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Urban Park Green Space (UPGS) is an essential component of cities, with a wide range of important services. There is a keener demand for green space in the process of urbanization. Previous studies have extensively evaluated the residents' accessibility to green space, which belonging to the demand of UPGS's social service function, but rarely combined the ecological service demand to conduct a refined calculation. This may lead to biased results in the evaluation of the satisfaction of green space. Considering the scarcity of urban land resources, it is difficult to support the efficient use of space based on these results. To fill this gap, this study evaluated the accessibility of various service functions that UPGS can provide from a variety of demand perspectives in central Beijing using multi-source geospatial big data. The results show that: (1) The accessibility results may be overestimated when ignoring eco-service demand. (2) Regions with worse or poor accessibility have the largest proportion, and accessibility presents an obvious low–high-low cyclic structure. (3) Urban peripheral areas are always in a significant disadvantaged position in terms of accessibility. Based on the accessibility results, the solution is further provided by using PSO algorithm to simulate the location of new parks to solve the problem of insufficient UPGS supply in the low accessibility area. Our study can provide better insights for city managers to formulate effective green space management strategies and references for optimization strategy.
Qin et al. (Mon,) studied this question.
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