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Optimization of Walk Score Based on Street Greening—A Case Study of Zhongshan Road in Qingdao

Author

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  • Ye Sun

    (School of Architecture and Arts, Dalian University of Technology, Dalian 116081, China)

  • Wei Lu

    (School of Architecture and Arts, Dalian University of Technology, Dalian 116081, China)

  • Peijin Sun

    (School of Architecture and Arts, Dalian University of Technology, Dalian 116081, China)

Abstract

Enhancing the walkability of urban streets is an effective means to improve public health, alleviate traffic congestion, and enhance the living environment. In China, the government has actively encouraged green travel and promoted improvements in the walk system. The walkability of the built environment is affected by many factors. In addition to the configuration of daily life facilities, street greening can have significant effects on walkability. To explore the rationality of street life facilities and understand the impact of the natural attributes of the block space (street-level greening) on the quality of the walking environment, we evaluated the walkability of Zhongshan Road in Qingdao, China and optimized the algorithm of the walk score. In this study, we selected residential areas as the starting point and modified the weight coefficients for facilities to evaluate the walkability of streets. Traditional research methods were combined with street view image capture, and the rate of the attenuation factor was used for the new optimization algorithm. We discussed the rationality of street life facilities and increased the green vision rate using a correction index. By comparing changes in walkability before and after joining, we analyzed the necessity of including new indicators. The results show that the average walking index of Zhongshan Road is 79.74, and the overall performance is good, showing a high trend in the west and a low trend in the east, and a high trend in the south and a low trend in the north. According to the general walking index, western stations and southern coastal areas have higher scores, and living facilities are well equipped; old northern and eastern residential areas have lower scores. Among them, the average weight of bookstores is 0.74, and the average weight of parks is 0.69. To meet residents’ needs for daily leisure activities, adding bookstores or similar facilities in community parks would be necessary to improve daily facilities and services. The average green viewing rate of Zhongshan Road is 20.48%, which is lower than the best visual perception value of 25.00%. Comparing the walking index changes before and after adding the green viewing rate, the high-scoring area shifted from the west to the south, and the west walking index has the most significant decline. Street greening has a certain impact on the quality of the walking environment. The results and conclusions of this study can be used as a reference in developing street walkability indicators and further improving the evaluation system.

Suggested Citation

  • Ye Sun & Wei Lu & Peijin Sun, 2021. "Optimization of Walk Score Based on Street Greening—A Case Study of Zhongshan Road in Qingdao," IJERPH, MDPI, vol. 18(3), pages 1-13, January.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:3:p:1277-:d:490546
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    References listed on IDEAS

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    1. Dustin T. Duncan & Jared Aldstadt & John Whalen & Steven J. Melly & Steven L. Gortmaker, 2011. "Validation of Walk Score ® for Estimating Neighborhood Walkability: An Analysis of Four US Metropolitan Areas," IJERPH, MDPI, vol. 8(11), pages 1-20, November.
    2. Jiabin Yu & Chen Yang & Shen Zhang & Diankai Zhai & Jianshe Li, 2020. "Comparison Study of Perceived Neighborhood-Built Environment and Elderly Leisure-Time Physical Activity between Hangzhou and Wenzhou, China," IJERPH, MDPI, vol. 17(24), pages 1-12, December.
    3. Alawadi, Khaled & Khanal, Asim & Doudin, Azhar & Abdelghani, Rahma, 2021. "Revisiting transit-oriented development: Alleys as critical walking infrastructure," Transport Policy, Elsevier, vol. 100(C), pages 187-202.
    4. Marsden, Greg, 2006. "The evidence base for parking policies--a review," Transport Policy, Elsevier, vol. 13(6), pages 447-457, November.
    5. Shaohua Tan & Fengxiao Cao & Jinsu Yang, 2020. "The Study on Spatial Elements of Health-Supportive Environment in Residential Streets Promoting Residents’ Walking Trips," IJERPH, MDPI, vol. 17(14), pages 1-33, July.
    6. Cain, Kelli L. & Millstein, Rachel A. & Sallis, James F. & Conway, Terry L. & Gavand, Kavita A. & Frank, Lawrence D. & Saelens, Brian E. & Geremia, Carrie M. & Chapman, James & Adams, Marc A. & Glanz,, 2014. "Contribution of streetscape audits to explanation of physical activity in four age groups based on the Microscale Audit of Pedestrian Streetscapes (MAPS)," Social Science & Medicine, Elsevier, vol. 116(C), pages 82-92.
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    4. Zhang, Zhehao & Wang, Haiming & Fisher, Thomas, 2024. "The development, validation, and application of the campus walk score measurement system," Transport Policy, Elsevier, vol. 152(C), pages 40-54.
    5. Le Zhang & Xueyan Li & Yanlong Guo, 2024. "Research on the Influencing Factors of Spatial Vitality of Night Parks Based on AHP–Entropy Weights," Sustainability, MDPI, vol. 16(12), pages 1-20, June.

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