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Título: | Soil parent material prediction through satellite multispectral analysis on a regional scale at the Western Paulista Plateau, Brazil |
Palavras-chave: | 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 |
Data do documento: | Set-2021 |
Editor: | Elsevier |
Citação: | 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. |
Resumo: | 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 |
Aparece nas coleções: | DCS - Artigos publicados em periódicos |
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