CTrees.org
10 Instituto Nacional de Pesquisas Espaciais (INPE)
11 National Center for Monitoring and Early Warning of Natural Disasters
12 Instituto Nacional de Pesquisas Espaciais (INPE)
13 NASA Jet Propulsion Laboratory
14 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor 1
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12 luiz.aragao@inpe.br
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14 lenio.galvao@inpe.br
Nome do EventoAGU FAll Meeting
Localização do EventoSan Francisco, CA
Data11-15 Dec. 2023
Editora (Publisher)AGU
Título do LivroProceedings
Histórico (UTC)2023-12-11 16:54:33 :: simone -> administrator ::
2024-01-02 17:16:56 :: administrator -> simone :: 2023
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Tipo de Versãopublisher
ResumoSelective logging and fire disturbances affect large areas of tropical forests every year causing forest degradation and the reduction of biomass and carbon. However, disturbances' true extent and impacts on carbon emissions are difficult to quantify. These limitations can be attributed to the fact that conventional monitoring systems do not accurately map these disturbances or provide attributions. In this study, we use a deep-learning approach and high-resolution Planet NICFI imagery (4.77-m) to map forests degraded by selective logging and fire in the entire Amazon region from 2017 to 2022 and estimate carbon emissions. To map degradation, we extended an approach based on the U-Net model, previously trained over Mato Grosso state (Brazil), to the entire Amazon basin, obtaining high accuracy (>80%). Carbon emissions were estimated for areas overlapping our degradation maps using both Airborne Laser Scanning (ALS) datasets collected by National Institute for Space Research (INPE/Brazil) between 2016 and 2018, and multi-temporal regional maps of Aboveground Carbon Density (ACD) derived from the Global Ecosystem Dynamics Investigation (GEDI) and remote sensing data. Our maps show that selective logging and fire degraded an average of 11,452 and 21,745 km2 of forests per year from 2017 to 2022, respectively. This area has been steadily increasing for logging and highly varying for fire, with the largest area found in 2020 (34,702 km2), which was a drought year. Logging and fire were mostly detected alongside the Arc of Deforestation. Logging occurred more clustered than fire, showing hotspots that overlapped known forest concessions such as Tapajós-Arapiuns/PA, Flona Tapajós/PA, Saracá-Taquera/PA, Flona Jamari/RO, and Itapiranga/AM. We also found other hotspots in Brazil at Paragominas/PA, Lábrea/AM, large areas of Mato Grosso state, as well as in Madre de Dios and west of Ucayali regions (Peru), in Guarayos (Bolivia), and in Suriname. For the Amazon basin, we estimated increasing carbon emissions from 2017 to 2022, with similar or higher magnitudes of carbon emissions from deforestation in some years, such as 2020. Overall, these new estimates of the extent and impacts of degradation for forest carbon in the Amazon region highlight that tackling degradation is key for reducing carbon emissions.
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4. Condições de acesso e uso
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Grupo de Usuáriossimone
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5. Fontes relacionadas
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6. Notas
Campos Vaziosarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress edition editor format isbn issn keywords label lineage mark mirrorrepository nextedition notes numberoffiles numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisheraddress readergroup readpermission rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle size sponsor subject targetfile tertiarymark tertiarytype type url volume
7. Controle da descrição
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