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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Soil Color and Mineralogy Mapping Using Proximal and Remote Sensing in Midwest Brazil

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Autor(es):
Poppiel, Raul Roberto [1] ; Coelho Lacerda, Marilusa Pinto [1] ; Rizzo, Rodnei [2] ; Safanelli, Jose Lucas [2] ; Bonfatti, Benito Roberto [2] ; Quinonez Silvero, Nelida Elizabet [2] ; Melo Dematte, Jose Alexandre [2]
Número total de Autores: 7
Afiliação do(s) autor(es):
[1] Univ Brasilia, Fac Agron & Vet Med, ICC Sul, Darcy Ribeiro Univ Campus, Postal Box 4508, BR-70910960 Brasilia, DF - Brazil
[2] Univ Sao Paulo, Dept Soil Sci, Luiz de Queiroz Coll Agr, Padua Dias Ave 11, Postal Box 09, BR-13416900 Sao Paulo - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: REMOTE SENSING; v. 12, n. 7 APR 2020.
Citações Web of Science: 0
Resumo

Soil color and mineralogy are used as diagnostic criteria to distinguish different soil types. In the literature, 350-2500 nm spectra were successfully used to predict soil color and mineralogy, but these attributes currently are not mapped for most Brazilian soils. In this paper, we provided the first large-extent maps with 30 m resolution of soil color and mineralogy at three depth intervals for 850,000 km(2) of Midwest Brazil. We obtained soil 350-2500 nm spectra from 1397 sites of the Brazilian Soil Spectral Library at 0-20 cm, 20-60, and 60-100 cm depths. Spectra was used to derive Munsell hue, value, and chroma, and also second derivative spectra of the Kubelka-Munk function, where key spectral bands were identified and their amplitude measured for mineral quantification. Landsat composites of topsoil and vegetation reflectance, together with relief and climate data, were used as covariates to predict Munsell color and Fe-Al oxides, and 1:1 and 2:1 clay minerals of topsoil and subsoil. We used random forest for soil modeling and 10-fold cross-validation. Soil spectra and remote sensing data accurately mapped color and mineralogy at topsoil and subsoil in Midwest Brazil. Hematite showed high prediction accuracy (R-2 > 0.71), followed by Munsell value and hue. Satellite topsoil reflectance at blue spectral region was the most relevant predictor (25% global importance) for soil color and mineralogy. Our maps were consistent with pedological expert knowledge, legacy soil observations, and legacy soil class map of the study region. (AU)

Processo FAPESP: 16/26124-6 - Pedologia de precisão: caracterização e mapeamento de solos em tempo real por geotecnologias
Beneficiário:Wanderson de Sousa Mendes
Modalidade de apoio: Bolsas no Brasil - Doutorado Direto
Processo FAPESP: 14/22262-0 - Geotecnologias no mapeamento digital pedológico detalhado e biblioteca espectral de solos do Brasil: desenvolvimento e aplicações
Beneficiário:José Alexandre Melo Demattê
Modalidade de apoio: Auxílio à Pesquisa - Temático
Processo FAPESP: 16/01597-9 - Pedotransferência por geotecnologias associada à fotopedologia com vistas ao mapeamento pedológico de áreas agrícolas do estado de São Paulo
Beneficiário:José Lucas Safanelli
Modalidade de apoio: Bolsas no Brasil - Doutorado Direto