Geospatial analysis for urban cycling planning and design

The aim of the thesis is to put a light on the urban cycling mobility observing the case study of the Municipality of Mappano – Metropolitan area of Turin, Piedmont, Italy. COVID-19 stresses the already-known unsustainability of the private car as the main mean of transport in urban environments giving some help to speed up the transition process from a car-oriented way of thinking the built environment into a more integrated and multimodal approach of moving. Active-mobility such as cycling has recorded strong increased rates due also to distrust on the safety-from-contagious in public transportation where ventilation is limited, and users cannot perfectly respect distances especially during rush hour. The municipality of Mappano is intended to augment the attention, and so finances, to cycling mobility demonstrating the growing importance of a good cycling network to give alternative solutions to move inside the municipality and outside its boundaries. Hence, the town has been chosen as the case study of this final project. An On-site inspection for spatial data collection took place to map the current condition of the municipal cycling infrastructure condition and a detailed somehow innovative database is developed for the spatial data classification. Chapters 2 and 3 are the theory on which the work is based on useful to understand the real potential of cycling. Concomitantly Chapter 4 is the basis of the data infrastructure project for the creation of the GeoDB explaining the logic of the model. Finally, a chapter on urban design interventions is presented. The methodology consists of a first phase of analysis to collect spatial data about the municipal cycling infrastructure network: a cargo bike was used for on-site analysis, equipped with a GNSS RTK system to trace the path, a Garmin action Cam for video recording of the pavement condition and a 360° Go Pro camera to observe the surrounding environment for understanding the safety perception of the rider on each link. The acquired data are then extracted and processed in the second phase in which the prototype of spatial data infrastructure model is applied. The GeoDB is obtained by the combination of existing OpenStreetMap and BDTRE Regione Piemonte attributes, but an additional new section of attributes is created, giving them hierarchical numeric coded values (1-5), to have further details such as maintenance status, type of cycle way, presence of impedance, road light condition, presence of dedicated road signs, safety perception, path dangerousness. A paragraph is dedicated to neighbourhood businesses and how positively might be impacted if scenarios of growing levels of walking and cycling are applied. Finally, a review of future intervention is presented focusing on the relevance that urban design has in cycling infrastructures and more in general in the built environment. Indeed, pleasant, well-design, inclusive and connected (not only) cycling networks can strongly attract new users and reduce car-dependency.