At the 12th International Rangeland Congress Australia 2025 in Adelaide, CEIGRAM researcher and member of the AgSystems Group Carlos G. H. Díaz-Ambrona presented the study: “Application of vegetation indices obtained from satellite for the management of Voisin rational grazing.”
The study addresses the challenges faced by livestock farmers in making informed decisions about the management of natural pastures, a complex task that often requires the use of external feed supplements. The work was carried out in collaboration with Professor Rafael G. Rodríguez and agricultural engineer and livestock farmer Raúl Montoya-Téllez.
Factors such as pasture degradation, the impact of climate change, and the current agricultural policy framework make it necessary to adopt more sustainable practices. Voisin Rational Grazing (VRG) is an efficient pasture management technique that manages grazing time according to the critical leaf area index or the accumulation of reserves. It is presented as a sustainable alternative, although it requires constant monitoring. PRV addresses the specific needs of plants (pastures and forages) and grazing animals (regardless of species), as well as what each soil needs to remain naturally fertile and productive.
The use of remote sensors to estimate growth, biomass, and other key parameters was evaluated to facilitate decision-making in PRV. The analysis took into account a real case on a 240-hectare farm and communal pastures in northern Madrid, with a Mediterranean climate, using Sentinel-2 images (2017–2020) and tools such as QGIS and Sen2Cor. Biomass samples were taken in the field and images were processed to assess pasture dynamics.
The results show that vegetation indices accurately reflect the grass growth curve and allow the optimal point of use to be identified. It is also possible to distinguish grazing with high instantaneous load, characteristic of PRV, and observe rapid regrowth of the grass in this case.
We believe that remote sensing can facilitate the implementation of PRV by improving natural resource management.
Study available at (pp1308): XII-IRC-Proceedings-Draft-com-compressed.pdf
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