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Registro Completo |
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Biblioteca(s): |
Embrapa Acre. |
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Data corrente: |
05/07/2017 |
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Data da última atualização: |
16/11/2023 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
PANTOJA, N. V.; OLIVEIRA, M. V. N. d'; HIGUCHI, N. |
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Afiliação: |
Nara Vidal Pantoja, Instituto Nacional de Pesquisas da Amazônia (Inpa); MARCUS VINICIO NEVES D OLIVEIRA, CPAF-Acre; Niro Higuchi, Instituto Nacional de Pesquisas da Amazônia (Inpa). |
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Título: |
Detecção da exploração madeireira a partir de imagens Landsat e dados LiDAR no Sudoeste da Amazônia. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... Santos: Inpe, 2017. |
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Páginas: |
8 p. |
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ISBN: |
978-85-17-00088-1 |
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Idioma: |
Português |
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Conteúdo: |
Structural changes on forest canopy produced by selective logging can be identified through satellite images, which shows the location and extent of these areas. The aim of this study was to analyze the detection of logging infrastructure using Landsat images and LiDAR data and verify how long logging scars can be identified through remote sensing. The study was carried out in an annual production unite at the Antimary State Forestry Acre State, western Amazon. We used Non-Photosynthetic Vegetation (NPV) images to identify log landings and compare its location with relative vegetation density models generated from LiDAR data. We also compared the log landing areas identified in the images with the location of 40 log landings obtained in the field through DGPS. The mean area of the detected by landsat images landings was 435 m2 while the undetected landings was 302 m2. The technique tested in this study allowed us to detect 30% of the log landings in NPV images and assisted in the visual interpretation of the canopy opened produced by selective logging. The relative vegetation density model tested in this study successfully identified altered by forest operations area two years after logging, while using Landsat images these areas could be detected only in the logging year. |
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Palavras-Chave: |
Acre; Amazônia Ocidental; Bujari (AC); Dossel florestal; Espacios vacíos en el dosel; Explotación forestal; Floresta Estadual do Antimary (AC); Geotécnica; Imagem de satélite; Manejo florestal; Manejo forestal; Monitoreo ambiental; Satélites; Sena Madureira (AC); Teledetección; Western Amazon. |
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Thesagro: |
Controle ambiental; Degradação ambiental; Extração da madeira; Raio laser; Sensoriamento remoto. |
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Thesaurus Nal: |
Canopy gaps; Environmental monitoring; Forest management; Landsat; Lásers; Lidar; Logging; Remote sensing; Satellites. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/161399/1/26341.pdf
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Marc: |
LEADER 02815nam a2200517 a 4500
001 2072021
005 2023-11-16
008 2017 bl uuuu u00u1 u #d
020 $a978-85-17-00088-1
100 1 $aPANTOJA, N. V.
245 $aDetecção da exploração madeireira a partir de imagens Landsat e dados LiDAR no Sudoeste da Amazônia.$h[electronic resource]
260 $aIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... Santos: Inpe$c2017
300 $a8 p.
520 $aStructural changes on forest canopy produced by selective logging can be identified through satellite images, which shows the location and extent of these areas. The aim of this study was to analyze the detection of logging infrastructure using Landsat images and LiDAR data and verify how long logging scars can be identified through remote sensing. The study was carried out in an annual production unite at the Antimary State Forestry Acre State, western Amazon. We used Non-Photosynthetic Vegetation (NPV) images to identify log landings and compare its location with relative vegetation density models generated from LiDAR data. We also compared the log landing areas identified in the images with the location of 40 log landings obtained in the field through DGPS. The mean area of the detected by landsat images landings was 435 m2 while the undetected landings was 302 m2. The technique tested in this study allowed us to detect 30% of the log landings in NPV images and assisted in the visual interpretation of the canopy opened produced by selective logging. The relative vegetation density model tested in this study successfully identified altered by forest operations area two years after logging, while using Landsat images these areas could be detected only in the logging year.
650 $aCanopy gaps
650 $aEnvironmental monitoring
650 $aForest management
650 $aLandsat
650 $aLásers
650 $aLidar
650 $aLogging
650 $aRemote sensing
650 $aSatellites
650 $aControle ambiental
650 $aDegradação ambiental
650 $aExtração da madeira
650 $aRaio laser
650 $aSensoriamento remoto
653 $aAcre
653 $aAmazônia Ocidental
653 $aBujari (AC)
653 $aDossel florestal
653 $aEspacios vacíos en el dosel
653 $aExplotación forestal
653 $aFloresta Estadual do Antimary (AC)
653 $aGeotécnica
653 $aImagem de satélite
653 $aManejo florestal
653 $aManejo forestal
653 $aMonitoreo ambiental
653 $aSatélites
653 $aSena Madureira (AC)
653 $aTeledetección
653 $aWestern Amazon
700 1 $aOLIVEIRA, M. V. N. d'
700 1 $aHIGUCHI, N.
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Registro original: |
Embrapa Acre (CPAF-AC) |
