In the framework of sustainable development, the study of urban mobility networks is fundamental, in particular, the role of active mobility and street networks. Active mobility is known to positively impact several Sustainable Development Goals (SDGs), which makes its analysis fundamental to achieve sustainable transportation. Using a generalised and globally applicable methodology that leverages the use of open and crowd-sourced data, we characterised walkability and bikeability of the urban areas of 16 medium and large cities around the world, spread in 8 geographical areas. The methodology employs a graph-based multimodal and multiscale approach over driving, pedestrian, and biking street networks to calculate 20 indices and metrics (e.g., intersection density, steepness, circuity, orientation entropy, etc.) that characterise walkability and bikeability. This study presents the results and interpretation of the calculation of multiple walkability and bikeability metrics for the selected cities, as well as a discussion on the limitations of using global and crowd-sourced data for the calculation of active mobility indices.

Calculating Walkability and Bikeability of Cities with a Multimodal and Multiscale Approach

Duque, Juan Pablo;Brovelli, Maria A.
2025-01-01

Abstract

In the framework of sustainable development, the study of urban mobility networks is fundamental, in particular, the role of active mobility and street networks. Active mobility is known to positively impact several Sustainable Development Goals (SDGs), which makes its analysis fundamental to achieve sustainable transportation. Using a generalised and globally applicable methodology that leverages the use of open and crowd-sourced data, we characterised walkability and bikeability of the urban areas of 16 medium and large cities around the world, spread in 8 geographical areas. The methodology employs a graph-based multimodal and multiscale approach over driving, pedestrian, and biking street networks to calculate 20 indices and metrics (e.g., intersection density, steepness, circuity, orientation entropy, etc.) that characterise walkability and bikeability. This study presents the results and interpretation of the calculation of multiple walkability and bikeability metrics for the selected cities, as well as a discussion on the limitations of using global and crowd-sourced data for the calculation of active mobility indices.
2025
bikeability
crowdsourced datasets
street networks
urban sustainability
walkability
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1301512
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