Prioritizing restoration hotspots in riparian corridors using integrated spatial decision-support framework for...

Urban riparian corridors are increasingly degraded due to rapid urbanization. Yet spatial tools for prioritizing restoration remain limited, especially in data-poor regions. This study presents an Integrated Spatial Decision-Support Framework (ISDSF) that integrates high-resolution Sentinel-2, terrain and soil datasets within a principal component analysis (PCA)-weighted multi-criteria framework across a 500 m corridor of the river Gomati in Lucknow, India to generate a Composite Restoration Index (CRI) at 10 m resolution. The CRI revealed that 36.4% of the study area fell under high or very-high restoration priority classes, characterized by low NDVI/LAI, elevated LST, depleted SOC and increased bare/impervious surfaces. Ground surveys showed that higher CRI values were associated with reduced native species richness and increased invasive dominance, while Random Forest-based internal consistency assessment showed strong agreement between the CRI and its component indicators (R² = 0.97; RMSE = 0.01). By combining objective weighting, internal model checking and floristic ground-truthing, the framework provides a locally calibratable decision-support tool for targeting riparian restoration under urban pressure.