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

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

Casali, Y. (TU Delft Transport and Logistics; Basque Centre for Climate Change)
Aydin, N.Y. (TU Delft System Engineering)
Comes, M. (TU Delft Transport and Logistics)

2024

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.

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

http://resolver.tudelft.nl/uuid:ee516813-bf31-4e57-a7b1-d11b06c4db1f

https://doi.org/10.1177/23998083241235246

2399-8083

Environment and Planning B: Urban Cities and City Science

Institutional Repository

journal article

© 2024 Y. Casali, N.Y. Aydin, M. Comes