Detailed Assessment of the Spatial Distribution of Urban Parks According to Day and Travel Mode Based on Web Mapping API: A Case Study of Main Parks in Wuhan.

Qiang Niu,Hao Wu,Yuan Xia,Ye Wang,Xi Tang

doi:10.3390/ijerph15081725

Abstract

This article employs two indexes—accessibility and effective service ratio (ESR)—to assess the spatial distribution of urban parks with the consideration of both equity and efficiency. Traditional approaches to calculate these two indexes are often based on the shortest distance to the park within its service radius by network analysis. Such approaches cannot reflect the actual travel behaviors of urban residents and require extensive data collection of road networks and complex parameter setting. To avoid these defects, this study directly acquires travel time data for various travel modes in a specific time period to the park through web mapping API (Application Program Interface), then calculates the accessibility and ESR of urban parks based on these detailed data. This method gets closer to actual park usage situation and avoids the cumbersome process of road network model building. At last, a case study is conducted on the assessment of spatial distribution of main parks in Wuhan, finding that districts with poor park accessibility in Wuhan can be divided into three types: districts with an absence of parks, districts with an insufficiency with parks, and districts separated from parks by traffic. Then, pertinent improvement suggestions are proposed, which provide some bases for decisions on future park planning and construction.

Highlights

As an important component of the ecosystem of urban greenspaces, urban parks play an important role in public health, urban environment [1,2], and biological diversity [3]
Parks are significant for improving city quality and living standards of residents, and the spatial distribution of a park determines its service level
This study utilized web mapping API data to evaluate the spatial distribution of park, dispensed with the complicated process of building road network data and calibrating parameters in traditional analysis, and considered actual usage of urban public parks with different days and modes of transport under the support of location big data owned by web map service providers

Summary

Introduction

As an important component of the ecosystem of urban greenspaces, urban parks play an important role in public health, urban environment [1,2], and biological diversity [3]. It can enhance social ties, create a sense of community, and improve living standards of urban residents [4,5], and it is considered to exert a great influence on the urban economy and real estate market [6,7]. People usually evaluate the spatial distribution of the park with indicators such as per capita park area, green space rate.

Methods

Results

Discussion

Conclusion