Assessing Park Accessibility Based on a Dynamic Huff Two-Step Floating Catchment Area Method and Map Service API

Abstract

Park green space (PGS) is an important part of urban ecosystem and green infrastructure, and the ease of access to PGS is closely related to the health of residents. A growing number of studies have attempted to identify accessibility disparities, but results have varied because of the travel mode choice and the measurement method. This study proposes a dynamic Huff two-step floating catchment area (H2SFCA) method based on map service API (Application Programming Interface) to assess the accessibility of PGS, with the Gini coefficient and bivariate local Moran’s I used to analyze accessibility equity. Results show that: (1) driving and biking modes have more significant spatiotemporal compression effects than dynamic modes, public transit, and walking mode. (2) The accessibility values and spatial patterns vary significantly by travel mode. The PGS availability pattern at the local level is more uneven than the distribution of accessibility at the regional level. In comparison with dynamic travel modes, the accessibility values for the single travel mode are more likely to be overestimated or underestimated. (3) The PGS accessibility by the dynamic modes generally has better spatial equity and residents can select suitable travel tools to acquire more equitable park services. In addition, there is a significant accessibility difference between dynamic driving-based mode and dynamic transit-based mode in four subdistricts, which are mainly located in the south of Tianhe District. The public transport facilities linking parks in these areas need to be optimized. This study further improves the accessibility evaluation method, with the findings conducive to the implementation of refined PGS planning and management.

Keywords

• accessibility
• park green space
• Huff 2SFCA
• dynamic travel mode
• map service API