Urban agglomeration transportation resilience: evaluation and evolution analysis using a data-driven model
As global urbanization accelerates, urban transportation systems increasingly face challenges from natural disasters and public safety issues. Resilience in urban transportation is essential for sustainable urban development. This study proposes an innovative, data-driven approach to quantify urban...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
|
| Series: | Environmental and Sustainability Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2665972725001357 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | As global urbanization accelerates, urban transportation systems increasingly face challenges from natural disasters and public safety issues. Resilience in urban transportation is essential for sustainable urban development. This study proposes an innovative, data-driven approach to quantify urban transportation resilience, integrating genetic algorithms (GA), backpropagation (BP) neural networks, and the entropy weighting method. This approach aims to eliminate the introduction of subjective biases by experts in traditional methods, providing a more accurate and objective evaluation results. For practical application, the Chengdu-Chongqing urban agglomeration was selected as a case study to evaluate the resilience of its transportation systems. Building on this, this research further investigates the evolving characteristics and patterns of urban transportation resilience, aiming to provide valuable insights for resilience research and strategic planning in urban transportation. The results indicate that an overall upward trend in the transportation resilience of the Chengdu-Chongqing area from 2012 to 2022, and presents a double-peak structure in 2022. Resilience characteristics within the agglomeration took various forms, such as ''pyramid,'' and ''core-edge.'' Throughout the period, the resilience exhibited α-convergence, while the spatial distribution displayed a negative spatial correlation. Moreover, when accounting for spatial correlations, a significant absolute β-convergence trend in resilience was observed. |
|---|---|
| ISSN: | 2665-9727 |