The Effect of Transportation on

Affordability in Greater Vancouver Group 1

April 22, 2013

Prepared for:

Dr. Jinhua Zhao

CIVL 441/PLAN 548J

Transportation Planning Analysis

Prepared by:

Michael Chow (69299089)

Lee Haber (79653127)

Evelyn Mah (41662081)

Caleb Stokkeland (21657119)

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Highlights  

1. Housing costs alone do not present an adequate measure of affordability

2. An index that combines housing and transportation costs may be a more relevant

tool in measuring affordability in Greater Vancouver

3. The Housing and Transportation (H+T) Affordability Index is used in almost 900

areas in the US

4. A comparison is made between the calculated H+T affordability and the

traditional housing affordability in Greater Vancouver

5. More communities in Greater Vancouver become unaffordable than affordable in

the new definition of affordability that includes transportation costs

6. Based on the new index, centrally located urban neighbourhoods are more

affordable than suburban areas.

7. The areas of greatest concern are those that are unaffordable and where the

residents are spending a significant portion of their income on transportation

costs. Most of these areas are located in suburban municipalities with low

densities and poor transit.

8. Transportation costs were found to decrease with increasing neighbourhood

walkability for communities in Greater Vancouver

9. The results of this study significantly changes our view of affordability and

should thus affect how people choose where to live.

10. The results are relevant for all levels of decision-makers (households, community

leaders, housing and transportation professionals, government officials, etc.)

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Abstract  

In the urban community, household transportation costs are subject to a number of

factors. These factors change across urban regions, and as a result, the percentage of

household income spent on transportation can vary considerably. The measure of location

affordability has traditionally been determined by housing costs alone. However, it is

shown in this study that transportation costs have a considerable impact on the

affordability of living in a given neighbourhood.

In the United States, the Center for Neighbourhood Technology (CNT) has

developed the Housing and Transportation (H+T) Affordability Index, which defines

affordability as a household spending less than 45% its income on housing and

transportation costs. Based on this definition of affordability, it has been found that many

urban areas previously considered unaffordable are actually quite affordable as they are

walkable and have good transit service. Similarly, many suburban areas that are viewed

as affordable when looking at housing costs alone are actually quite unaffordable, as they

areas require the ownership of an automobile and its inherent costs. This work by CNT

supports policies where land use and transportation planning are coordinated to ensure

communities are walkable and support a variety of uses.

This study applies a modified H+T index to determine the affordability in Greater

Vancouver, using 2006 Canadian Census and 2011 Translink Trip Diary data. Walkable

communities located in central areas with good transit service were found to be

considerably more affordable than areas with heavy auto-reliance. The most significant

outcome of our study is that Greater Vancouver is significantly less affordable when

transportation costs are included. A considerable number of suburban communities that

have affordable housing (mostly from Surrey, Coquitlam, and Langley) are deemed

unaffordable based in the new index. In addition, the concepts of actual and experienced

affordability are examined, based on median regional income and median local income,

respectively. This analysis shows that many areas in the suburbs are unaffordable and

have people spending a disproportionate amount of their income on housing and

transportation. Future transportation and planning initiatives should be focused in these

areas in order to produce the greatest improvement in affordability.

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While the H+T affordability has not yet been adopted across Canada by policy

makers and the public alike, we expect the results of this study to: 1) enable residents of

the Greater Vancouver area to make wiser choices when looking for a place to live and 2)

aid policy makers in where transit improvements and social housing initiatives are

focused. Furthermore, understanding the relationship between housing and transportation

with respect to affordability will enable local municipalities to prioritize related projects

in specific neighbourhoods, providing more affordable living for their residents.

 

Key  Words  

Affordability; Housing Costs; Housing and Transportation (H+T) Affordability Index;

Land Use; Transportation Costs; Walkability; Walk Score.

 

 

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Table  of  Contents  

List of Figures ................................................................................................................... vii

List of Tables ................................................................................................................... viii

1.0 Introduction ............................................................................................................... 1

2.0 Literature Review ...................................................................................................... 3

2.1 The Affordability Index .......................................................................................................... 3

2.2 Housing + Transportation Affordability in Washington, DC ................................................ 4

2.3 Coordinating Transportation and Land Use ........................................................................... 4

2.4 Transportation Affordability .................................................................................................. 5

3.0 Methodology ............................................................................................................. 7

3.1 Data Used ............................................................................................................................... 7

3.2 Housing and Transportation (H+T) Index .............................................................................. 7

3.2.1 H+T Overview ................................................................................................................ 7

3.2.2 H+T Methods .................................................................................................................. 8

3.3 Transportation Cost and Walkability ..................................................................................... 9

3.3.1 Walk Score Overview ..................................................................................................... 9

3.3.2 Comparing Transportation Cost and Walkability ......................................................... 11

4.0 Data Analysis and Interpretation ............................................................................. 13

4.1 H+T Results .......................................................................................................................... 13

4.2 Actual and Experienced Affordability ................................................................................. 21

4.3 Linear Regression Results .................................................................................................... 29

5.0 Discussion ............................................................................................................... 32

5.1 H+T Summary ...................................................................................................................... 32

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5.2 Transportation Cost and Walkability Summary ................................................................... 33

5.3 Impact and Policy Implications ............................................................................................ 35

5.4 Further Research ......................................................................................................... 36

6.0 References ................................................................................................................... 37

Appendix A: Housing and Transportation Index .............................................................. 38

Appendix B: Linear Regression Analysis ......................................................................... 51

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List  of  Figures  

Figure 1: Point grid used for population density weighted Walk Score ........................... 11  

Figure 2: The ten most affordable areas ........................................................................... 14  

Figure 3: The ten least affordable areas ............................................................................ 14  

Figure 4: Areas that became unaffordable when transportation costs were included ....... 15  

Figure 5: Areas that became affordable when transportation costs were included ........... 16  

Figure 6: Neighbourhoods that are affordable based on H+T costs below 45% of the

median household income. ........................................................................................ 19  

Figure 7: Affordability by municipality ............................................................................ 20  

Figure 8: Actual vs. experienced affordability for Greater Vancouver census tracts ....... 23  

Figure 9: Actual vs. experienced affordability for Vancouver census tracts .................... 24  

Figure 10: Actual vs. experienced affordability for Burnaby census tracts ...................... 24  

Figure 11: Actual vs. experienced affordability for Surrey census tracts ......................... 25  

Figure 12: Housing affordability in Greater Vancouver by sub-region ............................ 26  

Figure 13: H+T affordability in Greater Vancouver by sub-region .................................. 27  

Figure 14: Change in affordability in Greater Vancouver by sub-region ......................... 28  

Figure 15: Linear regression results for Greater Vancouver ............................................ 29  

Figure 16: Linear regression results for Vancouver ......................................................... 30  

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List  of  Tables  

Table 1: The most and least affordable areas in Greater Vancouver ................................ 13  

Table 2: Neighbourhoods that became unaffordable ........................................................ 16  

Table 3: Percentage of affordable areas by municipality .................................................. 18  

Table 4: Statistical results from linear regression analyses .............................................. 31  

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1.0 Introduction  

Affordability is an increasingly important issue in Greater Vancouver. In 2013,

Vancouver was rated one of the least affordable cities in the world (Demographia, 2013).

Existing studies of affordability have focused exclusively on housing costs and have

significantly influenced policy, often encouraging development away from the core of a

city.

However, focusing on housing alone provides an incomplete picture of affordability.

There are other necessities that have a significant impact on the cost of living.

Transportation is, on average, the second largest household expenditure and including it

in the definition of affordability has been found to produce a much clearer picture of

which areas are affordable and which ones are not.

In the United States, the Center for Neighborhood Technology (CNT) has

developed a Housing and Transportation (H+T) Affordability Index. It defines

affordability as spending less than 45% of household income on housing and

transportation costs. Many of the H+T index’s findings contradict the view of

affordability set out in conventional indices. For instance, urban neighbourhoods, where

residents have access to public transportation and are able to walk and cycle, experience

much lower transportation costs. Several neighbourhoods (such as the Upper East Side in

Manhattan) deemed unaffordable with previous methods have been found to be quite

affordable when transportation costs have been factored in. Similarly, locations in

suburban areas, though having lower housing prices, effectively require their residents to

own and drive a car. Many of these communities are therefore no longer deemed

affordable using the new index.

To date, there has been no similar study of location efficiency for Canadian cities.

Our project involves applying a modified H+T index to neighbourhoods in Greater

Vancouver. We also quantify the correlation between Walk Score, a measure of

walkability, and transportation costs. Below is an overview of the steps accomplished in

conducting this study:

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• Review the H+T Affordability Index developed by CNT and other associated

literature.

• Examine the H+T index to determine if it is feasible with available Canadian data

(specifically, data from Greater Vancouver).

• Develop an index that incorporates Statistics Canada housing and transportation

data and Translink trip diary data.

• Apply the H+T index to census tracts in Greater Vancouver and compare the

results with housing affordability alone.

• Analyze the differences between cities’ actual affordability (based on median

regional income) and experienced affordability (based on median local income)

• Compare Walk Score to transportation costs for various neighbourhoods in order

to identify the relationship between the two

Since our study utilized Canadian census data, the H+T index and its associated

analyses can be replicated for any other region in Canada; a housing and transportation

affordability index can be created with the same data.

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2.0 Literature  Review  

In order to fully understand the H+T index in more detail, literature on combined

housing and transportation affordability was reviewed. All of the literature reviewed

originates with CNT and relates to the development and application of the H+T index.

2.1  The  Affordability  Index  

From 2003 to 2008, the Brookings Metropolitan Policy Program operated a

special project called the Urban Markets Initiative. The goal of the initiative was to create

more accurate and accessible information for urban areas. The initiative developed the

“Affordability Index”, an information tool that combines the costs of housing and

transportation in American urban communities. The 2006 Brookings report, “The

Affordability Index: A New Tool for Measuring the True Affordability of a Housing

Choice”, describes the rationale for developing such an index and results from testing the

index in the regional area of Minneapolis-St. Paul, Minnesota.

In traditional affordability indices, location and transportation costs are either

underestimated or ignored. In the US, transportation is the second largest household

expenditure. Based on the 2003 Consumer Expenditure Survey, the average US

household allocates 19% of its budget to transportation costs (CTOD, CNT, 2006). The

Affordability Index takes into account transportation benefits from living in certain

locations, on both a metropolitan level and neighbourhood level. A comparison is made

between housing costs as a percent of income and H+T costs as a percent of income. As

an example, areas outside of the Minneapolis-St. Paul regional core experienced a

significant increase in living costs with the new index. This is due to the heavy reliance

on car ownership and usage. The cities of Minneapolis and St. Paul have the most

extensive bus system in the region, with daily non-auto commutes ranging from 15% to

23% (CTOD, CNT, 2006). This is reflected in the Affordability Index, which shows the

areas that are well equipped with public transit are indeed the most affordable.

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2.2  Housing  +  Transportation  Affordability  in  Washington,  DC  

Washington, DC has notoriously high housing costs in its core, as high as $5,200

per month in some areas (CNT, 2011). However, CNT postulates that the core may be

more affordable than what housing costs alone suggest if transportation costs are

considered. They found that there is generally an inverse relationship between housing

and transportation costs. The houses furthest from the city’s core have the highest

transportation cost.

Another driver for low transportation costs is high-density development. People

that live in high-density areas are more likely to own fewer or no personal vehicles. Many

people in the core of Washington spent more than 30% of their income on housing, but

less than 45% of their income on housing and transportation combined (CNT, 2011). This

means by the traditional housing-only indicator of affordability, these areas were deemed

unaffordable. However, when the H+T indicator was considered, these areas now are

considered affordable. This shows that in some cases the expensive housing in core areas

is offset by transportation cost savings. It should be noted that CNT does not suggest that

living in the most expensive areas will provide the lowest H+T cost. However, they do

suggest that the best way to look at affordability is to consider H+T, and as a result, the

most affordable locations in an urban region can be found.

2.3  Coordinating  Transportation  and  Land  Use  

It does not come as a surprise that transportation planning is important in peoples’

daily lives. Many people take for granted features that have been put in place to

encourage modes of travel other than driving, and oftentimes do not consider the trade-

off that is being made with respect to location, time spent traveling, or land use.

However, it is important to understand the relationship between transportation and land

use, as these are key factors that “can help minimize infrastructure investment needs

while improving safety, mobility and accessibility for…the traveling public” (Porter,

2006).

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When considering the planning of regional transportation and land use strategies,

it is important to keep in mind the context and “vision” of the transportation corridor.

This vision will set the framework for decisions such as facility design, access

management, and local land use controls. In the past, transportation corridor planning has

focused on a particular roadway and related transportation facilities, but planning

committees are beginning to understand the importance of the link between transportation

and land use. In Lexington, Kentucky, the city’s planners focused on coordinating

activities between the engineering and planning departments, resulting in a community-

supported corridor plan. This design included features such as narrower cross-sections,

bicycle and pedestrian accommodations, and extensive streetscaping and landscaping.

These objectives provide safety and mobility for vehicles and pedestrians, and have also

led to significant economic development benefits in certain business districts.

2.4  Transportation  Affordability  

The impact of transportation costs play a factor on economic development. The

Victoria Transport Policy Institute (VTPI) has produced a report that discusses the

impacts of affordability and offers strategies to help improve affordability. Living in an

area that is deemed unaffordable has been shown to drive up wages in order to fill

necessary positions in a given industry. For instance, there is a limit to the number of

workers living in a given neighbourhood who are willing to trade-off higher wages for

more affordable housing and transportation. Once this limit is reached by the industries in

the area, companies then need to increase the wage to attract workers from other areas, to

compensate for increased transportation costs due to longer commutes. As well, high cost

of living may reduce the number of professionals moving into a community and as a

result, reduce growth in associated industries.

The VTPI has noted that it is important to understand the difference between

accessibility and mobility, and moving from a mobility-based analysis to an accessibility-

based analysis is essential when conducting transportation planning. Mobility-based

analysis evaluates the transport system quality based only on physical movement, but an

accessibility-based analysis evaluates the transport system based on people’s ability to

reach desired goods, services and activities (Litman, pp 4). When considering

6

accessibility, alternative travel modes are considered rather than only vehicular travel, as

is the case in mobility-based analysis. Planning for transportation based on accessibility

is typically more cost effective and beneficial, as major consequences of mobility-based

analysis include high automobile costs, loss of time as drivers need to chauffeur non-

driving family members, and the reduction in physical health associated with extensive

automobile reliance.

In the VTPI’s suggestion for evaluating transportation affordability, they note the

fact that “peoples’ transportation needs and abilities vary” (Litman, pp 5). In order to

compensate for these differences, several factors should be considered when determining

transportation affordability. These include income and wealth, daily household

responsibilities (e.g. commuting to work), physical and mental abilities, ability to

understand and read the local language, and the ability to drive.

The report also delves into the relationship between land use and transportation

costs, noting that suburban and rural communities have increased transportation costs due

to less accessible land use patterns and more automobile-dependent transportation

networks. In addition, areas that have affordable housing and accessibility to multi-modal

travel generally resulted in increased affordability.

Transportation affordability becomes important when assessing a households’

economic resilience, such as being able to respond effectively to unexpected financial

burdens, like an increase in fuel price or a vehicle failure. In areas where transportation

costs are high (likely meaning a resident of that area would be vehicle-dependent), an

event that prohibits vehicle travel would cause a much larger financial strain to local

commuters, due to limited travel alternatives.

 

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3.0 Methodology  

This section outlines all of the data sources used to complete the analysis,

including a background of the theories and models in which the information is based. The

methods of analysis and the expected results are also described.

3.1  Data  Used  

To develop an H+T index for locations in Greater Vancouver, various types of

housing and transportation data were required. Calculated transportation costs were

compared to Walk Score to see if a correlation between transportation expenditures and

walkability for neighbourhoods in Greater Vancouver existed. The data that was required

is as follows:

• Transportation cost data for various regions of Greater Vancouver.

• Housing cost data for the corresponding regions.

• Walk Score data for the corresponding regions.

The data sources we used to collect the required data are as follows:

• Transportation trip data collection from Translink’s 2011 Trip Diary Analysis

Report and from Statistics Canada 2006 Census Report.

• Academic reports to find costs associated with corresponding trip mode types.

• Walk Score data for corresponding neighbourhoods from the Walk Score website.

3.2  Housing  and  Transportation  (H+T)  Index  

3.2.1  H+T  Overview  

The H+T index provides a holistic approach to evaluating affordability by

considering housing and transportation costs associated with living in a given area. Since

transportation costs are usually the second largest household expenditure, evaluating

affordability on housing alone may be incomplete and unreliable. For example, the cost

of a home in close proximity to rapid transit may be more expensive than a similar

8

suburban home. However, being close to public transit will likely reduce transportation

costs and may offset the increase in housing costs.

CNT’s approach to determining transportation costs for a given area is quite

different from the method used in our study. CNT uses indicating factors within a

neighbourhood to predict transportation costs, such as density, household income, access

to transit, etc. They use these factors as inputs to a model to generate the number of trips

by each mode and the associated cost. These resources were not available in order to

build a model for Greater Vancouver. Our study uses a method based on census data.

The H+T index consists of the average housing and transportation cost from

living in a given neighbourhood, normalized by the median household income.

Transportation costs include the costs of auto ownership, auto usage, and public

transportation usage. The formula for the H+T index is as follows:

𝐻+ 𝑇  𝑖𝑛𝑑𝑒𝑥 =ℎ𝑜𝑢𝑠𝑖𝑛𝑔  𝑐𝑜𝑠𝑡𝑠+ 𝑡𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡𝑎𝑡𝑖𝑜𝑛  𝑐𝑜𝑠𝑡𝑠

ℎ𝑜𝑢𝑠𝑒ℎ𝑜𝑙𝑑  𝑖𝑛𝑐𝑜𝑚𝑒

CNT has determined that the threshold for H+T index affordability is 45% of total

income (CNT, 2012). By using this index and threshold, instead of using a traditional

housing cost threshold of 30% of total income, some areas previously labeled as

unaffordable may be viewed as more affordable and vice versa.

3.2.2  H+T  Methods  

From the 2006 census data for Greater Vancouver, the costs of housing and

transportation for households in each census tract were calculated. The data lists the

number of drivers, passengers, and vehicles per household. Also, it reports the number of

people who use public transportation, walking, cycling, motorcycling, and taxi as their

primary mode of transportation. The Canadian Automobile Association (CAA) data was

used to find the average annual cost for auto ownership. However, this cost varies with

the number of Vehicle Kilometers Traveled (VKT) each year. Therefore, Translink’s Trip

Diary was used to determine the average VKT per year for each region of Vancouver and

came up with an average annual cost of owning and operating a vehicle. For average

public transportation costs, it was determined how likely people in each census tract were

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to travel within 1, 2, or 3 zones and the corresponding Translink fares were applied. For

cycling and walking, the cost of transportation was assumed to be zero. As the mode

share for motorcycle and taxi were very low, they were deemed negligible and omitted.

To determine the total transportation cost (T) for each census tract, the transportation

modes and costs of all users within the given census tract were averaged.

𝑇 =#  𝑣𝑒ℎ ∗ 𝑐𝑜𝑠𝑡  𝑝𝑒𝑟  𝑣𝑒ℎ + (#  𝑝𝑢𝑏  𝑡𝑟𝑎𝑛𝑠 ∗ 𝑝𝑢𝑏  𝑡𝑟𝑎𝑛𝑠  𝑐𝑜𝑠𝑡)

#𝑣𝑒ℎ+ #𝑝𝑢𝑏  𝑡𝑟𝑎𝑛𝑠+ #𝑤𝑎𝑙𝑘+ #𝑏𝑖𝑐𝑦𝑐𝑙𝑒+ #𝑚𝑜𝑡𝑜𝑟𝑐𝑦𝑐𝑙𝑒+ #𝑡𝑎𝑥𝑖

Using housing and transportation costs for various areas of Greater Vancouver, it

was determined which areas were affordable using the H+T index, based on the definition

of affordability as spending less than 45% of household income on housing and

transportation. These results are presented graphically throughout this report.

The methods used to determine transportation costs provide an estimate of costs

for households in each census tract. However, due to time limitations, the methods used

do have a few simplifying assumptions which could be improved upon in further studies.

For instance, the difference in parking costs between urban and suburban environments

was not accounted for. If this discrepancy was accounted for, it would presumably

increase transportation costs in urban areas. Also, since we do not know actual VKT for

each vehicle, we had to use an average for a fairly large area. By knowing VKT per

vehicle with more accuracy, we would increase the precision and validity of our

calculated transportation costs.

3.3  Transportation  Cost  and  Walkability  

3.3.1  Walk  Score  Overview  

Walkability is a key characteristic for urban neighbourhoods. In Greater

Vancouver, the ability to walk to basic amenities significantly adds value to living in a

given neighbourhood. A compact, walkable neighbourhood offers several benefits, such

as encouraging a healthier lifestyle, reducing vehicle carbon dioxide emissions through

less car reliance, and promoting a more social, interactive community. Walk Score is a

measurement of walkability created for Canada, the US, Australia, and New Zealand. A

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100-point scale is used to rate walkability, based on typical walking routes to common

destinations (schools, parks, restaurants, retail and grocery stores, etc.). Maximum points

are awarded for amenities that are situated within 0.25 miles of a given location, whereas

no points are awarded for amenities that are further than 1 mile away. The Walk Score

rating can be applied to specific point locations, neighbourhoods, or entire cities. A

walkable neighbourhood requires the following:

• A main centre

• Housing located near businesses

• Parks and public spaces

• Nearby schools and workplaces

• Streets designed for pedestrians, cyclists, and public transit

For neighbourhood or city Walk Scores, point location Walk Scores are taken at

approximately every city block (defined by a predetermined grid system), and combined

with a weighted average based on population density. The steps for calculating a

population density weighted Walk Score are summarized below.

1. Expand each point by 0.00075 decimal degrees to create a grid cell

2. Intersect the grid cell with the census blocks it intersects; for each census block:

• Calculate the percentage of the census block the grid cell intersects

• Multiply that percentage by the total population of that census block

• Sum these partial populations to get the grid cell population

3. Add the grid cell population to a variable called “total_population”

4. Calculate the Walk Score at the center of the grid cell and multiply it by the grid

cell population to get the weighted Walk Score

5. Add the weighted Walk Score of this grid cell to a variable called

“weighted_walk_score”

6. To calculate the Walk Score for an entire neighbourhood/city, divide

“weighted_walk_score” by “total_population” for the points within the boundary

of the neighbourhood/city.

(Source: Walk Score)

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Figure 1: Point grid used for population density weighted Walk Score

It should be noted that Walk Score does not take into account street design, safety,

pedestrian friendly design and orientation of streets and buildings, topography, and

weather.

3.3.2  Comparing  Transportation  Cost  and  Walkability  

Walkability has been shown to have an inverse relationship with transportation

costs. H+T data for individual census tracts in Greater Vancouver can be correlated with

Walk Scores for given neighbourhoods. The transportation cost is reported as a

percentage of household income, based on the median income for residents in each area

of Greater Vancouver. The transportation variable includes the costs and savings

associated with owning a vehicle, as described above.

We use a simple linear regression model to relate Walk Score (independent

variable) to transportation costs (dependent variable). This model can predict or forecast

the values of the dependent variable based on its relation of several given values of the

independent variable. However, a correlation can only be verified – the direction of the

causal relationship cannot be confirmed. The regression model is defined below.

y = β0 + β1x + ε

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Where:

x = independent variable (Walk Score)

y = dependent variable (transportation cost)

β0 = mean value of y when x is zero

β1 = change in mean value of y for a 1-unit increase in x

• For β1 > 0, x and y have a positive linear relationship

• For β1 < 0, x and y have a negative linear relationship

• For β1 = 0, x and y have no linear relationship

ε = error term

The objective of simple linear regression is to minimize the sum of squared errors,

thereby evaluating the equation where the expected value of ε is zero. The results of the

model yield several statistical values, such as R2, standard error, degrees of freedom, and

β0 and β1 with corresponding t-statistics. The R2 value is used to measure how much

variation is found between the inputted data and the linear regression line (i.e. how

accurate the model is in estimating Walk Score). The t-statistics for β0 and β1 verify their

statistical significance, based on the calculated degrees of freedom and standard error.

Microsoft Excel and StatPlus are used for the analysis. It was expected that the

results would show a negative relationship between transportation costs and Walk Score.

The goal is to quantify this relationship by determining the strength of the correlation.

Though our analysis, it is possible to make justified estimations of transportation cost in a

certain area, based on the Walk Score for that neighbourhood. As a result, the effect

walkability has on transportation costs in Greater Vancouver can be confirmed.

13

4.0 Data  Analysis  and  Interpretation  

4.1  H+T  Results  

After conducting the data analysis and applying the H+T index, it was determined

that the ten most affordable areas based on housing and transportation costs were located

solely within the municipalities of Vancouver and Burnaby. In comparison, the ten least

affordable areas based were located in Coquitlam, Port Moody, Surrey, and West

Vancouver. The top ten rankings for the most and least affordable areas can be found in

Table 1 and the detailed rankings can be found in Appendix A. The most and least

affordable areas lists appear to support the conclusion that areas that are centrally located

with good transit access and a mixture of uses are affordable when considering housing

and transportation costs. Conversely, automobile-oriented areas on the periphery bring

with them very high housing and transportation costs and are quite unaffordable.

Table 1: The most and least affordable areas in Greater Vancouver

Ranking Most Affordable Least Affordable

1 Mt. Pleasant/ Great Northern Way, Vancouver Rosemary, South Surrey

2 West End, Vancouver West Cloverdale, Surrey 3 Metrotown, Burnaby Westwood Plateau, Coquitlam

4 Grandview-Woodlands, Vancouver West Bay, West Vancouver

5 Strathcona, Vancouver Cypress Park, West Vancouver

6 Broadway Commercial, Vancouver Westwood Plateau, Coquitlam

7 West End, Vancouver East Newton North, Surrey 8 Metrotown, Burnaby Heritage Mountain, Port Moody 9 West End, Vancouver East Fleetwood, Surrey 10 West End, Vancouver British Properties, West Vancouver

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Figure 2: The ten most affordable areas

Figure 3: The ten least affordable areas

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From the data analysis, it was determined that the majority of people lived in

areas where housing was considered affordable to them. 336 out of the total 406 tracts

had people living where they could afford the housing (with 30% of the median

household income being spent on housing considered as affordable), but only 259 areas

had people living in areas where both housing and transportation costs were affordable

(with 45% of the median household income being spent on housing and transportation

considered as affordable).

After considering both housing and transportation costs, 49 areas that had

previously been deemed affordable based housing costs became unaffordable. In

comparison, only 9 areas that were previously unaffordable became affordable according

to the H+T index. These results are depicted in Figure 4 and Figure 5.

Figure 4: Areas that became unaffordable when transportation costs were included

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Figure 5: Areas that became affordable when transportation costs were included

All 9 areas that became affordable are neighbourhoods located in Vancouver:

Cambie, Kitslano, Point Grey, Mount Pleasant, Fairview, Downtown, False Creek North,

Coal Harbour and the West End.

Areas that became unaffordable were found to be far from Skytrain lines and

located towards the periphery of the region. Table 2 lists the different neighbourhoods

within each municipality that became unaffordable when taking into account the H+T

index. It is important to note that some neighbourhoods appeared more than once due to

multiple census tracts, therefore reinforcing the unaffordability of that area.

Table 2: Neighbourhoods that became unaffordable

Municipality Neighbourhood Burnaby • Burnaby South

• Buckingham/Lakeview Coquitlam • Cape Horn

• Cariboo/Burquitlam • Central Coquitlam • Central Coquitlam • Eagle Ridge • Hockaday/Nestor • Maillardville

17

• Ranch Park • River Heights

Delta • Ladner (3x) • North Delta (4x) • Tsawwassen (2x)

Langley • All neighbourhoods except Willoughby/Willowbrook

Maple Ridge • Albion, Thornhill • East Haney • Haney • Port Haney, Haney • The Ridge • The Ridge • The Ridge • Yennadon

North Shore • Dundarave • Kirkstone • Norgate • Upper West Lynn

Pitt Meadows • All neighbourhoods Port Coquitlam • Glenwood (2x)

• Lincoln Park Richmond • Blundell (3x)

• Broadmoor • City Centre (2x) • East Cambie • East Richmond • Gilmore • Sea Island • Seafair (2x) • Steveston (3x) • West Cambie

Surrey • Cloverdale (3x) • Guildford (9x) • Newton (9x) • South Surrey (4x) • Whalley (8x)

18

Overall, Figure 6 shows the areas that are affordable (depicted in yellow) when

considering both housing and transportation costs as less than 45% of the median

household income. Table 3 below also lists out the number of neighbourhoods that are

affordable in each municipality.

Table 3: Percentage of affordable areas by municipality

Municipality

Total Areas by Census Tract

Affordable based on

Housing Costs < 30% of Income

Affordable based on

Transportation Costs < 15% of

Income

Affordable based on Housing &

Transportation Costs < 45% of

Income Burnaby 41 93% 41% 88%

Coquitlam 22 68% 0% 23% Delta 19 79% 0% 32%

Langley 24 67% 0% 13% Maple Ridge 13 69% 0% 8%

New West 13 85% 62% 85% North Shore 33 33% 12% 24%

Pitt Meadows 3 100% 0% 0% Port

Coquitlam 9 44% 0% 11%

Port Moody 6 17% 0% 0% Richmond 33 82% 9% 42%

Surrey 78 55% 0% 13% Vancouver 108 78% 85% 85% White Rock 4 50% 0% 50%

19

Figure 6: Neighbourhoods that are affordable based on H+T costs below 45% of the median household income.

It is clear from the results, that the suburban nature of most of Greater Vancouver

means that when transportation costs are included, affordability decreases dramatically.

For instance, while Delta, Pitt Meadows, and Richmond have relatively more affordable

housing than other areas (79%, 100%, and 82% of census tracts had households spending

less than 30% on housing costs, respectively), when taking into consideration

transportation costs, the percentage of census tracts in those municipalities that were still

affordable dropped to 32%, 0%, and 42% for Delta, Pitt Meadows and Richmond

respectively. As well, it appears the higher housing costs of urban areas are generally

offset by having lower transportation costs. This is the case for the City of Vancouver

where the number of affordable census tracts increases 21% when including

transportation costs.

20

When considering both housing costs and transportation costs, Vancouver,

Burnaby and New Westminster appear to be exceptions to the general suburban nature of

the region. All three municipalities are quite affordable both when considering housing

costs alone as well as H+T (Vancouver, 64% affordable based on housing only, 85%

affordable based on housing and transportation Burnaby, 80% affordable based on

housing only, 88% affordable based on housing and transportation, and New

Westminster, 85% affordable based on housing only, 85% affordable based on housing

and transportation). Figure 7 shows the relationship between the affordability of housing

in comparison to the affordability of transportation costs and the affordability of housing

and transportation costs.

Figure 7: Affordability by municipality

0%  

20%  

40%  

60%  

80%  

100%  

120%  

Percen

tage  of  A

ffordab

le  Cen

sus  T

racts  

Municipality  

Affordability  by  Municipality  

Housing  Affordability  Transporta;on  Affordability  

21

4.2  Actual  and  Experienced  Affordability  

In order to determine areas where affordability needs to be improved the most, it

is important to not just know which areas are unaffordable, but in which areas people are

experiencing a lack of affordability.

Actual affordability indicates how affordable an area actually is. It is the

measure of affordability that is used by CNT and this study. It is the housing and

transportation costs divided by the median regional income. A person moving to Greater

Vancouver would use actual affordability to determine an affordable area to live in.

Experienced affordability indicates how people in an area are actually

experiencing affordability i.e. how much of their actual income they are spending on

housing and transportation costs.

There may be areas that are unaffordable to most, but the residents have high

incomes and therefore do not experience high living costs. For instance, the high housing

costs and the requirement of owning a car makes West Vancouver unaffordable for most.

However, for the most part only people with high incomes choose to live in West

Vancouver, meaning that its residents are not spending a significant portion of their

income on housing and transportation. It could be said in these areas wealth is

compensating for a lack of affordability. These are not areas where affordability

improvements should be focused.

Conversely, there are areas that are very affordable, but their residents have very

low incomes and are spending a significant portion of their income on living costs. The

Downtown East Side and Gastown are good examples of areas where affordability is

22

compensating for a lack of wealth. Besides locating social housing in these areas (which

in most cases is already being done), there are few additional measures that could be

implemented that would improve affordability and reduce the living expense pressures

that residents experience.

The areas where affordability improvements should be focused are areas that are

unaffordable and where residents are spending a disproportionate amount of housing and

transportation costs. Figure 8 illustrates every census tract in the Lower Mainland plotted

based on Actual and Experienced affordability. Forty-five (45) percent is used as the

divide between affordable and unaffordable for both measures. Since incomes vary more

than housing and transportation costs, there is a general trend going diagonally going

from the top-left to the bottom-right. The top-right quadrant indicates areas that are

actually unaffordable and where residents are experiencing a lack of affordability. Census

tracts in this area are of highest concern.

23

Figure 8: Actual vs. experienced affordability for Greater Vancouver census tracts

Centrally-located municipalities with walkable neighbourhoods and good transit

service have few census tracts that are of high-concern. Vancouver and Burnaby

combined have only two census tracts that are unaffordable and where residents

experience high living costs. This is despite a significant range in income and

affordability. This is illustrated in Figures 9 and 10.

24

Figure 9: Actual vs. experienced affordability for Vancouver census tracts

Figure 10: Actual vs. experienced affordability for Burnaby census tracts

25

In contrast, the suburban municipalities have many areas that are unaffordable and

where residents are experiencing a lack of affordability. Figure 11 shows affordability

and how it is experienced in Surrey census tracts. There is only one census tract in Surrey

that is affordable and where people are living within their means (bottom-left quadrant).

Low-income residents appear to be concentrated in the few census tracts that are

affordable, and are living beyond their means. However, what is of greater concern is the

high number of census tracts that are of high concern. It is clear that policies that would

improve affordability (move tracts to the bottom left) such as rapid transit would have

their greatest effect in the suburbs.

Figure 11: Actual vs. experienced affordability for Surrey census tracts

26

The concept of Actual vs. Experienced affordability can be applied at a regional

level. When looking at affordability, people like to compare the situation in different

municipalities or parts of the region, as opposed to by census tract. In Figures 12, 13 and

14, the percentage of affordable dwellings in each sub-region is plotted against the

percentage of residents living within their means. Figure 12 illustrates this when using the

conventional housing-cost-only definition of affordability.

Figure 12: Housing affordability in Greater Vancouver by sub-region

When looking at housing costs alone, most municipalities have the majority of

dwellings at an affordable price, the only exceptions being White Rock, the North Shore

and Port Moody. In all municipalities, the majority of people appear to be living within

their means with Vancouver having the smallest percentage. The region appears quite

affordable.

27

However, when transportation costs are included, most of the region is actually

quite unaffordable. Figure 13 shows that there are now only three municipalities

(Vancouver, Burnaby and New Westminster) where the majority of dwellings are in

affordable areas and where most people are living within their means. White Rock,

Coquitlam, Surrey and Maple Ridge are where the greatest concern lies as most of the

dwellings are in unaffordable areas and a majority of residents are living beyond their

means. (In White Rock, no one is living within their means.) This in stark contrast to the

housing-only definition where Surrey, Coquitlam and Maple Ridge were considered to be

places that were affordable and people were living within their means.

Figure 13: H+T affordability in Greater Vancouver by sub-region

28

The difference between the common perception of affordability (housing only)

and actual affordability situation is quite significant. This is illustrated in Figure 14. The

most dramatic differences can be seen in White Rock, Pitt Meadows, Surrey Maple Ridge

and Coquitlam. Vancouver is the only sub-region where the affordability situation

improves when including transportation costs.

Figure 14: Change in affordability in Greater Vancouver by sub-region

29

4.3  Linear  Regression  Results   Two linear regression analyses were conducted using Walk Score and

transportation cost data for 96 neighbourhoods in Greater Vancouver. We used 22

communities in Vancouver, 10 in Burnaby, 10 in Coquitlam, 8 in Richmond, 7 in Surrey,

6 in Maple Ridge, 6 in Langley, 6 in North Vancouver, 5 in West Vancouver, 5 in New

Westminster, 3 in Port Moody, 3 in Pitt Meadows, 2 in Port Coquitlam, 2 in Delta, and 1

in White Rock. Transportation costs were calculated by census tract, whereas Walk

Scores were based on one point location in each associated neighbourhood, except for

Vancouver, which had average Walk Score data for individual neighbourhoods. The

locations for single-point Walk Scores were carefully chosen to take into account the

population density of the communities. Because of the two types of Walk Score data, we

carried out one analysis for all 96 communities, and a second analysis for just the 22

Vancouver neighbourhoods. The inputted data points and the calculated linear regression

lines are depicted in Figure 15 and Figure 16, for Greater Vancouver and Vancouver,

respectively.

Figure 15: Linear regression results for Greater Vancouver

0  

5  

10  

15  

20  

25  

0   10   20   30   40   50   60   70   80   90   100  

Tran

sporta9o

n  Co

st  (%

 of  regiona

l  med

ian  

househ

old  income)  

Walk  Score  

Greater  Vancouver  

Observed   Linear  Regression  

30

Figure 16: Linear regression results for Vancouver

Upon visual inspection, it is clear the correlation between transportation cost and

Walk Score is much more defined when only Vancouver data points are considered. This

is likely due to the density weighted Walk Scores used for each Vancouver

neighbourhood. Average neighbourhood Walk Score data is not available for

municipalities outside of the City of Vancouver. The method of taking point location

Walk Scores for neighbourhoods outside of Vancouver brings about many potential

errors. In communities with mixed urban and rural areas (typical of Delta, Surrey,

Langley, Pitt Meadows, and Maple Ridge) a single point location Walk Score is not

entirely representative of the whole neighbourhood. Nonetheless, a negative relationship

between the two variables is clearly depicted in both analyses.

Table 4 summarizes the calculated statistical terms for each linear regression

analysis. Complete results from the analysis can be found in Appendix B.

0  

5  

10  

15  

20  

25  

0   10   20   30   40   50   60   70   80   90   100  Tran

sporta9o

n  Co

st  (%

 of  regiona

l  med

ian  

househ

old  income)  

Walk  Score  

Vancouver  

Observed   Linear  Regression  

31

Table 4: Statistical results from linear regression analyses

Standard Deviation β1 R2 Standard

Error t-statistic

Greater Vancouver 4.44966 -0.11391 0.38913 3.49621 -7.73821 Vancouver 2.84215 -0.22353 0.84003 1.16481 -10.24828

For the Greater Vancouver analysis, 38.9% of the variation of transportation cost

is explained by walkability. The standard error of 3.49 shows that the difference between

the observed data and the predicted outcomes is relatively small. The response of

transportation cost from variations in Walk Score is statistically significant (t-statistic = -

7.74). The scale of impact is moderate, one standard deviation difference resulting in a

possible 0.51% change in transportation cost (-0.11391 × 4.44966 = -0.51).

For the City of Vancouver, the explanatory power of the model is much higher,

with R2 = 84.00%. The accuracy also improves, with a standard error of just 1.16. The

statistical significance of the modal is greater, with t-statistic of -10.25. Finally, the scale

of impact is slightly higher (-0.22353 × 2.84215 = -0.64).

32

5.0 Discussion  

5.1  H+T  Summary  

The H+T Index research yields interesting results in which affordability across the

region was found to be somewhat worse than expected. Out of 406 census tracts, 278

were deemed affordable by housing costs alone, and only 190 were deemed affordable by

the H+T Index. This drop of 22% in affordable census tracts could have several causes.

People when considering affordable places to live, look only at housing costs and fail to

consider transportation costs and how expensive it is to own a vehicle. A survey could be

performed to see if it is the case the people fail to estimate or underestimate their

transportation costs.

The initial hypothesis that areas close to downtown would become more

affordable, and areas on the outskirts of Greater Vancouver would become less

affordable, when the H+T Index was applied was shown to be correct . This result shows

that the increased housing costs from living close to the downtown core can be offset by

reduced transportation costs. However, even though many areas close to downtown

became more affordable, some were still unaffordable in absolute terms (greater than

45% of income spent on housing and transportation).

Given our time and funding limitations, our method of determining transportation

costs is a rough estimate and could be expanded upon. The implementation of a survey

which records peoples’ actual transportation costs over an extended period of time would

be the most exact way of determining these costs. However, it would not have been

possible to obtain a sufficient sample size using this technique given our time constraints.

An example question for this type of survey is “how much do you spend on

transportation in a week?” With more accurate trip diary data, it may be possible to

determine the separate effects of transit and walkability improvements alone on

transportation costs.

33

Another alternative would be to employ a model that accurately predicts peoples’

activity patterns and mode choice. Translink is currently updating their transportation

model to make it much more accurate. Once Translink has completed the update, they

could team with researchers to give a complete and accurate picture of transportation

costs in Greater Vancouver.

Our method assigns a cost of zero for cycling. However, this is not completely

true. There are costs associated with owning a bicycle, but since it is so much lower than

costs associated with other modes of transit, we assigned a zero cost given our time

constraints. Furthermore, we neglected taxi and motorcycle trips, as well as a

neighbourhood’s built environment. The walkability of a given area is significant in a

person’s mode choice, though this factor is not included in our model. Future research on

the H+T Index in Vancouver may address these limitations and increase its accuracy.

5.2  Transportation  Cost  and  Walkability  Summary  

The results of the linear regression analyses are quite significant. The Vancouver

analysis yields a much more defined relationship between transportation cost and

walkability. This is primarily due to the use of average neighbourhood Walk Scores, as

opposed to single-point location ratings. Both the Vancouver and Greater Vancouver

models show a negative correlation between the two variables. This is expected, as

people who can easily walk to their basic amenities will generally spend less on

transportation than those who require the use of a personal vehicle.

Based on the β1 value calculated in the Vancouver analysis, a 10-point increase in

a neighbourhood’s Walk Score corresponds to a 2.24% decrease in transportation

expenditures, while the Greater Vancouver analysis yields a 1.14% decrease. In

perspective, a 10-point increase in Walk Score corresponds to a $1,085 reduction in

annual transportation expenditures, using the Vancouver model (assuming a regional

median household income of $48,527 per year). With the Greater Vancouver model, the

savings would be $553 per year for every 10-point increase in Walk Score. The results

from both of these models support the notion that living in a more walkable, pedestrian

friendly community can be less expensive than living in a car-dependent suburb.

34

There are some limitations and errors associated with the data used in these

models. Census tract boundaries are not exactly in line with neighbourhood boundaries.

In general, the area within a city neighbourhood is much larger than a census tract. Often,

a single neighbourhood will encompass several census tracts, or a single census tract will

include parts of two neighbourhoods. Therefore, the Walk Score neighbourhood ratings

may be taking into account areas that are not within the associated census tract. In

selecting census tracts to characterize each neighbourhood, consideration was taken to

avoid boundary overlaps.

The linear regression graph created for the Greater Vancouver model depicts a

heteroscedastic regression (the variance of residuals increases with increasing Walk

Score). This suggests that higher Walk Scores will predict transportation cost with less

certainty. This characteristic is ignored in linear regression, as the model assumes a

constant variance in the error term, ε.

One major assumption in our model is that the relationship between transportation

cost and walkability is linear. However, the relationship may in fact be a second-order

power function, where for higher values of Walk Score, a greater change in transportation

cost occurs. This would suggest that the cost of transportation is more sensitive to

changes in communities with high walkability, with the largest incremental cost reduction

occurring in neighbourhoods with the highest Walk Scores.

Finally, these results do not mean that improving walkability alone will reduce

transportation costs. Since walkability and transit access are highly correlated, it is

impossible to say from the Walk Score analysis that walkability has a certain effect. A

more in-depth analysis of Walk Score, transit access and transportation

35

5.3  Impact  and  Policy  Implications  

Since the majority of our results suggest that the transportation costs in

Vancouver are high, policy changes could be made to reduce the burden of transportation

cost on residents. The areas with the biggest need for reduction of transportation costs are

municipalities on the outskirts of Greater Vancouver, such as Surrey and Coquitlam that

are largely unaffordable and where the residents are spending a high portion of their

income on housing and transportation costs. Their high costs are likely due to the lack of

rapid transit and infrequent transit in these areas. Some people in these areas may be

interested in taking public transit more often, but they see it as being inefficient so they

choose to drive.

However, building rapid transit carries a large capital cost and Translink cannot

currently provide this to every municipality. A more cost effective solution could be to

consolidate existing bus routes into fewer, more effective routes. Also, including more

express busses to main transit hubs may increase ridership. However, these measures to

increase busses could alienate some existing users. Consolidated bus routes and express

busses are usually put on busy transit corridors. So, existing transit users that do not live

near these corridors would see no benefit to this increase. Great care must be taken to

ensure any policy decisions are equitable.

Transit improvements in suburban should be accompanied with rezoning

measures that make these areas more walkable. It was found that there was a strong

correlation between walkability and reduced transportation costs. To further support this

point, areas along the Millennium Line in North Burnaby that were still walkable did not

have significantly lower transportation costs than surrounding areas. Both transit and

walkability improvements should be a part of any policy to improve affordability.

Finally, policy makers and the public should be educated on this more complete

definition of affordability. Social housing should be placed in areas with low

transportation costs so that the earnings of their residents go further. With a better

knowledge of affordability, people will save money and be able to spend it on more

productive uses.

36

5.4  Further  Research  

The H+T methodology used in this study could be applied to other metropolitan

areas in Canada. This would serve as a useful comparison and may further cement the

findings that areas that are walkable and with good transit access are affordable. This

could be performed with the similar data sources.

With trip diary data at the census tract level, a more accurate estimate of

transportation costs could be produced. Not only could a more up-to-date affordability

picture be produced (that would account for the implementation of the Canada Line in

2009), the separate effects of walkability and transit could be determined. Thus, the

effects of site-specific improvements on affordability could be estimated.

In conclusion, this study of housing and transportation affordability in Greater

Vancouver should serve as a starting point for a more educated discussion on

affordability in Canada, one that will have serious policy implications.

 

37

6.0  References  

Center for Transit Oriented Development (CTOD) and Center for Neighborhood

Technology (CNT). 2006. The Affordability Index: New Tool for Measuring the

True Affordability of a Housing Choice. Brookings Institution’s Urban Markets

Initiative (January 2006), 1-7.

Center for Neighborhood Technology (CNT). 2011. Housing + Transportation

Affordability in Washington, DC, (July 2011), 1-70

Center for Neighbourhood Technology (CNT). 2012, H+T Methods. (February 2012), 1-

10

Porter, C. D. 2006. Coordinating Transportation and Land Use. Institute of

Transportation Engineers. ITE Journal (June 2006), 28-32.

Canadian Automobile Association (CAA). 2012. Driving Costs Beyond the Price Tag:

Understanding your Vehicle’s Expenses. Retrieved April 3, 2013 from

http://www.caa.ca/docs/eng/CAA_Driving_Costs_English.pdf

Demographia. 2013. 9th Annual Demographia International Housing Affordability

Survey: 2013. Retrieved April 3, 2013 from http://www.demographia.com/dhi.pdf

Walk Score. 2013. Retrieved April 7, 2013 from http://www.Walk Score.com/

T. Litman. (2011). Transportation Affordability: Evaluation and Improvement Strategies.

Victoria Transport Policy Institute.

38

Appendix  A:  Housing  and  Transportation  Index  

Geography Municipality Average Housing

Cost

Median Aftertax Income

Housing Index Local

Housing Index

Regional

Transport Index Local

Transport Index

Regional HT

Local HT

Regional HT

Local Rank

HT Regional

Rank

HT Afford Rank

9330001.01 Vancouver 928 48719 0.229 0.230 0.143 0.144 0.372 0.373 61 70 67 9330001.02 Vancouver 1101 51444 0.257 0.272 0.149 0.158 0.406 0.430 145 157 154 9330002.01 Vancouver 1056 46648 0.272 0.261 0.162 0.156 0.434 0.417 225 139 136 9330002.02 Vancouver 1036 50984 0.244 0.256 0.153 0.160 0.397 0.417 117 138 135 9330003.01 Vancouver 990 48141 0.247 0.245 0.154 0.153 0.401 0.398 134 100 97 9330003.02 Vancouver 1089 46790 0.279 0.269 0.141 0.136 0.420 0.405 190 113 110 9330004.01 Vancouver 1025 49562 0.248 0.253 0.138 0.141 0.386 0.395 90 97 94 9330004.02 Vancouver 1085 49386 0.264 0.268 0.129 0.131 0.392 0.399 106 103 100 9330005.00 Vancouver 772 30488 0.304 0.191 0.190 0.119 0.494 0.310 346 20 17 9330006.01 Vancouver 1089 45506 0.287 0.269 0.148 0.138 0.435 0.408 229 117 114 9330006.02 Vancouver 1174 45533 0.309 0.290 0.157 0.147 0.466 0.438 289 168 165 9330007.01 Vancouver 1215 57086 0.255 0.300 0.136 0.160 0.392 0.461 105 206 203 9330007.02 Vancouver 1717 72361 0.285 0.425 0.112 0.167 0.397 0.592 118 374 371 9330008.01 Vancouver 0 52497 0.000 0.000 0.145 0.157 0.145 0.157 9330008.02 Vancouver 1571 81527 0.231 0.388 0.100 0.169 0.332 0.557 13 350 347 9330009.00 Vancouver 1204 43113 0.335 0.298 0.159 0.141 0.494 0.439 347 169 166 9330010.01 Vancouver 1137 44195 0.309 0.281 0.157 0.143 0.466 0.424 288 153 150 9330010.02 Vancouver 1403 50803 0.331 0.347 0.148 0.155 0.479 0.502 319 278 275 9330011.00 Vancouver 1001 44512 0.270 0.248 0.144 0.132 0.414 0.380 176 74 71 9330012.00 Vancouver 1129 48687 0.278 0.279 0.130 0.130 0.408 0.409 155 122 119 9330013.01 Vancouver 950 44763 0.255 0.235 0.148 0.136 0.403 0.371 137 68 65 9330013.02 Vancouver 954 45381 0.252 0.236 0.159 0.149 0.412 0.385 170 87 84 9330014.01 Vancouver 852 43455 0.235 0.211 0.146 0.131 0.381 0.342 80 37 34 9330014.02 Vancouver 853 36657 0.279 0.211 0.185 0.140 0.465 0.351 285 46 43 9330015.01 Vancouver 1036 56317 0.221 0.256 0.125 0.145 0.346 0.401 25 109 106 9330015.02 Vancouver 1041 42813 0.292 0.258 0.161 0.142 0.453 0.400 266 105 102 9330016.01 Vancouver 891 39531 0.270 0.220 0.161 0.131 0.431 0.351 218 47 44 9330016.03 Vancouver 983 35811 0.330 0.243 0.152 0.112 0.482 0.355 321 54 51

39

9330016.04 Vancouver 970 45031 0.258 0.240 0.133 0.123 0.391 0.363 99 60 57 9330017.01 Vancouver 973 45621 0.256 0.241 0.150 0.141 0.406 0.382 151 84 81 9330017.02 Vancouver 1018 45266 0.270 0.252 0.138 0.128 0.407 0.380 154 75 72 9330018.01 Vancouver 1006 46427 0.260 0.249 0.138 0.132 0.398 0.381 124 80 77 9330018.02 Vancouver 1086 51756 0.252 0.269 0.137 0.146 0.389 0.415 95 133 130 9330019.00 Vancouver 995 45687 0.261 0.246 0.133 0.125 0.394 0.371 110 66 63 9330020.00 Vancouver 1298 54503 0.286 0.321 0.129 0.145 0.415 0.466 177 219 216 9330021.00 Vancouver 1840 117164 0.188 0.455 0.068 0.163 0.256 0.618 1 390 387 9330022.00 Vancouver 1163 39204 0.356 0.288 0.189 0.153 0.545 0.440 378 171 168 9330023.00 Vancouver 1509 69459 0.261 0.373 0.111 0.158 0.371 0.532 59 329 326 9330024.00 Vancouver 1420 78958 0.216 0.351 0.101 0.164 0.316 0.515 6 294 291 9330025.00 Vancouver 1465 68804 0.255 0.362 0.101 0.143 0.356 0.505 30 283 280 9330026.00 Vancouver 1326 57661 0.276 0.328 0.127 0.151 0.403 0.478 138 238 235 9330027.00 Vancouver 1312 53549 0.294 0.324 0.142 0.157 0.436 0.482 235 246 243 9330028.00 Vancouver 1709 62935 0.326 0.423 0.111 0.144 0.437 0.566 238 357 354 9330029.00 Vancouver 1267 52636 0.289 0.313 0.098 0.107 0.387 0.420 93 142 139 9330030.00 Vancouver 1144 51592 0.266 0.283 0.118 0.126 0.385 0.409 87 120 117 9330031.01 Vancouver 1191 52989 0.270 0.294 0.111 0.121 0.380 0.415 77 135 132 9330031.02 Vancouver 1118 47087 0.285 0.277 0.114 0.111 0.399 0.387 129 89 86 9330032.00 Vancouver 987 43774 0.271 0.244 0.128 0.115 0.398 0.359 126 57 54 9330033.00 Vancouver 1061 44547 0.286 0.262 0.141 0.130 0.427 0.392 209 95 92 9330034.01 Vancouver 955 45079 0.254 0.236 0.146 0.135 0.400 0.372 132 69 66 9330034.02 Vancouver 1005 45562 0.265 0.248 0.126 0.119 0.391 0.367 100 62 59 9330035.01 Vancouver 964 40648 0.284 0.238 0.153 0.128 0.437 0.366 240 61 58 9330035.02 Vancouver 916 43444 0.253 0.226 0.138 0.124 0.391 0.350 102 43 40 9330036.01 Vancouver 986 49333 0.240 0.244 0.134 0.136 0.374 0.380 67 76 73 9330036.02 Vancouver 1131 55500 0.244 0.280 0.135 0.154 0.379 0.434 72 163 160 9330037.01 Vancouver 1055 38846 0.326 0.261 0.143 0.114 0.468 0.375 293 72 69 9330037.02 Vancouver 938 31222 0.361 0.232 0.151 0.097 0.512 0.329 362 30 27 9330038.00 Vancouver 913 32750 0.335 0.226 0.139 0.094 0.474 0.320 300 24 21 9330039.01 Vancouver 1027 37210 0.331 0.254 0.127 0.097 0.458 0.351 275 50 47 9330039.02 Vancouver 1089 48189 0.271 0.269 0.102 0.101 0.373 0.370 64 65 62 9330040.01 Vancouver 901 37855 0.285 0.223 0.116 0.090 0.401 0.313 135 21 18 9330040.02 Vancouver 907 38323 0.284 0.224 0.133 0.105 0.417 0.329 181 29 26

40

9330041.01 Vancouver 1006 43853 0.275 0.249 0.108 0.097 0.383 0.346 84 40 37 9330041.02 Vancouver 1297 50791 0.306 0.321 0.120 0.125 0.426 0.446 203 183 180 9330042.00 Vancouver 1375 53898 0.306 0.340 0.104 0.115 0.410 0.455 164 197 194 9330043.01 Vancouver 1277 54382 0.282 0.316 0.108 0.121 0.390 0.437 97 167 164 9330043.02 Vancouver 1532 75806 0.243 0.379 0.094 0.146 0.336 0.525 16 314 311 9330044.00 Vancouver 1265 62038 0.245 0.313 0.100 0.128 0.345 0.441 24 175 172 9330045.01 Vancouver 1518 53373 0.341 0.375 0.102 0.113 0.444 0.488 249 256 253 9330045.02 Vancouver 1266 50950 0.298 0.313 0.102 0.107 0.400 0.420 133 143 140 9330046.00 Vancouver 1024 41064 0.299 0.253 0.111 0.094 0.410 0.347 163 41 38 9330047.01 Vancouver 991 42636 0.279 0.245 0.131 0.115 0.409 0.360 162 58 55 9330047.02 Vancouver 995 42528 0.281 0.246 0.126 0.110 0.406 0.356 149 55 52 9330048.00 Vancouver 1110 43049 0.309 0.274 0.127 0.113 0.437 0.387 237 88 85 9330049.01 Vancouver 1219 54667 0.267 0.301 0.104 0.117 0.371 0.418 60 140 137 9330049.02 Vancouver 1108 48295 0.275 0.274 0.116 0.115 0.391 0.390 103 91 88 9330050.02 Vancouver 767 28658 0.321 0.190 0.144 0.085 0.465 0.274 284 9 6 9330050.03 Vancouver 806 32236 0.300 0.199 0.149 0.099 0.449 0.298 257 14 11 9330050.04 Vancouver 711 28282 0.302 0.176 0.146 0.085 0.448 0.261 255 4 1 9330051.00 Vancouver 992 44519 0.267 0.245 0.137 0.126 0.405 0.371 144 67 64 9330052.01 Vancouver 960 38659 0.298 0.237 0.156 0.124 0.453 0.361 267 59 56 9330052.02 Vancouver 953 50258 0.228 0.236 0.140 0.145 0.367 0.380 51 78 75 9330053.01 Vancouver 1028 48787 0.253 0.254 0.137 0.138 0.390 0.392 96 94 91 9330053.02 Vancouver 1014 44141 0.276 0.251 0.154 0.140 0.429 0.391 214 93 90 9330054.01 Vancouver 1059 47060 0.270 0.262 0.111 0.107 0.381 0.369 78 64 61 9330054.02 Vancouver 1000 51637 0.232 0.247 0.133 0.141 0.365 0.389 48 90 87 9330055.01 Vancouver 820 31207 0.315 0.203 0.175 0.113 0.490 0.315 339 22 19 9330055.02 Vancouver 825 32552 0.304 0.204 0.171 0.115 0.475 0.319 307 23 20 9330056.01 Vancouver 708 28076 0.303 0.175 0.169 0.098 0.472 0.273 298 7 4 9330056.02 Vancouver 916 35127 0.313 0.226 0.140 0.101 0.453 0.328 265 28 25 9330057.01 Vancouver 537 16215 0.398 0.133 0.176 0.059 0.574 0.192 397 3 9330057.02 Vancouver 735 23987 0.367 0.182 0.185 0.091 0.552 0.273 386 8 5 9330058.00 Vancouver 437 11350 0.462 0.108 0.221 0.052 0.683 0.160 403 1 9330059.03 Vancouver 1539 55715 0.331 0.381 0.105 0.121 0.437 0.501 236 277 274 9330059.04 Vancouver 1101 34175 0.386 0.272 0.104 0.074 0.491 0.346 341 39 36 9330059.05 Vancouver 1314 45241 0.348 0.325 0.095 0.089 0.443 0.413 248 131 128

41

9330059.06 Vancouver 538 11904 0.542 0.133 0.209 0.051 0.751 0.184 406 2 9330060.01 Vancouver 949 35953 0.317 0.235 0.090 0.066 0.406 0.301 150 15 12 9330060.02 Vancouver 955 31468 0.364 0.236 0.112 0.073 0.476 0.309 308 19 16 9330061.00 Vancouver 917 34981 0.315 0.227 0.093 0.067 0.408 0.294 156 12 9 9330062.00 Vancouver 941 38399 0.294 0.233 0.092 0.073 0.386 0.305 89 16 13 9330063.00 Vancouver 891 34145 0.313 0.220 0.107 0.075 0.420 0.295 191 13 10 9330064.00 Vancouver 866 30528 0.340 0.214 0.079 0.050 0.419 0.264 189 5 2 9330065.00 Vancouver 922 32207 0.343 0.228 0.088 0.059 0.432 0.286 220 10 7 9330066.00 Vancouver 1358 46832 0.348 0.336 0.076 0.073 0.424 0.409 198 121 118 9330067.00 Vancouver 1111 35441 0.376 0.275 0.104 0.076 0.480 0.351 320 44 41 9330068.00 Vancouver 962 35741 0.323 0.238 0.094 0.069 0.417 0.307 180 18 15 9330069.00 Vancouver 1211 33406 0.435 0.300 0.119 0.082 0.554 0.382 388 83 80 9330100.01 North Shore 1174 51514 0.273 0.290 0.144 0.153 0.418 0.443 183 176 173 9330100.02 North Shore 1145 48488 0.283 0.283 0.164 0.164 0.447 0.447 253 186 183 9330101.02 North Shore 1036 39746 0.313 0.256 0.184 0.151 0.497 0.407 352 116 113 9330101.03 North Shore 926 38135 0.291 0.229 0.176 0.138 0.467 0.367 290 63 60 9330101.04 North Shore 1024 35179 0.349 0.253 0.201 0.146 0.550 0.399 382 102 99 9330102.00 North Shore 1217 49546 0.295 0.301 0.157 0.160 0.451 0.461 262 207 204 9330103.00 North Shore 1045 39100 0.321 0.258 0.195 0.157 0.516 0.416 366 137 134 9330104.00 North Shore 1331 55060 0.290 0.329 0.153 0.174 0.443 0.503 247 279 276 9330110.01 North Shore 1457 75787 0.231 0.360 0.132 0.207 0.363 0.567 46 358 355 9330110.02 North Shore 1515 75507 0.241 0.375 0.140 0.217 0.380 0.592 73 375 372 9330111.01 North Shore 1328 60378 0.264 0.328 0.159 0.198 0.423 0.526 195 318 315 9330111.02 North Shore 1427 71567 0.239 0.353 0.137 0.202 0.376 0.555 70 348 345 9330111.03 North Shore 1354 57931 0.281 0.335 0.151 0.181 0.432 0.516 224 297 294 9330112.00 North Shore 1219 52580 0.278 0.301 0.169 0.183 0.447 0.484 252 250 247 9330113.00 North Shore 1161 53682 0.260 0.287 0.164 0.182 0.424 0.469 199 224 221 9330114.00 North Shore 1489 74106 0.241 0.368 0.125 0.191 0.366 0.560 50 352 349 9330115.00 North Shore 1330 57534 0.277 0.329 0.151 0.179 0.428 0.508 212 285 282 9330116.00 North Shore 1420 73455 0.232 0.351 0.127 0.192 0.359 0.543 35 337 334 9330117.00 North Shore 1474 77291 0.229 0.364 0.123 0.196 0.352 0.560 27 353 350 9330118.00 North Shore 1142 47021 0.291 0.282 0.177 0.171 0.468 0.454 292 193 190 9330119.00 North Shore 1236 63049 0.235 0.306 0.138 0.179 0.373 0.485 65 252 249 9330120.00 North Shore 1637 75150 0.261 0.405 0.133 0.205 0.394 0.610 109 387 384

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9330121.00 North Shore 1582 77744 0.244 0.391 0.124 0.199 0.368 0.590 53 372 369 9330122.00 North Shore 1663 81392 0.245 0.411 0.120 0.201 0.365 0.612 47 388 385 9330130.01 North Shore 1187 40090 0.355 0.294 0.208 0.172 0.563 0.465 393 216 213 9330130.03 North Shore 1073 37892 0.340 0.265 0.190 0.148 0.529 0.413 375 130 127 9330130.04 North Shore 0 27047 0.000 0.000 0.216 0.120 0.216 0.120 9330131.00 North Shore 1500 74247 0.242 0.371 0.119 0.181 0.361 0.552 38 346 343 9330132.00 North Shore 1806 92276 0.235 0.447 0.107 0.204 0.342 0.651 21 403 400 9330133.01 North Shore 1608 76215 0.253 0.398 0.126 0.198 0.379 0.596 71 381 378 9330133.02 North Shore 1804 97029 0.223 0.446 0.102 0.203 0.325 0.649 10 402 399 9330134.00 North Shore 1750 73063 0.287 0.433 0.128 0.193 0.416 0.626 178 394 391 9330135.00 North Shore 1801 85567 0.253 0.445 0.110 0.193 0.362 0.638 41 397 394 9330140.02 Richmond 1160 61718 0.226 0.287 0.146 0.186 0.372 0.473 62 230 227 9330140.03 Richmond 1024 49286 0.249 0.253 0.167 0.170 0.416 0.423 179 150 147 9330140.04 Richmond 1343 62604 0.257 0.332 0.141 0.182 0.398 0.514 127 292 289 9330141.00 Richmond 1146 55593 0.247 0.283 0.146 0.167 0.393 0.451 108 189 186 9330142.01 Richmond 1114 64873 0.206 0.276 0.131 0.175 0.337 0.450 17 188 185 9330142.02 Richmond 1127 66127 0.205 0.279 0.134 0.182 0.338 0.461 19 208 205 9330142.03 Richmond 1012 47115 0.258 0.250 0.166 0.161 0.424 0.411 196 124 121 9330143.01 Richmond 1129 60557 0.224 0.279 0.146 0.183 0.370 0.462 56 209 206 9330143.02 Richmond 963 41672 0.277 0.238 0.204 0.176 0.482 0.414 322 132 129 9330143.03 Richmond 1106 44661 0.297 0.274 0.187 0.172 0.484 0.445 326 181 178 9330143.04 Richmond 1147 56032 0.246 0.284 0.154 0.178 0.400 0.462 131 210 207 9330144.03 Richmond 1373 58617 0.281 0.339 0.146 0.176 0.427 0.515 206 295 292 9330144.04 Richmond 1045 43635 0.287 0.258 0.182 0.164 0.470 0.422 295 149 146 9330144.05 Richmond 1003 48691 0.247 0.248 0.176 0.177 0.424 0.425 197 154 151 9330144.06 Richmond 1219 59208 0.247 0.301 0.149 0.181 0.396 0.483 115 248 245 9330145.00 Richmond 1164 53489 0.261 0.288 0.159 0.176 0.420 0.463 192 212 209 9330146.00 Richmond 1153 56335 0.246 0.285 0.154 0.179 0.400 0.464 130 213 210 9330147.01 Richmond 1177 39579 0.357 0.291 0.206 0.168 0.563 0.459 395 204 201 9330147.04 Richmond 928 38843 0.287 0.229 0.200 0.160 0.487 0.390 333 92 89 9330147.05 Richmond 1024 36235 0.339 0.253 0.204 0.152 0.543 0.405 377 114 111 9330147.06 Richmond 925 38962 0.285 0.229 0.194 0.155 0.479 0.384 316 85 82 9330147.07 Richmond 814 25881 0.377 0.201 0.243 0.130 0.620 0.331 401 32 29 9330147.08 Richmond 866 35939 0.289 0.214 0.185 0.137 0.474 0.351 303 48 45

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9330148.00 Richmond 841 30386 0.332 0.208 0.228 0.143 0.560 0.351 391 45 42 9330149.02 Richmond 1179 56337 0.251 0.291 0.155 0.180 0.406 0.471 147 227 224 9330149.03 Richmond 1248 54565 0.274 0.309 0.155 0.175 0.430 0.483 215 249 246 9330149.04 Richmond 1019 49043 0.249 0.252 0.159 0.161 0.409 0.413 158 129 126 9330149.05 Richmond 1269 41891 0.364 0.314 0.199 0.172 0.563 0.486 392 254 251 9330150.00 Richmond 1116 71725 0.187 0.276 0.121 0.179 0.308 0.455 5 196 193 9330151.01 Richmond 1156 43330 0.320 0.286 0.190 0.169 0.510 0.455 360 195 192 9330151.03 Richmond 1252 51214 0.293 0.310 0.160 0.169 0.453 0.479 268 240 237 9330151.05 Richmond 1111 49874 0.267 0.275 0.161 0.165 0.428 0.440 211 172 169 9330151.06 Richmond 1171 47625 0.295 0.290 0.181 0.178 0.477 0.468 309 222 219 9330160.01 Delta 1292 82163 0.189 0.320 0.114 0.193 0.303 0.513 4 290 287 9330160.02 Delta 1166 58465 0.239 0.288 0.156 0.188 0.395 0.476 112 235 232 9330160.03 Delta 1177 64568 0.219 0.291 0.134 0.179 0.353 0.470 28 226 223 9330160.04 Delta 1081 49937 0.260 0.267 0.171 0.176 0.431 0.444 219 177 174 9330161.01 Delta 1224 60197 0.244 0.303 0.154 0.191 0.398 0.493 121 264 261 9330161.02 Delta 1078 53053 0.244 0.267 0.159 0.174 0.403 0.440 139 173 170 9330161.03 Delta 1138 62327 0.219 0.281 0.142 0.183 0.361 0.464 40 214 211 9330161.05 Delta 1157 61603 0.225 0.286 0.141 0.179 0.366 0.465 49 215 212 9330161.06 Delta 1111 64880 0.206 0.275 0.138 0.185 0.344 0.460 22 205 202 9330162.01 Delta 1162 69620 0.200 0.287 0.125 0.180 0.326 0.467 11 220 217 9330162.02 Delta 1177 68680 0.206 0.291 0.130 0.184 0.336 0.475 15 233 230 9330162.03 Delta 1113 48804 0.274 0.275 0.165 0.166 0.439 0.441 241 174 171 9330162.04 Delta 1236 82252 0.180 0.306 0.111 0.188 0.291 0.494 2 265 262 9330163.01 Delta 1235 73641 0.201 0.305 0.122 0.185 0.323 0.490 9 258 255 9330163.04 Delta 1176 68865 0.205 0.291 0.132 0.187 0.337 0.478 18 237 234 9330163.05 Delta 1096 55362 0.238 0.271 0.143 0.163 0.380 0.434 75 162 159 9330163.06 Delta 1048 53704 0.234 0.259 0.170 0.188 0.404 0.447 142 185 182 9330163.07 Delta 1018 56737 0.215 0.252 0.140 0.164 0.356 0.416 29 136 133 9330163.08 Delta 1182 61527 0.231 0.292 0.140 0.177 0.370 0.470 58 225 222 9330170.03 White Rock 752 33491 0.269 0.186 0.284 0.196 0.553 0.382 387 81 78 9330170.04 White Rock 1316 53739 0.294 0.325 0.215 0.238 0.509 0.564 358 356 353 9330170.05 White Rock 775 34753 0.268 0.192 0.291 0.208 0.559 0.400 390 106 103 9330170.06 White Rock 1243 51887 0.287 0.307 0.219 0.234 0.506 0.541 356 334 331 9330180.01 Surrey 1749 95676 0.219 0.433 0.125 0.246 0.344 0.679 23 406 403

44

9330180.02 Surrey 1130 62334 0.218 0.280 0.193 0.247 0.410 0.527 167 321 318 9330181.01 Surrey 901 49013 0.221 0.223 0.215 0.217 0.435 0.440 232 170 167 9330181.03 Surrey 1365 72612 0.226 0.338 0.162 0.242 0.387 0.579 92 366 363 9330181.04 Surrey 1260 62651 0.241 0.312 0.186 0.240 0.427 0.551 208 345 342 9330181.05 Surrey 1064 44885 0.284 0.263 0.237 0.220 0.522 0.483 372 247 244 9330181.06 Surrey 969 50950 0.228 0.240 0.225 0.237 0.454 0.476 269 236 233 9330181.07 Surrey 1250 73229 0.205 0.309 0.158 0.238 0.362 0.547 42 341 338 9330181.08 Surrey 1174 69855 0.202 0.290 0.167 0.240 0.369 0.531 55 328 325 9330181.09 Surrey 1246 73870 0.202 0.308 0.158 0.240 0.360 0.548 37 342 339 9330182.01 Surrey 1456 73911 0.236 0.360 0.161 0.245 0.397 0.605 120 385 382 9330182.02 Surrey 1692 73806 0.275 0.418 0.164 0.249 0.439 0.668 243 405 402 9330182.03 Surrey 1392 69400 0.241 0.344 0.165 0.236 0.406 0.581 146 368 365 9330182.04 Surrey 1560 79799 0.235 0.386 0.148 0.243 0.382 0.628 82 395 392 9330182.05 Surrey 1450 70195 0.248 0.358 0.162 0.234 0.410 0.593 165 378 375 9330182.06 Surrey 1214 61741 0.236 0.300 0.199 0.253 0.435 0.553 230 347 344 9330183.01 Surrey 1232 62703 0.236 0.305 0.187 0.241 0.422 0.546 194 339 336 9330183.03 Surrey 1043 45385 0.276 0.258 0.245 0.229 0.520 0.487 371 255 252 9330183.04 Surrey 1550 64772 0.287 0.383 0.187 0.250 0.475 0.634 305 396 393 9330183.05 Surrey 1494 68102 0.263 0.369 0.168 0.235 0.431 0.605 217 386 383 9330183.06 Surrey 1081 48747 0.266 0.267 0.224 0.225 0.490 0.493 340 263 260 9330183.07 Surrey 1198 71672 0.201 0.296 0.168 0.248 0.369 0.544 54 338 335 9330184.01 Surrey 1443 66496 0.260 0.357 0.174 0.238 0.434 0.595 228 380 377 9330184.02 Surrey 863 43647 0.237 0.213 0.234 0.211 0.471 0.424 297 152 149 9330184.05 Surrey 1267 61615 0.247 0.313 0.180 0.228 0.427 0.542 207 335 332 9330184.06 Surrey 1479 60893 0.291 0.366 0.187 0.235 0.479 0.601 317 383 380 9330184.07 Surrey 968 47631 0.244 0.239 0.216 0.212 0.459 0.451 277 190 187 9330184.08 Surrey 1248 56132 0.267 0.309 0.191 0.221 0.458 0.530 274 325 322 9330184.09 Surrey 1213 66318 0.219 0.300 0.163 0.223 0.383 0.523 83 311 308 9330184.10 Surrey 1337 57630 0.278 0.331 0.201 0.238 0.479 0.569 318 360 357 9330184.11 Surrey 1615 67620 0.287 0.399 0.174 0.243 0.461 0.642 280 400 397 9330185.05 Surrey 1005 43727 0.276 0.249 0.227 0.204 0.503 0.453 354 192 189 9330185.06 Surrey 1303 66461 0.235 0.322 0.174 0.238 0.409 0.561 161 354 351 9330185.07 Surrey 1265 61440 0.247 0.313 0.182 0.230 0.429 0.543 213 336 333 9330185.08 Surrey 1571 80534 0.234 0.389 0.141 0.234 0.375 0.623 69 392 389

45

9330185.09 Surrey 1022 43609 0.281 0.253 0.230 0.206 0.511 0.459 361 203 200 9330185.10 Surrey 1150 49114 0.281 0.284 0.193 0.195 0.474 0.480 301 244 241 9330185.11 Surrey 1022 45306 0.271 0.253 0.220 0.206 0.491 0.459 342 202 199 9330185.12 Surrey 1245 61288 0.244 0.308 0.169 0.214 0.413 0.522 174 310 307 9330185.13 Surrey 1249 52466 0.286 0.309 0.200 0.217 0.486 0.525 331 315 312 9330185.14 Surrey 1035 46522 0.267 0.256 0.211 0.202 0.478 0.458 315 200 197 9330185.15 Surrey 1094 47893 0.274 0.271 0.211 0.208 0.485 0.478 328 239 236 9330185.16 Surrey 1165 49698 0.281 0.288 0.205 0.210 0.487 0.498 332 273 270 9330186.01 Surrey 1214 53560 0.272 0.300 0.197 0.217 0.469 0.518 294 301 298 9330186.02 Surrey 1012 45821 0.265 0.250 0.213 0.201 0.478 0.451 312 191 188 9330186.05 Surrey 994 48533 0.246 0.246 0.212 0.212 0.457 0.458 273 199 196 9330186.06 Surrey 1136 49341 0.276 0.281 0.207 0.210 0.483 0.491 324 260 257 9330186.07 Surrey 1143 55889 0.246 0.283 0.188 0.217 0.434 0.500 226 275 272 9330186.08 Surrey 1144 48720 0.282 0.283 0.196 0.197 0.478 0.480 313 243 240 9330187.03 Surrey 1209 56505 0.257 0.299 0.187 0.218 0.444 0.517 250 299 296 9330187.04 Surrey 1174 45565 0.309 0.290 0.196 0.184 0.505 0.475 355 231 228 9330187.05 Surrey 1137 50826 0.268 0.281 0.205 0.214 0.473 0.495 299 270 267 9330187.06 Surrey 1202 55260 0.261 0.297 0.196 0.223 0.457 0.520 272 306 303 9330187.07 Surrey 1566 75077 0.250 0.387 0.162 0.251 0.413 0.639 173 398 395 9330187.09 Surrey 1223 56099 0.262 0.302 0.187 0.217 0.449 0.519 256 305 302 9330187.10 Surrey 1213 53465 0.272 0.300 0.206 0.227 0.478 0.527 314 319 316 9330187.11 Surrey 1221 52116 0.281 0.302 0.213 0.229 0.494 0.530 348 327 324 9330188.01 Surrey 1413 56625 0.299 0.349 0.210 0.245 0.509 0.594 359 379 376 9330188.02 Surrey 1562 60615 0.309 0.386 0.174 0.218 0.483 0.604 325 384 381 9330188.03 Surrey 1450 71766 0.242 0.358 0.164 0.242 0.406 0.601 148 382 379 9330188.04 Surrey 1419 66945 0.254 0.351 0.170 0.235 0.424 0.586 200 371 368 9330188.05 Surrey 1294 73368 0.212 0.320 0.161 0.243 0.372 0.563 63 355 352 9330188.06 Surrey 1267 70898 0.214 0.313 0.156 0.227 0.370 0.541 57 333 330 9330189.03 Surrey 1086 54288 0.240 0.269 0.194 0.217 0.434 0.485 227 253 250 9330189.05 Surrey 883 37142 0.285 0.218 0.266 0.203 0.551 0.421 383 146 143 9330189.06 Surrey 952 45121 0.253 0.235 0.210 0.195 0.463 0.430 283 158 155 9330189.07 Surrey 1092 45552 0.288 0.270 0.198 0.186 0.486 0.456 330 198 195 9330189.08 Surrey 773 31155 0.298 0.191 0.251 0.161 0.549 0.352 380 51 48 9330189.09 Surrey 1189 53573 0.266 0.294 0.194 0.214 0.460 0.508 278 286 283

46

9330189.10 Surrey 1088 49772 0.262 0.269 0.194 0.198 0.456 0.468 270 221 218 9330190.01 Surrey 868 38235 0.273 0.215 0.215 0.170 0.488 0.384 335 86 83 9330190.03 Surrey 947 40769 0.279 0.234 0.207 0.174 0.485 0.408 329 118 115 9330190.04 Surrey 1089 50211 0.260 0.269 0.214 0.221 0.474 0.491 302 259 256 9330190.05 Surrey 886 41905 0.254 0.219 0.234 0.202 0.488 0.421 334 145 142 9330191.02 Surrey 925 35512 0.313 0.229 0.251 0.184 0.564 0.412 396 127 124 9330191.03 Surrey 1155 53219 0.260 0.286 0.190 0.208 0.450 0.494 260 266 263 9330191.04 Surrey 851 34805 0.293 0.210 0.256 0.184 0.549 0.394 381 96 93 9330192.00 Surrey 1049 44813 0.281 0.259 0.226 0.209 0.507 0.468 357 223 220 9330200.00 New West 1339 58200 0.276 0.331 0.137 0.165 0.413 0.496 175 271 268 9330201.00 New West 1272 60022 0.254 0.314 0.127 0.157 0.381 0.472 79 228 225 9330202.00 New West 973 46147 0.253 0.241 0.146 0.138 0.399 0.379 128 73 70 9330203.00 New West 1179 59716 0.237 0.291 0.124 0.153 0.361 0.444 39 179 176 9330204.01 New West 845 37131 0.273 0.209 0.162 0.124 0.436 0.333 234 33 30 9330204.02 New West 869 34428 0.303 0.215 0.191 0.135 0.494 0.350 345 42 39 9330205.01 New West 815 31445 0.311 0.201 0.208 0.135 0.519 0.336 368 35 32 9330205.02 New West 753 32708 0.276 0.186 0.213 0.144 0.490 0.330 338 31 28 9330206.00 New West 898 40436 0.266 0.222 0.125 0.104 0.392 0.326 104 26 23 9330207.00 New West 840 38758 0.260 0.208 0.157 0.126 0.417 0.333 182 34 31 9330208.00 New West 1085 48598 0.268 0.268 0.154 0.154 0.422 0.422 193 148 145 9330209.00 New West 1115 57462 0.233 0.276 0.135 0.160 0.368 0.436 52 165 162 9330210.00 New West 975 43490 0.269 0.241 0.157 0.141 0.426 0.382 201 82 79 9330220.00 Burnaby 1206 49553 0.292 0.298 0.161 0.164 0.453 0.462 264 211 208 9330221.01 Burnaby 980 66564 0.177 0.242 0.124 0.169 0.300 0.412 3 126 123 9330221.03 Burnaby 1115 66694 0.201 0.276 0.126 0.173 0.327 0.449 12 187 184 9330221.04 Burnaby 1020 52460 0.233 0.252 0.141 0.152 0.374 0.404 68 112 109 9330222.01 Burnaby 1068 48303 0.265 0.264 0.145 0.144 0.410 0.408 166 119 116 9330222.02 Burnaby 1063 48989 0.260 0.263 0.137 0.139 0.398 0.402 123 110 107 9330223.01 Burnaby 1051 47172 0.267 0.260 0.144 0.140 0.411 0.400 169 104 101 9330223.02 Burnaby 982 37760 0.312 0.243 0.176 0.137 0.488 0.380 337 77 74 9330224.01 Burnaby 909 30794 0.354 0.225 0.202 0.128 0.556 0.353 389 52 49 9330224.02 Burnaby 758 27807 0.327 0.188 0.272 0.156 0.600 0.344 399 38 35 9330225.01 Burnaby 1067 50392 0.254 0.264 0.149 0.155 0.403 0.419 141 141 138 9330225.02 Burnaby 975 40236 0.291 0.241 0.161 0.134 0.452 0.375 263 71 68

47

9330226.02 Burnaby 1042 50871 0.246 0.258 0.134 0.141 0.380 0.399 74 101 98 9330226.03 Burnaby 851 30587 0.334 0.210 0.180 0.114 0.514 0.324 364 25 22 9330226.04 Burnaby 744 32081 0.278 0.184 0.166 0.109 0.444 0.293 251 11 8 9330227.01 Burnaby 752 27066 0.333 0.186 0.151 0.084 0.485 0.270 327 6 3 9330227.02 Burnaby 748 34603 0.259 0.185 0.171 0.122 0.430 0.307 216 17 14 9330228.02 Burnaby 1043 55968 0.224 0.258 0.133 0.154 0.357 0.412 31 125 122 9330228.03 Burnaby 889 32266 0.330 0.220 0.162 0.108 0.492 0.327 344 27 24 9330228.04 Burnaby 844 36629 0.277 0.209 0.173 0.130 0.449 0.339 258 36 33 9330229.00 Burnaby 967 49241 0.236 0.239 0.155 0.158 0.391 0.397 101 99 96 9330230.01 Burnaby 1084 65797 0.198 0.268 0.123 0.167 0.321 0.435 8 164 161 9330230.02 Burnaby 996 40909 0.292 0.246 0.182 0.154 0.475 0.400 304 107 104 9330231.00 Burnaby 1267 57449 0.265 0.313 0.153 0.181 0.418 0.495 184 269 266 9330232.00 Burnaby 1192 66408 0.215 0.295 0.132 0.180 0.347 0.475 26 232 229 9330233.00 Burnaby 1122 52734 0.255 0.278 0.143 0.155 0.398 0.432 122 160 157 9330234.00 Burnaby 1216 63052 0.231 0.301 0.127 0.165 0.359 0.466 34 218 215 9330235.02 Burnaby 1089 51865 0.252 0.269 0.145 0.155 0.397 0.424 119 151 148 9330235.03 Burnaby 832 33103 0.302 0.206 0.217 0.148 0.518 0.354 367 53 50 9330235.04 Burnaby 936 37644 0.298 0.232 0.164 0.127 0.463 0.359 282 56 53 9330236.00 Burnaby 1343 78485 0.205 0.332 0.114 0.185 0.320 0.517 7 300 297 9330237.00 Burnaby 969 43436 0.268 0.240 0.180 0.161 0.448 0.401 254 108 105 9330238.01 Burnaby 1149 53630 0.257 0.284 0.134 0.148 0.391 0.432 98 159 156 9330238.02 Burnaby 1021 50427 0.243 0.253 0.152 0.158 0.395 0.410 111 123 120 9330239.00 Burnaby 992 48706 0.245 0.245 0.160 0.160 0.404 0.406 143 115 112 9330240.01 Burnaby 1150 45797 0.301 0.284 0.160 0.151 0.462 0.436 281 166 163 9330240.02 Burnaby 973 45334 0.258 0.241 0.174 0.163 0.432 0.403 222 111 108 9330241.00 Burnaby 1043 47824 0.262 0.258 0.157 0.155 0.419 0.412 186 128 125 9330242.00 Burnaby 1068 49571 0.259 0.264 0.160 0.164 0.419 0.428 187 155 152 9330243.01 Burnaby 1029 49222 0.251 0.254 0.158 0.160 0.409 0.415 159 134 131 9330243.02 Burnaby 1123 52665 0.256 0.278 0.132 0.143 0.388 0.421 94 144 141 9330250.01 Remote 1259 60918 0.248 0.311 0.161 0.202 0.409 0.513 160 291 288 9330250.02 Remote 1567 84220 0.223 0.388 0.136 0.236 0.359 0.623 36 393 390 9330260.02 Port Moody 1218 51909 0.282 0.301 0.194 0.207 0.475 0.508 306 288 285 9330260.04 Port Moody 1221 60483 0.242 0.302 0.176 0.219 0.418 0.521 185 308 305 9330260.05 Port Moody 1051 57991 0.218 0.260 0.178 0.212 0.395 0.472 113 229 226

48

9330260.06 Port Moody 1425 82202 0.208 0.352 0.132 0.223 0.340 0.576 20 364 361 9330260.07 Port Moody 1214 59818 0.244 0.300 0.165 0.203 0.408 0.504 157 280 277 9330260.08 Port Moody 1705 76471 0.268 0.422 0.139 0.220 0.407 0.642 152 399 396 9330280.00 Coquitlam 1122 72704 0.185 0.277 0.148 0.222 0.334 0.500 14 276 273 9330281.01 Coquitlam 1234 67724 0.219 0.305 0.166 0.231 0.384 0.536 85 332 329 9330281.02 Coquitlam 1082 51529 0.252 0.268 0.213 0.226 0.465 0.494 287 267 264 9330282.00 Coquitlam 1009 44975 0.269 0.250 0.225 0.209 0.495 0.458 350 201 198 9330283.00 Coquitlam 952 39968 0.286 0.235 0.240 0.197 0.526 0.433 374 161 158 9330284.01 Coquitlam 974 41328 0.283 0.241 0.212 0.181 0.495 0.421 351 147 144 9330284.02 Coquitlam 1072 49369 0.261 0.265 0.210 0.214 0.471 0.479 296 242 239 9330285.01 Coquitlam 783 30500 0.308 0.194 0.298 0.187 0.606 0.381 400 79 76 9330285.02 Coquitlam 1145 66972 0.205 0.283 0.168 0.232 0.374 0.516 66 296 293 9330286.01 Coquitlam 1166 63695 0.220 0.288 0.174 0.228 0.393 0.516 107 298 295 9330286.02 Coquitlam 1177 63456 0.223 0.291 0.159 0.208 0.382 0.499 81 274 271 9330286.03 Coquitlam 1211 71735 0.203 0.299 0.155 0.228 0.357 0.528 32 323 320 9330287.01 Coquitlam 1202 55277 0.261 0.297 0.181 0.207 0.442 0.504 245 282 279 9330287.02 Coquitlam 1345 71784 0.225 0.333 0.160 0.236 0.385 0.569 86 359 356 9330287.06 Coquitlam 1101 39162 0.338 0.272 0.240 0.193 0.577 0.466 398 217 214 9330287.08 Coquitlam 979 43850 0.268 0.242 0.227 0.205 0.495 0.447 349 184 181 9330287.09 Coquitlam 797 35096 0.273 0.197 0.273 0.198 0.546 0.395 379 98 95 9330287.10 Coquitlam 1689 70393 0.288 0.418 0.155 0.225 0.443 0.643 246 401 398 9330287.11 Coquitlam 1258 61707 0.245 0.311 0.163 0.207 0.407 0.518 153 304 301 9330287.12 Coquitlam 1497 55302 0.325 0.370 0.195 0.222 0.520 0.593 370 377 374 9330287.13 Coquitlam 1580 43397 0.437 0.391 0.255 0.228 0.692 0.618 404 391 388 9330287.14 Coquitlam 1707 63771 0.321 0.422 0.181 0.238 0.502 0.660 353 404 401 9330290.02 Port Coquitlam 956 39213 0.293 0.236 0.259 0.209 0.551 0.446 384 182 179 9330290.03 Port Coquitlam 1245 59376 0.252 0.308 0.184 0.225 0.436 0.533 233 331 328 9330290.04 Port Coquitlam 1360 77540 0.210 0.336 0.152 0.243 0.363 0.580 45 367 364 9330290.05 Port Coquitlam 1236 71176 0.208 0.306 0.150 0.219 0.358 0.525 33 313 310 9330291.01 Port Coquitlam 1023 46340 0.265 0.253 0.212 0.202 0.477 0.455 310 194 191 9330291.02 Port Coquitlam 1128 56627 0.239 0.279 0.187 0.219 0.426 0.498 205 272 269 9330292.01 Port Coquitlam 1181 69296 0.204 0.292 0.158 0.226 0.363 0.518 44 303 300 9330292.03 Port Coquitlam 1267 57178 0.266 0.313 0.184 0.216 0.449 0.530 259 326 323 9330292.04 Port Coquitlam 1252 60470 0.248 0.310 0.190 0.237 0.439 0.547 242 340 337

49

9330400.02 Maple Ridge 1159 55502 0.251 0.287 0.208 0.238 0.459 0.525 276 312 309 9330400.03 Maple Ridge 1441 66921 0.258 0.356 0.170 0.234 0.428 0.590 210 373 370 9330400.04 Maple Ridge 1516 64150 0.284 0.375 0.181 0.240 0.465 0.615 286 389 386 9330401.01 Maple Ridge 1025 44870 0.274 0.253 0.250 0.231 0.524 0.484 373 251 248 9330401.02 Maple Ridge 882 37050 0.286 0.218 0.278 0.212 0.563 0.430 394 156 153 9330402.01 Maple Ridge 1023 45224 0.271 0.253 0.242 0.226 0.514 0.479 363 241 238 9330402.02 Maple Ridge 1126 54227 0.249 0.278 0.211 0.236 0.460 0.514 279 293 290 9330403.01 Maple Ridge 1085 55951 0.233 0.268 0.193 0.223 0.426 0.491 202 261 258 9330403.03 Maple Ridge 1143 50992 0.269 0.283 0.214 0.225 0.483 0.507 323 284 281 9330403.04 Maple Ridge 1160 61258 0.227 0.287 0.175 0.221 0.402 0.508 136 287 284 9330403.05 Maple Ridge 1180 64566 0.219 0.292 0.177 0.236 0.397 0.528 116 322 319 9330404.01 Maple Ridge 1368 64927 0.253 0.338 0.182 0.244 0.435 0.582 231 369 366 9330404.02 Maple Ridge 1378 62027 0.267 0.341 0.184 0.235 0.450 0.576 261 363 360 9330410.02 Pitt Meadows 1025 50586 0.243 0.254 0.213 0.222 0.456 0.475 271 234 231 9330410.03 Pitt Meadows 1167 60372 0.232 0.289 0.187 0.233 0.419 0.522 188 309 306 9330410.04 Pitt Meadows 1000 57844 0.207 0.247 0.195 0.233 0.403 0.480 140 245 242 9330500.00 Langley 1049 50069 0.251 0.259 0.237 0.244 0.488 0.504 336 281 278 9330501.01 Langley 1026 50808 0.242 0.254 0.225 0.236 0.468 0.490 291 257 254 9330501.02 Langley 1192 68370 0.209 0.295 0.186 0.262 0.396 0.557 114 351 348 9330501.03 Langley 1112 64036 0.208 0.275 0.190 0.250 0.398 0.525 125 316 313 9330502.01 Langley 1150 65153 0.212 0.284 0.174 0.233 0.386 0.518 88 302 299 9330502.02 Langley 964 49983 0.231 0.238 0.246 0.253 0.477 0.492 311 262 259 9330502.03 Langley 1255 68911 0.218 0.310 0.168 0.239 0.386 0.549 91 343 340 9330502.05 Langley 1120 57278 0.235 0.277 0.207 0.244 0.441 0.521 244 307 304 9330502.06 Langley 1289 73549 0.210 0.319 0.152 0.231 0.362 0.549 43 344 341 9330502.07 Langley 1137 59828 0.228 0.281 0.198 0.245 0.426 0.526 204 317 314 9330503.01 Langley 1333 73160 0.219 0.330 0.162 0.244 0.380 0.573 76 361 358 9330503.03 Langley 1288 65561 0.236 0.319 0.176 0.238 0.412 0.556 171 349 346 9330503.06 Langley 911 39050 0.280 0.225 0.272 0.219 0.552 0.444 385 178 175 9330503.07 Langley 651 24313 0.321 0.161 0.380 0.190 0.701 0.351 405 49 46 9330503.08 Langley 939 40249 0.280 0.232 0.257 0.213 0.537 0.445 376 180 177 9330503.09 Langley 1097 38309 0.344 0.271 0.282 0.223 0.626 0.494 402 268 265 9330504.01 Langley 1423 58473 0.292 0.352 0.199 0.240 0.491 0.592 343 376 373 9330504.03 Langley 1366 68269 0.240 0.338 0.171 0.240 0.411 0.578 168 365 362

50

9330504.04 Langley 1179 59072 0.239 0.291 0.197 0.240 0.437 0.532 239 330 327 9330504.05 Langley 1320 64692 0.245 0.326 0.187 0.249 0.432 0.575 221 362 359 9330504.06 Langley 1161 62292 0.224 0.287 0.189 0.242 0.412 0.529 172 324 321 9330505.00 Langley 1406 65521 0.257 0.348 0.174 0.235 0.432 0.583 223 370 367 9330506.01 Langley 1147 49233 0.280 0.284 0.240 0.243 0.519 0.527 369 320 317 9330506.02 Langley 1098 48037 0.274 0.272 0.240 0.238 0.514 0.509 365 289 286

51

Appendix  B:  Linear  Regression  Analysis    1 Using linear regression model for Greater Vancouver

2 Using linear regression model for Vancouver

Census  Tract  

Municipality   Neighbourhood  Transport  Cost  (fraction  of  

monthly  income)  

Transportation  Cost  (%  of  

monthly  income)  

Walk  Score  

Predicted  Transportation  

Cost1  

Predicted  Transportation  

Cost2  

9330059.05   Vancouver   Downtown   0.088554802   8.855480229   96   13.65085   8.118991078  

9330063.00   Vancouver   West  End   0.075154288   7.515428786   94   13.87867   8.566060465  

9330057.02   Vancouver   Strathcona   0.091365043   9.136504325   93   13.99259   8.789595159  

9330046.00   Vancouver   Kitslano   0.093555206   9.355520557   89   14.44824   9.683733934  

9330041.01   Vancouver   Fairview   0.097412258   9.741225818   89   14.44824   9.683733934  

9330038.00   Vancouver   Mount  Pleasant   0.093783133   9.378313316   88   14.56216   9.907268627  

9330054.01   Vancouver  Grandview-­‐Woodland   0.1072838   10.72838001   86   14.78999   10.35433801  

9330030.00   Vancouver   Riley  Park   0.125966772   12.59667721   80   15.47347   11.69554618  

9330029.00   Vancouver   South  Cambie   0.106639825   10.66398247   77   15.81521   12.36615026  

9330033.00   Vancouver  Kensington-­‐Cedar  Cottage   0.12979033   12.979033   76   15.92913   12.58968495  

9330044.00   Vancouver   West  Point  Grey   0.128453916   12.84539162   74   16.15696   13.03675434  

9330005.00   Vancouver   Marpole   0.119112765   11.91127654   72   16.38479   13.48382373  

9330036.01   Vancouver  Renfrew-­‐Collingwood   0.136249536   13.6249536   72   16.38479   13.48382373  

9330027.00   Vancouver   Arbutus-­‐Ridge   0.157050971   15.70509711   70   16.61261   13.93089311  

9330053.01   Vancouver   Hastings-­‐Sunrise   0.137563131   13.75631307   69   16.72653   14.15442781  

9330024.00   Vancouver   Dunbar-­‐Southland   0.163721154   16.37211541   68   16.84044   14.3779625  

9330021.00   Vancouver   Shaughnessy   0.163153   16.31529995   66   17.06827   14.82503189  

9330013.02   Vancouver   Sunset   0.148827979   14.88279794   63   17.41001   15.49563597  

9330007.02   Vancouver   Kerrisdale   0.167006276   16.70062755   63   17.41001   15.49563597  

9330001.02   Vancouver   Killarney   0.157788504   15.77885038   62   17.52393   15.71917066  

9330014.01   Vancouver  Victoria-­‐Fraserview   0.130917122   13.09171218   62   17.52393   15.71917066  

9330010.02   Vancouver   Oakridge   0.154851572   15.48515724   61   17.63784   15.94270536  

9330150.00   Richmond   Sea  Island   0.179178288   17.9178288   22   22.08049      

9330149.03   Richmond   Thompson   0.174576226   17.45762261   57   18.09350      

9330142.03   Richmond   West  Richmond   0.160820195   16.0820195   48   19.11873      

9330141.00   Richmond   Steveston   0.167191017   16.7191017   92   14.10650      

9330151.01   Richmond   City  Centre   0.169422973   16.94229733   70   16.61261      

9330144.04   Richmond   South  Arm   0.164056224   16.40562236   27   21.51092      

9330151.06   Richmond   East  Richmond   0.17806202   17.80620198   82   15.24564      

9330140.04   Richmond   Hamilton   0.181933296   18.19332956   37   20.37178      

9330102.00  North  Vancouver   Marine-­‐Hamilton   0.159863701   15.98637012   85   14.90390      

52

9330103.00  North  Vancouver   Mahon   0.157458677   15.74586766   62   17.52393      

9330101.04  North  Vancouver   Central  Lonsdale   0.145762131   14.57621309   82   15.24564      

9330101.02  North  Vancouver   Lower  Lonsdale   0.15086794   15.08679398   92   14.10650      

9330104.00  North  Vancouver   Grand  Boulevard   0.173636979   17.36369786   65   17.18218      

9330100.02  North  Vancouver   Moodyville   0.163874349   16.3874349   67   16.95436      

9330133.01  West  Vancouver   Horseshoe  Bay   0.197813091   19.78130906   62   17.52393      

9330133.02  West  Vancouver   Caulfield   0.203318672   20.33186724   63   17.41001      

9330132.00  West  Vancouver   Westmount   0.204331092   20.43310923   18   22.53615      

9330130.03  West  Vancouver   Ambleside   0.147981576   14.79815757   88   14.56216      

9330135.00  West  Vancouver   British  Properties   0.193119829   19.31198288   7   23.78921      

9330161.06   Delta   Ladner   0.184944173   18.49441731   90   14.33433      

9330160.03   Delta   Tsawwassen   0.178775305   17.87753052   50   18.89090      

9330170.03   White  Rock   White  Rock   0.195718061   19.57180612   72   16.38479      

9330186.01   Surrey   Whalley   0.217395779   21.73957795   35   20.59961      

9330190.05   Surrey   City  Centre   0.201957246   20.19572457   85   14.90390      

9330189.03   Surrey   Guildford   0.216760551   21.67605511   82   15.24564      

9330187.09   Surrey   Fleetwood   0.216618269   21.66182685   72   16.38479      

9330185.16   Surrey   Newton   0.210087971   21.00879709   93   13.99259      

9330183.03   Surrey   Cloverdale   0.228722222   22.87222219   78   15.70130      

9330181.09   Surrey   South  Surrey   0.240031688   24.00316883   35   20.59961      

9330200.00  New  Westminster   Queensborough   0.16470362   16.47036197   52   18.66307      

9330205.02  New  Westminster   Glenbrook  North   0.14388669   14.38866903   58   17.97958      

9330206.00  New  Westminster   Downtown   0.104270961   10.42709608   97   13.53693      

9330209.00  New  Westminster   Glenbrook  South   0.159858005   15.98580048   58   17.97958      

9330210.00  New  Westminster   Brunette  Creek   0.140609877   14.06098768   62   17.52393      

9330243.02   Burnaby  Simon  Fraser  University   0.143226205   14.32262046   72   16.38479      

9330239.00   Burnaby   Brentwood   0.160246557   16.02465573   55   18.32133      

9330242.00   Burnaby   Capitol  Hill   0.163721002   16.37210021   50   18.89090      

9330229.00   Burnaby   Burnaby  Hospital   0.157703305   15.77033052   57   18.09350      

9330223.02   Burnaby   Edmonds   0.13717872   13.71787205   77   15.81521      

9330224.01   Burnaby   Highgate   0.128156432   12.81564318   78   15.70130      

9330226.03   Burnaby   Metrotown   0.113543957   11.35439567   97   13.53693      

9330237.00   Burnaby   Montecito   0.161115257   16.11152566   50   18.89090      

9330221.03   Burnaby   South  Slope   0.17348901   17.34890102   40   20.03004      

9330241.00   Burnaby   Burnaby  Heights   0.15457724   15.45772402   55   18.32133      

9330260.08   Port  Moody   Anmore   0.219817298   21.98172982   42   19.80221      

9330260.04   Port  Moody   College  Park   0.219433886   21.94338865   38   20.25787      

53

9330260.02   Port  Moody  Port  Moody  Centre   0.206996662   20.69966619   80   15.47347      

9330287.02   Coquitlam   Northeast   0.236070765   23.60707652   13   23.10572      

9330287.14   Coquitlam  Westwood  Plateau   0.237808781   23.78087811   23   21.96658      

9330287.01   Coquitlam   Hockaday-­‐Nestor   0.206734288   20.67342878   28   21.39701      

9330287.08   Coquitlam   Town  Centre   0.204697154   20.46971538   82   15.24564      

9330287.11   Coquitlam   Eagle  Ridge   0.206712452   20.67124523   77   15.81521      

9330286.02   Coquitlam   Ranch  Park   0.208056655   20.80566546   18   22.53615      

9330286.01   Coquitlam   Central  Coquitlam   0.227876767   22.7876767   35   20.59961      

9330281.01   Coquitlam   Cape  Horn   0.231025888   23.10258876   43   19.68830      

9330282.00   Coquitlam   Maillardville   0.208930965   20.89309653   62   17.52393      

9330283.00   Coquitlam  Cariboo-­‐Burquitlam   0.197381137   19.73811367   62   17.52393      

9330291.02  Port  Coquitlam  

North  Port  Coquitlam   0.21862017   21.86201704   62   17.52393      

9330290.02  Port  Coquitlam  

South  Port  Coquitlam   0.209094485   20.9094485   70   16.61261      

9330403.04   Maple  Ridge   The  Ridge   0.221105403   22.11054027   48   19.11873      

9330402.02   Maple  Ridge   Haney   0.236020503   23.6020503   40   20.03004      

9330403.03   Maple  Ridge   Hammond   0.224536322   22.45363218   58   17.97958      

9330404.01   Maple  Ridge   East  Haney   0.244096503   24.40965035   15   22.87789      

9330404.02   Maple  Ridge   Yennadon   0.234988858   23.4988858   10   23.44746      

9330400.02   Maple  Ridge   Albion   0.238431673   23.84316729   13   23.10572      

9330410.03   Pitt  Meadows   City  Centre   0.23293165   23.29316504   65   17.18218      

9330410.02   Pitt  Meadows  West  Pitt  Meadows   0.221753722   22.17537222   12   23.21963      

9330410.04   Pitt  Meadows  North  Pitt  Meadows   0.23302172   23.30217196   5   24.01703      

9330504.03   Langley  Walnut  Grove-­‐Fort  Langley   0.239949668   23.99496676   45   19.46047      

9330504.01   Langley  Willowbrook-­‐Tall  Timbers   0.240225808   24.02258084   57   18.09350      

9330503.03   Langley  Langley  City-­‐Murrayville   0.23761258   23.76125796   63   17.41001      

9330502.05   Langley   Campbell  Valley   0.243963437   24.39634372   12   23.21963      

9330505.00   Langley   Glen  Valley   0.235123312   23.51233124   18   22.53615      

9330506.02   Langley   Aldergrove   0.237690675   23.76906749   62   17.52393      

54

Linear Regression Results: Greater Vancouver

Linear Regression Regression Statistics R 0.62381 R Square 0.38913 Adjusted R Square 0.38264 Standard Error 3.49621 Total Number Of Cases 96

Transportation Cost (% of monthly income) = 24.5866 - 0.1139 * Walk Score

ANOVA d.f. SS MS F p-level

Regression 1. 731.94013 731.94013 59.8799 1.12667E-

11 Residual 94. 1,149.00623 12.22347 Total 95. 1,880.94636

Coefficients Standard

Error LCL UCL t Stat p-level H0 (2%) rejected? Intercept 24.5866 0.94466 22.35091 26.8223 26.02698 0.E+0 Yes

Walk Score -0.11391 0.01472 -0.14875 -

0.07907 -7.73821 1.12667E-

11 Yes T (2%) 2.36667

Linear Regression Results: Vancouver

Linear Regression Regression Statistics

R 0.91653 R Square 0.84003 Adjusted R Square 0.83204 Standard Error 1.16481 Total Number Of Cases 22

Transportation Cost (% of monthly income) = 29.5783 - 0.2235 * Walk Score ANOVA

d.f. SS MS F p-level Regression 1. 142.49896 142.49896 105.0272 0. Residual 20. 27.13563 1.35678 Total 21. 169.6346

Coefficients Standard

Error LCL UCL t Stat p-level H0 (2%) rejected?

Intercept 29.57832 1.67424 25.34587 33.81077 17.66667 1.13687E-

13 Yes

Walk Score -0.22353 0.02181 -0.27867 -0.16839 -

10.24828 0. Yes T (2%) 2.52798