Promoting Public Health Through Urban Walkability: A GIS-Based Assessment Approach, Experienced in Milan

Introduction. The global challenge of physical inactivity necessitates innovative approaches and strategies to optimize built environments in order to promote healthy and sustainable lifestyles, such as active transportation. For this reason, walkability is a crucial area of research in urban health, with several studies focusing on assessment frameworks. However, a gap persists between theoretical development and practical implementation. This study explores the application of the Milan Walkability Measurement Tool (MWM-Tool), a walkability assessment framework previously developed by Politecnico di Milano, to evaluate the urban features in favor of walkability by integrating GIS technology with an extended testing scope. It is based on a scientific approach utilizing 10 sub-indicators divided into three macro-areas (Density, Diversity, Design), identified through a comprehensive literature review. Method. Focusing on the application of the MWM-Tool in Milan, the study employs the 88 Nuclei of Local Identity (NILs), which are the official designations for Milan’s neighborhoods, as the units of urban analysis. Based on previous experience, the digitalization of the assessment framework has been improved: geospatial data corresponding to 10 sub-indicators were filtered to generate vector layers, primarily sourced from two public geographical platforms. The GIS-based method produces thematic maps evaluating all neighborhoods according to the dimensions of Density, Diversity, and Design. Darker and lighter colors represent the range of the scores. Both single indicators and macro-area maps, as well as overall walkability level maps, were generated to illustrate the results. Result. The results of the macro dimension assessment, combining 10 sub-indicators, provide an objective view of the distribution of walkable space quality in Milan. Only 7 out of 88 neighborhoods achieved the highest score, all of which are located in the city center, while suburban areas showed significantly lower scores. By incorporating census GIS data, the study also identified the population distribution across areas with varying walkability levels. Based on the results of the assessment, it may be possible to develop and prioritize the optimization of walkable features, revitalizing underserved areas and fostering a healthier community environment. Conclusion. The georeferenced-data maps represent an effective tool to highlight both neighborhoods with high urban quality, which could be used to promote active mobility and healthy lifestyle adoption, as well as those requiring improvement strategies from policy and decision makers. The research output provides a reference for further urban planning initiatives in Milan and contributes to enhancing pedestrian-oriented built environments. Using GIS open-source data, the method is scalable and can be easily replicated in other cities. It could also be used as a system for monitoring walkability over time.