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Monitoring integrated crop-livestock systems through remote sensing and precision agriculture for more sustainable production - towards low carbon agriculture

Grant number: 17/50205-9
Support type:Research Projects - Thematic Grants
Duration: July 01, 2018 - June 30, 2022
Field of knowledge:Agronomical Sciences - Agricultural Engineering
Cooperation agreement: Netherlands Organisation for Scientific Research (NWO)
Principal Investigator:Paulo Sergio Graziano Magalhães
Grantee:Paulo Sergio Graziano Magalhães
Principal investigator abroad: Ramon F. Hansen
Institution abroad: Delft University of Technology (TU Delft), Netherlands
Home Institution: Núcleo Interdisciplinar de Planejamento Energético (NIPE). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Co-Principal Investigators:Jansle Vieira Rocha ; Rubens Augusto Camargo Lamparelli
Associated scholarship(s):18/25473-2 - Influence of geostatistical rigor on the quality of maps used in precision agriculture, BP.MS
18/24707-0 - Assessing the effects of integrated crop-livestock systems and associated management practices on soil carbon and nitrogen cycling processes using the Daycent model, BP.PD
18/24985-0 - Methodology for mapping and monitoring different pasture-based Livestock management and Mixed Crop-Livestock systems with remote sensing, BP.PD
18/24493-0 - Precision agriculture in integrated crop-livestock systems, BP.PD


The aim or the proposed study is to provide sustainability-related supports for the Brazilian low carbon agriculture program from an water use efficiency, productivity and soil quality point of view, exploiting the capabilities of satellite remote sensing data and precision agriculture analysis. This program, established in 2010, aims at reducing greenhouse gas emissions by 160 million tons of carbon dioxide equivalent annually by 2020 (CGIAR, 2017). Three main proposed measures include the stimulation of integrated crop-livestock-forestry (lCLF) systems, the recuperation of 15 million degraded pastures into more productive agricultural systems and biological nitrogen fixation (EMBRAPA, 2017; IPAM, 2012). Through remote sensing and precision agriculture data, we aim to compare the water use efficiency, biomass productivity and soil quality of ICLF systems to conventional croplands and pastures. Analysis based on remote sensing data has the unique advantage of acquiring quantitative and qualitative states of (specific for this proposal) agriculture-related processes over large areas and long time series with high spatial and temporal resolutions. Remote sensing data can be analyzed in combination with soil quality parameters. These analyses can be used to outline the sustainability benefits related to the ICLF systems and to estimate the potential for (degraded) pastureland recuperation. Consequently, the Brazilian authorities can use this information to re-evaluate the success and potential of the program and stimulate the use of resources offered by the Ministry of Agriculture, Livestock and Food Supply (MAPA) by farmers to adopt the program's measures through the dissemination of our scientifically acquired results and case studies. (AU)