Multi-temporal and multi-sensor approach for land use mapping: application to irrigated crops in the lower Mejerda Valley (Northeast Tunisia)

The present research explores land use dynamics and irrigation practices in the Lower Mejerda Valley in Tunisia, a region deeply influenced by agricultural activities and water resource management. Since the United Nations Conference of Stockholm 1972, studies on land use and land cover have become essential for monitoring environmental changes, especially in the context of global warming. Agrarian reform in Tunisia since the 1960s has profoundly transformed its agricultural landscape, making irrigation a cornerstone of the national economy. This research focuses on the effects of prolonged droughts and revised water policies since the 1980s, which have impacted the irrigated areas in the Lower Medjerda Valley. By integrating multisource and multi-resolution satellite data, including Sentinel-1, Sentinel-2, and SPOT, the study aims to provide a detailed cartographic analysis of land use and irrigation practices. Using NDVI and RVI indices derived from optical and radar data, it evaluates the health and extent of vegetative cover over a five-year period (2016–2020). Spatio-temporal distribution indicated a significant chlorophyll activity for July 2017, 2019, and 2020, with NDVI values around 0.6 and 0.8 for irrigated plots. The RVI index, calculated from Sentinel-1 radar data, also shows correlation, albeit with slight noise due to sensor quality, with values around 2.4. The evaluation of the SAM method on SPOT 7 images shows it effectively discriminates land cover in agricultural environments. Despite some limitations in differentiating similar classes, the results justify using SAM for detailed land cover mapping. The results reveal significant fluctuations in vegetation indices, correlated with variations in water reserves and irrigation management practices. This comprehensive analysis highlights the crucial link between water resource availability and agricultural productivity, offering insights for optimizing water use and enhancing sustainable agricultural practices in the region.