This project, led by undergraduate researchers from Argentina's Universidad Nacional del Nordeste, investigates the impact of human-induced land-use changes on flood patterns in the Coronel Mollinedo basin in Salta, Argentina. Due to aggressive deforestation and unsustainable agricultural practices, soil erosion and increased hydraulic runoff have dramatically transformed this region. Using EOSDA LandViewer, the team gathered satellite data over a 50-year period (1968–2018), analyzing vegetation indices and land cover changes to compute the Curve Number (CN) an indicator of runoff potential that correlates with flood risk. Their comprehensive methodology combined supervised and unsupervised classification techniques, allowing for detailed mapping of the basin's vegetation cover and soil moisture status. Through rigorous classification of land cover types and analysis of runoff potential, the study highlighted a consistent increase in CN, correlating with elevated flood risk, affecting local infrastructure, including railways and roads.