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

Autor(es)

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

Afiliação do(s) autor(es)

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

• Tipo de documento: Artigo Científico
• Fonte: Geoderma; v. 385, MAR 1 2021.
• Citações Web of Science: 3

Resumo

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)

• 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