Author
Listed:
- Xinlin Ma
- Yan Song
- Fangzheng Lyu
- Yang Yang
- Yuhua Wang
- Xijing Li
- Shaopeng Zhong
Abstract
Urban retrofitting is a fundamental approach for achieving sustainable and resilient urban development in the face of contemporary challenges. The increasing prevalence of urban big data presents an opportunity to establish a robust analytical framework for urban retrofitting, enabling more effective comparative studies and informed decision‐making. This paper introduces a comprehensive 5R framework—Re‐inhabitation, Re‐building, Re‐transportation, Re‐capitalization, and Re‐greening—to provide a multidimensional perspective on urban retrofitting. The 5R framework facilitates a holistic understanding of urban transformation processes and establishes standardized metrics for analyzing urban retrofitting initiatives using diverse urban big data sources. To demonstrate the adaptability and effectiveness of the 5R framework in a real‐world context, we conduct a case study of Charlotte, North Carolina. By applying innovative methods for the integration and analysis of extensive datasets, our study offers new insights into the evaluation of urban retrofitting efforts, such as transportation accessibility, micro‐scale building improvements, investment patterns, green space enhancements, and overall livability. This approach addresses existing research gaps by providing a structured set of indicators that assess each dimension of urban transformation comprehensively. Beyond academic advancements, the 5R framework offers practical tools for policymakers and urban planners to evaluate retrofitting interventions, quantify their outcomes, and understand the dynamics of evolving urban spaces. The insights gained through our research highlight the importance of using big data to enhance the scope and impact of urban development strategies, ultimately bridging the gap between theoretical concepts and real‐world urban retrofitting applications. Our findings demonstrate the potential of the 5R framework to serve as a guiding model for more sustainable, data‐driven urban growth and revitalization.
Suggested Citation
Xinlin Ma & Yan Song & Fangzheng Lyu & Yang Yang & Yuhua Wang & Xijing Li & Shaopeng Zhong, 2025.
"Revitalizing Cities: The 5R Framework Approach to Urban Retrofitting and Big Data Insights,"
Growth and Change, Wiley Blackwell, vol. 56(1), March.
Handle:
RePEc:bla:growch:v:56:y:2025:i:1:n:e70018
DOI: 10.1111/grow.70018
Download full text from publisher
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:bla:growch:v:56:y:2025:i:1:n:e70018. 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.
We have no bibliographic references for this item. You can help adding them by using 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0017-4815 .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.