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dc.contributor.authorPANTOJA, N. V.pt_BR
dc.contributor.authorOLIVEIRA, M. V. N. d'pt_BR
dc.contributor.authorHIGUCHI, N.pt_BR
dc.date.accessioned2017-07-05T11:11:11Zpt_BR
dc.date.available2017-07-05T11:11:11Zpt_BR
dc.date.created2017-07-05pt_BR
dc.date.issued2017pt_BR
dc.identifier.citationIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... Santos: Inpe, 2017.pt_BR
dc.identifier.isbn978-85-17-00088-1pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1072021pt_BR
dc.descriptionStructural 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.pt_BR
dc.language.isoporpt_BR
dc.rightsopenAccesspt_BR
dc.subjectGeotécnicapt_BR
dc.subjectManejo florestalpt_BR
dc.subjectDossel florestalpt_BR
dc.subjectFloresta Estadual do Antimary (AC)pt_BR
dc.subjectBujari (AC)pt_BR
dc.subjectSena Madureira (AC)pt_BR
dc.subjectAcrept_BR
dc.subjectAmazônia Ocidentalpt_BR
dc.subjectWestern Amazonpt_BR
dc.subjectImagem de satélitept_BR
dc.subjectEspacios vacíos en el doselpt_BR
dc.subjectExplotación forestalpt_BR
dc.subjectManejo forestalpt_BR
dc.subjectMonitoreo ambientalpt_BR
dc.subjectSatélitespt_BR
dc.subjectTeledetecciónpt_BR
dc.titleDetecção da exploração madeireira a partir de imagens Landsat e dados LiDAR no Sudoeste da Amazônia.pt_BR
dc.typeArtigo em anais e proceedingspt_BR
dc.date.updated2017-11-08T11:11:11Zpt_BR
dc.subject.thesagroDegradação ambientalpt_BR
dc.subject.thesagroControle ambientalpt_BR
dc.subject.thesagroSensoriamento remotopt_BR
dc.subject.thesagroExtração da madeirapt_BR
dc.subject.thesagroRaio laserpt_BR
dc.subject.nalthesaurusForest managementpt_BR
dc.subject.nalthesaurusLoggingpt_BR
dc.subject.nalthesaurusEnvironmental monitoringpt_BR
dc.subject.nalthesaurusRemote sensingpt_BR
dc.subject.nalthesaurusSatellitespt_BR
dc.subject.nalthesaurusLandsatpt_BR
dc.subject.nalthesaurusLidarpt_BR
dc.subject.nalthesaurusCanopy gapspt_BR
dc.subject.nalthesaurusLáserspt_BR
dc.format.extent28 p.pt_BR
riaa.ainfo.id1072021pt_BR
riaa.ainfo.lastupdate2017-11-08 -02:00:00pt_BR
dc.contributor.institutionNara 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).pt_BR
Aparece en las colecciones:Artigo em anais de congresso (CPAF-AC)

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