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  • Soil parent material predic...
    Mello, Fellipe A.O.; Bellinaso, Henrique; Mello, Danilo C.; Safanelli, José L.; Mendes, Wanderson De S.; Amorim, Merilyn T.A.; Gomez, Andrés M.R.; Poppiel, Raul R.; Silvero, Nélida E.Q.; Gholizadeh, Asa; Silva, Sérgio H.G.; Curi, Nilton; Demattê, José A.M.

    Geoderma Regional, September 2021, 2021-09-00, Letnik: 26
    Journal Article

    Parent material is the main source for soil textural, mineralogical, and other physical attributes. The knowledge over this factor is explored generally in low scale geology maps, insufficient for most users. Remote sensing can offer assistance in this regard, since it allows the evaluation of soil properties, as largely indicated in literature, being a potential tool to delineate parent material. Thus, we explored a multi temporal Landsat image composition with bare soil reflectance to extract soil properties and distinguish discrepant lithological classes at the western plateau, São Paulo State, Brazil. The area is 247,737 ha large, where 981 soil samples were collected at 0–20 cm depth. We acquired the synthetic soil image and linked the pixel's spectra with soil attributes. We performed a digital soil mapping procedure to generate maps of attributes related to parent material. The soil maps offered a great input on identifying the transitions between sandstone and basalt as soils from these formations have significant differences in clay, sand, Fe2O3 and TiO2 contents. Therefore, the use of remote sensing coupled with digital soil mapping is a strong alternative to conventional methods to improve low scale PM maps to enhance detail on regional and local scales. •The sand and clay content at 0–20 cm are significantly different (p < 0.001) in soils developed from sandstone and basalt.•Bare soil reflectance is significantly different (p < 0.001) over soils developed from sandstone and basalt.•DSM products can be used to identify PM through statistical analysis•PM prediction through environmental variables reached accuracy of 0.75 and kappa coefficient of 0.4