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

Autor(es):Mostrar menos -

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]

Afiliação do(s) autor(es)

^[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

• Tipo de documento: Artigo Científico
• Fonte: Geoderma; v. 396, AUG 15 2021.
• Citações Web of Science: 0

Resumo

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)

• Processo FAPESP: 18/21356-1 - Geotecnologias para o mapeamento de áreas agrícolas do estado de São Paulo
• Beneficiário: José Lucas Safanelli
• Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - 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