GIS-Based Assessment of Grassland Dynamics and Sustainable Pasture Planning in South and Nabatieh Governorates, Lebanon (2000–2024)

Abstract

Sustainable pasture management is essential for preserving ecosystem services and supporting livestock production in Mediterranean environments experiencing increasing land-use pressure and climate variability. This study evaluates grassland dynamics in South Lebanon between 2000 and 2024 using multi-temporal Landsat imagery integrated with Geographic Information Systems (GISs) and Random Forest classification. Historical Landsat surface reflectance products were processed using standardized preprocessing procedures, cross-sensor harmonization, and supervised classification. Classification accuracy was assessed using independent validation samples, yielding overall accuracy values ranging from 91.8% to 98.6% and Kappa coefficients between 0.918 and 0.975. Pasture areas were subsequently classified into dense and dispersed grasslands using quantitative NDVI thresholds. A pixel-based transition matrix was employed to quantify land-cover persistence, gains, losses, and conversions throughout the study period. The results reveal substantial spatial redistribution of grasslands associated with agricultural intensification and greenhouse expansion. FAO GIEWS NDVI and Vegetation Health Index products were incorporated only as regional environmental context. The resulting spatial database provides a robust framework for sustainable pasture planning, grazing management, and future land-use policy development in South Lebanon.