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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

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

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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]
Total Authors: 9
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
Total Affiliations: 5
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