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

Int J Environ Res Public Health. 2022 Sep 26;19(19):12178. doi: 10.3390/ijerph191912178.

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.

Keywords: geospatial model; geovisual analytics; multi-source data; post-disaster reconstruction; sustainable development.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Big Data
  • Built Environment
  • China
  • Cities
  • City Planning / methods
  • Disasters*
  • Earthquakes*

Grants and funding

This research was funded by Sichuan University, Fundamental Research Funds for the Central Universities, grant number 2021SCU12125.