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Spatial Characteristics of the Abandonment Degree of Residential Quarters Based on Data of the Housing Sales Ratio—A Case Study of Kunming, China

Author(s):
ORCID



Medium: journal article
Language(s): English
Published in: Buildings, , n. 1, v. 13
Page(s): 29
DOI: 10.3390/buildings13010029
Abstract:

The abandonment degree of an urban residential building can reflect the popularity of residential areas. This study uses this idea as a basis for proposing the concept of using residential quarters’ abandonment rate to measure the abandonment degree of an area. The spatial pattern of the abandonment rate and its clustering characteristics were obtained by taking 2517 residential quarters in Kunming’s Main Urban District as research object, and using their listing for sale ratio data. Thereafter, curve estimation was used to explore the influencing factors of abandonment rate. The results are as follows. (1) The abandonment rate of the four circles in Kunming’s Main Urban District increases from inside to outside, showing the pattern of the core area–second ring area–third ring area–new urban district, with evident “core–edge” characteristics. (2) The relationship between distance from the city center, housing ages, and abandonment rate can be well fitted using a quadratic function and shows an inverted “U”-shaped “rising–declining” trend. The relationship between housing prices and abandonment rate is fitted by the inverse function, showing an evident “up” trend. This study is a reference for managers of relevant departments and urban planners in formulating reasonable urban housing development policies.

Copyright: © 2023 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
    10712379
  • Published on:
    21/03/2023
  • Last updated on:
    10/05/2023
 
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