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| Demattê,José A. M.; Terra,Fabrício da Silva; Otto,Rafael; Toma,Raul Shiso; Pereira,Luiz Henrique; Nascimento,Alexandre Ferreira do; Bortoletto,Marco Antonio Melo. |
| ABSTRACT When the harvesting of sugarcane involves a mechanized process, plant residues remain on the soil surface, which makes proximal and remote sensing difficult to monitor. This study aimed to evaluate, under laboratory conditions, differences in the soil spectral behavior of surface layers Quartzipsamment and Hapludox soil classes due to increasing levels of sugarcane’s dry (DL) and green (GL) leaf cover on the soil. Soil cover was quantified by supervised classification of the digital images (photography) taken of the treatments. The spectral reflectance of the samples was obtained using the FieldSpec Pro (350 to 2500 nm). TM-Landsat bands were simulated and the Normalized Difference Vegetation Index (NDVI) and soil line were also determined. Soil... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: TM-Landsat; NDVI; Soil remote sensing; Soil proximal sensing; Soil line. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162016000200159 |
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| Nanni, Marcos Rafael; Universidade Estadual de Maringá; Demattê, José Alexandre Melo; Escola Superior de Agricultura "Luiz de Queiróz"; Chicati, Marcelo Luiz; Universidade Estadual de Maringá; Fiorio, Peterson Ricardo; Escola Superior de Agricultura "Luiz de Queiróz"; Cézar, Everson; Universidade Estadual de Maringá; Oliveira, Roney Berti; Universidade Estadual de Maringá. |
| The aim of this study was to develop and test a method to determine and discriminate soil classes in the state of São Paulo, Brazil, based on spectral data obtained via Landsat satellite imagery. Satellite reflectance images were extracted from 185 spectral reading points, and discriminant equations were obtained to establish each soil class within the studied area. Sixteen soil classes were analyzed, and discriminant equations that comprised TM5/Landsat sensor bands 1, 2, 3, 4, 5, and 7 were established. The results showed that this methodology could effectively identify individual soil classes using discriminant analyses of the spectral data obtained from the surface. Success rates of > 40% were achieved for 14 of the 16 evaluated soil classes... |
| Tipo: Pesquisa de campo e laboratório |
Palavras-chave: 5.01.01.00-5 discriminant analysis; TM-Landsat; Brazilian soil classes; Spectral response Solos. |
| Ano: 2011 |
URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/12204 |
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