Introduction

Urban areas are increasingly facing significant shock events and chronic stresses. Shock events include natural disasters like earthquakes and severe storms, which may damage infrastructure and displace populations, as well as cyberattacks that disrupt critical services and public health crises that strain healthcare systems. At the same time, chronic stresses, such as income inequality, housing unafford ability, and inadequate public transportation, gradually erode a city’s capacity to maintain stability. As a result, there is an increasing need to understand and respond to how these challenges impact our economy, communities, and environment. In this context, urban resilience the ability of individuals, communities, businesses, governments, and urban systems to survive, adapt, and thrive becomes crucial. Ensuring resilience is vital for maintaining functionality and supporting the well-being of residents during these disruptive events, enabling cities to withstand both acute shocks and ongoing stresses.

To effectively enhance urban resilience, advanced data-driven techniques play a pivotal role by empowering cities to proactively enhance infrastructure, promote social equity, and optimise access to essential services. By leveraging machine learning, predictive analytics, and data mining, cities can gain actionable insights to anticipate disruptions, allocate resources efficiently, and implement timely interventions. These data-driven strategies not only strengthen cities’ capacity to adapt to evolving challenges but also ensure sustainable development and improved well-being for all residents. 

The objective of this workshop is to provide a collaborative platform for discussing and showcasing advanced data-driven techniques that enhance urban resilience. It will focus on methodologies that support urban areas in responding effectively to acute shocks and chronic stresses, ensuring sustainability, adaptability and long-term urban well-being.