A data-driven approach to analyse the co-evolution of urban systems through a resilience lens: A Helsinki case study

Ylenia Casali*, Nazli Yonca Aydin, Tina Comes

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Urban areas are dynamic systems, in which different infrastructural, social and economic subsystems continuously co-evolve. As such, disruptions in one system can propagate to another. However, open challenges remain in (i) assessing the long-term implications of change for resilience and (ii) understanding how resilience propagates throughout urban systems over time. Despite the increasing reliance on data in smart cities, few studies empirically investigate long-term urban co-evolution using data-driven methods, leading to a gap in urban resilience assessments. This paper presents an approach that combines Getis-ord Gi* statistical and correlation analyses to investigate how cities recover from crises and adapt by analysing how the spatial patterns of urban characteristics and their relationships changed over time. We illustrate our approach through a study on Helsinki’s road infrastructure, socioeconomic system and built-up area from 1991 to 2016, a period marked by a major socioeconomic crisis. By analysing this case study, we provide insights into the co-evolution over more than two decades, thereby addressing the lack of longitudinal studies on urban resilience.

Original languageEnglish
Number of pages18
JournalEnvironment and Planning B: Urban Analytics and City Science
DOIs
Publication statusPublished - 2024

Keywords

  • Co-evolution
  • Getis-Ord Gi*
  • recovery
  • resilience
  • road network
  • spatiotemporal data

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