NDERSTANDING THE STRUCTURE AND DYNAMICS OF METROPOLITAN AREAS: THE CASE OF GMCA

Abstract

In urban planning, the study of metropolitan areas has lagged behind other urban scales. This remains true despite the fact that the metropolitan scale is becoming an objective of policy-makers in major national governments. This thesis presents a body of work on the theme of understanding the structure and development of metropolitan areas. It explores the challenges in understanding the drivers that shape metropolitan structure and presents several models that demonstrate the benefits to planners and policymakers from understanding these drivers. The research draws on tools from complexity sciences. Three independent but re- lated models are presented, each focusing on a different element of the metropolitan scale. First, a model is presented that utilises community detection methods applied to commuter flows to identify the structure of metropolitan areas. It concludes that ex- isting administrative boundaries play a key role in shaping metropolitan structure and comments on the slow shifting nature of communities. Second, a well studied bounded confidence model, the Deffuant model, is modified from its theoretical grounding in social simulation theory to be used in metropolitan settings. The model explores the interactions and consensus formation dynamics of urban agents when faced with nego- tiations on different forms of metropolitan projects. Finally, a third model is presented in the form of multilayer urban network model. It builds on elements of each of the two preceding models to explore the relationships between drivers of metropolitan struc- ture at different scales of the metropolitan hierarchy. This thesis highlights that investigating the drivers of metropolitan areas is a com- plex task. Underpinning this difficulty is a lack of urban data that accommodates for the modelling of urban systems at multiple levels of the metropolitan scale and the rel- ative lack of tools to model such systems. Despite this, the presented models demon- strate novel insights into understanding the formation of metropolitan areas and lay the foundations for further work

Date of Award	31 Dec 2024
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Iain Deas (Supervisor), Eva Navarro Lopez (Supervisor) & Nuno Pinto (Supervisor)