Integrating Remote Sensing, GIS, and Citizen Science to Map Illegal Waste Dumping Susceptibility in Dakar, Senegal

Solid waste management remains a critical challenge in rapidly urbanizing regions of the Global South, where limited infrastructure and informal disposal practices compromise environmental and public health. This study addresses the issue of illegal waste dumping in Dakar, Senegal, by integrating remote sensing, geographic information systems, and citizen science into a multi-criteria framework to identify areas most susceptible to dumping. Using Landsat 8 and Sentinel-2 imagery, indicators such as land surface temperature, vegetation, soil, and water indices were combined with demographic and infrastructural data. A citizen survey involving local university students provided social perception scores and criterion weights through the Analytic Hierarchy Process. The resulting susceptibility maps revealed that high and very high dumping probabilities are concentrated around the Mbeubeuss landfill and densely populated areas of Keur Massar, while Malika showed lower susceptibility. Sensitivity analysis confirmed the model’s robustness but highlighted the influence of thermal and social perception variables. The results show that 28–35% of the study area falls under high or very high susceptibility, with hotspots concentrated near wetlands, informal settlements, and poorly serviced road networks. The weighted model demonstrates stronger spatial coherence compared to the unweighted version, offering improved interpretability for waste monitoring. These findings provide actionable insights for the Société Nationale de Gestion Intégrée des Déchets (SONAGED) and for municipal planners to prioritize interventions in high-susceptibility zones. Rather than being entirely novel, this study builds on existing remote sensing, geographic information systems and citizen science approaches by integrating them within a multi-criteria framework specifically adapted to a West African context.