Wetlands in the eastern Democratic Republic of Congo (D.R.C) are crucial ecosystems that sustain biodiversity, support livelihoods, and regulate hydrological and climatic processes. However, since decades they are facing rapid ecological and social transformations driven by human activities, demographic growth, and land use changes. This research provides a comprehensive analysis of their spatial distribution, ecological characteristics, ecosystem services provided, and degradation dynamics in the South-Kivu Province. It uses an integrated approach combining remote sensing, field surveys, soil analyses, and socio-ecological assessments. First, wetland mapping was conducted using optical and Synthetic Aperture Radar (SAR) imagery integrated with topographic, hydrological, and vegetation indices. Four statistical classifiers (Random Forest “RF”, Artificial Neural Network “ANN”, Boosted Regression Tree “BRT”, and Maximum Entropy “MaxEnt”) were tested, with RF performing best (∼ 95:67%). The results revealed that wetlands cover ∼ 13:5% (898,690 ha) of the province, with significant spatial variability across territories. Second, the study characterized 137 wetlands based on soil, vegetation, and hydrological parameters, identifying four main types: permanently flooded marshes, peatlands, swamps, and seasonally floodplain/inland valleys (FP/IV). Anthropogenic pressures—especially agriculture, brickmaking, and fuelwood collection—have significantly altered their physicochemical and ecological functions. Statistical analyses showed that wetland use, drainage intensity, and location (in agroecological zones “AEZ”) largely explain variations in soil quality and biodiversity. Third, through a survey of 510 households, perceptions of wetland ecosystem services (WES) were analyzed revealing that provisioning and regulating services as the most recognized ES, with variations across wetland types and social groups. They are mainly perceived for their food and materials production, with limited recognition of their roles in biodiversity support and environmental regulation. From the Structural Equation Modeling (SEM) results four latent variables—livelihood, knowledge, personal, and geographical factors—were found to shape perceptions, highlighting the sociocultural intertwining of human–wetland relationships. Fourth, a Wetland soil degradation indicator (WSDI) was developed to quantify ecological degradation. The indicator, combining GIS, remote sensing, and soil profile data, revealed higher degradation in brickmaking areas compared to agricultural and intact wetland zones. Proximity to roads and settlements emerged as the main degradation drivers, confirming a spatial gradient of decline from edges to the wetland core. Finally, landscape analysis from 2000 to 2024 demonstrated a steady conversion of natural wetlands into agricultural and human-modified landscapes, resulting in fragmentation and habitat loss. These transformations reflect broader socioeconomic and environmental dynamics that intertwine governance, equity, and climate pressures. Sustainable wetland management in eastern D.R.C thus requires integrated strategies linking ecological restoration with social participation and adaptive land-use planning. This thesis contributes novel insights into the mapping, classification, and socioecological understanding of wetlands in a tropical, data-scarce region. It provides critical tools and frameworks for guiding conservation, restoration, and more sustainable policies across rural landscapes in the great lakes African region.