Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using rusle, remote sensing and GIS.

Detalhes bibliográficos
Autor(a) principal: LU, D.
Data de Publicação: 2004
Outros Autores: LI, G., VALLADARES, G. S., BATISTELLA, M.
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/994981
Resumo: This article discusses research in which the authors applied the Revised Universal Soil Loss Equation (RUSLE), remote sensing, and geographical information system (GIS) to the maping of soil erosion risk in Brazilian Amazonia. Soil map and soil survey data were used to develop the soil erodibility factor (K), and a digital elevation model image was used to generate the topographic factor (LS). The cover-management factor (C) was developed based on vegetation, shade, and soil fraction images derived from spectral mixture analysis of a Landsat Enhanced Thematic Mapper Plus image. Assuming the same climatic conditions and no support practice in the study area, the rainfall?runoff erosivity (R) and the support practice (P) factors were not used. The majority of the study area has K values of less than 0.2, LS values of less than 2.5, and C values of less than 0.25. A soil erosion risk map with five classes (very low, low, medium, medium-high, and high) was produced based on the simplified RUSLE within the GIS environment, and was linked to land use and land cover (LULC) image to explore relationships between soil erosion risk and LULC distribution. The results indicate that most successional and mature forests are in very low and low erosion risk areas, while agroforestry and pasture are usually associated with medium to high risk areas. This research implies that remote sensing and GIS provide promising tools for evaluating and mapping soil erosion risk in Amazonia.
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spelling Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using rusle, remote sensing and GIS.Brazilian AmazoniaGISRUSLESoil erosion riskRemote sensingThis article discusses research in which the authors applied the Revised Universal Soil Loss Equation (RUSLE), remote sensing, and geographical information system (GIS) to the maping of soil erosion risk in Brazilian Amazonia. Soil map and soil survey data were used to develop the soil erodibility factor (K), and a digital elevation model image was used to generate the topographic factor (LS). The cover-management factor (C) was developed based on vegetation, shade, and soil fraction images derived from spectral mixture analysis of a Landsat Enhanced Thematic Mapper Plus image. Assuming the same climatic conditions and no support practice in the study area, the rainfall?runoff erosivity (R) and the support practice (P) factors were not used. The majority of the study area has K values of less than 0.2, LS values of less than 2.5, and C values of less than 0.25. A soil erosion risk map with five classes (very low, low, medium, medium-high, and high) was produced based on the simplified RUSLE within the GIS environment, and was linked to land use and land cover (LULC) image to explore relationships between soil erosion risk and LULC distribution. The results indicate that most successional and mature forests are in very low and low erosion risk areas, while agroforestry and pasture are usually associated with medium to high risk areas. This research implies that remote sensing and GIS provide promising tools for evaluating and mapping soil erosion risk in Amazonia.DENGSHENG LU, INDIANA UNIVERSITY; G. LI, INDIANA STATE UNIVERSITY; GUSTAVO S. VALLADARES, CNPM; MATEUS BATISTELLA, CNPM.LU, D.LI, G.VALLADARES, G. S.BATISTELLA, M.2014-09-15T11:11:11Z2014-09-15T11:11:11Z2014-09-1520042014-09-15T11:11:11Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleLand Degradation & Development, v. 15, p. 499-512, 2004.http://www.alice.cnptia.embrapa.br/alice/handle/doc/99498110.1002/ldr.634porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2017-08-16T00:06:10Zoai:www.alice.cnptia.embrapa.br:doc/994981Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542017-08-16T00:06:10falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-08-16T00:06:10Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using rusle, remote sensing and GIS.
title Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using rusle, remote sensing and GIS.
spellingShingle Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using rusle, remote sensing and GIS.
LU, D.
Brazilian Amazonia
GIS
RUSLE
Soil erosion risk
Remote sensing
title_short Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using rusle, remote sensing and GIS.
title_full Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using rusle, remote sensing and GIS.
title_fullStr Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using rusle, remote sensing and GIS.
title_full_unstemmed Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using rusle, remote sensing and GIS.
title_sort Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using rusle, remote sensing and GIS.
author LU, D.
author_facet LU, D.
LI, G.
VALLADARES, G. S.
BATISTELLA, M.
author_role author
author2 LI, G.
VALLADARES, G. S.
BATISTELLA, M.
author2_role author
author
author
dc.contributor.none.fl_str_mv DENGSHENG LU, INDIANA UNIVERSITY; G. LI, INDIANA STATE UNIVERSITY; GUSTAVO S. VALLADARES, CNPM; MATEUS BATISTELLA, CNPM.
dc.contributor.author.fl_str_mv LU, D.
LI, G.
VALLADARES, G. S.
BATISTELLA, M.
dc.subject.por.fl_str_mv Brazilian Amazonia
GIS
RUSLE
Soil erosion risk
Remote sensing
topic Brazilian Amazonia
GIS
RUSLE
Soil erosion risk
Remote sensing
description This article discusses research in which the authors applied the Revised Universal Soil Loss Equation (RUSLE), remote sensing, and geographical information system (GIS) to the maping of soil erosion risk in Brazilian Amazonia. Soil map and soil survey data were used to develop the soil erodibility factor (K), and a digital elevation model image was used to generate the topographic factor (LS). The cover-management factor (C) was developed based on vegetation, shade, and soil fraction images derived from spectral mixture analysis of a Landsat Enhanced Thematic Mapper Plus image. Assuming the same climatic conditions and no support practice in the study area, the rainfall?runoff erosivity (R) and the support practice (P) factors were not used. The majority of the study area has K values of less than 0.2, LS values of less than 2.5, and C values of less than 0.25. A soil erosion risk map with five classes (very low, low, medium, medium-high, and high) was produced based on the simplified RUSLE within the GIS environment, and was linked to land use and land cover (LULC) image to explore relationships between soil erosion risk and LULC distribution. The results indicate that most successional and mature forests are in very low and low erosion risk areas, while agroforestry and pasture are usually associated with medium to high risk areas. This research implies that remote sensing and GIS provide promising tools for evaluating and mapping soil erosion risk in Amazonia.
publishDate 2004
dc.date.none.fl_str_mv 2004
2014-09-15T11:11:11Z
2014-09-15T11:11:11Z
2014-09-15
2014-09-15T11:11:11Z
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Land Degradation & Development, v. 15, p. 499-512, 2004.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/994981
10.1002/ldr.634
identifier_str_mv Land Degradation & Development, v. 15, p. 499-512, 2004.
10.1002/ldr.634
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/994981
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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