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Precision pedology: soil characterisation and mapping in real time using geotechnologies

Grant number: 16/26124-6
Support type:Scholarships in Brazil - Doctorate (Direct)
Effective date (Start): March 01, 2017
Effective date (End): April 30, 2020
Field of knowledge:Agronomical Sciences - Agronomy
Principal Investigator:José Alexandre Melo Demattê
Grantee:Wanderson de Sousa Mendes
Home Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Associated research grant:14/22262-0 - Geotechnologies on a detailed digital soil mapping and the Brazilian soil spectral library: development and applications, AP.TEM


This study aims to create a new concept in Pedology, that is, Precision Pedology which will use geotechnical equipment integrated to statistical and computational methods. These will identify and characterise several in-situ soil body. Several strategies will be developed combining techniques and variables related to factors of soil formation for mapping three pilot areas in the region of Piracicaba, SP. The study will be carried out in two steps. Firstly, surveys will be held in office aiming to gathering information for a prezoning field procedure. In this step will be used: geological letters; digital elevation models for the extraction of terrain attributes such as slope, LS relief form factor and relative location; aerial photographs of 1:5,000 scale color; satellite images to obtain digital spectra that it will be used in the identification and characterization of targets of interest; gama-ray spectrometer bound to a car platform; terrain models and color aerial photographs with high spatial resolution and hyperspectral cameras with (300-1100 nm) in RGB, respectively, coupled with an unmanned aerial vehicle. After that, the study will be carried out in field with the prezoning maps and prospect points generated in the first step. On this occasion, spectroradiometers (VIS-NIR-SWIR-MIR), gama-ray spectometer, magnetic susceptibility meters, Ground-Penetrating Radar (GPR), conductivity analyzer and Munsell color chips will be used to record and process information located geographically using a geographic information system (laptop, GIS software and GPS device). These equipment will provide greater support to pedologist at interpretations and allocation of new sampling points in real time because of the use of prediction models of attributes based on previously developed databases. Thus, this process seeks to delimitate and characterize the soil body with high resolution. After data collection, we will generate maps of soil attributes certain/estimated with the aid of Geotechnology. These maps will enable the identification of mapping units, which they will be also studied in representative profiles with the use of geotechnical equipment associated with the traditional morphological description. Finally, it will be obtained maps of soil classes with high level of detail. (AU)

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
MENDES, WANDERSON DE S.; MEDEIROS NETO, LUIZ G.; DEMATTE, JOSE A. M.; GALLO, BRUNA C.; RIZZO, RODNEI; SAFANELLI, JOSE L.; FONGARO, CAIO T. Is it possible to map subsurface soil attributes by satellite spectral transfer models?. Geoderma, v. 343, p. 269-279, JUN 1 2019. Web of Science Citations: 1.
FONGARO, CAIO T.; DEMATTE, JOSE A. M.; RIZZO, RODNEI; SAFANELLI, JOSE LUCAS; MENDES, WANDERSON DE SOUSA; DOTTO, ANDRE CARNIELETTO; VICENTE, LUIZ EDUARDO; FRANCESCHINI, MARSTON H. D.; USTIN, SUSAN L. Improvement of Clay and Sand Quantification Based on a Novel Approach with a Focus on Multispectral Satellite Images. REMOTE SENSING, v. 10, n. 10 OCT 2018. Web of Science Citations: 0.
GALLO, BRUNA C.; DEMATTE, JOSE A. M.; RIZZO, RODNEI; SAFANELLI, JOSE L.; MENDES, WANDERSON DE S.; LEPSCH, IGO F.; SATO, MARCUS V.; ROMERO, DANILO J.; LACERDA, MARILUSA P. C. Multi-Temporal Satellite Images on Topsoil Attribute Quantification and the Relationship with Soil Classes and Geology. REMOTE SENSING, v. 10, n. 10 OCT 2018. Web of Science Citations: 3.

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