Table 16 presents modal shares for trips with destinations within the study areas. These trips may originate inside or outside these areas. A striking finding is the correspondence between the modal shares of study areas and the well-documented decline in public transit patronage (and corresponding increase in automobile shares) from the centre to the periphery of the Greater Toronto Area (Crowley and Dalton, 1998; McLeod, 1999: 8; Miller, Dalton and Briggs, 1998). This tendency is illustrated by differences in the modal shares of the Yonge-Eglinton node and North York Centre, both of which are on the Yonge subway line and thus enjoy similar levels of transit service. While 32.6 per cent of the trips to a Yonge-Eglinton destination rely on public transit, the equivalent proportion for North York Centre is 22.8 per cent. The reverse relationship between the proportion of public transit trips and the distance of study areas from downtown Toronto can be linked to transportation conditions in the areas surrounding these nodes.
Table 16: Per cent modal shares of all trips with destinations in study areas, in their respective urban zone or municipality and in two business parks, and ratios of study area shares relative to those of their urban zone or municipality
|
|
Auto Driver |
Auto Passenger |
Public Transit |
Walking |
Cycling |
Other |
|
Downtown Toronto |
35.5% |
7.9% |
46.6% |
8.9% |
2.3% |
1.9% |
|
Inner City |
43.2% |
10.6% |
33.6% |
8.5% |
2.3% |
1.7% |
|
Ratio: Downtown Toronto / Inner City |
0.75 |
0.74 |
1.39 |
1.05 |
1.00 |
1.12 |
|
Yonge-Eglinton |
47.5% |
10.4% |
32.6% |
6.7% |
0.9% |
1.9% |
|
Inner City |
43.2% |
10.6% |
33.6% |
8.5% |
2.3% |
1.7% |
|
Ratio: Yonge-Eglinton / Inner City |
1.10 |
0.98 |
0.97 |
0.79 |
0.39 |
1.12 |
|
North York Centre |
58.0% |
13.4% |
22.8% |
4.3% |
0.7% |
0.7% |
|
City of North York |
61.5% |
15.4% |
16.9% |
4.8% |
0.4% |
1.0% |
|
Ratio: North York Centre / North York |
0.94 |
0.87 |
1.35 |
0.89 |
1.75 |
0.70 |
|
Scarborough Town Centre |
58.2% |
17.3% |
18.9% |
4.6% |
0.2% |
0.8% |
|
City of Scarborough |
60.9% |
17.2% |
15.1% |
5.3% |
0.3% |
1.1% |
|
Ratio: Scarborough Town Centre / Scarborough |
0.95 |
1.01 |
1.25 |
0.87 |
0.67 |
0.73 |
|
Mississauga City Centre |
67.3% |
17.8% |
9.5% |
3.9% |
0.1% |
1.3% |
|
City of Mississauga |
70.1% |
16.0% |
6.3% |
4.9% |
0.3% |
2.4% |
|
Ratio: Mississauga City Centre / Mississauga |
0.96 |
1.11 |
1.51 |
0.79 |
0.33 |
0.54 |
|
Downtown Oakville |
79.8% |
15.1% |
3.1% |
0.6% |
0.3% |
1.2% |
|
Town of Oakville |
73.1% |
16.0% |
3.8% |
3.8% |
0.5% |
2.7% |
|
Ratio: Downtown Oakville / Oakville |
1.09 |
0.94 |
0.81 |
0.16 |
0.60 |
0.44 |
|
Downtown Kitchener |
81.1% |
12.6% |
4.6% |
1.1% |
0.6% |
N.A. |
|
Waterloo Region |
68.8% |
17.1% |
3.4% |
7.8% |
0.7% |
2.0% |
|
Ratio: Downtown / Waterloo Region |
1.18 |
0.74 |
1.35 |
0.14 |
0.86 |
N.A. |
|
Yonge Street Corridor |
50.6% |
10.9% |
28.6% |
6.9% |
1.1% |
1.8% |
|
Inner City |
43.2% |
10.6% |
33.6% |
8.5% |
2.3% |
1.7% |
|
Ratio: Yonge Street Corridor / Inner City |
1.17 |
1.03 |
0.85 |
0.81 |
0.48 |
1.06 |
|
Mississauga East Corridor |
64.3% |
16.9% |
9.1% |
7.1% |
0.3% |
2.3% |
|
City of Mississauga |
70.1% |
16.0% |
6.3% |
4.9% |
0.3% |
2.4% |
|
Ratio: Mississauga East Corridor / City of Mississauga |
0.92 |
1.06 |
1.44 |
1.45 |
1.00 |
0.96 |
|
Business Park, Highway 404, North East of Steele |
76.0% |
15.4% |
5.1% |
1.4% |
0.2% |
1.9% |
|
Business Park, Highway 401 South of Pearson Airport |
80.2% |
13.9% |
4.1% |
0.3% |
0.1% |
1.3% |
Source: 2001 Transportation Tomorrow Survey.
The availability of different modes of transportation within their catchment zones and the extent to which the built environment of these zones (density and mixture of uses) is conducive to transit use and walking are mirrored in modal shares recorded for trips to study areas. We can conclude that conditions outside the study areas have more influence on the modal split of trips to these areas than conditions prevailing within their boundaries. The modal choice for people travelling to a destination within the study areas is largely influenced by transportation options at the point of origin.
Variations in the availability of free parking also account for differences in modal shares. The effect of parking costs is particularly noticeable in the four nodes, where it adds to the impact of public transit levels. As in downtown Toronto, there is a virtual absence of free parking in Yonge-Eglinton and North York Centre, although parking rates there tend to be lower than in downtown Toronto. In contrast, free parking is plentiful around Scarborough Town Centre and Mississauga City Centre.
Downtown Kitchener is an exception to the tendency for transit use to decline as distance from downtown Toronto increases. Transit modal split in downtown Kitchener is slightly higher than it is in downtown Oakville (4.6 vs. 3.1 per cent). As a metropolitan region in its own right, the Kitchener CMA (which corresponds broadly to the administrative boundaries of Waterloo Region) reproduces to some extent the transit use gradients observed in the Toronto CMA; that is, downtown Kitchener has a higher transit modal share than the metropolitan region as a whole. But transit use peaks and metropolitan-wide shares are considerably lower in Waterloo Region than they are in Toronto CMA, although not below those in Toronto's outer suburbs.
Despite the varied land use patterns and the transportation conditions of their surroundings, public transit modal shares of trips to places within the study areas generally exceed those of trips to destinations elsewhere in the surrounding urban zone or municipality of these areas. No doubt, high-density clusters of mixed activities are associated with higher levels of transit use than those of surrounding areas. However, it does not mean that study areas display high transit modal shares. For Mississauga City Centre and the Mississauga East corridor, the transit modal splits are 9.5 and 9.1 per cent, respectively, well above the Mississauga average of 6.3 per cent, but hardly impressive in themselves.
The two study areas where public transit modal shares score below the average for their urban region or municipality are the Yonge Street corridor and downtown Oakville. In the first case, this is partly due to an elevation of inner-city averages by the heavy dependence of downtown-bound trips on public transit. In downtown Oakville, one explanation is the attraction of this district for people from outside the downtown and surrounding neighbourhoods.
Differences in walking follow a different logic.16 Walking modal shares in the study areas tend to be lower than those of their respective urban zone or municipality. Given the TTS methodology, and the scarcity of schools in the study areas, this finding is likely due to a dearth of trips to these areas for educational purposes. The juxtaposition of employment and housing does not generate sufficient numbers of people walking to work to compensate for the lack of students walking to school.
Only in downtown Toronto and the Mississauga East corridor do walking levels exceed those of the surrounding urban zone or municipality. In the first case, this is due to the presence of many residential units in the downtown, which encourages walking to workplaces and educational establishments (including two universities). In the Mississauga East corridor, the proximity of Mississauga City Centre employment and a scattering of schools within a high-density suburban-like layout explain walking levels that are higher than the average for the municipality.
The reverse correlation between public transit shares and distance from the core is not true of walking. Walking appears to be more sensitive to the presence of employment and schools and the morphology of study areas than to an area's location within the region. The study areas that provide an environment hospitable to pedestrians (downtown Toronto, Yonge-Eglinton, and the Yonge Street corridor) register relatively high walking shares. Those that are less well-adapted to the needs of pedestrians (North York Centre, Scarborough Town Centre, and Mississauga City Centre) have lower walking modal splits. There are exceptions. We have discussed why the walking share is relatively high in the Mississauga East corridor. Circumstances are different in downtown Oakville and downtown Kitchener. Despite a layout and design that appear to be conducive to walking, these sectors register the lowest walking modal shares among our study areas, due to the absence of schools and relative lack of employment opportunities (compared to the other study areas) in downtown Oakville. Table 16 suggests an absence of walking-based connectivity between downtown Kitchener employment and nearby residential neighbourhoods.
There is another explanation for variations in levels of transit use and walking. The literature has identified the critical role of self-selection of individuals according to values and life-style preferences in accounting for high transit use and walking in certain areas (see Cao, Mokhtarian and Handy, 2006; Choo and Mokhtarian, 2004). According to this view, individuals inclined to rely on transit and walking are attracted to sectors with good public transit services and a pedestrian-friendly environment. Still, one must keep in mind that for such preferences to be actualized, transit- and pedestrian-friendly urban environments must be in place.
Overall, the study areas are not characterized by high levels of transit use and walking. Walking generally lags behind the averages for urban zone or municipality, and in the outer suburbs, transit modal shares fail to reach 10 per cent. In all the study areas, with the exception of downtown Toronto, public transit modal shares are considerably lower than automobile driver shares. The picture changes, however, when the study areas are compared with suburban business parks. In the two business parks selected for comparative purposes, walking is nearly non-existent and the public transit modal share is about half that of the lowest share recorded in the study areas, except for downtown Oakville and downtown Kitchener.
Trips out of the study areas
Table 17 shows the modal split of home-based trips made by residents of the study areas. As in the previous table, transit use declines as distance from the core rises. There is, however, a major difference between the two tables. Home-based trips generated within study areas are much more reliant on walking than trips into these areas. In Yonge-Eglinton, North York Centre, Scarborough Town Centre, Mississauga City Centre, downtown Oakville, and downtown Kitchener, walking modal shares are approximately twice as high as those shown in Table 16. The discrepancy between the two tables' walking shares is most pronounced in downtown Toronto. Home-based trips originating from this sector are three times more likely to involve walking than trips to a downtown Toronto destination.
In all cases, with the exception of downtown Toronto, high walking levels resulted in reduced auto driver shares compared to those of Table 16. In downtown Toronto, it is transit use that is most affected by the walking modal share. The findings suggest an adaptation of the travel patterns of residents to the mixed-use nature of the study areas. A higher reliance on walking for study area residents relative to people coming from outside the study areas is accounted for by proximity to workplaces and the presence of pedestrian-friendly environments.
Table 17: Per cent modal shares of home-based trips of residents from study areas and their respective urban zone or municipality, and ratios of study area shares relative to those of their urban zone or municipality
|
|
Auto Driver |
Auto Passenger |
Public Transit |
Walking |
Cycling |
Other |
|
Downtown Toronto |
22.3% |
6.9% |
27.8% |
35.6% |
3.6% |
3.9% |
|
Inner City |
40.8% |
10.6% |
30.9% |
12.0% |
3.3% |
2.3% |
|
Ratio: Downtown Toronto / Inner City |
0.55 |
0.65 |
0.90 |
2.97 |
1.09 |
1.69 |
|
Yonge-Eglinton |
40.9% |
9.3% |
33.1% |
13.0% |
0.9% |
2.8% |
|
Inner City |
40.8% |
10.6% |
30.9% |
12.0% |
3.3% |
2.3% |
|
Ratio: Yonge-Eglinton / Inner City |
1.00 |
0.88 |
1.07 |
1.08 |
0.27 |
1.22 |
|
North York Centre |
50.2% |
15.0% |
24.3% |
8.5% |
1.1% |
0.8% |
|
City of North York |
56.2% |
16.5% |
18.5% |
7.0% |
0.5% |
1.1% |
|
Ratio: North York Centre / North York |
0.89 |
0.91 |
1.31 |
1.21 |
2.20 |
0.73 |
|
Scarborough Town Centre |
51.9% |
17.7% |
17.9% |
10.9% |
0.1% |
1.3% |
|
City of Scarborough |
57.3% |
17.9% |
16.5% |
6.5% |
0.4% |
1.3% |
|
Ratio: Scarborough Town Centre / Scarborough |
0.90 |
0.99 |
1.08 |
1.68 |
0.25 |
1.00 |
|
Mississauga City Centre |
59.8% |
18.2% |
12.0% |
7.3% |
0.2% |
2.5% |
|
City of Mississauga |
66.5% |
17.1% |
7.1% |
6.2% |
0.3% |
2.7% |
|
Ratio: Mississauga City Centre / Mississauga |
0.90 |
1.06 |
1.69 |
1.18 |
0.67 |
0.92 |
|
Downtown Oakville |
78.2% |
9.0% |
10.2% |
1.3% |
N.A. |
1.3% |
|
Town of Oakville |
70.1% |
16.7% |
4.3% |
4.8% |
0.7% |
3.3% |
|
Ratio: Downtown Oakville / Oakville |
1.11 |
0.54 |
2.37 |
0.27 |
N.A. |
0.39 |
|
Downtown Kitchener |
68.7% |
28.1% |
N.A. |
3.2% |
N.A. |
N.A. |
|
Waterloo Region |
65.4% |
17.0% |
3.3% |
11.0% |
1.0% |
2.3% |
|
Ratio: Downtown / Waterloo Region |
1.05 |
1.65 |
N.A. |
0.29 |
N.A. |
N.A. |
|
Yonge Street Corridor |
48.9% |
10.6% |
25.6% |
11.2% |
1.4% |
2.3% |
|
Inner City |
40.8% |
10.6% |
30.9% |
12.0% |
3.3% |
2.3% |
|
Ratio: Yonge Street Corridor / Inner City |
1.20 |
1.00 |
0.83 |
0.93 |
0.42 |
1.00 |
|
Mississauga East Corridor |
60.7% |
17.2% |
10.3% |
9.1% |
0.3% |
2.4% |
|
City of Mississauga |
66.5% |
17.1% |
7.1% |
6.2% |
0.3% |
2.7% |
|
Ratio: Mississauga East Corridor / City of Mississauga |
0.91 |
1.00 |
1.45 |
1.47 |
1.00 |
0.89 |
Source: 2001 Transportation Tomorrow Survey.
Table 18 focuses on work-bound trips made by residents of the study areas.17 As in most metropolitan regions, reliance on public transit for work trips is higher than it is for all trips (the previous tables did not distinguish different trip purposes). The same goes for walking modal shares. The only exception is the Mississauga East corridor, which contains little employment, but several schools. The residents of downtown Toronto rely heavily on walking for commuting, and their walking registers the highest of all modal shares. Four of the other study areas have walking modal splits for commuting between 9.9 and 16.1 per cent: Yonge-Eglinton, downtown Oakville, downtown Kitchener, and the Yonge Street Corridor. Mississauga City Centre and especially Scarborough Town Centre lag far behind.
Table 18: Per cent modal shares of work-bound trips of residents from study areas and their respective urban zone or municipality, and ratios of study area shares relative to those of their urban zone or municipality
|
|
Auto Driver |
Auto Passenger |
Public Transit |
Walking |
Cycling |
Other |
|
Downtown Toronto |
23.0% |
1.8% |
33.7% |
36.9% |
2.1% |
2.2% |
|
Inner City |
39.0% |
4.0% |
41.0% |
11.9% |
3.0% |
1.2% |
|
Ratio: Downtown Toronto / Inner City |
0.59 |
0.45 |
0.82 |
3.09 |
0.72 |
1.87 |
|
Yonge-Eglinton |
32.7% |
2.4% |
50.1% |
12.1% |
1.6% |
1.3% |
|
Inner City |
39.0% |
4.0% |
41.0% |
11.9% |
3.0% |
1.2% |
|
Ratio: Yonge-Eglinton / Inner City |
0.84 |
0.60 |
1.22 |
1.01 |
0.54 |
1.13 |
|
North York Centre |
47.8% |
2.3% |
42.4% |
7.2% |
0.1% |
0.3% |
|
City of North York |
58.9% |
5.7% |
30.2% |
4.0% |
0.4% |
0.6% |
|
Ratio: North York Centre / North York |
0.81 |
0.4 |
1.40 |
1.80 |
0.27 |
0.47 |
|
Scarborough Town Centre |
64.1% |
7.5% |
24.5% |
2.8% |
0% |
1.0% |
|
City of Scarborough |
59.3% |
6.6% |
30.4% |
2.8% |
0.3% |
0.6% |
|
Ratio: Scarborough Town Centre / Scarborough |
1.08 |
1.14 |
0.81 |
1.02 |
0 |
1.59 |
|
Mississauga City Centre |
66.9% |
5.8% |
21.8% |
4.0% |
0.0% |
2.0% |
|
City of Mississauga |
74.7% |
7.1% |
14.7% |
2.6% |
0.3% |
0.6% |
|
Ratio: Mississauga City Centre / Mississauga |
0.90 |
0.81 |
1.48 |
1.57 |
0.0 |
3.38 |
|
Downtown Oakville |
71.3% |
1.3% |
13.3% |
13.3% |
0.0% |
0.0% |
|
Town of Oakville |
75.8% |
6.3% |
13.4% |
3.3% |
0.4% |
0.8% |
|
Ratio: Downtown Oakville / Oakville |
0.94 |
0.21 |
0.99 |
4.03 |
0.0 |
0.0 |
|
Downtown Kitchener |
51.4% |
6.2% |
9.3% |
16.1% |
16.1% |
0.8% |
|
Kitchener CMA |
81.3% |
8.0% |
3.9% |
4.9% |
1.1% |
0.6% |
|
Ratio: Downtown Kitchener / Kitchener CMA |
0.63 |
0.77 |
2.38 |
3.28 |
14.64 |
1.33 |
|
Yonge Street Corridor |
42.1% |
2.5% |
43.4% |
9.9% |
1.4% |
1.0% |
|
Inner City |
39.0% |
4.0% |
41.0% |
11.9% |
3.0% |
1.2% |
|
Ratio: Yonge Street Corridor / Inner City |
1.08 |
0.63 |
1.06 |
0.83 |
0.47 |
0.85 |
|
Mississauga East Corridor |
70.6% |
7.4% |
18.5% |
2.6% |
0.3% |
2.0% |
|
City of Mississauga |
74.7% |
7.1% |
14.7% |
2.6% |
0.3% |
0.6% |
|
Ratio: Mississauga East Corridor / City of Mississauga |
0.95 |
1.04 |
1.26 |
1.03 |
0.97 |
3.38 |
Source: Statistics Canada, 2001 Census.
Trip distance
Table 19 indicates the average distance of trips to the different study areas. Trip length is calculated as a straight line between origin and destination.
One group of study areas stands out: downtown Toronto and the two expressway-oriented business parks, which register trip lengths that exceed those of the other study areas. We can infer from this finding that employment in these three study areas is more oriented towards the entire metropolitan region than is the case in the other areas, which have a more local focus (see maps in Appendix C).
The "all trips" category presents the largest discrepancy in trip distance. There is a 65 per cent difference in the length of trips to the Yonge Street corridor and those to downtown Toronto. As a group, nodes register trip lengths below those of the three highest-scoring districts and higher proportions of trips originating from within a 6-km radius. The business parks record the lowest proportion of trips of 6 km or less. These findings indicate an interaction with local catchment areas that is important in downtown Kitchener, the Yonge Street corridor, the Mississauga East corridor, the Yonge-Eglinton node, downtown Oakville, Scarborough Town Centre, and Mississauga City Centre. Reliance on the local trade area is least pronounced in the two business parks and in downtown Toronto. North York Centre is also among the study areas with the lowest percentage of trips that are 6 km or less.
As Table 19 shows, work trips are longer on average than those in the "non-work" category, which includes trips for the purpose of shopping, education, and childcare. This finding suggests an explanation for differences among the study areas related to distances in the "all trips" category. With the exception of downtown Kitchener, which is in a largely self-contained, medium-sized metropolitan region, areas that register the longest trips are also the ones with the highest proportions of commuter trips. The shorter trips to corridors are related to their low proportion of work trips.
Still, the distribution of commuter trip distances fits with prior observations on catchment areas. The longer distances of work trips to downtown Toronto and the business parks point to a metropolitan orientation, while the orientation of the other study areas appears to be more concentrated. But differences in commuting distances are not all that important. North York Centre and Mississauga City Centre register distances that come very close to those of downtown Toronto and of one of the business parks.
The link between nodes and their local catchment areas is stronger for non-work trips than for work trips. This pattern is consistent with metropolitan-wide patterns in which work-trip distances are longer than those for other types of trips, and access to shops and services tends to take place at a median scale within the metropolitan region (Jones and Simmons, 1993). We can attribute, to a certain extent, the "localism" of the catchment areas of nodes to their distribution of activities, more specifically, a strong presence of retailing and services. But there also appears to be an orientation towards local catchment areas, albeit a weak one, that is not accounted for by their functional makeup. Nodes record commuter-trip distances that are slightly below those of downtown Toronto and the business parks.
The corridors register shorter trips than nodes do. Such a finding is not very surprising, for by definition nodes contain activities such as shops, workplaces, and civic establishments, which attract people from a distance; this is not necessarily the case in corridors. Journeys to downtown Oakville are relatively long, because of the attraction of its restaurants and boutique-type shopping for distant clients. Finally, the relatively short distances of all trips to downtown Kitchener destinations, despite the strong presence of employment, is a function of the location of this district within a self-standing urban area. It stands to reason that trip lengths in a medium-sized metropolitan region will be shorter than those in a larger region. For the GTA as a whole, the average distance for all trips is 10.08 km, whereas in Waterloo Region it is only 6.85 km. Equivalent values for commuting trips are 14.83 and 8.66 km, respectively.
Table 19: Average distances of trips to destinations in study areas
|
|
All Trips (km) |
Per Cent Trips |
Work Trips (km) |
Per Cent Trips |
Non-work Trips (km) |
Per Cent Trips < 6 km |
Work Trips as % of All Trips |
Non-Work Trips as % of All Trips |
|
Downtown Toronto |
13.4 |
43.3 |
15.9 |
32.4 |
10.6 |
55.4 |
53 |
47 |
|
Yonge-Eglinton Node |
8.8 |
59.2 |
12.7 |
41.0 |
7.3 |
66.3 |
28 |
72 |
|
North York Centre |
10.3 |
45.6 |
14.6 |
25.6 |
8.7 |
53.5 |
28 |
72 |
|
Scarborough Town Centre |
9.1 |
56.9 |
13.1 |
38.6 |
8.1 |
61.7 |
21 |
79 |
|
Mississauga City Centre |
9.3 |
55.6 |
14.2 |
39.7 |
8.4 |
61.9 |
20 |
80 |
|
Downtown Oakville |
10.3 |
58.5 |
13.9 |
43.0 |
8.9 |
64.1 |
26 |
74 |
|
Downtown Kitchener |
9.5 |
71.3 |
10.2 |
62.7 |
8.7 |
82.3 |
56 |
44 |
|
Yonge Street Corridor |
8.1 |
62.5 |
12.7 |
41.4 |
6.8 |
68.9 |
23 |
77 |
|
Mississauga East Corridor |
8.4 |
60.6 |
12.5 |
40.8 |
7.9 |
62.9 |
11 |
89 |
|
Highway 401-Airport Corporate Centre |
11.6 |
42.0 |
14.7 |
25.6 |
9.5 |
52.8 |
44 |
56* |
|
Highway 404-Steeles Business Park |
12.7 |
40.2 |
16.2 |
24.0 |
9.5 |
55.4 |
48 |
52* |
Source: 2001 Transportation Tomorrow Survey (in the case of downtown Kitchener, 1996 TTS survey).
* The relatively important proportion of non-work trips in the two business parks is due to the presence of some retailing and hospitality establishments within their traffic zones.
Travel within nodes
A survey carried out in 1999 measured the extent to which office workers in North York Centre, Scarborough Town Centre, and Mississauga City Centre use the retail and hospitality facilities within their respective node (that is, the internal capture of these nodes), and how they travel to reach these facilities (Filion, 2001). The study was intended to gauge the degree of inter-functional synergy within these nodes.
As Table 20 shows, the built environment of the nodes and the location of their restaurants influence patronage by office workers. In North York Centre, where much of the office space is in multi-use complexes that include shopping areas and restaurants, a high proportion of office employees frequent restaurants within their own building (or complex). In Scarborough Town Centre too, many of the employees eat in their own building, probably because of the long distance and unpleasant walking environment to the shopping mall. In Mississauga City Centre, the shopping mall stands out as a preferred place to eat, given its wide variety of restaurants and a walking environment connecting office buildings to the mall that may be somewhat more pleasant than that of Scarborough Town Centre.
Table 20: Office workers' use of restaurants in their node (twice a week or more), North York Centre, Scarborough Town Centre, and Mississauga City Centre
|
|
North York Centre |
Scarborough Town Centre (n = 124) |
Mississauga City Centre (n = 146) |
|
In Own Building Mean |
58% 2.3 |
50% 2.1 |
21% 0.9 |
|
In Regional Mall Mean |
None |
22% 1.1 |
41% 1.6 |
|
Elsewhere in the Node Mean |
44% 1.8 |
13% 0.6 |
23% 1.0 |
|
Total Out of Own Building Mean |
44% 1.8 |
31% 1.7 |
52% 2.6 |
Source: Survey of office worker carried out in 1999 (Filion, 2001).
Table 21: Percentage of total non-food shopping carried out by office workers in their node, North York Centre, Scarborough Town Centre, and Mississauga City Centre
|
Percentage |
North York Centre |
Scarborough Town Centre (n = 123) |
Mississauga City Centre (n = 144) |
|
< 10 |
82% |
33% |
29% |
|
10-49 |
15% |
39% |
44% |
|
> 50 |
3% |
28% |
26% |
|
Mean Value |
10% |
34% |
31% |
Source: Survey of office worker carried out in 1999 (Filion, 2001).
Table 22: Per cent modal shares for trips within nodes, North York Centre, Scarborough Town Centre, and Mississauga City Centre
|
Mode |
North York Centre |
Scarborough Town Centre (n = 122) |
Mississauga City Centre (n = 144) |
|
Car |
16 |
31 |
38 |
|
Walking |
67 |
30 |
56 |
|
Bus or Subway |
17 |
39 |
6 |
Source: Survey of office worker carried out in 1999 (Filion, 2001).
The 1999 survey also revealed that office workers do relatively little shopping in their node (see Table 21). Despite the presence of large regional malls, workers in Scarborough Town Centre and Mississauga City Centre spend only slightly more than a quarter of their non-food shopping budget in their nodes. The probable explanation is a propensity to shop closer to home than to work (Jones and Simmons, 1993).
Again, differences between the nodes mirror their configuration. North York Centre, where shopping is available along the street and in shopping concourses, does not provide anything close to the variety present in the other two nodes. The low level of shopping within the node by North York Centre office workers could thus have been predicted.
A reliance on walking for intra-nodal journeys by office workers does not mirror the variations shown in Table 17 in home-based trips carried out on foot (in descending order: Scarborough Town Centre, North York Centre, and Mississauga City Centre). More so than home-based journeys, intra-nodal trips carried out by office workers seem to respond to variations in the quality of the pedestrian environment of the different nodes. Table 22 indicates that North York Centre records the highest reliance on walking, followed by Mississauga City Centre and Scarborough Town Centre. A disturbing finding, which underscores the poor quality of certain nodes' pedestrian environment, is a relatively high automobile reliance for intra-nodal journeys: from 16 per cent in North York Centre to 38 per cent in Mississauga City Centre.
Travel statistics point to some effect of downtowns, nodes, and corridors on modal shares. The data, however, show that the effect is not as pronounced as could have been anticipated and certainly considerably lower than the ambitious transit patronage goals advanced in official plans. One reason is the configuration of some of the study areas, which does not break from the automobile orientation that typifies the suburb. Another is the effect of the layout and transportation features of the surroundings of study areas on transit use and walking, which may interfere with the transit- and pedestrian-friendly features of study areas. An understanding of the travel patterns of study areas demands a consideration of their inner land-use and transportation conditions, and those of surrounding districts.
Notes
16. Note that the Transportation Tomorrow Survey, from which our transportation statistics originate, only records walking (and cycling) journeys that have work or education as a destination or origin.
17. These statistics come from a different data base from those presented in the two previous tables. Data for work journeys are from the 2001 census long-form questionnaire, which was distributed to 20 per cent of households, a much larger sample than the Transportation Tomorrow Survey, the source of the data used in Tables 15 and 16.