IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i19p12178-d925297.html
   My bibliography  Save this article

How Did the Built Environment Affect Urban Vibrancy? A Big Data Approach to Post-Disaster Revitalization Assessment

Author

Listed:
  • Hongyu Gong

    (School of Architecture and Environment, Sichuan University, Chengdu 610065, China)

  • Xiaozihan Wang

    (Wuyuzhang Honors College, Sichuan University, Chengdu 610065, China)

  • Zihao Wang

    (School of Architecture and Environment, Sichuan University, Chengdu 610065, China)

  • Ziyi Liu

    (School of Architecture and Environment, Sichuan University, Chengdu 610065, China)

  • Qiushan Li

    (Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu 610065, China)

  • Yunhan Zhang

    (School of Architecture and Environment, Sichuan University, Chengdu 610065, China)

Abstract

Quantitative assessment of urban vibrancy is crucial to understanding urban development and promoting sustainability, especially for rapidly developing areas and regions that have experienced post-disaster reconstruction. Taking Dujiangyan City, the hardest-hit area of the earthquake, as an example, this paper quantifies the urban economic, social, and cultural vibrancy after reconstruction by the use of multi-source data, and conducts a geographic visualization analysis. The purpose is to establish an evaluation framework for the relationship between the urban built environment elements and vibrancy in different dimensions, to evaluate the benefits of post-disaster restoration and reconstruction. The results show that the urban vibrancy reflected by classified big data can not be completely matched due to the difference in the data generation and collection process. The Criteria Importance Though Inter-criteria Correlation and entropy (CRITIC-entropy) method is used to construct a comprehensive model is a better representation of the urban vibrancy spatial characteristics. On a global scale, comprehensive vibrancy demonstrates high continuity and a bi-center structure. In the old town, the distribution of various urban vibrancies show diffusion characteristics, while those in the new district demonstrated a high degree of aggregation, and the comprehensive vibrancy is less sensitive to land-use mixture and more sensitive to residential land.

Suggested Citation

  • Hongyu Gong & Xiaozihan Wang & Zihao Wang & Ziyi Liu & Qiushan Li & Yunhan Zhang, 2022. "How Did the Built Environment Affect Urban Vibrancy? A Big Data Approach to Post-Disaster Revitalization Assessment," IJERPH, MDPI, vol. 19(19), pages 1-25, September.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:12178-:d:925297
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/19/12178/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/19/12178/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shumei Zhang & Wenshi Zhang & Ying Wang & Xiaoyu Zhao & Peihao Song & Guohang Tian & Audrey L. Mayer, 2020. "Comparing Human Activity Density and Green Space Supply Using the Baidu Heat Map in Zhengzhou, China," Sustainability, MDPI, vol. 12(17), pages 1-14, August.
    2. Runde Fu & Xinhuan Zhang & Degang Yang & Tianyi Cai & Yufang Zhang, 2021. "The Relationship between Urban Vibrancy and Built Environment: An Empirical Study from an Emerging City in an Arid Region," IJERPH, MDPI, vol. 18(2), pages 1-20, January.
    3. Yu Liu & Xi Liu & Song Gao & Li Gong & Chaogui Kang & Ye Zhi & Guanghua Chi & Li Shi, 2015. "Social Sensing: A New Approach to Understanding Our Socioeconomic Environments," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 105(3), pages 512-530, May.
    4. Alan March & Yogita Rijal & Sara Wilkinson & Ebru Firidin Özgür, 2012. "Measuring Building Adaptability and Street Vitality," Planning Practice & Research, Taylor & Francis Journals, vol. 27(5), pages 531-552.
    5. Deyi Feng & Lingli Tu & Zhongwei Sun, 2019. "Research on Population Spatiotemporal Aggregation Characteristics of a Small City: A Case Study on Shehong County Based on Baidu Heat Maps," Sustainability, MDPI, vol. 11(22), pages 1-19, November.
    6. Shiwei Lu & Chaoyang Shi & Xiping Yang, 2019. "Impacts of Built Environment on Urban Vitality: Regression Analyses of Beijing and Chengdu, China," IJERPH, MDPI, vol. 16(23), pages 1-16, November.
    7. Shaojun Liu & Ling Zhang & Yi Long, 2019. "Urban Vitality Area Identification and Pattern Analysis from the Perspective of Time and Space Fusion," Sustainability, MDPI, vol. 11(15), pages 1-27, July.
    8. Yuqing Zhang & Kun Shang & Zhipeng Shi & Hui Wang & Xueming Li, 2022. "Spatial Pattern of the Vitality of Chinese Characteristic Towns: A Perspective from Nighttime Lights," Land, MDPI, vol. 11(1), pages 1-17, January.
    9. Lingjun Tang & Yu Lin & Sijia Li & Sheng Li & Jingyi Li & Fu Ren & Chao Wu, 2018. "Exploring the Influence of Urban Form on Urban Vibrancy in Shenzhen Based on Mobile Phone Data," Sustainability, MDPI, vol. 10(12), pages 1-21, December.
    10. Xin Li & Yongsheng Qian & Junwei Zeng & Xuting Wei & Xiaoping Guang, 2021. "The Influence of Strip-City Street Network Structure on Spatial Vitality: Case Studies in Lanzhou, China," Land, MDPI, vol. 10(11), pages 1-17, October.
    11. Yihao Jiang & Zhaojin Chen & Pingjun Sun, 2022. "Urban Shrinkage and Urban Vitality Correlation Research in the Three Northeastern Provinces of China," IJERPH, MDPI, vol. 19(17), pages 1-22, August.
    12. Bo Huang & Yulun Zhou & Zhigang Li & Yimeng Song & Jixuan Cai & Wei Tu, 2020. "Evaluating and characterizing urban vibrancy using spatial big data: Shanghai as a case study," Environment and Planning B, , vol. 47(9), pages 1543-1559, November.
    13. He, Qingsong & He, Weishan & Song, Yan & Wu, Jiayu & Yin, Chaohui & Mou, Yanchuan, 2018. "The impact of urban growth patterns on urban vitality in newly built-up areas based on an association rules analysis using geographical ‘big data’," Land Use Policy, Elsevier, vol. 78(C), pages 726-738.
    14. Wang, Xiaoxi & Zhang, Yaojun & Yu, Danlin & Qi, Jinghan & Li, Shujing, 2022. "Investigating the spatiotemporal pattern of urban vibrancy and its determinants: Spatial big data analyses in Beijing, China," Land Use Policy, Elsevier, vol. 119(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jinyao Lin & Yaye Zhuang & Yang Zhao & Hua Li & Xiaoyu He & Siyan Lu, 2022. "Measuring the Non-Linear Relationship between Three-Dimensional Built Environment and Urban Vitality Based on a Random Forest Model," IJERPH, MDPI, vol. 20(1), pages 1-18, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jinyao Lin & Yaye Zhuang & Yang Zhao & Hua Li & Xiaoyu He & Siyan Lu, 2022. "Measuring the Non-Linear Relationship between Three-Dimensional Built Environment and Urban Vitality Based on a Random Forest Model," IJERPH, MDPI, vol. 20(1), pages 1-18, December.
    2. Wang, Xiaoxi & Zhang, Yaojun & Yu, Danlin & Qi, Jinghan & Li, Shujing, 2022. "Investigating the spatiotemporal pattern of urban vibrancy and its determinants: Spatial big data analyses in Beijing, China," Land Use Policy, Elsevier, vol. 119(C).
    3. Yuan Lai & Jiatong Li & Jiachen Zhang & Lan Yan & Yifeng Liu, 2022. "Do Vibrant Places Promote Active Living? Analyzing Local Vibrancy, Running Activity, and Real Estate Prices in Beijing," IJERPH, MDPI, vol. 19(24), pages 1-19, December.
    4. Kai Zhao & Jinhan Guo & Ziying Ma & Wanshu Wu, 2023. "Exploring the Spatiotemporal Heterogeneity and Stationarity in the Relationship between Street Vitality and Built Environment," SAGE Open, , vol. 13(1), pages 21582440231, February.
    5. Yihao Jiang & Zhaojin Chen & Pingjun Sun, 2022. "Urban Shrinkage and Urban Vitality Correlation Research in the Three Northeastern Provinces of China," IJERPH, MDPI, vol. 19(17), pages 1-22, August.
    6. Xucai Zhang & Yeran Sun & Ting On Chan & Ying Huang & Anyao Zheng & Zhang Liu, 2021. "Exploring Impact of Surrounding Service Facilities on Urban Vibrancy Using Tencent Location-Aware Data: A Case of Guangzhou," Sustainability, MDPI, vol. 13(2), pages 1-23, January.
    7. Nuria Vidal Domper & Gonzalo Hoyos-Bucheli & Marta Benages Albert, 2023. "Jane Jacobs’s Criteria for Urban Vitality: A Geospatial Analysis of Morphological Conditions in Quito, Ecuador," Sustainability, MDPI, vol. 15(11), pages 1-19, May.
    8. Wanshu Wu & Ziying Ma & Jinhan Guo & Xinyi Niu & Kai Zhao, 2022. "Evaluating the Effects of Built Environment on Street Vitality at the City Level: An Empirical Research Based on Spatial Panel Durbin Model," IJERPH, MDPI, vol. 19(3), pages 1-24, January.
    9. Jing Huang & Xiao Hu & Jieqiong Wang & Andong Lu, 2023. "How Diversity and Accessibility Affect Street Vitality in Historic Districts?," Land, MDPI, vol. 12(1), pages 1-23, January.
    10. Xiaojia Liu & Xi Chen & Yan Huang & Weihong Wang & Mingkan Zhang & Yang Jin, 2023. "Landscape Aesthetic Value of Waterfront Green Space Based on Space–Psychology–Behavior Dimension: A Case Study along Qiantang River (Hangzhou Section)," IJERPH, MDPI, vol. 20(4), pages 1-22, February.
    11. Ziyu Wang & Nan Xia & Xin Zhao & Xing Gao & Sudan Zhuang & Manchun Li, 2023. "Evaluating Urban Vitality of Street Blocks Based on Multi-Source Geographic Big Data: A Case Study of Shenzhen," IJERPH, MDPI, vol. 20(5), pages 1-20, February.
    12. Shaojun Liu & Yao Long & Ling Zhang & Hao Liu, 2021. "Quantifying and Characterizing Urban Leisure Activities by Merging Multiple Sensing Big Data: A Case Study of Nanjing, China," Land, MDPI, vol. 10(11), pages 1-20, November.
    13. Bahram Zikirya & Xiong He & Ming Li & Chunshan Zhou, 2021. "Urban Food Takeaway Vitality: A New Technique to Assess Urban Vitality," IJERPH, MDPI, vol. 18(7), pages 1-18, March.
    14. Renyang Wang & Qingsong He & Lu Zhang & Huiying Wang, 2021. "Coupling Cellular Automata and a Genetic Algorithm to Generate a Vibrant Urban Form—A Case Study of Wuhan, China," IJERPH, MDPI, vol. 18(21), pages 1-15, October.
    15. Xuanxuan Xia & Kexin Lin & Yang Ding & Xianlei Dong & Huijun Sun & Beibei Hu, 2020. "Research on the Coupling Coordination Relationships between Urban Function Mixing Degree and Urbanization Development Level Based on Information Entropy," IJERPH, MDPI, vol. 18(1), pages 1-24, December.
    16. He Liu & Xueming Li, 2022. "Understanding the Driving Factors for Urban Human Settlement Vitality at Street Level: A Case Study of Dalian, China," Land, MDPI, vol. 11(5), pages 1-20, April.
    17. Jian-gang Shi & Wei Miao & Hongyun Si, 2019. "Visualization and Analysis of Mapping Knowledge Domain of Urban Vitality Research," Sustainability, MDPI, vol. 11(4), pages 1-17, February.
    18. Runde Fu & Xinhuan Zhang & Degang Yang & Tianyi Cai & Yufang Zhang, 2021. "The Relationship between Urban Vibrancy and Built Environment: An Empirical Study from an Emerging City in an Arid Region," IJERPH, MDPI, vol. 18(2), pages 1-20, January.
    19. Liguo Zeng & Chunqing Liu & Mo Wang & Chengling Zhou & Guanhong Xie & Binsheng Wu, 2023. "Delineating the Dichotomy and Synergistic Dynamics of Environmental Determinants on Temporally Responsive Park Vitality," Sustainability, MDPI, vol. 15(17), pages 1-17, August.
    20. Yanyan Chen & Hanqiang Qian & Yang Wang, 2020. "Analysis of Beijing’s Working Population Based on Geographically Weighted Regression Model," Sustainability, MDPI, vol. 12(12), pages 1-16, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:12178-:d:925297. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.