Leveraging the application of Earth observation data for mapping cropland soils in Brazil

Author(s):Show less -

Safanelli, Jose L. ^[1] ; Dematte, Jose A. M. ^[1] ; Chabrillat, Sabine ^[2] ; Poppiel, Raul R. ^[1] ; Rizzo, Rodnei ^[1] ; Dotto, Andre C. ^[1] ; Silvero, Nelida E. Q. ^[1] ; Mendes, Wanderson de S. ^[1] ; Bonfatti, Benito R. ^[3] ; Ruiz, Luis F. C. ^[1] ; ten Caten, Alexandre ^[4] ; Dalmolin, Ricardo S. D. ^[5]

Affiliation

^[1] Univ Sao Paulo, Luiz de Queiroz Coll Agr, Piracicaba - Brazil

^[2] GFZ German Res Ctr Geosci, Potsdam - Germany

^[3] Univ Estado Minas Gerais, Passos - Brazil

^[4] Univ Fed Santa Catarina, Curitibanos - Brazil

^[5] Univ Fed Santa Maria, Santa Maria, RS - Brazil

• Document type: Journal article
• Source: Geoderma; v. 396, AUG 15 2021.
• Web of Science Citations: 0

Abstract

Despite the natural spatial variability, cropland soils are subject to many interventions that can lead to alterations of soil functioning. As the cropland expansion took place in Brazil the last decades, leading to significant land-use change and environmental impacts, detailed information about soils is fundamental for sustainable development. Thus, considering the lack of spatially explicit information about cropland soils in Brazil, we aimed at performing high-resolution mapping of key topsoil attributes using spectral and terrain features extracted from Earth observation data (EOD). With the resulting information, we also aimed at performing a general examination of the main agricultural regions and estimate the total organic carbon stocks on croplands soils. For this, we obtained environmental predictors from the historical collection of Landsat data and the digital elevation model from Shuttle Radar Topographic Mission at the cloud-based platform of Google Earth Engine. The environmental predictors (30 m spatial resolution) with georeferenced soil samples (n = 5097) were used for predicting the topsoil content (0-20 cm) of clay, sand, silt, cation exchange capacity, pH, soil organic carbon (SOC) and SOC stock. Prediction models of clay, sand, SOC content, and SOC stocks had the best performance metrics, achieving a R2 ranging from 0.44 to 0.74 and ratio of performance to the interquartile range higher than 1.5. The predicted maps revealed the variability of topsoil among the cropped areas, indicating that the agricultural expansion took place on sandy soils. The SOC stock map provided consistent estimates compared to previous datasets but revealed additional information at the local and regional scales. Thus, this study supports the proposition that EOD is a valuable source for extracting environmental features for mapping and monitoring cropland soils at finer resolutions, assisting the evaluation of soil spatial distribution and the historical agriculture expansion over large geographical areas. (AU)

• FAPESP's process: 18/21356-1 - Geotechnologies for mapping agricultural soils of São Paulo state
• Grantee: José Lucas Safanelli
• Support Opportunities: Scholarships abroad - Research Internship - 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)