Establishing a "dynamic two-step floating catchment area method" to assess the accessibility of urban green space in Shenyang based on dynamic population data and multiple modes of transportation

Abstract

As an integral part of the urban environment, urban green space (UGS) is of great significance in maintaining urban ecosystem balance and biodiversity. Spatial accessibility is an important indicator of UGS distribution and can be calculated by the two-step floating catchment area method (2SFCA). However, problems exist in previous studies using 2SFCA: (1) the dynamics in population distributions are ignored when measuring UGS demand; and (2) travel costs are calculated for only a single mode of transportation. To address these problems, this study proposes a dynamic two-step floating catchment area method (D2SFCA) based on the Baidu heatmap and direction application programming interface and compares it with the traditional 2SFCA to investigate the characteristics of and differences in UGS accessibility in the first-ring built-up area of Shenyang, China. The results show the following: (1) the dynamic population distribution data calculated by the heatmap yielded the highest population density raster (581.0–1342.0 p/hm2) in areas with dense road networks and the lowest population density raster (2.0–91.0 p/hm2) in areas with railways and rivers, thereby more accurately reflecting reality and better quantifying the UGS demand than the static population distribution data; (2) the D2SFCA and 2SFCA findings had a slightly different distribution, and the D2SFCA assessment results more accurately reflected actual patterns, especially when the road data were inaccurate. In summary, the D2SFCA is more suitable for assessing accessibility and can identify specific areas that lack UGS. This study provides a scientific basis and methodological support for improving the services level and equity of UGS.