Use of the linear spectral mixture model in the Saracá-Taquera National Forest
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Revista de Ciências Agrárias (Belém. Online) |
Texto Completo: | https://ajaes.ufra.edu.br/index.php/ajaes/article/view/3424 |
Resumo: | The Saracá-Taquera Conservation Unit is one of the most exuberant National Forests, rich in biodiversity and with a high potential for the use of natural resources. The objective of this study was to identify signs from forest exploiting and activities with potential for degradation in the Saracá-Taquera National Forest (FLONA-ST), using the linear spectral mixture model (LSMM) in an image recorded in 2020. The study was carried out at FLONA-ST, located in the mesoregion of the Lower Amazon. The images were acquired with the Geological Service of the United States. The collected scenes, 228/061 and 229/061, were submitted to compositions of bands 6, 5, and 4 of Landsat 8, mosaic, and the image clipping corresponding to the area of FLONA. The LSMM was applied and the Spectral Index of Forest Degradation (DEGRADI) was determined. Then, the technique of slicing and vectoring of images was applied, for further classification based on visual interpretation. The use of LSMM and DEGRADI were able to identify the deforested areas in FLONA-ST. In general, FLONA was predominant in areas covered with dense and heterogeneous vegetation. However, areas with exposed soil were observed in the central, north, northeast, southeast, and south parts, whether intended for mining, agricultural activities, housing, or for the exploitation of forest resources in FLONA. The forest exploitation in FLONA was observed, mostly, within the Forest Management Units, where exploration caused by disordered and geometric selective logging was found. |
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Use of the linear spectral mixture model in the Saracá-Taquera National ForestUse of the linear spectral mixture model in the Saracá-Taquera National Forestfraction-imageforage index spectral indexlandsat 8remote senseForest ProtectionRemote SensingSpectral Mixture Linear ModelDigital Image ProcessingSpectral Index of Forest Degradationimagem-fraçãoíndice espectral de degradação florestallandsat 8sensoriamento remotoProteção FlorestalSensoriamento RemotoModelo Linear de Mistura EspectralProcessamento Digital de ImagensÍndice Espectral de Degradação FlorestalThe Saracá-Taquera Conservation Unit is one of the most exuberant National Forests, rich in biodiversity and with a high potential for the use of natural resources. The objective of this study was to identify signs from forest exploiting and activities with potential for degradation in the Saracá-Taquera National Forest (FLONA-ST), using the linear spectral mixture model (LSMM) in an image recorded in 2020. The study was carried out at FLONA-ST, located in the mesoregion of the Lower Amazon. The images were acquired with the Geological Service of the United States. The collected scenes, 228/061 and 229/061, were submitted to compositions of bands 6, 5, and 4 of Landsat 8, mosaic, and the image clipping corresponding to the area of FLONA. The LSMM was applied and the Spectral Index of Forest Degradation (DEGRADI) was determined. Then, the technique of slicing and vectoring of images was applied, for further classification based on visual interpretation. The use of LSMM and DEGRADI were able to identify the deforested areas in FLONA-ST. In general, FLONA was predominant in areas covered with dense and heterogeneous vegetation. However, areas with exposed soil were observed in the central, north, northeast, southeast, and south parts, whether intended for mining, agricultural activities, housing, or for the exploitation of forest resources in FLONA. The forest exploitation in FLONA was observed, mostly, within the Forest Management Units, where exploration caused by disordered and geometric selective logging was found.A unidade de conservação Saracá-Taquera está entre as Florestas Nacionais mais exuberantes, com alta biodiversidade e potencial de uso dos recursos naturais. O objetivo desse estudo foi identificar as cicatrizes de exploração florestal e as atividades com potencial de degradação na Floresta Nacional de Saracá-Taquera (FLONA-ST), com o uso do modelo linear de mistura espectral (MLME) em imagem registrada no ano de 2020. O estudo foi realizado na FLONA-ST, localizado na mesorregião do Baixo Amazonas. A aquisição das imagens foi feita junto ao Serviço Geológico dos Estados Unidos. As cenas coletadas, 228/061 e 229/061, foram submetidas a composições das bandas 6, 5 e 4 do Landsat 8, mosaico e o recorte da imagem correspondente a área da FLONA. Foi aplicado o MLME e determinado o Índice Espectral de Degradação Florestal (DEGRADI). Em seguida, foi aplicada a técnica de fatiamento e vetorização de imagens, para posterior classificação com base na interpretação visual. O uso do MLME e do DEGRADI foram adequados para identificar as áreas desmatadas na FLONA-ST. De maneira geral, a FLONA apresentou predominância em áreas cobertas com vegetação densa e heterogênea. No entanto, áreas com solo exposto foram observadas nas porções central, norte, nordeste, sudeste e sul, seja destinada a mineração, atividades agropecuárias, habitação ou para exploração dos recursos florestais da FLONA. A exploração florestal na FLONA foi observada, em sua maioria, dentro das Unidades de Manejo Florestal, sendo detectado exploração por corte seletivo desordenado e geométrico.Universidade Federal Rural da Amazônia/UFRA2021-10-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext; Imagetexto; imagemapplication/pdfhttps://ajaes.ufra.edu.br/index.php/ajaes/article/view/3424Amazonian Journal of Agricultural Sciences Journal of Agricultural and Environmental Sciences; Vol 64 (2021): RCA AJAESRevista de Ciências Agrárias Amazonian Journal of Agricultural and Environmental Sciences; v. 64 (2021): RCA AJAES2177-87601517-591Xreponame:Revista de Ciências Agrárias (Belém. Online)instname:Universidade Federal Rural da Amazônia (UFRA)instacron:UFRAporhttps://ajaes.ufra.edu.br/index.php/ajaes/article/view/3424/1628Copyright (c) 2021 Michel Keisuke Sato, João Almiro Corrêa Soares, Bruna Naiara Rocha, Cássio Furtado Limahttps://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessSato, Michel KeisukeCorrêa Soares, João AlmiroRocha, Bruna Naiara Furtado Lima, Cássio2021-10-28T18:21:40Zoai:ojs.www.periodicos.ufra.edu.br:article/3424Revistahttps://ajaes.ufra.edu.br/index.php/ajaes/PUBhttps://ajaes.ufra.edu.br/index.php/ajaes/oaiallan.lobato@ufra.edu.br || ajaes.suporte@gmail.com2177-87601517-591Xopendoar:2021-10-28T18:21:40Revista de Ciências Agrárias (Belém. Online) - Universidade Federal Rural da Amazônia (UFRA)false |
dc.title.none.fl_str_mv |
Use of the linear spectral mixture model in the Saracá-Taquera National Forest Use of the linear spectral mixture model in the Saracá-Taquera National Forest |
title |
Use of the linear spectral mixture model in the Saracá-Taquera National Forest |
spellingShingle |
Use of the linear spectral mixture model in the Saracá-Taquera National Forest Sato, Michel Keisuke fraction-image forage index spectral index landsat 8 remote sense Forest Protection Remote Sensing Spectral Mixture Linear Model Digital Image Processing Spectral Index of Forest Degradation imagem-fração índice espectral de degradação florestal landsat 8 sensoriamento remoto Proteção Florestal Sensoriamento Remoto Modelo Linear de Mistura Espectral Processamento Digital de Imagens Índice Espectral de Degradação Florestal |
title_short |
Use of the linear spectral mixture model in the Saracá-Taquera National Forest |
title_full |
Use of the linear spectral mixture model in the Saracá-Taquera National Forest |
title_fullStr |
Use of the linear spectral mixture model in the Saracá-Taquera National Forest |
title_full_unstemmed |
Use of the linear spectral mixture model in the Saracá-Taquera National Forest |
title_sort |
Use of the linear spectral mixture model in the Saracá-Taquera National Forest |
author |
Sato, Michel Keisuke |
author_facet |
Sato, Michel Keisuke Corrêa Soares, João Almiro Rocha, Bruna Naiara Furtado Lima, Cássio |
author_role |
author |
author2 |
Corrêa Soares, João Almiro Rocha, Bruna Naiara Furtado Lima, Cássio |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Sato, Michel Keisuke Corrêa Soares, João Almiro Rocha, Bruna Naiara Furtado Lima, Cássio |
dc.subject.por.fl_str_mv |
fraction-image forage index spectral index landsat 8 remote sense Forest Protection Remote Sensing Spectral Mixture Linear Model Digital Image Processing Spectral Index of Forest Degradation imagem-fração índice espectral de degradação florestal landsat 8 sensoriamento remoto Proteção Florestal Sensoriamento Remoto Modelo Linear de Mistura Espectral Processamento Digital de Imagens Índice Espectral de Degradação Florestal |
topic |
fraction-image forage index spectral index landsat 8 remote sense Forest Protection Remote Sensing Spectral Mixture Linear Model Digital Image Processing Spectral Index of Forest Degradation imagem-fração índice espectral de degradação florestal landsat 8 sensoriamento remoto Proteção Florestal Sensoriamento Remoto Modelo Linear de Mistura Espectral Processamento Digital de Imagens Índice Espectral de Degradação Florestal |
description |
The Saracá-Taquera Conservation Unit is one of the most exuberant National Forests, rich in biodiversity and with a high potential for the use of natural resources. The objective of this study was to identify signs from forest exploiting and activities with potential for degradation in the Saracá-Taquera National Forest (FLONA-ST), using the linear spectral mixture model (LSMM) in an image recorded in 2020. The study was carried out at FLONA-ST, located in the mesoregion of the Lower Amazon. The images were acquired with the Geological Service of the United States. The collected scenes, 228/061 and 229/061, were submitted to compositions of bands 6, 5, and 4 of Landsat 8, mosaic, and the image clipping corresponding to the area of FLONA. The LSMM was applied and the Spectral Index of Forest Degradation (DEGRADI) was determined. Then, the technique of slicing and vectoring of images was applied, for further classification based on visual interpretation. The use of LSMM and DEGRADI were able to identify the deforested areas in FLONA-ST. In general, FLONA was predominant in areas covered with dense and heterogeneous vegetation. However, areas with exposed soil were observed in the central, north, northeast, southeast, and south parts, whether intended for mining, agricultural activities, housing, or for the exploitation of forest resources in FLONA. The forest exploitation in FLONA was observed, mostly, within the Forest Management Units, where exploration caused by disordered and geometric selective logging was found. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-10-28 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion text; Image texto; imagem |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://ajaes.ufra.edu.br/index.php/ajaes/article/view/3424 |
url |
https://ajaes.ufra.edu.br/index.php/ajaes/article/view/3424 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://ajaes.ufra.edu.br/index.php/ajaes/article/view/3424/1628 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal Rural da Amazônia/UFRA |
publisher.none.fl_str_mv |
Universidade Federal Rural da Amazônia/UFRA |
dc.source.none.fl_str_mv |
Amazonian Journal of Agricultural Sciences Journal of Agricultural and Environmental Sciences; Vol 64 (2021): RCA AJAES Revista de Ciências Agrárias Amazonian Journal of Agricultural and Environmental Sciences; v. 64 (2021): RCA AJAES 2177-8760 1517-591X reponame:Revista de Ciências Agrárias (Belém. Online) instname:Universidade Federal Rural da Amazônia (UFRA) instacron:UFRA |
instname_str |
Universidade Federal Rural da Amazônia (UFRA) |
instacron_str |
UFRA |
institution |
UFRA |
reponame_str |
Revista de Ciências Agrárias (Belém. Online) |
collection |
Revista de Ciências Agrárias (Belém. Online) |
repository.name.fl_str_mv |
Revista de Ciências Agrárias (Belém. Online) - Universidade Federal Rural da Amazônia (UFRA) |
repository.mail.fl_str_mv |
allan.lobato@ufra.edu.br || ajaes.suporte@gmail.com |
_version_ |
1797231630363918336 |