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Sustainable Renewal of Historical Urban Areas: A Demand–Potential–Constraint Model for Identifying the Renewal Type of Residential Buildings

Author(s): ORCID

Medium: journal article
Language(s): English
Published in: Buildings, , n. 8, v. 12
Page(s): 1210
DOI: 10.3390/buildings12081210
Abstract:

The assessment of buildings facilitates the exploration of the viability of progressive and organic renewal, prevents the aimless and unorganized demolition of residential buildings in previous urban renewal projects, and facilitates the balancing of the preservation and sustainable development of historical urban areas. Studies have rarely examined the effect of regional factors on building renewal or differentiated the effects of historic preservation and development conditions. The fundamental function of historical urban areas in China is to provide residence. Therefore, this study developed a framework to identify the renewal type of residential buildings. The developed framework was used to construct a demand–potential–constraint model with assessment indicators related to three dimensions, namely renewal demand, development potential, and preservation constraint. Moreover, discriminant matrices were employed to divide the renewal of residential buildings into four modes and subdivide it into six types. The historical urban area of Suzhou was selected as the study site. According to the results of renewal type identification, renewal schedules and models with high referential value can be developed by urban renewal planners, which facilitates the optimization of resource allocation. The developed framework provides novel theoretical and practical insights regarding building renewal assessment in historical urban areas.

Copyright: © 2022 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10688733
  • Published on:
    13/08/2022
  • Last updated on:
    10/11/2022
 
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