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Provision of urban green spaces is largely unbalanced. Therefore, urban municipalities are concerned to improve citizens' accessibility to vegetated areas. This study proposes a workflow that identifies spatial inequalities in provision of already existing green spaces and suggests locations for potential green space implementations. The workflow was probed in the city of Szeged, Hungary; however its flexibility allows transferability to other urban settings. First, potential vegetation classes were identified based on their heights and spectral behavior, all sourced from very high resolution stereo satellite imagery. Then locations of societal demand for green space provision were identified by using attribute and spatial information from census tracks. By using OpenStreetMap road network, the data analysis will measure distances between population with green space demand and existing green spaces, compares the results with actual green space visits, and finally proposes potential vegetation patches which can be transferred to community utilization. The expected outcomes will be threefold: differences between potential travel distances to potential green spaces and actual travelled distances to existing green spaces; map of hot spots of spatial inequalities in urban green space availability; and map of locations of unused green surfaces that have a potential for community use.