Urban green spaces are a critical component of cities, providing environmental, social, cultural, and economic benefits. To support smart(er) decisions by city planners and managers, this study aims to investigate how open data sources could be integrated into urban green space management. Specifically, it proposes a novel GIS-based method to prioritise urban green space in a resource-constraint scenario so that social benefits are maximised. To quantify the social benefits, the methodology is based on the WHO indicator, which recommends access to at least 0.5-1 ha of green space within 300 metres\u27 linear distance to all the city residents. The approach assigns each urban green space an \u27accessibility score\u27 based on its significance in the city, and a \u27quality score\u27 based on its performance on different quality parameters (size, greenness, quietness, and safety). Urban green spaces are ranked with respect to these two scores, enabling to prioritise spaces under resource constraints such as water shortage, limited staff, or budget. This approach is demonstrated through a case study on a mid-size German city and is transferable to other cities worldwide with varying weightage factors
