ANALYSIS OF THE DEGREE OF GRASSLAND DEGRADATION USING REMOTE SENSING

Detalhes bibliográficos
Autor(a) principal: Santos Motta, Jaiza
Data de Publicação: 2021
Outros Autores: Encina, César Claudio Cáceres, Guaraldo, Eliane, Gonçalves, Ariadne Barbosa, Gamarra, Roberto Macedo, Paranhos Filho, Antonio Conceição
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Caminhos de Geografia
Texto Completo: https://seer.ufu.br/index.php/caminhosdegeografia/article/view/54817
Resumo: The objective of this study is to adapt the calculations of the Pasture Degradation Index (GDI) to the Brazilian savannah using medium spatial resolution satellite image for the dry season. Vegetation cover is the main evaluation parameter used to calculate the GDI. The extreme ranges of the grazing class were determined by the NDVI histogram of a single date. Pasture cover was distinguished into five classes called Vegetable Pasture Cover (GVC), derived from NDVI and compared with five other classes derived from field photographs, named Green Coverage Percentage (GCP). The similarity between GVC and GVP demonstrated that GVC can be used to classify pasture cover. As a product of GVC, GDI was obtained. The GDI showed that pasture degradation in Paraíso das Águas is very serious. Extremely severe and Severe degradation occupy 9.28% and 25.22% of the study area, moderate and light degradation of pasture occupy 8.29% and 4.50%, respectively, and the non-degradation area covers 1.43 % of pastures. The results suggest the possibility of applying the GDI, originally developed for natural fields and multitemporal remote sensing data, to evaluate the conditions of the tropical savanna planted fields by means of a unique image.
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spelling ANALYSIS OF THE DEGREE OF GRASSLAND DEGRADATION USING REMOTE SENSINGANALYSIS OF THE DEGREE OF GRASSLAND DEGRADATION USING REMOTE SENSINGCrescimento urbano.Ordenamento territorial.Instrumentos legais urbanos.Especulação imobiliária.Urban growth.Spatial planning.Urban legal instruments.Real estate speculation.The objective of this study is to adapt the calculations of the Pasture Degradation Index (GDI) to the Brazilian savannah using medium spatial resolution satellite image for the dry season. Vegetation cover is the main evaluation parameter used to calculate the GDI. The extreme ranges of the grazing class were determined by the NDVI histogram of a single date. Pasture cover was distinguished into five classes called Vegetable Pasture Cover (GVC), derived from NDVI and compared with five other classes derived from field photographs, named Green Coverage Percentage (GCP). The similarity between GVC and GVP demonstrated that GVC can be used to classify pasture cover. As a product of GVC, GDI was obtained. The GDI showed that pasture degradation in Paraíso das Águas is very serious. Extremely severe and Severe degradation occupy 9.28% and 25.22% of the study area, moderate and light degradation of pasture occupy 8.29% and 4.50%, respectively, and the non-degradation area covers 1.43 % of pastures. The results suggest the possibility of applying the GDI, originally developed for natural fields and multitemporal remote sensing data, to evaluate the conditions of the tropical savanna planted fields by means of a unique image.O objetivo deste estudo é adaptar os cálculos do Índice de Degradação de Pastagens (GDI) à savana brasileira usando imagem de satélite de média resolução espacial para estação seca. A cobertura vegetal é o principal parâmetro de avaliação usado para calcular o GDI. Os intervalos extremos da classe de pastagem foram determinados pelo histograma do NDVI. A cobertura de pastagem foi distinguida em cinco classes denominadas Cobertura Vegetal de Pastagem (GVC), derivada do NDVI e correlacionada com outras cinco classes derivadas de fotografias de campo, nomeadas de Porcentagem de Coberta Verde (GCP). A semelhança entre a GVC e a GVP demonstrou que a GVC pode ser usada para classificar a cobertura de pastagem. Como produto da GVC, foi obtido o GDI. O GDI demonstrou que a degradação de pastagem em Paraíso das Águas é muito séria. Degradação Extremamente Severa e Severa e ocupam 9,28% e 25,22%, da área de estudo, degradação de pastagem Moderada e Leve ocupam 8.29% e 4,50%, respectivamente, e a área não degrada cobrem 0,9% das pastagens. Os resultados sugerem a possibilidade de aplicar o GDI, originalmente desenvolvido para pastagens naturais e dados de sensoriamento remoto multitemporal, para avaliar as condições de pastagens plantadas em savanas tropicais.EDUFU - Editora da Universidade Federal de Uberlândia2021-04-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAvaliado pelos paresapplication/pdfhttps://seer.ufu.br/index.php/caminhosdegeografia/article/view/5481710.14393/RCG228054817Caminhos de Geografia; Vol. 22 No. 80 (2021): Abril; 201-219Caminhos de Geografia; Vol. 22 Núm. 80 (2021): Abril; 201-219Caminhos de Geografia; v. 22 n. 80 (2021): Abril; 201-2191678-6343reponame:Caminhos de Geografiainstname:Universidade Federal de Uberlândia (UFU)instacron:UFUenghttps://seer.ufu.br/index.php/caminhosdegeografia/article/view/54817/31417Copyright (c) 2021 Jaiza Santos Motta, César Claudio Cáceres Encina, Eliane Guaraldo, Ariadne Barbosa Gonçalves, Roberto Macedo Gamarra, Antonio Conceição Paranhos Filhoinfo:eu-repo/semantics/openAccessSantos Motta, JaizaEncina, César Claudio Cáceres Guaraldo, ElianeGonçalves, Ariadne Barbosa Gamarra, Roberto Macedo Paranhos Filho, Antonio Conceição 2021-05-24T15:25:55Zoai:ojs.www.seer.ufu.br:article/54817Revistahttps://seer.ufu.br/index.php/caminhosdegeografia/indexPUBhttp://www.seer.ufu.br/index.php/caminhosdegeografia/oaiflaviasantosgeo@gmail.com1678-63431678-6343opendoar:2021-05-24T15:25:55Caminhos de Geografia - Universidade Federal de Uberlândia (UFU)false
dc.title.none.fl_str_mv ANALYSIS OF THE DEGREE OF GRASSLAND DEGRADATION USING REMOTE SENSING
ANALYSIS OF THE DEGREE OF GRASSLAND DEGRADATION USING REMOTE SENSING
title ANALYSIS OF THE DEGREE OF GRASSLAND DEGRADATION USING REMOTE SENSING
spellingShingle ANALYSIS OF THE DEGREE OF GRASSLAND DEGRADATION USING REMOTE SENSING
Santos Motta, Jaiza
Crescimento urbano.
Ordenamento territorial.
Instrumentos legais urbanos.
Especulação imobiliária.
Urban growth.
Spatial planning.
Urban legal instruments.
Real estate speculation.
title_short ANALYSIS OF THE DEGREE OF GRASSLAND DEGRADATION USING REMOTE SENSING
title_full ANALYSIS OF THE DEGREE OF GRASSLAND DEGRADATION USING REMOTE SENSING
title_fullStr ANALYSIS OF THE DEGREE OF GRASSLAND DEGRADATION USING REMOTE SENSING
title_full_unstemmed ANALYSIS OF THE DEGREE OF GRASSLAND DEGRADATION USING REMOTE SENSING
title_sort ANALYSIS OF THE DEGREE OF GRASSLAND DEGRADATION USING REMOTE SENSING
author Santos Motta, Jaiza
author_facet Santos Motta, Jaiza
Encina, César Claudio Cáceres
Guaraldo, Eliane
Gonçalves, Ariadne Barbosa
Gamarra, Roberto Macedo
Paranhos Filho, Antonio Conceição
author_role author
author2 Encina, César Claudio Cáceres
Guaraldo, Eliane
Gonçalves, Ariadne Barbosa
Gamarra, Roberto Macedo
Paranhos Filho, Antonio Conceição
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Santos Motta, Jaiza
Encina, César Claudio Cáceres
Guaraldo, Eliane
Gonçalves, Ariadne Barbosa
Gamarra, Roberto Macedo
Paranhos Filho, Antonio Conceição
dc.subject.por.fl_str_mv Crescimento urbano.
Ordenamento territorial.
Instrumentos legais urbanos.
Especulação imobiliária.
Urban growth.
Spatial planning.
Urban legal instruments.
Real estate speculation.
topic Crescimento urbano.
Ordenamento territorial.
Instrumentos legais urbanos.
Especulação imobiliária.
Urban growth.
Spatial planning.
Urban legal instruments.
Real estate speculation.
description The objective of this study is to adapt the calculations of the Pasture Degradation Index (GDI) to the Brazilian savannah using medium spatial resolution satellite image for the dry season. Vegetation cover is the main evaluation parameter used to calculate the GDI. The extreme ranges of the grazing class were determined by the NDVI histogram of a single date. Pasture cover was distinguished into five classes called Vegetable Pasture Cover (GVC), derived from NDVI and compared with five other classes derived from field photographs, named Green Coverage Percentage (GCP). The similarity between GVC and GVP demonstrated that GVC can be used to classify pasture cover. As a product of GVC, GDI was obtained. The GDI showed that pasture degradation in Paraíso das Águas is very serious. Extremely severe and Severe degradation occupy 9.28% and 25.22% of the study area, moderate and light degradation of pasture occupy 8.29% and 4.50%, respectively, and the non-degradation area covers 1.43 % of pastures. The results suggest the possibility of applying the GDI, originally developed for natural fields and multitemporal remote sensing data, to evaluate the conditions of the tropical savanna planted fields by means of a unique image.
publishDate 2021
dc.date.none.fl_str_mv 2021-04-05
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Avaliado pelos pares
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://seer.ufu.br/index.php/caminhosdegeografia/article/view/54817
10.14393/RCG228054817
url https://seer.ufu.br/index.php/caminhosdegeografia/article/view/54817
identifier_str_mv 10.14393/RCG228054817
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://seer.ufu.br/index.php/caminhosdegeografia/article/view/54817/31417
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv EDUFU - Editora da Universidade Federal de Uberlândia
publisher.none.fl_str_mv EDUFU - Editora da Universidade Federal de Uberlândia
dc.source.none.fl_str_mv Caminhos de Geografia; Vol. 22 No. 80 (2021): Abril; 201-219
Caminhos de Geografia; Vol. 22 Núm. 80 (2021): Abril; 201-219
Caminhos de Geografia; v. 22 n. 80 (2021): Abril; 201-219
1678-6343
reponame:Caminhos de Geografia
instname:Universidade Federal de Uberlândia (UFU)
instacron:UFU
instname_str Universidade Federal de Uberlândia (UFU)
instacron_str UFU
institution UFU
reponame_str Caminhos de Geografia
collection Caminhos de Geografia
repository.name.fl_str_mv Caminhos de Geografia - Universidade Federal de Uberlândia (UFU)
repository.mail.fl_str_mv flaviasantosgeo@gmail.com
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