A layout optimization approach to urban park green spaces based on accessibility evaluation: a case study of the central area in Wuxi city

ABSTRACT

Planning urban park green spaces equitably and effectively is a central concern for maintaining a sustainable city and enhancing the quality of life of urban dwellers. In this case study of Wuxi city, facilitated by multisource big data, a new approach for optimizing the urban park green space distribution was explored. The improved two-step floating catchment area method was employed in combination with the network analyst in ArcGIS, the real entrances of urban park green spaces as search centres, multiple radii, and the distance decay function. The districts with low accessibility to urban park green spaces were mapped accurately as the main zones for equity promotion. Then, the key plots for the layout optimization of urban park green spaces at different scales were identified based on the location-allocation model. The results indicated a significant spatial gradient pattern of the accessibility index and a lower degree of spatial fitting between the service capacity of urban park green spaces and user demands in the old town. Additionally, operable location selection strategies prioritizing the urban natural environment and integrating the urban inventory space for urban park green space layout to improve the accessibility level were tentatively proposed. Finally, for the factors influencing accessibility, the park’s size and conditions, transportation network, and the social attribute of urban residents were further discussed. This study could help city managers and planners conduct the layout optimization of urban park green spaces more effectively with the aim of promoting an environmentally equitable and sustainable life.

KEYWORDS:

• Urban park green spaces
• accessibility
• layout optimization
• 2SFCA method
• LA model

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under grant number 51838003; and National Key Research and Development Program of China under grant number 2019YFD1100405.