We live in a time where data is the principal resource we turn to when solving problems on an urban scale. From transportation, to disaster management, to sustainability, different aspects of urban life are heavily shaped by the information we extract from data. Despite this, scarcity of data and inadequate analysis methodologies often prevent the development of meaningful answers or even lead to harmful interventions. This thesis aims to apply novel methods for geo-spatial data analysis to some of the most pressing problems in contemporary urban planning. I will combine a dataset of geographical data describing the structural properties of the urban context with a dataset of high-frequency location-based data describing the movement of a set of citizens in a given period of time. Taking as a reference the framework of the 15−minutes city, stating that in an optimally designed city every service could be accessible in less than 15 minutes by bike, I will reveal a common pattern in European metropolitan areas. While the core municipalities would already have the structural capability for allowing a 15−minutes model of mobility, smaller cities in the fringes of the metropolitan area often lack even the basic infrastructure to make it possible. In addition to this, I will show how these structural inequalities provoke a negative feedback loop with the behavioral components of the urban dynamics. Areas with less access to services of good quality will attract people with lower socio-economic status. In parallel, areas inhabited by people with lower socio-economic status will be less likely to improve their access to services. This feedback loop is the leading factor behind the disproportionate inequality between central and peripheric areas we observed in the first part of the analysis. Lastly, I will aggregate the within-city metrics to obtain a city-wide inequality measure, that can be used to compare the general mobility efficiency between cities. The results of this analysis are published on an open-access interactive online platform.

Measuring accessibility in urban contexts: from micro to macro / Chiappetta, Claudio. - (2023 Jan 23).

Measuring accessibility in urban contexts: from micro to macro

CHIAPPETTA, CLAUDIO
23/01/2023

Abstract

We live in a time where data is the principal resource we turn to when solving problems on an urban scale. From transportation, to disaster management, to sustainability, different aspects of urban life are heavily shaped by the information we extract from data. Despite this, scarcity of data and inadequate analysis methodologies often prevent the development of meaningful answers or even lead to harmful interventions. This thesis aims to apply novel methods for geo-spatial data analysis to some of the most pressing problems in contemporary urban planning. I will combine a dataset of geographical data describing the structural properties of the urban context with a dataset of high-frequency location-based data describing the movement of a set of citizens in a given period of time. Taking as a reference the framework of the 15−minutes city, stating that in an optimally designed city every service could be accessible in less than 15 minutes by bike, I will reveal a common pattern in European metropolitan areas. While the core municipalities would already have the structural capability for allowing a 15−minutes model of mobility, smaller cities in the fringes of the metropolitan area often lack even the basic infrastructure to make it possible. In addition to this, I will show how these structural inequalities provoke a negative feedback loop with the behavioral components of the urban dynamics. Areas with less access to services of good quality will attract people with lower socio-economic status. In parallel, areas inhabited by people with lower socio-economic status will be less likely to improve their access to services. This feedback loop is the leading factor behind the disproportionate inequality between central and peripheric areas we observed in the first part of the analysis. Lastly, I will aggregate the within-city metrics to obtain a city-wide inequality measure, that can be used to compare the general mobility efficiency between cities. The results of this analysis are published on an open-access interactive online platform.
23-gen-2023
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Note: Measuring Accessibility in urban context: from micro to macro
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1672561
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