Walking is a sustainable mode of transport and a healthy way of doing physical activity. Walkability is a concept that has gained enormous popularity in recent years due to its potential to promote more sustainable urban environments and healthy lifestyles. This paper provides a literature review to analyze the influence of built environment attributes on walkability. The Scopus and Web of Science databases were chosen to survey the peer-reviewed documents published up to June 2020. A total of 132 documents were selected by the search. The review of these 132 documents showed that various built environment attributes were differently analyzed and assessed. More specifically, the search identified 32 built environment attributes that were assessed by using 63 measures. Intersection density, residential density and land use mix were the most used attributes for assessing walkability, namely by using objective methods, such as ratios and spatial score tools. In turn, attributes related to streetscape design and security were much less adopted in walkability assessments. This paper provides additional insights into how built environment attributes influence walkability and identifies gaps and issues that should be analyzed in-depth in the future. The review could be helpful for researchers and urban planners in developing walkability studies and in defining policies to improve walkability.

Walking is undoubtedly a sustainable and healthy mode of transport. However, the decision to walk is influenced by many built environment and streetscape attributes. Specifically, the term walkability is used to describe the extent to which the urban environment is pedestrian-friendly, usually by quantifying multiple built environment attributes at the neighbourhood scale. The present study adopts a qualitative approach to evaluate perceived walkability. Based on a questionnaire (n = 1438) administered in the cities of Bologna and Porto, this paper analyses how respondents perceived and evaluated 19 built environment and streetscape attributes. An Exploratory Factor Analysis was carried out to examine the correlations between the various attributes and to identify the underlying walkability determinants. The analysis indicated that 13 attributes were highly correlated, resulting in four determinants: (i) urban ambiance, which includes land use and street design attributes, such as land use mix, enclosure, transparency, and architectural and landscape diversity; (ii) pedestrian infrastructure, which is related to sidewalk conditions; (iii) street connectivity and proximity to community facilities; and iv) access to other modes of transport. In turn, traffic safety and security were not correlated with perceived walkability in both cities. These findings suggest that specific urban design and pedestrian infrastructure attributes should be highly considered when formulating policies aiming to create more pedestrian-friendly cities, as well as in walkability studies and when developing walkability scores and indexes.

In many Brazilian cities, the most common procedure for planning cycling networks is using aggregated population data in census tracts, which may not take into account the true origin and destination of trips. It may also not identify potential users of a particular mode of transport. This is particularly important considering that implementing cycling infrastructures should be based on the assumption that they are able to meet the users' needs. Therefore, the aim of this study is to develop and adopt an objective method to design and compare cycling networks based on data-mining of disaggregated origin-destination data, GIS resources, and multicriteria analysis techniques. The method follows three steps: 1) identifying potential users based on real user profiles, 2) designing proposed cycling networks and 3) a comparison between the networks proposed in this study and those developed by the municipality selected as a case study, considering real and potential users, as well as cost and benefit criteria. As a positive outcome, using disaggregated data allows for a reasonable estimate of the number of people served by the networks, a detailed analysis of their proximity to the infrastructure, as well as identifying potential users. Comparing cycling networks considering cost and benefit criteria shows that the chosen criteria were effective. It was also determined that the cycling network of the studied city poorly serves bicycle transport users, if compared to the proposed networks. These findings indicate that appropriate methods for planning cycling networks are still needed.