Integrated remote sensing and multi-criteria evaluation to assess coastal ecosystem degradation under climate and human pressures: Insights from Bangladesh

Ecosystems provide vital services for human well-being and economic growth but are increasingly degraded by natural and human activities. Coastal ecosystems, particularly Bangladesh's exposed coast, are experiencing severe soil loss due to erosion, land use alterations from human activities, and increased pressure from climate change-induced hazards and disasters, leading to ecosystem degradation. Thus, this study attempts to identify the spatiotemporal pattern of land-based eco-environmental degradation using remote sensing and multi-criteria evaluation (MCE) analysis from 2000 to 2024. Seven criteria, namely soil loss, spatial severity of impact (SSI), ecological integrity depletion (EID), normalized difference vegetation index (NDVI), normalized difference water index (NDWI), land-based carbon emission (LCE), and bio-capacity (BC), are considered to assess the degradation pattern. The analytical hierarchy process (AHP) is used to weigh these criteria, and the weighted sum technique is applied. The findings show that nearly 37 percent of the land experienced high to very high degradation, whereas 42 percent of the land was affected by moderate degradation. The degradation factors vary by region, with deforestation and aquaculture being the primary drivers in the Sundarbans (western coast), erosion in the Meghna Estuary (central coast), and ecological loss as the source of urban expansion in coastal cities such as Chittagong (eastern shore). The degradation model was successfully validated with a predictive performance that seems high (AUC = 0.94) and indicates robustness of the indicators and methods selected. Although the study mainly used environmental data, social and climate factors may be integrated and will give more precise results in future research. Even so, the findings can help improve land use planning, restoration, and climate action under different national plans. This study aims to develop an innovative approach to achieving spatiotemporal degradation patterns, thereby aiding stakeholders and policymakers in creating a resilient ecosystem.