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Methodology for mapping and monitoring integrated crop-livestock systems using remote sensing data

Grant number: 21/15001-9
Support Opportunities:Scholarships in Brazil - Post-Doctoral
Start date: February 01, 2022
End date: May 31, 2023
Field of knowledge:Agronomical Sciences - Agricultural Engineering
Agreement: Netherlands Organisation for Scientific Research (NWO)
Principal Investigator:João Francisco Gonçalves Antunes
Grantee:Inacio Thomaz Bueno
Host Institution: Núcleo Interdisciplinar de Planejamento Energético (NIPE). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Associated research grant:17/50205-9 - Monitoring integrated crop-livestock systems through remote sensing and precision agriculture for more sustainable production - towards low carbon agriculture, AP.TEM

Abstract

Agricultural expansion over pastureland in Brazil, mainly by grains and sugarcane, led to livestock intensification in the remaining pasture within those regions. During the past decades, Brazil has dramatically increased agricultural (grains) production, mostly due to increases in yield. On the other hand, in recent years, sugarcane has increased its production mainly based on area expansion mainly over pasture areas. In the same period, Brazil has become a leading global beef producer. Although general agricultural statistics indicate that pasture intensification has been occurring in recent years, a more detailed analysis is needed, considering, for instance, geographical distribution, the types of systems involved (e.g. purely pasture and mixed pasture and crops) and management variables. This plan focuses on what can be learned about pasture management from remote sensing - a powerful tool that has seen relatively little application in this context. (AU)

News published in Agência FAPESP Newsletter about the scholarship:
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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)
TORO, ANA P. S. G. D. D.; BUENO, INACIO T.; WERNER, JOAO P. S.; ANTUNES, JOAO F. G.; LAMPARELLI, RUBENS A. C.; COUTINHO, ALEXANDRE C.; ESQUERDO, JULIO C. D. M.; MAGALHAES, PAULO S. G.; FIGUEIREDO, GLEYCE K. D. A.. SAR and Optical Data Applied to Early-Season Mapping of Integrated Crop-Livestock Systems Using Deep and Machine Learning Algorithms. REMOTE SENSING, v. 15, n. 4, p. 16-pg., . (17/50205-9, 21/15001-9)