Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/50014
Title: Soil parent material prediction through satellite multispectral analysis on a regional scale at the Western Paulista Plateau, Brazil
Keywords: Remote sensing
Digital soil mapping
Parent material
Satellite data
Synthetic soil image
Lithological transitions
Multiple soil classes delineation
Sensoriamento remoto
Mapeamento digital do solo
Material principal
Dados de satélite
Imagem de solo sintético
Transições litológicas
Delineamento de várias classes de solo
Issue Date: Sep-2021
Publisher: Elsevier
Citation: MELLO, F. A. O. et al. Soil parent material prediction through satellite multispectral analysis on a regional scale at the Western Paulista Plateau, Brazil. Geoderma Regional, [S. l.], v. 26, e00412, Sept. 2021. DOI: 10.1016/j.geodrs.2021.e00412.
Abstract: 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.
URI: https://doi.org/10.1016/j.geodrs.2021.e00412
http://repositorio.ufla.br/jspui/handle/1/50014
Appears in Collections:DCS - Artigos publicados em periódicos

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