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1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Sitemtc-m21d.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34T/47TM37P
Repositóriosid.inpe.br/mtc-m21d/2022/11.03.13.20   (acesso restrito)
Última Atualização2022:11.03.13.20.47 (UTC) simone
Repositório de Metadadossid.inpe.br/mtc-m21d/2022/11.03.13.20.47
Última Atualização dos Metadados2023:07.08.07.14.37 (UTC) administrator
DOI10.1002/rse2.264
ISSN2056-3485
Chave de CitaçãoSilvaWaEmStGaOmAr:2022:CaPaCo
TítuloCanopy palm cover across the Brazilian Amazon forests mapped with airborne LiDAR data and deep learning
Ano2022
MêsOct.
Data de Acesso05 maio 2024
Tipo de Trabalhojournal article
Tipo SecundárioPRE PI
Número de Arquivos1
Tamanho2504 KiB
2. Contextualização
Autor1 Silva, Ricardo Dalagnol da
2 Wagner, Fabien Hubert
3 Emilio, Thaise
4 Streher, Annia Susin
5 Galvão, Lênio Soares
6 Ometto, Jean Pierre Henry Balbaud
7 Aragão, Luiz Eduardo Oliveira e Cruz de
Identificador de Curriculo1
2
3
4
5 8JMKD3MGP5W/3C9JHLF
ORCID1 0000-0002-7151-8697
2 0000-0002-9623-1182
Grupo1 DIOTG-CGCT-INPE-MCTI-GOV-BR
2 DIOTG-CGCT-INPE-MCTI-GOV-BR
3
4 DIOTG-CGCT-INPE-MCTI-GOV-BR
5 DIOTG-CGCT-INPE-MCTI-GOV-BR
6 DIPE3-COGPI-INPE-MCTI-GOV-BR
7 DIOTG-CGCT-INPE-MCTI-GOV-BR
Afiliação1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Universidade Estadual de Campinas (UNICAMP)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
5 Instituto Nacional de Pesquisas Espaciais (INPE)
6 Instituto Nacional de Pesquisas Espaciais (INPE)
7 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1 ricds@hotmail.com
2 wagner.h.fabien@gmail.com
3
4 annia.streher@gmail.com
5 lenio.galvao@hotmail.com
6 jean.ometto@inpe.br
7 luiz.aragao@inpe.br
RevistaRemote Sensing in Ecology and Conservation
Volume8
Número5
Páginas601-614
Histórico (UTC)2022-11-03 13:21:28 :: simone -> administrator :: 2022
2023-07-08 07:14:37 :: administrator -> simone :: 2022
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Tipo de Versãopublisher
Palavras-ChaveAirborne LiDAR
Amazon
biodiversity
deep learning
palm cover
ResumoThe Amazon region in Brazil contains c. 5% of the palm species of the world. However, palm cover at macroecological scales has not yet been quantified in this biome. Here, we used high spatial resolution LiDAR data, acquired from 610 flightlines over the Brazilian Amazon, to map canopy palm cover for the first time using a deep learning approach. The image segmentation model from U-Net deep learning was selected for mapping palm segments using the LiDAR canopy height model (CHM) at 0.5-m spatial resolution. To train and validate the model, we manually delineated 6971 canopy palm segments over 931.43 ha of forests on four training sites by inspecting their unique star-shaped crown architecture in the CHM. The results indicated an accuracy of 80% to automatically map canopy palm area. The approach detected >1.1 million palm segments over the 480 000 ha sampled by LiDAR and roughly estimated 1.05 billion palm segments for the Brazilian Amazon. Palm cover was not evenly distributed over the Amazon, revealing undocumented hotspots of high cover (>5%) in eastern Amazon (Pará state), and confirming documented hotspots in southwest (Acre state) and north of the region (Roraima state). Palm segment height was strongly and positively correlated with forest height, where palm segments showed overall lower height. A higher canopy palm cover was observed over shorter forests, while the opposite was found over taller forests, where palms may not be visible from the canopy. Palm segments occurred more frequently at valleys but they were also observed in other landscapes, depending on site location and forest height. Our findings highlight the disproportional occurrence of palm cover in some Amazonian canopies. This fact should be taken into account to improve regional carbon cycle representation and promote initiatives of biodiversity conservation and bioeconomic use of these forests.
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4. Condições de acesso e uso
Idiomaen
Arquivo AlvoRemote Sens Ecol Conserv - 2022 - Dalagnol - Canopy palm cover across the Brazilian Amazon forests mapped with airborne.pdf
Grupo de Usuáriossimone
Grupo de Leitoresadministrator
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Visibilidadeshown
Permissão de Leituradeny from all and allow from 150.163
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/46KUATE
8JMKD3MGPCW/46L2FGP
Lista de Itens Citandosid.inpe.br/mtc-m21/2012/07.13.14.53.28 1
sid.inpe.br/bibdigital/2022/04.04.04.47 1
DivulgaçãoWEBSCI; PORTALCAPES; SCOPUS.
Acervo Hospedeirourlib.net/www/2021/06.04.03.40
6. Notas
Campos Vaziosalternatejournal archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark mirrorrepository nextedition notes parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url
7. Controle da descrição
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