Measuring the accessibility of public green spaces in urban areas using web map services

Zhang, Jiamin; Yue, Wenze; Fan, Peilei; Gao, Jiabin

doi:10.1016/j.apgeog.2020.102381

Cited by 55 publications

(28 citation statements)

References 75 publications

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“…Street view images, POIs, and web-crawled building data provide the possibility to evaluate the detailed features of street design accurately at the city level, including the landscape, building space, sidewalk, and greening. The greening is part of the green infrastructure, emphasizing the connection between green spaces and functions, and contributing to the formation of a green space network [79][80][81][82]. The greening factors on a large scale can be measured more efficiently by using street view images; thus, the street design can be characterized with high quality [44].…”

Section: Discussionmentioning

confidence: 99%

Evaluating the Effects of Built Environment on Street Vitality at the City Level: An Empirical Research Based on Spatial Panel Durbin Model

Guo

et al. 2022

IJERPH

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There is evidence that the built environment has an influence on street vitality. However, previous studies seldom assess the direct, indirect, and total effect of multiple environmental elements at the city level. In this study, the features of the street vitality on Xiamen Island are described based on the location-based service Big Data. Xiamen Island is the central urban area of Xiamen, one of the national central cities in China. With the help of multi-source data such as street view images, the condition of design that is difficult to effectively measure with traditional data can be better explored in detail on a macro scale. The built environment is measured through a 5D system at the city level, including Density, Diversity, Design, Destination accessibility, and Distance to transit. Spatial panel Durbin models are constructed to analyze the influence of the built environment on the street vitality on weekdays and weekends, and the direct, indirect, and total effects are evaluated. Results indicate that at the city level, the built environment plays a significant role in promoting street vitality. Functional density is not statistically significant. Most of the elements have spatial effects, except for several indicators in the condition of the design. Compared with the conclusions of previous studies, some indicators have different effects on different spatial scales. For instance, on the micro scale, greening can enhance the attractiveness of streets. However, on the macro scale, too much greening brings fewer functions along the street, which inhibits the street vitality. The condition of design has the greatest effect, followed by destination accessibility. The differences in the influences of weekdays and weekends are mainly caused by commuting behaviors. Most of the built environment elements have stronger effects on weekends, indicating that people interact with the environment more easily during this period.

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Section: Discussionmentioning

confidence: 99%

Evaluating the Effects of Built Environment on Street Vitality at the City Level: An Empirical Research Based on Spatial Panel Durbin Model

Guo

et al. 2022

IJERPH

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“…Central Wuhan was selected as the study area for the following reasons. Firstly, most previous studies on the equity of UGS in specific cities in China have focused on the eastern coastal zone [ 63 , 64 ], which has advantages in terms of geographic location and economic development. In recent years, Wuhan, Zhengzhou, and other cities in central China have been developing rapidly.…”

Section: Methodsmentioning

confidence: 99%

Community-Level Urban Green Space Equity Evaluation Based on Spatial Design Network Analysis (sDNA): A Case Study of Central Wuhan, China

Peng

Cheng

2021

IJERPH

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Urban green spaces (UGSs) provide numerous irreplaceable environmental and social benefits to humankind, but the lack of baseline information makes it difficult to propose a reasonable greening strategy so as to achieve an equitable allocation of community green spaces. This paper divides UGSs into three classes using the spatial design network analysis (sDNA) and quantifies the UGS accessibility of communities in central Wuhan. Based on these results and the Gini coefficient, we analyze the UGS equity of the spatial distribution at the community level, then propose future greening strategies both at the city and community levels. The results show that the railway station and old Wuhan city are the core areas of traffic network strength (TNS). UGSs are evenly distributed in the core areas of TNS, but the number of UGSs in non-core areas is small, and their distribution is relatively uneven, and the number of communities with medium UGS accessibility is the largest, carrying the densest residential population. Most communities perform well in terms of UGS equity, but the UGS equity of 163 communities, covering a population of more than one million, remains to be improved. The method and conclusions of this study will contribute to the future greening policy making of 965 communities in central Wuhan, thus promoting the orderly planning and high-quality construction of community living circles.

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“…Based on previous studies [42], we assumed that there were two kinds of reasonable threshold values of time consumption for public green space in the time-cost decay functions. The first threshold is the maximum point, which represents the time period which residents prefer over all others.…”

Section: Time-cost Decay Analysis and Indicators Of Time Thresholdsmentioning

confidence: 99%

“…We further compared tolerance time thresholds for visiting parks with some research based on questionnaires [11,42], and found that the average actual travel time in Shanghai was larger than that reported in the latter, which was about 20-25 min for public transport. There seems to be, then, an inconsistency between subjective intentions and actual travel activities.…”

Section: Spatial Relationship Between Park Service Area and Accessibility Based On Time Thresholdsmentioning

confidence: 99%

“…With the advancements in information technology, online platforms such as Google, Yahoo, and Facebook have made their databases easily accessible to users through Application Programming Interfaces (APIs). Time costs with related distances and routes can be accurately obtained by using APIs offered by online maps, such as Google Maps in Western countries, and Baidu Map and AMap in China [41][42][43]. In contrast to network analysis by ArcGIS, the latest road networks will no longer need to be established ahead of time.…”

Section: Introductionmentioning

confidence: 99%

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Exploring Spatial Distribution of Urban Park Service Areas in Shanghai Based on Travel Time Estimation: A Method Combining Multi-Source Data

Hui

Yan

2021

IJGI

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Due to a growing appreciation for the ecological and recreational benefits of public green spaces, the evaluation of urban parks’ service efficiency, as well as citizens’ behavioral preferences for daily recreation, have become an increasing academic focus. However, due to the lack of empirical approaches, existing research on exploring park service areas has been simplified by their use of Euclidean distance or buffer sets by simulation, ignoring the fact that the likelihood of citizens visiting urban parks is time sensitive. Utilizing mobile signaling data and web map services, this study proposes an approach to estimating the travel times of park visitors and analyzing the characteristics of park service areas from the perspective of actual time consumption. Taking Shanghai as a case study, this research firstly identified the time–cost decay of parks with different areas and locations. A comparison analysis was then used to examine the spatial relationship between park service areas and their accessibility defined by time consumption. The results show that (1) urban parks in Shanghai have larger mean service radii than existing planning guidelines, and park service areas were significantly influenced by park locations; (2) people have a great preference for urban parks whose travel times by public transit are under 40 min, and they have no desire to visit parks located within or outside the Middle Ring Road when the travel times reach 60 min and 75 min, respectively; (3) the shapes of park service areas are consistent with the high-accessibility districts defined by time thresholds, in spite of some differences caused by citizens’ choices. These findings provide an effective tool for evaluating the actual characteristics of park recreational services, along with direct implications for policymakers aiming to establish effective strategies for improving the accessibility and vitality of urban parks.

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Measuring the accessibility of public green spaces in urban areas using web map services

Cited by 55 publications

References 75 publications

Evaluating the Effects of Built Environment on Street Vitality at the City Level: An Empirical Research Based on Spatial Panel Durbin Model

Evaluating the Effects of Built Environment on Street Vitality at the City Level: An Empirical Research Based on Spatial Panel Durbin Model

Community-Level Urban Green Space Equity Evaluation Based on Spatial Design Network Analysis (sDNA): A Case Study of Central Wuhan, China

Exploring Spatial Distribution of Urban Park Service Areas in Shanghai Based on Travel Time Estimation: A Method Combining Multi-Source Data

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