2017
DOI: 10.5380/raega.v42i0.45524
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Identificação De Áreas Com Perda De Solo Acima Do Tolerável Usando Ndvi Para O Cálculo Do Fator C Da Usle

Abstract: RESUMOUm dos principais problemas relacionados à conservação dos solos das bacias hidrográficas é a erosão hídrica do solo com o consequente transporte de partículas do solo aos corpos hídricos, especialmente em regiões com presença de atividades agrícolas. Portanto, o presente estudo teve como objetivo demonstrar a aplicação de uma metodologia para calcular o fator C por meio do Normalized Difference Vegetation Index (NDVI) utilizando técnicas de geoprocessamento e modelagem matemática para quantificar a perd… Show more

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Cited by 9 publications
(7 citation statements)
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“…The C factor derived from NDVI (pixel-a-pixel) enabled a more accurate coverage analysis, rather than the establishment of a single C factor per coverage class. C factor values ranged from 0.10 to 0.68 (Figure 4C) and it was found that the variations in coverage density in the different plant classes present in the sub-basin were adequately represented by NDVI, as that's also observed in the studies by Carvalho et al (2014), when estimating the C factor using NDVI for the RUSLE model, and Silva et al (2013) and Silva et al (2017) for the USLE model. In the analysis of the C factor derived from the intensity of the photosynthetic activities by the NDVI, it was possible to point out that the vegetation with the highest quantity of biomass, identified by the darker shades of gray (lower values), are more frequent in the southern part of the sub-basin that is mainly occupied by the native FESDA vegetation along the Mogi Guaçu River's margins (Figure 2C).…”
Section: R K Ls and C Factorssupporting
confidence: 58%
“…The C factor derived from NDVI (pixel-a-pixel) enabled a more accurate coverage analysis, rather than the establishment of a single C factor per coverage class. C factor values ranged from 0.10 to 0.68 (Figure 4C) and it was found that the variations in coverage density in the different plant classes present in the sub-basin were adequately represented by NDVI, as that's also observed in the studies by Carvalho et al (2014), when estimating the C factor using NDVI for the RUSLE model, and Silva et al (2013) and Silva et al (2017) for the USLE model. In the analysis of the C factor derived from the intensity of the photosynthetic activities by the NDVI, it was possible to point out that the vegetation with the highest quantity of biomass, identified by the darker shades of gray (lower values), are more frequent in the southern part of the sub-basin that is mainly occupied by the native FESDA vegetation along the Mogi Guaçu River's margins (Figure 2C).…”
Section: R K Ls and C Factorssupporting
confidence: 58%
“…A aplicação de geotecnologias, como o sensoriamento remoto, permite a realização de monitoramentos através de series temporais sem a necessidade de coletas em campo. Este procedimento é imprescindível para que possam ser realizadas análises temporais reduzindo a necessidade de coletas de dados in situ (Meira et al, 2016;Sales et al, 2017;Silva et al, 2017), diminuindo com isso os custos no monitoramento e avaliação dos recursos hídricos e possibilitando a obtenção de informações que auxiliam na gestão estratégica destes. Nesse contexto, objetivou-se avaliar a área dos reservatórios em uma bacia hidrográfica do semiárido comparando informações obtidas a partir de índices espectrais com dados da classificação do MapBiomas.…”
Section: Introductionunclassified
“…Inúmeros trabalhos foram desenvolvidos para estimar a perda de solo com base na USLE no Brasil (e.g., Braz et al, 2014;Volk e Cogo, 2014;Graça et al, 2015;Bagio et a., 2016;Medeiros et al, 2016;Silva et al, 2017;Schick et al, 2017;Cassol et al, 2018;Weiler et al, 2019;Avanzi et al, 2019) e no exterior (e.g,. Zola e Juvenal, 2016;Ali e Hagos, 2016;Tuchtenhagen et al, 2017;Schmidt et al, 2019), mas o diagnóstico por si só das áreas suscetíveis às perdas não é o bastante.…”
Section: Introductionunclassified