Urban accessibility has been studied for decades as one of the most important dimensions of cities, considered both a factor of growth and quality of life (Smoyer-Tomic et al., 2004; Handy and Niemeier, 1997; Dalvi and Martin, 1976). As urban scholarship evolved from positivist towards post-positivist traditions and to more comprehensive frameworks of theory and practice, conceptualizations of accessibility evolved as well. Following this distinction, there are two noticeably contrasting definitions of accessibility: the first considers accessibility as a quantifiable measure; the second considers accessibility qualitatively, as part of a larger social reality and concerned with whether cities are equitable and inclusive.
This thesis uses both dimensions of accessibility by quantifying and qualifying accessibility to six types of amenities in the St. John’s CMA. In particular, I am concerned here with counting facilities and services via three coverage criteria,
measuring distances to services via both Euclidean and network distances and using the average of those two sets of calculations as well as demographic data to assess
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based accessibility. A last step in my assessment involves evaluating the relationship between urban form and accessibility through a series of urban form metrics.
Before the 1960s, much of the literature that addressed accessibility consisted of studies on the form of the city or on urban population, which offered highly aggregated measures of accessibility (Hansen, 1959). One such measure was the distance of an origin point to the centre of the city. A second measurement was aggregate travel, understood as the sum of travel distances by every person travelling to a certain area(s). Other
measurements were based on calculations of proximities of certain areas to the residential population and on potential interactions between people. Subsequent studies (Apparicio et al., 2008; Hewko et al., 2002) have attempted to disaggregate accessibility measures to make them more precise. Presently, accessibility studies are conducted at the census subdivision level, and when local data is available, such as city-wide or metropolitan surveys and census, data can be analysed at even smaller scales.
One of the first studies offering a more specific operational definition of
accessibility was Ingram (1971), who advanced two definitions: i) integral accessibility, or “the degree of interconnection for a given point with all other points on the same surface” (Dalvi and Martin, 1976, p. 18); ii) relative accessibility, or “the degree to which two places (or points) on the same surface are connected” (Dalvi and Martin, 1976, p.18).
These are expressed by Dalvi and Martin (1976, p. 18) as:
Ai =
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where Ai=integral accessibility at the ith point; aij = relative accessibility of point j at i
Other studies claim that accessibility is the potential of opportunities for interaction (Handy and Neimeier, 1997; Hansen, 1959) and, more specifically, as the
“measurement of the spatial distribution of an activity [(opportunities for interaction)]
adjusted for the ability and desire of people or firms to overcome spatial separation”
(Hansen, 1959, p. 4). This definition involves two principal elements of accessibility:
transportation (or impedance) and activity (or attraction) (Handy and Neimeier, 1997).
Transportation is often measured by travel distance, time or cost, while activity is measured by the number and location of different activities, such as facilities, services, spaces and places (Handy and Neimeier, 1997). The measurement of these two elements constitutes the operationalization of accessibility. Different studies have used a range of methods, from extremely simple to more complex calculations, but it is clear from the literature that a triangulation approach which combines various measurements yields more accurate results.
The spatial distribution of an activity can be quantified by simply counting the number of destinations within a geographic unit. Handy and Neimeier defines this as the
‘container’ approach; Talen and Anselin (1998) name it the ‘coverage’ method; Pirie (1979) names it ‘cumulative-opportunity measure’ (Pirie, 1979, p. 301; see also: Pasch et al., 2009; Sharkey et al., 2009; Smoyer-Tomic et al., 2008; Apparicio et al., 2007; and Smoyer-Tomic et al., 2004). In this research, four coverage criteria are used to calculate
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cumulative opportunities for interaction. The first coverage criterion (CCI) counts the number of facilities within the boundaries of a dissemination area. The second criterion (CCII) calculates the total number of amenities within a 500-m buffer area and the third criterion (CCIII) counts facilities within a 500-m service area. Service areas commonly use the facility itself as point of origin and measure the extension of an area that is serviced by the amenity, along the street network (for studies using this method, see:
Larsen and Gilliland, 2008; Cervigni et al. 2008; Oh and Jeong 2007; and Nicholls, 2001). In this study, I generate service areas with the DA centroid as point of origin, in order to count amenities within a 500-m area using the street network. This is different from the 500-m buffer area in that the extension is not a circle with a straight 500m line, but it is rather an irregular area shaped by the street network. The fourth and final criterion (CCIV) is the average of the first three, which is used as a final method to evaluate equity in accessibility.
Another method used in parallel with the coverage approach is the minimum distance approach, by which I calculate the distance to the closest amenity from a point of origin. This allows me to discern with more accuracy how accessible an amenity is. This study uses both Euclidean – straight line – and network – along streets – distances (for studies using minimum distance criteria, see Shah et al., 2016; McKenzie, 2014; Larsen
& Gilliland, 2008; Apparicio et al., 2004; and Nicholls, 2001).
The four coverage criteria and the two minimum distance methods measure the potential for interaction based on the number of destinations and the distance to them, and these can be easily quantified with the right data. Some other studies, however, have
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become more interested in the actual, rather than potential, use of accessibility as a measure of access (Morris et al., 1979). However, research studying potential accessibility depends on different types of methodologies, such as surveys and
observation. Access as opportunities for interaction is the most common definition used because it is also the most readily available for analysis, using spatial and census data.