Indicators of Vegetation cover Deterioration in Sahel region, Using Remote Sensing, and local ecological knowledge (LEK), case study of Kordofan, Sudan

The Sahel region of Sudan is a highly vulnerable ecosystem that faces significant pressures from climate change, land degradation, and human activities. Monitoring changes in vegetation cover is essential for understanding the extent of these pressures and for informing effective mitigation and adaptation strategies.  Satellite-based remote sensing approaches provide a cost-efficient means of collecting information on the world’s forests and repeatedly surveying large or inaccessible forest areas. However, it may not always be possible to ground-truth associated findings using direct ecological field surveys conducted by trained forest scientists. Local ecological knowledge (LEK) is an alternative form of data that can be used to complement, interpret, and verify information from satellite data. In this study, we integrated remote sensing and LEK data to measure indicators of vegetation cover and understand patterns and drivers of forest cover change. LEK reports often concurred with or provided key information to enable the interpretation of satellite data. This reveals that between 1975 and 2000, North Kordofan experienced high, but uneven, rates of deforestation. There was a pronounced shift in the study area deforestation in the mid-1980s, coinciding with a period of extreme drought and famine, and associated with the clearance of trees in areas as an economic and fuel resource, as well as the conversion of forest to agricultural cropland. Threats increase the vulnerability of the study area's socio-ecological systems to future environmental change and are an obstacle to the recovery of threatened species across the Sahel zone. This research reviews key indicators used to assess changes in vegetation cover in the Sudanese Sahel, in Sudan, North Kordofan State - Al Dodyia and Umm Seimema area, focusing on remote sensing-based, and the role of ground-based surveys and local ecological knowledge (LEK) in validating remote sensing data and providing valuable insights into the drivers and indicators vegetation change