Author
Listed:
- Blanca López-Catalán
- Victor A. Bañuls
- Josune Hernantes Apezetxea
- Leire Labaka
Abstract
Problem, research strategy, and findingsIn terms of resilience, city planners encounter challenges in assessing, improving, and continually updating both the dimensions they cover and the indicators needed to adapt to the specific time, risk, or context they aim to address. These difficulties can lead to considering city resilience from a partial perspective, yielding constrained outcomes and a restricted appraisal of the inherent risks and vulnerabilities of urban settings. Here we propose artificial intelligence (AI) tools for extracting key resilience topics from the academic literature and resilience plans and generating urban resilience indicators for any resilience framework. This holistic approach covers a wide range of approaches. We discuss how AI can be also used as a tool for monitoring and improving planning for enhancing resilience. Our methodology is based on an innovative combination of topic modeling, content analysis, and generative AI. The model is based on 1,452 indicators that can be extended automatically through a machine learning process. We also present an updated literature review on urban resilience indicators. The main contribution of our research is the proposal of an innovative methodology based on AI that addresses two challenges in city planning: the synthesis of key topics on resilience and the context-dependent construction of resilience indicators for urban planning.Takeaway for practiceThis research is aimed at guiding urban planners, researchers, and policymakers to tackle urban resilience more comprehensively with AI and to update resilience frameworks since there is no global view of the topics covered by urban resilience. We demonstrate a practical application of the Smart Mature Resilience framework focusing on urban planning. We detail the topics that should be considered to define indicators and actions for developing resilience plans. Our study provides practical guidance for city planners, enabling them to create context-specific resilience indicators by emphasizing a hands-on approach to indicator design.
Suggested Citation
Blanca López-Catalán & Victor A. Bañuls & Josune Hernantes Apezetxea & Leire Labaka, 2025.
"Artificial Intelligence for Extracting Key City Resilience Indicators: An Application to the Smart Mature Resilience Framework,"
Journal of the American Planning Association, Taylor & Francis Journals, vol. 91(4), pages 537-554, October.
Handle:
RePEc:taf:rjpaxx:v:91:y:2025:i:4:p:537-554
DOI: 10.1080/01944363.2025.2501560
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