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1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Sitemtc-m21c.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34R/3T72B35
Repositóriosid.inpe.br/mtc-m21c/2019/04.23.17.56
Última Atualização2019:04.23.17.56.42 (UTC) simone
Repositório de Metadadossid.inpe.br/mtc-m21c/2019/04.23.17.56.42
Última Atualização dos Metadados2020:01.06.11.42.13 (UTC) administrator
DOI10.3390/rs11070817
ISSN2072-4292
Chave de CitaçãoDalagnolPhGlGaWaLoAr:2019:QuCaTr
TítuloQuantifying canopy tree loss and gap recovery in tropical forests under low-intensity logging using VHR satellite imagery and airborne LiDAR
Ano2019
MêsApr.
Data de Acesso09 maio 2024
Tipo de Trabalhojournal article
Tipo SecundárioPRE PI
Número de Arquivos1
Tamanho13670 KiB
2. Contextualização
Autor1 Dalagnol, Ricardo
2 Phillips, Oliver L.
3 Gloor, Emanuel
4 Galvão, Lênio Soares
5 Wagner, Fabien Hubert
6 Locks, Charton J.
7 Aragão, Luiz Eduardo Oliveira e Cruz de
Identificador de Curriculo1
2
3
4 8JMKD3MGP5W/3C9JHLF
ORCID1 0000-0002-7151-8697
2
3
4
5 0000-0002-9623-1182
6
7 0000-0002-4134-6708
Grupo1 SER-SRE-SESPG-INPE-MCTIC-GOV-BR
2
3
4 DIDSR-CGOBT-INPE-MCTIC-GOV-BR
5 DIDSR-CGOBT-INPE-MCTIC-GOV-BR
6
7 DIDSR-CGOBT-INPE-MCTIC-GOV-BR
Afiliação1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 University of Leeds
3 University of Leeds
4 Instituto Nacional de Pesquisas Espaciais (INPE)
5 Instituto Nacional de Pesquisas Espaciais (INPE)
6 Serviço Florestal Brasileiro
7 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1 ricds@hotmail.com
2 o.phillips@leeds.ac.uk
3 e.gloor@leeds.ac.uk
4 lenio.galvao@inpe.br
5 wagner.h.fabien@gmail.com
6 charton.locks@florestal.gov.br
7 luiz.aragao@inpe.br
RevistaRemote Sensing
Volume11
Número7
Nota SecundáriaB3_GEOGRAFIA B3_ENGENHARIAS_I B4_GEOCIÊNCIAS B4_CIÊNCIAS_AMBIENTAIS B5_CIÊNCIAS_AGRÁRIAS_I
Histórico (UTC)2019-04-23 17:56:42 :: simone -> administrator ::
2019-04-23 17:56:42 :: administrator -> simone :: 2019
2019-04-23 17:57:19 :: simone -> administrator :: 2019
2020-01-06 11:42:13 :: administrator -> simone :: 2019
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-Chaveremote sensing
forest management
disturbance monitoring
forest dynamics
multi-temporal analysis
WorldView-2
GeoEye-1
random forest
Amazon
Jamari National Forest
ResumoLogging, including selective and illegal activities, is widespread, affecting the carbon cycle and the biodiversity of tropical forests. However, automated approaches using very high resolution (VHR) satellite data (≤ 1 m spatial resolution) to accurately track these small-scale human disturbances over large and remote areas are not readily available. The main constraint for performing this type of analysis is the lack of spatially accurate tree-scale validation data. In this study, we assessed the potential of VHR satellite imagery to detect canopy tree loss related to selective logging in closed-canopy tropical forests. To do this, we compared the tree loss detection capability of WorldView-2 and GeoEye-1 satellites with airborne LiDAR, which acquired pre- and post-logging data at the Jamari National Forest in the Brazilian Amazon. We found that logging drove changes in canopy height ranging from -5.6 to -42.2 m, with a mean reduction of -23.5 m. A simple LiDAR height difference threshold of -10 m was enough to map 97% of the logged trees. Compared to LiDAR, tree losses can be detected using VHR satellite imagery and a random forest (RF) model with an average precision of 64%, while mapping 60% of the total tree loss. Tree losses associated with large gap openings or tall trees were more successfully detected. In general, the most important remote sensing metrics for the RF model were standard deviation statistics, especially those extracted from the reflectance of the visible bands (R, G, B), and the shadow fraction. While most small canopy gaps closed within ∼2 years, larger gaps could still be observed over a longer time. Nevertheless, the use of annual imagery is advised to reach acceptable detectability. Our study shows that VHR satellite imagery has the potential for monitoring the logging in tropical forests and detecting hotspots of natural disturbance with a low cost at the regional scale.
ÁreaSRE
Arranjo 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Quantifying canopy tree...
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4. Condições de acesso e uso
URL dos dadoshttp://mtc-m21c.sid.inpe.br/ibi/8JMKD3MGP3W34R/3T72B35
URL dos dados zipadoshttp://mtc-m21c.sid.inpe.br/zip/8JMKD3MGP3W34R/3T72B35
Idiomaen
Arquivo Alvoremotesensing-11-00817-v2.pdf
Grupo de Usuáriossimone
Grupo de Leitoresadministrator
simone
Visibilidadeshown
Política de Arquivamentoallowpublisher allowfinaldraft
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/3ER446E
8JMKD3MGPCW/3F3NU5S
Lista de Itens Citandosid.inpe.br/bibdigital/2013/10.18.22.34 3
sid.inpe.br/mtc-m21/2012/07.13.14.53.28 1
sid.inpe.br/bibdigital/2013/09.13.21.11 1
DivulgaçãoWEBSCI; PORTALCAPES; MGA; COMPENDEX; SCOPUS.
Acervo Hospedeirourlib.net/www/2017/11.22.19.04
6. Notas
Campos Vaziosalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark mirrorrepository nextedition notes pages parameterlist parentrepositories previousedition previouslowerunit progress project readpermission rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url
7. Controle da descrição
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