Abstract
The evaluation of grazing intensity is one of the key parameters to develop an efficient and sustainable management of pastures (Bernués et al., 2011). The use of remote sensing techniques, namely by exploiting vegetation indices (VI), has been tested as a new methodology to aid pasture management by monitoring grazing intensity (GI) (Jansen et al., 2021, Li et al., 2016). Moreover, recently developed platforms, such as Google Earth Engine (GEE), give the possibility to exploit very large catalogs of readily processable satellite data and to drastically reduce the amount of time needed to process images. In our study, we were able to integrate innovative pasture management technologies such as GPS locations of grazing animals (from virtual fencing collars) and remote-sensed derived VIs from Sentinel-2 (processed in GEE), with the aim to establish a methodology for monitoring grazing intensity in a Mediterranean silvopastoral system using pixel-level validation.