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Spatial technology applied on the remote sensing of soil and vegetation: Applications in the mapping of agricultural and preserved lands.

Grant number: 18/23760-4
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): December 01, 2018
Effective date (End): April 30, 2021
Field of knowledge:Agronomical Sciences - Agronomy - Soil Science
Principal researcher:José Alexandre Melo Demattê
Grantee:Rodnei Rizzo
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


The soil mapping is necessary to achieve the goal of improvement in the field of production and environmental monitoring. By the use of sensors, such result can be reached faster and with more quality. The objective of this work will be to develop a methodology to assemble data from multi-source satellite images with different features, getting higher detail for digital mapping. The study area covers five municipalities located in the region of Piracicaba, São Paulo. Multi temporal satellite data from RapidEye, Sentinel-2, Landsat 5-8 and Planet Constellation will be used. For each one satellite sensor, bare soil locations in every image will be determined and assembled into a new image, designated as SYSI (Synthetic Soil Image). There will be several SYSIs, one for each satellite sensor, which would cover a particular region. These SYSIs will be assembled (overlay) into a single image (bare soil composite) based on data of all the satellites, giving priority, in the sequence, to those with better spatial and spectral resolution. The same methodological basis will be used for vegetation. Therefore, the final SYSI of the entire study area will be transformed to color and via color related to drainage and pedological classification issues. After that, an image in the reverse direction will be created; in other words, only with vegetation. Thus, the SYVEI (Synthetic Vegetation Image) will allow to verify the soil variations using the vegetation reflectance as a "sensor" of the soil properties. The union of soil and vegetation reflectance information will allow to specialize the color of the soil and other important attributes in the pedological classification, as well as in the evaluation of the productive potential.

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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)
MELLO, FELLIPE A. O.; DEMATTE, JOSE A. M.; RIZZO, RODNEI; DOTTO, ANDRE C.; POPPIEL, RAUL R.; MENDES, WANDERSON DE S.; GUIMARAES, CLECIA C. B. Expert-based maps and highly detailed surface drainage models to support digital soil mapping. Geoderma, v. 384, FEB 15 2021. Web of Science Citations: 0.
BONFATTI, BENITO R.; DEMATTE, JOSE A. M.; MARQUES, KARINA P. P.; POPPIEL, RAUL R.; RIZZO, RODNEI; MENDES, WANDERSON DE S.; SILVERO, NELIDA E. Q.; SAFANELLI, JOSE L. Digital mapping of soil parent material in a heterogeneous tropical area. Geomorphology, v. 367, OCT 15 2020. Web of Science Citations: 0.

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