Improvement of Clay and Sand Quantification Based on a Novel Approach with a Focus on Multispectral Satellite Images

Author(s)

Fongaro, Caio T. ^[1] ; Dematte, Jose A. M. ^[1] ; Rizzo, Rodnei ^[2] ; Safanelli, Jose Lucas ^[1] ; Mendes, Wanderson de Sousa ^[1] ; Dotto, Andre Carnieletto ^[1] ; Vicente, Luiz Eduardo ^[3] ; Franceschini, Marston H. D. ^[4] ; Ustin, Susan L. ^[5]

Affiliation

^[1] Univ Sao Paulo, Luiz de Queiroz Coll Agr, Dept Soil Sci, Ave Padua Dias 11, Cx Postal 09, BR-13416900 Piracicaba, SP - Brazil

^[2] Univ Sao Paulo, Ctr Nucl Energy Agr, Centenario Ave 303, BR-13416000 Piracicaba, SP - Brazil

^[3] Embrapa Environm Low Carbon Agr Platform, Rd SP-340, Km 127, 5, POB 69, BR-13820000 Jaguariuna, SP - Brazil

^[4] Wageningen Univ & Res, Lab Geoinformat Sci & Remote Sensing, POB 47, NL-6700 AA Wageningen - Netherlands

^[5] Univ Calif Davis, Dept Land Air & Water Resources, 1 Shields Ave, Davis, CA 95616 - USA

• Document type: Journal article
• Source: REMOTE SENSING; v. 10, n. 10 OCT 2018.
• Web of Science Citations: 0

Abstract

Soil mapping demands large-scale surveys that are costly and time consuming. It is necessary to identify strategies with reduced costs to obtain detailed information for soil mapping. We aimed to compare multispectral satellite image and relief parameters for the quantification and mapping of clay and sand contents. The Temporal Synthetic Spectral (TESS) reflectance and Synthetic Soil Image (SYSI) approaches were used to identify and characterize texture spectral signatures at the image level. Soil samples were collected (0-20 cm depth, 919 points) from an area of 14,614 km(2) in Brazil for reference and model calibration. We compared different prediction approaches: (a) TESS and SYSI; (b) Relief-Derived Covariates (RDC); and (c) SYSI plus RDC. The TESS method produced highly similar behavior to the laboratory convolved data. The sandy textural class showed a greater increase in average spectral reflectance from Band 1 to 7 compared with the clayey class. The prediction using SYSI produced a better result for clay (R-2 = 0.83; RMSE = 65.0 g kg(-1)) and sand (R-2 = 0.86; RMSE = 79.9 g kg(-1)). Multispectral satellite images were more stable for the identification of soil properties than relief parameters. (AU)

• FAPESP's process: 13/18769-9 - Multitemporal orbital images and algorithm external parameter orthogonalization on the maximization of the use of sensors: useful tools on digital soil mapping
• Grantee: José Alexandre Melo Demattê
• Support type: Scholarships abroad - Research
• FAPESP's process: 17/03207-6 - Geotechnologies in detailed pedological digital mapping and Brazilian spectral soil library: development and applications
• Grantee: Andre Carnieletto Dotto
• Support type: Scholarships in Brazil - Post-Doctorate
• FAPESP's process: 16/26124-6 - Precision pedology: soil characterisation and mapping in real time using geotechnologies
• Grantee: Wanderson de Sousa Mendes
• Support type: 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 type: 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 type: Scholarships in Brazil - Doctorate (Direct)
• FAPESP's process: 13/20377-1 - Development of soybean virtual water map for the Upper Xingu basin, Mato Grosso - Brazil
• Grantee: Rodnei Rizzo
• Support type: Scholarships in Brazil - Doctorate