Temporal analysis of pasture vegetation cover incentral-western Brazil using remote sensing
¹Federal University of Goiás, Department of Biosystems Engineering, College of Agronomy, BR74690-900 Goiânia, Goiás, Brazil
²Centro Universitário UniAraguaia, Department of Agronomic Engineering,
BR74223-060 Goiânia, Goiás, Brazil
³University of Florence, Department of Agriculture, Food, Environment and Forestry, Via San Bonaventura 13, IT50145 Firenze, Italy
*Correspondence: rafaella.andrade@ufg.br, gianluca.bambi@unifi.it
Abstract:
Brazil is the world’s leading exporter of beef, consolidating beef cattle farming as an important branch of national livestock farming. The expansion of livestock farming and agriculture in recent decades has resulted in a notable increase in pasture areas in Brazil. However, the country faces the growing challenge of pasture degradation, a problem that threatens sustainability and food production. On the other hand, livestock farming in Brazil’s Central-West region, the country’s largest cattle-producing area, particularly in the state of Goiás, can cause environmental damage when sustainable practices are disregarded. Thus, the objective of this article was to evaluate pasture degradation, at different levels, in the Ribeirão Serra Negra Watershed, in the municipality of Piracanjuba, Goiás, Brazil. Using images from the Sentinel-2A orbital sensor, the NDVI (Normalized Difference Vegetation Index) vegetation index and the vegetation cover classes of pastures were obtained between 2017 and 2021. During this period, the results showed that more than 98% of the areas had some level of degradation, with an average coverage of 6,586.1 ha. There was an upward evolution in the levels of vegetation cover between 2017 and 2019, with the best pasture conditions predominating in 2019. These assessments help identify areas that require greater attention and often necessitate conservation practices and management plans. In this context, monitoring degraded areas is a practice that facilitates the improvement of existing pastures, promotes the rational management of inputs, conserves natural resources, and aligns with development programs focused on sustainability.
Key words:
livestock grazing, pasture quality degradation, Remote sensing, sustainable, vegetation indices