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

光栅图形 人口 流域 环境科学 分布(数学) 光栅数据 集水区 计算机科学 流动人口 空格(标点符号) 运输工程 地理 环境资源管理 数学 地图学 工程类 数学分析 社会学 人口学 人工智能 操作系统
作者
Wen Wu,Tianhao Zheng
出处
期刊:Urban Forestry & Urban Greening [Elsevier]
卷期号:82: 127893-127893 被引量:37
标识
DOI:10.1016/j.ufug.2023.127893
摘要

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.

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