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 Opportunities: Research Projects - Thematic Grants
• Start date: July 01, 2018
• End date: September 30, 2023
• Field of knowledge: Agronomical Sciences - Agricultural Engineering
• Agreement: Netherlands Organisation for Scientific Research (NWO)
• Principal Investigator: Paulo Sergio Graziano Magalhães
• Grantee: Paulo Sergio Graziano Magalhães
• Principal researcher abroad: Ramon F. Hansen
• Institution abroad: Delft University of Technology (TU Delft), Netherlands
• Host Institution: Núcleo Interdisciplinar de Planejamento Energético (NIPE). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Pesquisadores principais:( Últimos ): João Francisco Gonçalves Antunes ; Rubens Augusto Camargo Lamparelli
• Pesquisadores principais:( Antigos ): Jansle Vieira Rocha
• Associated scholarship(s): 22/12718-2 - Assessing the effects of integrated crop-livestock systems and associated management practices on soil carbon cycling process using the Agro-IBIS model, BP.PD; 21/15001-9 - Methodology for mapping and monitoring integrated crop-livestock systems using remote sensing data, BP.PD; 20/06775-8 - Assessing the effects of integrated crop-livestock systems and associated management practices on soil carbon cycling process using the Agro-IBIS model, BP.PD; + associated scholarships 20/02223-0 - Precision agriculture in integrated crop-livestock systems, BP.PD; 18/25473-2 - Influence of geostatistical rigor on the quality of maps used in precision agriculture, BP.MS; 18/24493-0 - Precision agriculture in integrated crop-livestock systems, BP.PD; 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 - associated scholarships

Abstract

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)

Scientific publications

(15)

(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)

DA SILVA, YANE DE FREITAS; APARECIDA DOS REIS, ALINY; SAMPAIO WERNER, JOAO PAULO; VASCONCELOS VALADARES, RAFAEL; CAMPBELL, ELEANOR E.; AUGUSTO CAMARGO LAMPARELLI, RUBENS; MAGALHAES, PAULO SERGIO GRAZIANO; FIGUEIREDO, GLEYCE KELLY DANTAS ARAUJO. Assessing the capability of MODIS to monitor mixed pastures with high-intensity grazing at a fine-scale. GEOCARTO INTERNATIONAL, MAY 2021. (17/50205-9, 18/24707-0, 18/24985-0)

FREITAS, RODRIGO G.; PEREIRA, FRANCISCO R. S.; DOS REIS, ALINY A.; MAGALHA, PAULO S. G.; FIGUEIREDO, GLEYCE K. D. A.; DO AMARAL, LUCAS R.. Estimating pasture aboveground biomass under an integrated crop-livestock system based on spectral and texture measures derived from UAV images. COMPUTERS AND ELECTRONICS IN AGRICULTURE, v. 198, p. 10-pg., 2022-07-01. (17/50205-9, 18/24985-0)

DOS REIS, ALINY A.; WERNER, JOAO P. S.; SILVA, BRUNA C.; FIGUEIREDO, GLEYCE K. D. A.; ANTUNES, JOAO F. G.; ESQUERDO, JULIO C. D. M.; COUTINHO, ALEXANDRE C.; LAMPARELLI, RUBENS A. C.; ROCHA, V, JANSLE; MAGALHAES, PAULO S. G.. Monitoring Pasture Aboveground Biomass and Canopy Height in an Integrated Crop-Livestock System Using Textural Information from PlanetScope Imagery. REMOTE SENSING, v. 12, n. 16, AUG 2020. (18/24985-0, 17/50205-9)

CAMARGO, LIVIA ARANTES; DO AMARAL, LUCAS RIOS; DOS REIS, ALINY APARECIDA; BRASCO, THIAGO LUIS; GRAZIANO MAGALHAES, PAULO SERGIO. mproving soil organic carbon mapping with a field-specific calibration approach through diffuse reflectance spectroscopy and machine learning algorithm. SOIL USE AND MANAGEMENT, v. 38, n. 1, NOV 2021. (18/24985-0, 17/50205-9, 18/24493-0)

SILVA, YANE FREITAS; VALADARES, RAFAEL VASCONCELOS; DIAS, HENRIQUE BORIOLO; CUADRA, SANTIAGO VIANNA; CAMPBELL, ELEANOR E.; LAMPARELLI, RUBENS A. C.; MORO, EDEMAR; BATTISTI, RAFAEL; ALVES, MARCELO R.; MAGALHAES, PAULO S. G.; et al. Intense Pasture Management in Brazil in an Integrated Crop-Livestock System Simulated by the DayCent Model. SUSTAINABILITY, v. 14, n. 6, p. 24-pg., 2022-03-01. (20/06775-8, 18/24707-0, 17/50205-9)

DOS SANTOS, L. T.; WERNER, J. P. S.; DOS REIS, A. A.; TORO, A. P. G.; ANTUNES, J. F. G.; COUTINHO, A. C.; LAMPARELLI, R. A. C.; MAGALHAES, P. S. G.; ESQUERDO, J. C. D. M.; FIGUEIREDO, G. K. D. A.; et al. MULTITEMPORAL SEGMENTATION OF SENTINEL-2 IMAGES IN AN AGRICULTURAL INTENSIFICATION REGION IN BRAZIL. XXIV ISPRS CONGRESS: IMAGING TODAY, FORESEEING TOMORROW, COMMISSION III, v. 5-3, p. 7-pg., 2022-01-01. (18/24985-0, 17/50205-9)

PUSCH, MAIARA; SAMUEL-ROSA, ALESSANDRO; MAGALHAES, PAULO SERGIO GRAZIANO; DO AMARAL, LUCAS RIOS. Covariates in sample planning optimization for digital soil fertility mapping in agricultural areas. Geoderma, v. 429, p. 14-pg., 2023-01-01. (17/50205-9)

PEREIRA, FRANCISCO R. DA S.; DOS REIS, ALINY A.; FREITAS, RODRIGO G.; OLIVEIRA, STANLEY R. DE M.; DO AMARAL, LUCAS R.; FIGUEIREDO, GLEYCE K. D. A.; ANTUNES, JOAO F. G.; LAMPARELLI, RUBENS A. C.; MORO, EDEMAR; MAGALHAES, PAULO S. G.. Imputation of Missing Parts in UAV Orthomosaics Using PlanetScope and Sentinel-2 Data: A Case Study in a Grass-Dominated Area. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, v. 12, n. 2, p. 15-pg., 2023-02-01. (17/50205-9, 18/24985-0)

CENNEYA L. MARTINS; AGDA L. G. OLIVEIRA; ISABELLA A. DA CUNHA; HENRIQUE OLDONI; JULIANA C. PEREIRA; LUCAS R. DO AMARAL. CLASSIFICATION OF THE OCCURRENCE OF BROADLEAF WEEDS IN NARROW-LEAF CROPS. Engenharia Agrícola, v. 44, 2024-04-19. (17/50205-9, 20/02223-0)

DA SILVA, YANE DE FREITAS; APARECIDA DOS REIS, ALINY; SAMPAIO WERNER, JOAO PAULO; VASCONCELOS VALADARES, RAFAEL; CAMPBELL, ELEANOR E.; AUGUSTO CAMARGO LAMPARELLI, RUBENS; MAGALHAES, PAULO SERGIO GRAZIANO; FIGUEIREDO, GLEYCE KELLY DANTAS ARAUJO. Assessing the capability of MODIS to monitor mixed pastures with high-intensity grazing at a fine-scale. GEOCARTO INTERNATIONAL, v. 37, n. 20, p. 19-pg., 2021-05-07. (18/24707-0, 18/24985-0, 17/50205-9)

DIAS, HENRIQUE BORIOLO; CUADRA, SANTIAGO VIANNA; BOOTE, KENNETH J.; LAMPARELLI, RUBENS AUGUSTO CAMARGO; FIGUEIREDO, GLEYCE KELLY DANTAS ARAUJO; SUYKER, ANDREW E.; MAGALHAES, PAULO SERGIO GRAZIANO; HOOGENBOOM, GERRIT. Coupling the CSM-CROPGRO-Soybean crop model with the ECOSMOS Ecosystem Model - An evaluation with data from an AmeriFlux site. Agricultural and Forest Meteorology, v. 342, p. 16-pg., 2023-09-09. (17/50205-9, 20/06775-8)

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., 2023-02-01. (17/50205-9, 21/15001-9)

PUSCH, MAIARA; SAMUEL-ROSA, ALESSANDRO; GONCALVES OLIVEIRA, AGDA LOUREIRO; GRAZIANO MAGALHAES, PAULO SERGIO; DO AMARAL, LUCAS RIOS. Improving soil property maps for precision agriculture in the presence of outliers using covariates. PRECISION AGRICULTURE, v. N/A, p. 29-pg., 2022-03-21. (17/50205-9)

PEREIRA, F. R. DA S.; DE LIMA, J. P.; FREITAS, R. G.; DOS REIS, A. A.; DO AMARAL, L. R.; FIGUEIREDO, G. K. D. A.; LAMPARELLI, R. A. C.; MAGALHAES, P. S. G.. itrogen variability assessment of pasture fields under an integrated crop-livestock system using UAV, PlanetScope, and Sentinel-2 dat. COMPUTERS AND ELECTRONICS IN AGRICULTURE, v. 193, FEB 2022. (17/50205-9, 18/24985-0)

RODRIGUEZ MIRANDA, DIANA ALEXANDRA; ALARI, FERNANDO DE OLIVEIRA; OLDONI, HENRIQUE; BAZZI, CLAUDIO LEONES; DO AMARAL, LUCAS RIOS; GRAZIANO MAGALHAES, PAULO SERGIO. Delineation of management zones in integrated crop-livestock systems. AGRONOMY JOURNAL, v. 113, n. 6, NOV 2021. (17/50205-9, 20/02223-0)