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Registro Completo |
Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Pantanal. |
Data corrente: |
17/04/2023 |
Data da última atualização: |
27/10/2023 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
LOUZADA, R. O.; REIS, L. K.; DINIZ, J. M. F. de S.; ROQUE, F. de O.; GAMA, F. F.; BERGIER, I. |
Afiliação: |
RÔMULLO OLIVEIRA LOUZADA, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; LETÍCIA K. REIS, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; JULIANA MARIA FERREIRA DE SOUZA DINIZ, INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS; FÁBIO DE OLIVEIRA ROQUE, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; FÁBIO F. GAMA, INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS; IVAN BERGIER TAVARES DE LIMA, CPAP. |
Título: |
Combining optical and microwave remote sensing for assessing gullies in human-disturbed vegetated landscapes. |
Ano de publicação: |
2023 |
Fonte/Imprenta: |
Catena, v. 228, 107127, July 2023. |
ISSN: |
1872-6887 |
DOI: |
https://doi.org/10.1016/j.catena.2023.107127 |
Idioma: |
Inglês |
Conteúdo: |
The accurate assessment of the gully is key to stopping soil loss, especially in agricultural landscapes. This study aims to combine freely distributed remote sensing data for the evaluation of gullies located in a tropical watershed with a history of cattle production. Eighty-four vectorized gullies were defined in the Pirizal River basin, part of the highly eroded Upper Taquari (Brazil). We examined 56 variables from Sentinel-1/2 and ALOS-PALSAR-1 datasets, including SAR products and optical products like textures, water, vegetation, and terrain indices. Following a correlation analysis, 19 variables were selected for mapping in a Random Forest classifier by considering samples of active (soil) and stabilized (vegetation) pixels. The method reached an overall accuracy of 89%, in which soil abundance was responsible for 44% of the overall importance in the classification. Optical indices and texture products outperformed SAR products, whose importance represented only 14%. In the studied river basin, about 63% of the gullies were found stabilized, 30% in the process of stabilization, and only 7% active. The method proved effective, low cost, and promptly replicable to general river basins with gullies, mainly those in the tropics where vegetation has a significant role in soil loss control. |
Palavras-Chave: |
Classificação de floresta aleatória; Desmistura espectral; Detecção de ravinas; Gully detection; Random Forest classification; SAR; Spectral unmixing. |
Thesagro: |
Sensoriamento Remoto; Uso da Terra. |
Thesaurus Nal: |
Land use; Landscapes; Remote sensing. |
Categoria do assunto: |
-- X Pesquisa, Tecnologia e Engenharia |
Marc: |
LEADER 02359naa a2200349 a 4500 001 2157557 005 2023-10-27 008 2023 bl uuuu u00u1 u #d 022 $a1872-6887 024 7 $ahttps://doi.org/10.1016/j.catena.2023.107127$2DOI 100 1 $aLOUZADA, R. O. 245 $aCombining optical and microwave remote sensing for assessing gullies in human-disturbed vegetated landscapes.$h[electronic resource] 260 $c2023 520 $aThe accurate assessment of the gully is key to stopping soil loss, especially in agricultural landscapes. This study aims to combine freely distributed remote sensing data for the evaluation of gullies located in a tropical watershed with a history of cattle production. Eighty-four vectorized gullies were defined in the Pirizal River basin, part of the highly eroded Upper Taquari (Brazil). We examined 56 variables from Sentinel-1/2 and ALOS-PALSAR-1 datasets, including SAR products and optical products like textures, water, vegetation, and terrain indices. Following a correlation analysis, 19 variables were selected for mapping in a Random Forest classifier by considering samples of active (soil) and stabilized (vegetation) pixels. The method reached an overall accuracy of 89%, in which soil abundance was responsible for 44% of the overall importance in the classification. Optical indices and texture products outperformed SAR products, whose importance represented only 14%. In the studied river basin, about 63% of the gullies were found stabilized, 30% in the process of stabilization, and only 7% active. The method proved effective, low cost, and promptly replicable to general river basins with gullies, mainly those in the tropics where vegetation has a significant role in soil loss control. 650 $aLand use 650 $aLandscapes 650 $aRemote sensing 650 $aSensoriamento Remoto 650 $aUso da Terra 653 $aClassificação de floresta aleatória 653 $aDesmistura espectral 653 $aDetecção de ravinas 653 $aGully detection 653 $aRandom Forest classification 653 $aSAR 653 $aSpectral unmixing 700 1 $aREIS, L. K. 700 1 $aDINIZ, J. M. F. de S. 700 1 $aROQUE, F. de O. 700 1 $aGAMA, F. F. 700 1 $aBERGIER, I. 773 $tCatena$gv. 228, 107127, July 2023.
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