Modeling women's perceived level of safety at night in Milan

This article outlines the data analysis and modeling processes of the perceived level of safety for women at night time in the city of Milan. This research effort consists of the final phase of the STEP UP project, which was aimed to assess walkability for women in Milan using geospatial data analysis methods and involved three phases: literature review, data collection, and data analysis. The modeling of perceived safety proposed in this paper takes into consideration a wide set of geospatial data, acquired from open data and proprietary platforms, quantifying factors identified in the literature review, and the Wher app data, a crowdsourced dataset of women's self-disclosed perceived safety on the street network. These two sets of information are used to explore the relationship between the built environment and safety perception. Moreover, this article covers the processes of filtering the factors emerged from scientific literature, and the translation from concepts into operationalizable quantitative indicators. The process of identifying the relations between the safety factors and the perceived safety consisted in testing several statistical models, ultimately leading to the implementation of a Geographically Weighted Regression (GWR) model, which appeared as the most suitable for capturing the spatial heterogeneity of the factors. The results of the project showed the presence of three statistically significant indicators, namely Public Lighting, Public Transport, and Food & Beverage, and include the spatial variation of Local R2 and Beta coefficient values, allowing for the inference of site-specific phenomena and complexities. Overall, the approach proposed in this article aims to bridge the gap between subjective crowdsourced data and city characteristics data, proposing a layered methodology to fine-tune the association between factors relevant to safety and geospatial data. It also proposed a quantitative approach to model the nighttime safety perception of women in Milan, ultimately contributing to the overarching goal of paving the way for additional gender-inclusive mobility planning and research routes.