Caracterização e mapeamento biofísico ambiental da bacia hidrográfica do rio vermelho a partir de dados remotamente sensoriados
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFG |
dARK ID: | ark:/38995/0013000006w3f |
Texto Completo: | http://repositorio.bc.ufg.br/tede/handle/tede/4084 |
Resumo: | The agricultural expansion in the Brazilian Cerrado represents nowadays more than half of the total biome area, where conversion of the natural vegetation to pasturelands is the main dynamics imposed by the productive sector along the relatively recent historical occupation process. Such transformations tend to create distinct spatial patterns regarding the biophysical behavior of the main existent vegetation formations, which can be identified and discriminated through a variety of available remote sensing products. This study, focused on the rio Vermelho watershed, a representative unit of the Cerrado biome, and considering a variety of satellite data for the 2001 – 2011 period, pursued a detailed analysis of the biophysical responses in face of the historical processes that determined and shaped the landscape transformations. Specifically, the following datasets were utilized: MODIS (vegetation index, evapotranspiration and primary productivity) and TRMM (Tropical Rainfall Measurement Mission) precipitation. Our results indicated that climatic factors, such as seasonality, have a direct influence on biomass levels of key vegetation formations, particularly those with shallow root systems, for which reductions in radiometric values, as high as 50%, could be observed during the dry season. In fact, natural vegetation areas, comparatively to areas dominated by cultivated pastures, show very distinct and significant biophysical behavior (p < 0.05). Likewise, two major landscapes could be identified, i.e. “Region 1” and “Region 2”, where converted and remnant vegetation areas predominate, respectively. The distribution of natural and cultivated pastures seems to be related to local edafoclimatic factors, such as soil (depth/lithic content) and water availability, which explain the occurrence of most grass species. Based on field biomass, it is possible to say: 1) cultivated pastures found in “Region 1” are slightly more productive comparatily to those from “Region 2” (for both dry- and wet-seasons) and 2) there is a correspondence between “natural” and “cultivated” green biomass during the dry season, as opposed to the wet season. However, and based on the seasonal moderate spatial resolution MODIS images, it is not possible to separate between natural and cultivated pastures. In fact, such separation can be accomplished via the supervised classification (Support Vector Machine) of medium spatial resolution imagery (Landsat). Based on high spatial resolution (5m) RapidEye/BlackBridge images, it was produced a land cover / land use map for the entire basin at the 1:50.000 scale, in which it was possible to discriminate the major converted and natural physiognomies, and distinct grass species, in particular (Overall Accuracy ~ 90% and Kappa = 0.83). |
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Ferreira Júnior, Laerte Guimarãeshttp://lattes.cnpq.br/8647270006257055Brreira, Celene Cunha Monteiro AntunesOliveira, José deVieira, Pedro AlvesBrito, Jorge Luíshttp://lattes.cnpq.br/0760329930979190Santos, Pablo Santana2015-02-05T09:54:10Z2014-05-15SANTOS, Pablo Santana. Caracterização e mapeamento biofísico ambiental da bacia hidrográfica do rio vermelho a partir de dados remotamente sensoriados. 2014. 149 f. Tese (Doutorado em Geografia) - Universidade Federal de Goiás, Goiânia, 2014.http://repositorio.bc.ufg.br/tede/handle/tede/4084ark:/38995/0013000006w3fThe agricultural expansion in the Brazilian Cerrado represents nowadays more than half of the total biome area, where conversion of the natural vegetation to pasturelands is the main dynamics imposed by the productive sector along the relatively recent historical occupation process. Such transformations tend to create distinct spatial patterns regarding the biophysical behavior of the main existent vegetation formations, which can be identified and discriminated through a variety of available remote sensing products. This study, focused on the rio Vermelho watershed, a representative unit of the Cerrado biome, and considering a variety of satellite data for the 2001 – 2011 period, pursued a detailed analysis of the biophysical responses in face of the historical processes that determined and shaped the landscape transformations. Specifically, the following datasets were utilized: MODIS (vegetation index, evapotranspiration and primary productivity) and TRMM (Tropical Rainfall Measurement Mission) precipitation. Our results indicated that climatic factors, such as seasonality, have a direct influence on biomass levels of key vegetation formations, particularly those with shallow root systems, for which reductions in radiometric values, as high as 50%, could be observed during the dry season. In fact, natural vegetation areas, comparatively to areas dominated by cultivated pastures, show very distinct and significant biophysical behavior (p < 0.05). Likewise, two major landscapes could be identified, i.e. “Region 1” and “Region 2”, where converted and remnant vegetation areas predominate, respectively. The distribution of natural and cultivated pastures seems to be related to local edafoclimatic factors, such as soil (depth/lithic content) and water availability, which explain the occurrence of most grass species. Based on field biomass, it is possible to say: 1) cultivated pastures found in “Region 1” are slightly more productive comparatily to those from “Region 2” (for both dry- and wet-seasons) and 2) there is a correspondence between “natural” and “cultivated” green biomass during the dry season, as opposed to the wet season. However, and based on the seasonal moderate spatial resolution MODIS images, it is not possible to separate between natural and cultivated pastures. In fact, such separation can be accomplished via the supervised classification (Support Vector Machine) of medium spatial resolution imagery (Landsat). Based on high spatial resolution (5m) RapidEye/BlackBridge images, it was produced a land cover / land use map for the entire basin at the 1:50.000 scale, in which it was possible to discriminate the major converted and natural physiognomies, and distinct grass species, in particular (Overall Accuracy ~ 90% and Kappa = 0.83).A expansão da atividade agropecuária no Cerrado brasileiro representa hoje mais da metade da área total deste bioma, onde a conversão das áreas naturais em pastagens cultivadas foi a principal dinâmica imposta pelo setor produtivo ao longo de um processo histórico de ocupação relativamente recente. Tais transformações tendem a resultar em padrões espaciais distintos quanto ao comportamento biofísico das principais formações vegetais existentes, os quais podem ser identificados e discriminados através dos vários produtos de sensoriamento remoto disponíveis. O presente trabalho, ao utilizar a bacia hidrográfica do rio Vermelho como unidade experimental do bioma Cerrado, teve como objetivo principal realizar uma análise detalhada das respostas biofísicas frente aos processos históricos que condicionaram as transformações na paisagem, considerando o período entre 2001 a 2011, e uma ampla base de dados satelitária, obtida a partir dos produtos MODIS (índice de vegetação, evapotranspiração, produtividade primária) e TRMM (Tropical Rainfall Measurement Mission/precipitação). Os nossos resultados evidenciam que fatores climáticos, a exemplo da sazonalidade, tem uma influência direta na biomassa das principais formações vegetais, principalmente àquelas que apresentam sistemas radiculares superficiais, com reduções nos valores radiométricos de até 50% durante o período da seca. De forma significativa, as áreas de vegetação natural, comparadas às áreas de pastagens cultivadas, apresentaram comportamentos distintos do ponto de vista biofísico (p < 0,05). Em fato, dois macroambientes puderam ser definidos para a área de estudo, onde predominam a ocupação antrópica (“Região 1”) e a vegetação natural remanescente (Região 2), respectivamente. A distribuição das pastagens cultivadas e naturais está associada a fatores edafoclimáticos locais, como características de solo (profundidade/pedregosidade) e disponibilidade hídrica, os quais explicam a ocorrência da maioria das espécies forrageiras. Com base nos dados de biomassa coletados em campo, é possível afirmar: 1) as pastagens cultivadas encontradas na “Região 1” são ligeiramente mais produtivas do que as encontradas na “Região 2”, tanto no período seco quanto chuvoso, e 2) há uma correspondência entre a biomassa verde encontrada no período seco para as duas categorias de pastagens, ao contrário do observado no período chuvoso. Entretanto, e tendo por base as imagens biofísicas sazonais de resolução espacial moderada (MODIS), não é possível separar entre pastagens nativas e cultivadas. Por sua vez, esta separação se mostra possível através da classificação supervisionada (Support Vector Machine) de imagens de resolução espacial média (Landsat). Com base em imagens RapidEye/BlackBridge, com resolução espacial de 5m, foi produzido um mapa de cobertura e uso da terra à escala de 1:50.000, no qual foi possível separar as áreas de pastagens quanto à sua tipologia, bem como individualizálas em outras formas de uso e fito-fisionomias remanescentes (Acurácia Total ~ 90% e Kappa = 0,83).Submitted by Luanna Matias (lua_matias@yahoo.com.br) on 2015-02-04T19:08:20Z No. of bitstreams: 3 Tese - Pablo Santana Santos - 2014 - Parte 01.pdf: 5282585 bytes, checksum: fab627afa4b6a3b55752f51b90659610 (MD5) Tese - Pablo Santana Santos - 2014 - Parte 02.pdf: 3067324 bytes, checksum: d46d29a129169e109e2f94a8068ec633 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5)Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2015-02-05T09:54:10Z (GMT) No. of bitstreams: 3 Tese - Pablo Santana Santos - 2014 - Parte 01.pdf: 5282585 bytes, checksum: fab627afa4b6a3b55752f51b90659610 (MD5) Tese - Pablo Santana Santos - 2014 - Parte 02.pdf: 3067324 bytes, checksum: d46d29a129169e109e2f94a8068ec633 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5)Made available in DSpace on 2015-02-05T09:54:10Z (GMT). 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dc.title.eng.fl_str_mv |
Caracterização e mapeamento biofísico ambiental da bacia hidrográfica do rio vermelho a partir de dados remotamente sensoriados |
dc.title.alternative.eng.fl_str_mv |
Characterization and mapping biophsical environment of the rio Vermelho watershed from remotely sensed data |
title |
Caracterização e mapeamento biofísico ambiental da bacia hidrográfica do rio vermelho a partir de dados remotamente sensoriados |
spellingShingle |
Caracterização e mapeamento biofísico ambiental da bacia hidrográfica do rio vermelho a partir de dados remotamente sensoriados Santos, Pablo Santana Sensoriamento remoto Pastagem Análise biofísica Remote sensing Pasture Biophysical analysis CONSERVACAO DA NATUREZA::CONSERVACAO DE BACIAS HIDROGRAFICAS |
title_short |
Caracterização e mapeamento biofísico ambiental da bacia hidrográfica do rio vermelho a partir de dados remotamente sensoriados |
title_full |
Caracterização e mapeamento biofísico ambiental da bacia hidrográfica do rio vermelho a partir de dados remotamente sensoriados |
title_fullStr |
Caracterização e mapeamento biofísico ambiental da bacia hidrográfica do rio vermelho a partir de dados remotamente sensoriados |
title_full_unstemmed |
Caracterização e mapeamento biofísico ambiental da bacia hidrográfica do rio vermelho a partir de dados remotamente sensoriados |
title_sort |
Caracterização e mapeamento biofísico ambiental da bacia hidrográfica do rio vermelho a partir de dados remotamente sensoriados |
author |
Santos, Pablo Santana |
author_facet |
Santos, Pablo Santana |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Ferreira Júnior, Laerte Guimarães |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/8647270006257055 |
dc.contributor.referee1.fl_str_mv |
Brreira, Celene Cunha Monteiro Antunes |
dc.contributor.referee2.fl_str_mv |
Oliveira, José de |
dc.contributor.referee3.fl_str_mv |
Vieira, Pedro Alves |
dc.contributor.referee4.fl_str_mv |
Brito, Jorge Luís |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/0760329930979190 |
dc.contributor.author.fl_str_mv |
Santos, Pablo Santana |
contributor_str_mv |
Ferreira Júnior, Laerte Guimarães Brreira, Celene Cunha Monteiro Antunes Oliveira, José de Vieira, Pedro Alves Brito, Jorge Luís |
dc.subject.por.fl_str_mv |
Sensoriamento remoto Pastagem Análise biofísica |
topic |
Sensoriamento remoto Pastagem Análise biofísica Remote sensing Pasture Biophysical analysis CONSERVACAO DA NATUREZA::CONSERVACAO DE BACIAS HIDROGRAFICAS |
dc.subject.eng.fl_str_mv |
Remote sensing Pasture Biophysical analysis |
dc.subject.cnpq.fl_str_mv |
CONSERVACAO DA NATUREZA::CONSERVACAO DE BACIAS HIDROGRAFICAS |
description |
The agricultural expansion in the Brazilian Cerrado represents nowadays more than half of the total biome area, where conversion of the natural vegetation to pasturelands is the main dynamics imposed by the productive sector along the relatively recent historical occupation process. Such transformations tend to create distinct spatial patterns regarding the biophysical behavior of the main existent vegetation formations, which can be identified and discriminated through a variety of available remote sensing products. This study, focused on the rio Vermelho watershed, a representative unit of the Cerrado biome, and considering a variety of satellite data for the 2001 – 2011 period, pursued a detailed analysis of the biophysical responses in face of the historical processes that determined and shaped the landscape transformations. Specifically, the following datasets were utilized: MODIS (vegetation index, evapotranspiration and primary productivity) and TRMM (Tropical Rainfall Measurement Mission) precipitation. Our results indicated that climatic factors, such as seasonality, have a direct influence on biomass levels of key vegetation formations, particularly those with shallow root systems, for which reductions in radiometric values, as high as 50%, could be observed during the dry season. In fact, natural vegetation areas, comparatively to areas dominated by cultivated pastures, show very distinct and significant biophysical behavior (p < 0.05). Likewise, two major landscapes could be identified, i.e. “Region 1” and “Region 2”, where converted and remnant vegetation areas predominate, respectively. The distribution of natural and cultivated pastures seems to be related to local edafoclimatic factors, such as soil (depth/lithic content) and water availability, which explain the occurrence of most grass species. Based on field biomass, it is possible to say: 1) cultivated pastures found in “Region 1” are slightly more productive comparatily to those from “Region 2” (for both dry- and wet-seasons) and 2) there is a correspondence between “natural” and “cultivated” green biomass during the dry season, as opposed to the wet season. However, and based on the seasonal moderate spatial resolution MODIS images, it is not possible to separate between natural and cultivated pastures. In fact, such separation can be accomplished via the supervised classification (Support Vector Machine) of medium spatial resolution imagery (Landsat). Based on high spatial resolution (5m) RapidEye/BlackBridge images, it was produced a land cover / land use map for the entire basin at the 1:50.000 scale, in which it was possible to discriminate the major converted and natural physiognomies, and distinct grass species, in particular (Overall Accuracy ~ 90% and Kappa = 0.83). |
publishDate |
2014 |
dc.date.issued.fl_str_mv |
2014-05-15 |
dc.date.accessioned.fl_str_mv |
2015-02-05T09:54:10Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
SANTOS, Pablo Santana. Caracterização e mapeamento biofísico ambiental da bacia hidrográfica do rio vermelho a partir de dados remotamente sensoriados. 2014. 149 f. Tese (Doutorado em Geografia) - Universidade Federal de Goiás, Goiânia, 2014. |
dc.identifier.uri.fl_str_mv |
http://repositorio.bc.ufg.br/tede/handle/tede/4084 |
dc.identifier.dark.fl_str_mv |
ark:/38995/0013000006w3f |
identifier_str_mv |
SANTOS, Pablo Santana. Caracterização e mapeamento biofísico ambiental da bacia hidrográfica do rio vermelho a partir de dados remotamente sensoriados. 2014. 149 f. Tese (Doutorado em Geografia) - Universidade Federal de Goiás, Goiânia, 2014. ark:/38995/0013000006w3f |
url |
http://repositorio.bc.ufg.br/tede/handle/tede/4084 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.program.fl_str_mv |
7888271059505704147 |
dc.relation.confidence.fl_str_mv |
600 600 600 600 |
dc.relation.department.fl_str_mv |
4536785967207850203 |
dc.relation.cnpq.fl_str_mv |
666243318065955022 |
dc.relation.sponsorship.fl_str_mv |
-2555911436985713659 |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Goiás |
dc.publisher.program.fl_str_mv |
Programa de Pós-graduação em Geografia (IESA) |
dc.publisher.initials.fl_str_mv |
UFG |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Instituto de Estudos Socioambientais - IESA (RG) |
publisher.none.fl_str_mv |
Universidade Federal de Goiás |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFG instname:Universidade Federal de Goiás (UFG) instacron:UFG |
instname_str |
Universidade Federal de Goiás (UFG) |
instacron_str |
UFG |
institution |
UFG |
reponame_str |
Repositório Institucional da UFG |
collection |
Repositório Institucional da UFG |
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tasesdissertacoes.bc@ufg.br |
_version_ |
1815172583330414592 |