Walkability in Metropolitan Area

Walkability in Metropolitan Area

DOI: 10.4018/978-1-5225-7943-4.ch003


Promoting active trips has been considered as a key element towards achieving more sustainable transportation. Walking as a mode of transportation can contribute to more sustainable and healthy travel habits. This chapter presents a new approach for measuring walkability within Melbourne region, Australia. An integrated approach combining transport and land-use planning concepts was employed to construct the walking access index (WAI), which is a location-based measure for accessibility. The WAI along with a common existing walkability index were employed in regression models to examine how the new index performs in transport modelling. Key findings indicate that residents are more likely to have walking trips when living in a more walkable environment. Furthermore, it was found using statistical modelling that the WAI produces better results than one of the common approaches.
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3.1 Introduction

A substantial body of planning studies have conducted indicating that active transportation is consistently positively associated with urban form variables, including mixed land use, street connectivity and residential density (Frank et al., 2010). On the other hand, promoting active transportation has recently attracted a considerable attention by the health practitioners (Frank et al., 2004, Ewing et al., 2003, Saelens et al., 2003). Walking is known as the most common moderate-intensity activity of adults, and is found to be associated with significant health benefits (Manson et al., 1999, Hayashi et al., 1999).

Several definitions are found for “walkability” or “walkable” neighbourhoods. Bauman et al. (Bauman et al., 2012) argued that walkable neighbourhoods are designed in a way that residents can walk from home to nearby destinations. Manaugh and El-Geneidy (2011) claimed that walkability can be defined as a ‘‘match’’ between residents’ desires and expectations for various types of destinations, their willingness to walk a given distance and the quality of the required path. Hence, neighbourhoods that have this match between the form of the built environment, and residents’ needs will likely have higher rates of walking trips. In another study, Frank et al. (Frank et al., 2010) defined walkability as proximity from home to non-residential destinations and concluded people living in walkable neighbourhoods are less likely to be overweight or obese than people living in more suburban areas that require motorised transportation.

Improving the built environment to make it more convenient for people to be physically active, is an essential component of increasing physical activity (Dannenberg et al., 2003, Frank et al., 2003, Lavizzo-Mourey and McGinnis, 2003). In other words, the arrangement or distribution of facilities and activities in the surroundings of residential areas is one of the main factors found to influence urban transport patterns. Providing services and utilities for residents in proximity to their houses minimize the need to travel long distances and increase the chance of active travels. There has been a long tradition of investigating the association between the built environment and travel behaviour. Transport and urban planners have recently focused on promoting physical activity by environment-based solutions.

Pedestrian infrastructure including sidewalk access, quality and street connectivity have also been found as important criteria for determining walkability in neighbourhood areas, principally in micro-level studies (Lo, 2009). In some studies, these features have been found to affect comfort and safety of pedestrians (2004, Cervero and Duncan, 2003, Lo, 2009).

“Walk-Score” is one of the common approaches for measuring walkability. First introduced in 2007, it has been used in macro-level studies or when investigating land use features that affect proximity. The Walk Score algorithm considers points based on the distance to the closest facility in each land use category. In the closest facility in a category the distance ranges from 0.4 km to 1.6 km (REDFIN, 2015). In this approach facilities are categorised into offices, parks, theatres, schools and other common destinations. Duncan et al. (2011) and Carr et al. (2010) used walk-score in their study and claimed that walkability in neighbourhoods is based on the distance to different categories of services, including schools, parks and libraries.

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