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Mathematical modelling of social phenomena in urban areas

Cabrera Arnau, Carmen; (2021) Mathematical modelling of social phenomena in urban areas. Doctoral thesis (Ph.D), UCL (University College London). Green open access

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The world is undergoing a rapid urbanisation process such that the ma- jority of people now live in urban areas. In this context, it is crucial to understand the behaviour that emerges in cities as a result of complex in- teractions between environmental, social, economic and political factors. To improve our knowledge, different techniques are used in this thesis in order to quantitatively model how one city compares with another. Owing to the present-day ease of access to information, most of the results in the following pages have been obtained via assessment of real-world data, made available by different public organisations. Urban scaling is used as the main modelling framework. This approach concerns the relationship between the population size of an urban area and some other urban characteristic. The work is applied to two specific topics of interest. Firstly, the amount of coverage given by the media to Mexican urban areas, before and after the 2017 Puebla earthquake, which affected several regions in Mexico. Secondly, the number of road traffic accidents per person in urban areas from several European countries for different degrees of accident severity or different definitions for the urban areas. The thesis also contains methodological contributions regarding the problem of accounting for urban areas with extremely large population in urban scaling models. Finally, this work explores the impact of the findings presented here to support the creation of new policies involving urban areas.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Mathematical modelling of social phenomena in urban areas
Event: UCL (University College London)
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Copyright © The Author 2021. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis
URI: https://discovery.ucl.ac.uk/id/eprint/10139346
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