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

Author(s)

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]

Affiliation

^[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

• Document type: Journal article
• Source: REMOTE SENSING; v. 12, n. 7 APR 2020.
• Web of Science Citations: 0

Abstract

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)

• FAPESP's process: 16/26124-6 - Precision pedology: soil characterisation and mapping in real time using geotechnologies
• Grantee: Wanderson de Sousa Mendes
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• FAPESP's process: 14/22262-0 - Geotechnologies on a detailed digital soil mapping and the Brazilian soil spectral library: development and applications
• Grantee: José Alexandre Melo Demattê
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 16/01597-9 - Pedotransfer functions by geotecnologies associated with photopedology for pedological mapping in agricultural areas of São Paulo State
• Grantee: José Lucas Safanelli
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)