Soil surface spectral data from Landsat imagery for soil class discrimination

dc.creatorMarcos Rafael Nanni
dc.creatorJosé Alexandre Melo Demattê
dc.creatorMarcelo Luiz Chicati
dc.creatorPeterson Ricardo Fiorio
dc.creatorEverson Cézar
dc.creatorRoney Berti de Oliveira
dc.date2012
dc.date.accessioned2026-07-07T03:55:24Z
dc.descriptionThe 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 when applying the satellite image data. When the 10 soil classes containing the largest number of minimum cartographic areas were used, the hit rate increased to > 50%, for seven soil classes with a global hit rate of 52%. When the soil classes were grouped based on their parent materials, the hit rate increased to 70%. Thus, we concluded that the spectral method for soil classification was efficient.
dc.formatapplication/pdf
dc.identifier1679-9275
dc.identifierhttps://www.redalyc.org/articulo.oa?id=303026475014
dc.identifier10.4025/actasciagron.v34i1.12204
dc.identifier.urihttp://hdl.handle.net/123456789/447531
dc.languageen
dc.publisherUniversidade Estadual de Maringá
dc.relationhttp://www.redalyc.org/revista.oa?id=3030
dc.rightsActa Scientiarum. Agronomy
dc.sourceActa Scientiarum. Agronomy (Brasil) Num.1 Vol.34
dc.subjectAgrociencias
dc.titleSoil surface spectral data from Landsat imagery for soil class discrimination
dc.typeartículo científico

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