A conceptual model for identifying the risk susceptibility of urban green spaces using geo-spatial techniques

摘要: Urban green spaces are often regarded as the harbinger of sustainability in rapidly urbanizing world. This study forwards a conceptual framework towards urban space (UGS) management by quantification risk susceptibility UGS at neighborhood level using remote sensing data and geo-spatial techniques. Objective measure was performed weighted evaluation NDVI 20 m × 20 m grid over city Kolkata. The normalized index (NGI) developed to quantify implication built-up fabric. Both satellite image NGI values were spatially auto-correlated bivariate Moran’s I derive intricate relationship between area LISA. It observed that low green-spaces greatly influenced high around it. inference extended on Kolkata’s grid, results revealed older part had most susceptible zones, whereas surrounded wetlands stable region bearing resilience urbanization. Hence, determining risky zones for degradation, planners policy makers can efficiently allocate resources sustainable development conserving promoting UGS.