Thesis subject
MSc thesis topic: Quantifying urban spatial resilience
Cities are composed of interconnected social, economic, and ecological networks. These networks face increasing challenges from changing weather patterns, natural disasters, and other crises, which can disrupt urban life. Urban resilience refers to the ability of cities to absorb, adapt to, and transform in response to these shocks and stresses. Within this broader concept, urban spatial resilience focuses specifically on the physical and spatial characteristics of cities that contribute to their overall resilience. Evaluating spatial resilience involves considering multiple dimensions, making it a complex but essential task.
This research aims to identify the key components that define spatial resilience and to use probabilistic graphical models to study uncertainties and dependencies among these components. By applying this approach, the study will assess the current state of an urban environment to determine areas under pressure and provide insights for improving resilience strategies.
Background
Spatial resilience describes how well a city can withstand disruptions and continue to function. It is influenced by physical infrastructure, ecological services, and socio-economic structures, all of which interact to shape urban adaptability. Strong and well-maintained physical infrastructure, such as buildings, roads, and utilities, ensures that cities can absorb shocks and recover quickly from disasters. Ecological services, including green spaces, wetlands, and waterways, help regulate the environment by reducing flood risks, mitigating heat, and improving air quality. Socio-economic structures, which include land use patterns, community networks, and economic diversity, determine how well people and businesses adapt to crises.
Given the complexity of these interactions, traditional assessment methods often fail to capture the full scope of spatial resilience. This study applies probabilistic graphical models, which allow for a structured analysis of uncertainties and dependencies within urban systems. By mapping these relationships, this research will provide a clearer understanding of how different factors contribute to resilience.
Objectives and Research questions
This research aims to identify and analyze the key components of urban spatial resilience and to develop a probabilistic graphical model that quantifies uncertainties and dependencies among these components.
Requirements
Literature and information
- https://doi.org/10.1016/j.scs.2024.105527
- https://doi.org/10.1016/j.ijdrr.2024.104694
- https://doi.org/10.1016/j.envres.2015.11.009
Theme(s): Modelling & visualisation; Human – space interaction