Mapping post-crop biomass for grazing in Alessandria Province, north West Italy: Moving towards sustainable agriculture through the support of remote sensing

Effective management of crop residues and strategic identification of potential grazing areas are essential components of sustainable agriculture. Crop residues, when properly managed, constitute a valuable forage resource for livestock. This integrated land use approach promotes a balanced relationship between agriculture, livestock, and the environment. This study aimed to map potential grazing areas in the Alessandria province (NW Italy) by analyzing vegetation dynamics during the transition from the end of one growing season to the beginning of the next one, focusing on the availability of crop residues and spontaneous vegetation for grazing. Using data from the Copernicus Land Monitoring Services and Sentinel-2 satellite imagery, three maps were developed based on Modified Soil-Adjusted Vegetation Index (MSAVI) time series analysis to assess grazing biomass variability, duration, and density respectively. Unlike conventional studies that analyze peak vegetation periods, this approach analyzes off-peak periods to capture residual and regrowth vegetation. Based on these maps, an ISODATA clustering analysis was then applied to classify grazing suitability areas. The MSAVI-based maps provided detailed insights into spatial and temporal patterns of biomass availability and grazing potential. The ISODATA clustering effectively identified areas with varying suitability for grazing, highlighting the role of post-harvest vegetation, including weeds, in supporting livestock forage systems. This study demonstrates a novel remote sensing-based approach for integrating crop residue management into grazing systems. By optimizing the use of available biomass and enhancing sustainability in agricultural practices, the methodology supports more resilient and environmentally responsible land use planning. • Crop residues can support livestock and reduce farming's environmental impact. • The study maps post-harvest grazing areas in NW Italy using remote sensing tools. • MSAVI time series maps and ISODATA clustering were used to map grazing suitability. • The analysis revealed spatial-temporal grazing potential from crop residues and weeds. • A replicable approach to enhance sustainability for land use planning was proposed.