Integration of multispectral and hyperspectral data to map magnetic susceptibility and soil attributes at depth: A novel framework

Author(s)

Mendes, Wanderson de Sousa ^[1] ; Dematte, Jose A. M. ^[1] ; Quinonez Silvero, Nelida Elizabet ^[1] ; Campos, Lucas Rabelo ^[1]

Affiliation

^[1] Univ Sao Paulo, Luiz de Queiroz Coll Agr, Dept Soil Sci, Av Padua Dias 11, Portal Box 9, BR-13418140 Piracicaba, SP - Brazil

• Document type: Journal article
• Source: Geoderma; v. 385, MAR 1 2021.
• Web of Science Citations: 3

Abstract

The understanding of attributes and magnetic susceptibility (chi) at soil surface, mainly subsurface, is crucial due to their role to identify climate changes, soil degradation, soil classification systems, soil fertility, and pedogenesis. The integration of proximal sensing (PS) and remote sensing (RS) data sources could increase the efficiency of Digital Soil Mapping. Nevertheless, products of this integration need to be evaluated in hybrid, stochastic, and deterministic models to predict soil attributes and chi at surface and subsurface. This study investigates the PS and RS integration by applying four deterministic (e.g. Bayesian Regularised Neural Network, Generalised Linear Model, Random Forest and Cubist) and hybrid models (e.g. Regression Kriging of residuals of the best-fitted model) to create a new environmental variable, the Best Synthetic Soil Image (BSSI), at three soil depths (e.g. 0 - 20, 40 - 60 and 80 - 100 cm) that quantitatively represent the soil spectral signature. We also used the BSSI in a comparison with bare soil surface (e.g. SYSI - Synthetic Soil Image) to predict soil attributes and chi by performing the deterministic and hybrid models. We hypothesize that the BSSI, which integrates PS and RS data, enhances soil modelling predictions at subsurface by selecting the best model approach. The BSSI demonstrated original and valuable contribution to increase the predictive model power at deeper layers, while SYSI was effective at upper layers. The PS and RS integration helped to identify the main soil patterns horizontally and vertically, which traditional soil surveys have not been capable of representing. (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