Safety, mobility and the built environment – A micro-macro study of Valencia, Spain.
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School of Engineering |
Master's thesis
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Authors
Date
2024-09-30
Department
Major/Subject
Sustainable Urban Mobility Transitions
Mcode
Degree programme
Master's Programme in Urban Mobility
Language
en
Pages
77
Series
Abstract
The objective of this study is twofold. First (1), it aims at assessing the built environment, where harassments occurred within the municipality of Valencia, Spain. Second (2), it characterizes the people, who are experiencing harassment within the municipality. Hence, this study follows the structure of an initial descriptive to a confirmatory analysis. Data from a Valencian Mobility Survey, collected from December 23, 2020, to January 4, 2021, within the European research project TInnGO, open data from the municipality of Valencia, and data collected during fieldwork serve as the base of the analysis. Regarding (1), field-work in combination with the use of Geographical Information Systems (QGIS), was carried out to characterize the areas and places of harassment and to develop a proximity analyses. For (2), python and stata were used to develop a binary logit regression model, aiming at explaining the dependent variable ‘harassment’ within the municipality of Valencia. The findings show that various commonalities within the place and area characteristics were found. Low visibility leading to poor natural surveillance and high proximity to vegetation, bike in-frastructure and bus stops capture a large share of the harassment locations. On the other hand, the binary logistic regression model shows that harassment with-in the municipality of Valencia is to a higher degree situational than based on individual characteristics. While using your own bike, traveling with an independent person, and longer trip durations, on the other hand, having a disability are key determinants for harassment within the study area. These findings suggest that safety interventions need to be location specific and that they can vary between situational and individual factors. Moreover, these implications should guide the work of urban planners within their mobility and safety interventions, eventually allowing to uptake sustainable urban mobility options.Description
Supervisor
Mladenovic, MilosThesis advisor
Ceccato, VaniaSteriu, Mircea
Keywords
harassment, mobility behaviour, urban design, Python, binary logistic regression model, GIS