Mapping Land and Vegetation Changes in Sudan Using Landsat Satellite Data (1994–2018)

Monitoring rapid environmental modifications and surface transformations in vulnerable arid catchments requires robust multi-temporal satellite data analysis. This study presents an earth observation framework designed to detect, map, and evaluate Land Use and Land Cover (LULC) changes across a 24-year monitoring timeline (1994, 2009, and 2018). Utilizing multispectral datasets obtained from Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Operational Land Imager (OLI), a hybrid classification approach was applied, combining unsupervised classification with field-based reference data collected during ground surveys, which were subsequently used to guide a supervised reclassification of the imagery. This iterative combination of remote and field-based information was adopted to reinforce classification reliability prior to change detection. The classification matrix successfully isolated six distinct environmental classes: bare land, clay soil, sandy soil, settlements, open water bodies, and vegetation cover. The classification results reveal substantial spatial changes: vegetation cover in Omdurman remained limited throughout the study period, representing 3.2%, 3.1%, and 4.2% of the total area for 1994, 2009, and 2018, respectively. Conversely, Sharg El-Neel exhibited pronounced vegetation fluctuations, with the largest relative area estimated at 31.4% in 1994 and peaking at 41.3% in 2009, before declining to 24.7% in 2018. This notable temporal reduction in vegetative surfaces coincided with a rapid expansion of mobile sandy soils, which occupied 26.3%, 14.8%, and 38.3% of Sharg El-Neel in 1994, 2009, and 2018, respectively. This research concludes that multi-sensor Landsat processing combined with field-based hybrid classification provides an effective, high-frequency approach to monitoring desertification and surface degradation, establishing a reliable digital observation baseline for sustainable land-use planning and ecological risk governance in vulnerable desert environments.