Land Use Density and Clustering
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Victoria Transport Policy Institute
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Updated 6 September 2019
This chapter describes how increased density (number of people or employees located in an area) and clustering (locating related activities close together) tend to reduce travel distances and improve travel options. Density and clustering support and are supported by many TDM strategies.
Density refers to the number of people or jobs in a given area. Clustering (also called Compact Development) refers to Land Use patterns in which related activities are located close together, usually within convenient walking distance. Clustering improves Accessibility by reducing travel distances and improving Transportation Options. It is an important part of land use management strategies including Access Management, Location Efficient Development, New Urbanism, Smart Growth and Transit Oriented Development.
Table 1 Typical Densities
Definition |
Population Density |
Typical Housing |
|
Rural |
Less than 0.5 residents per acre. |
Houses on large lots (>5 acres) |
|
Low-Density – Suburban |
0.5-5 residents per acre. |
Houses on lots 0.5 to 5 acres |
|
Mid-Density – Suburban Cluster or Urban |
5-12 residents per acre. |
Houses on lots 0.2 to 0.5 acres (2-5 houses per acre) |
|
Compact – Urban |
More than 12 residents per acre. |
Various combinations of detached houses on small lots, duplexes, townhouses, and low-rise (under 4 story) apartments and condominiums. |
|
High-density |
More than 20 residents per acre |
Low- and high-rise (more than 4 story) apartments and condominiums. |
Density and Clustering are somewhat different concepts. Density refers to the number of people or jobs per unit of land (acre, hectare, square kilometer or square mile), while Clustering to the location and mix of activities in an area. For example, simply increasing population densities in a residential-only area may do less to improve accessibility than clustering destinations such as schools and shops in the center of the development. Rural and suburban areas have low densities, but common destinations such as schools, shops and other public services can be clustered in villages and towns. This increases accessibility by making it easier to run several errands at the same time, increases opportunities to interact with neighbors, and creates transportation nodes (rideshare stops, bus stops, etc.).
Density alone has modest impacts on vehicle travel and mode share; for example, the Los Angeles region is dense but automobile-dependent (Eidlin 2010). Clustering is more effective at reducing automobile use if it includes other TDM strategies. For example, automobile commuting tends to decline if employment centers are clustered with shops, restaurants and daycare centers (destinations that employees want to visit during their breaks), and if such areas have Pedestrian Improvements, a Rideshare program, Transit Improvements and Commute Trip Reduction programs. Put another way, other Commute Trip Reduction strategies tend to be more effective if worksites are clustered.
Density and Clustering can occur at various scales and in many different ways. Office buildings, campuses, shopping malls, commercial districts, towns and cities are examples of clustering. Density and Clustering at a neighborhood level (areas of less than a mile in diameter) with good pedestrian conditions creates multi-modal centers (also called urban villages, transit villages or walkable centers), which are suitable for walking and transit.
Clustering can be implemented in urban, suburban or rural conditions, either incrementally or as part of a master-planned development. Clusters can range from just a few small buildings (for example, a restaurant, a medical office and a single retail store) to a large commercial center with hundreds of businesses.
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Measuring Density (Kolko 2011; Rowlands 2017) Conventional density is measured as the number of people, housing units or workers per unit of area (acre, hectare, square kilometer or square mile). But metropolitan areas and states often include undeveloped or sparsely developed land, so conventional density measures can understate the density of the settled areas where people actually live and work.
Weighted density helps to account for this. Weighted density measures the number of people, or housing units or workers in the areas where people actually live or work and therefore better reflect the land use patterns experienced by a typical person or worker.
Weighted density for a metropolitan area is the weighted average of Census tract population density weighted by the tract’s share of metropolitan population. Tracts without population receive a weight of zero and therefore do not affect the weighted density of the metropolitan area. In effect, the weighted-density measure equals the tract density for the average person within a metropolitan area; we use the same method to calculate housing and employment density.
Because tracts with more population (or housing or employment) tend to have higher density, tract-weighted density measures for metropolitan areas tend to be higher than unweighted density measures. An alternative method for excluding undeveloped land is “net density”: population (or employment) divided by land area excluding farmland, public lands, and other undeveloped areas. Net density requires detailed data on land uses in order to identify and exclude undeveloped land, whereas weighted density requires only on tract population (or employment) and land area.
To understand how weighted density measures work, consider two hypothetical cities, Sparseville and Densetown. Each has a population of 1,000 residents and consists of two one-square mile Census tracts. In Sparseville, 500 people live in each tract, whereas in Densetown, all 1,000 residents live in one tract and the other is undeveloped. Both Sparseville and Densetown have a conventional density of 500 people per square mile (1,000 residents divided by 2 square miles). But the weighted density measure is 500 people per square mile in Sparseville, since the average person lives in a tract with 500 people per square mile, while the weighted density measure in Densetown is 1,000 people per square mile, since the average person (in fact, all people) lives in a tract with 1,000 people per square mile. |
Here are some examples to provide a feel for various types of densities.
A typical apartment has 800 to 1,500 square feet of floor area. If a three-story apartment building has twelve units averaging 1,200 square feet each, its footprint (the area of land the building actually covers) is about 5,000 square feet (4 x 1,200, plus a little extra for hallways). Apartments typically have 1.0 to 3.0 occupants, depending on the number of bedrooms.
A typical modern house has 2,000 to 3,000 square feet of floor area. If a 2,500 square foot house is two stories, it will have a 1,250 square foot footprint. Houses typically have 2.0 to 4.0 occupants, depending on the number of bedrooms.
In addition to the building (apartment or house) itself, a development may also include sidewalks, driveways, parking lots or garages, porches, decks, outbuildings and greenspace (lawns and gardens). The portion of a site of land that is covered with pavement or buildings (together called impervious surface) is called the coverage, measured as a percent of the total land area.
A typical city lot is 50 feet wide by 100 feet deep, totalling 5,000 square feet, or about one-eighth of an acre. If such a lot contains 2,500 square foot single-story house, a 500 square foot two-car garage, a 40-foot driveway, a 5-foot sidewalk, the coverage will total 3,570 square feet, or 71% of the land area, leaving just 1,430 square feet for greenspace.
However, if the same size house is built in two stories, and the garage is incorporated into the house or accessed from a back alley, minimizing the driveway length, the lot coverage declines to 2,250 square feet, leaving about half of the lot as greenspace. With single-family housing, a setback of 5 to 8 feet is needed between each house and the lot line. Sharing walls (building a duplex or townhouse) eliminates the need for setbacks, allowing the narrower lots.
With 3.0 average occupants per house, density averages 24 residents per acre for 5,000 square foot lots, about 33 residents per acre in duplexes on 4,000 square foot lots, and 43 residents per acre in townhouses on 3,000 square foot lots. Density in single-family housing can be increased by adding secondary suites (also called granny flats), that is, a small rental unit incorporated into the house or in an outbuilding.
A four-story, low-rise apartment or condominium with 16 total units has a footprint of about 4,500 square feet. If located on a double lot (100’ x 100’), half the parcel may be used for a combination of surface parking and greenspace. These will typically have 1.2 occupants per unit, about 20 total occupants per building or 80 residents per acre.
These represent net densities. Gross densities over the entire area are lower to account for land devoted to non-residential uses such as commercial and industrial facilities, schools, parks and recreational facilities, and undeveloped land.
As a general rule of thumb, 4-7 dwelling units per acre are required to create demand for “basic” bus transit service (20-40 buses per day), 6-15 units per acre are required to create demand for “frequent” bus transit service, 9 units per acre are needed to create demand for light rail transit, and 12 units per acre are needed to create demand for rapid transit (Transit Evaluation). However, these density requirements vary depending on additional factors, including the size of the Downtown and other commercial areas served by transit, Parking Management practices (such as whether parking is priced), and whether there are Commute Trip Reduction programs at worksites.
New Urbanism and Transit Oriented Development involve clustering developments into walkable neighborhoods of 0.5 to 1.0 mile in diameter (a typical walking catchment area for commercial centers and transit stations), an area of 125 to 500 acres. Ideally, this includes a mixture of higher-density multi-family and small-lot single-family. For example, if a transit village has 200 total acres, of which 150 are devoted to residential, 25 acres are 4-story apartments, 25 acres are townhouses, and 100 acres are single-family houses on 5,000 square foot lots. The table below summarizes the total residents in such a community.
Table 2 Total Residents Within A Walkable Area
|
Type |
Units Per Acre |
Occupants Per Unit |
Occupants Per Acre |
Acres |
Total |
|
Multi-Family |
80 |
1.2 |
96 |
25 |
2,400 |
|
Townhouses |
43 |
2.0 |
86 |
25 |
2,150 |
|
Single-Family |
8 |
3.0 |
24 |
100 |
2,400 |
|
|
|
|
|
|
6,950 |
Some people have negative attitudes about density and clustering (Bula 2017). They believe that it is harmful to individuals and society, and that consumers always prefer lower-density development patterns (Moretti, 1999). Some critics claim that urban densities increase mental illness, but research is mixed: city living may increase some forms of psychosis and mood disorders, drug addiction, and some people’s unhappiness, but tends reduce dementia, alcohol abuse and suicide rates, and many people are happier in cities than they would be in smaller communities (Litman 2016). Many consumers value living in walkable urban neighborhoods that have amenities such as personal security and good schools. One survey (NHBA, 1999) found that 83% of consumers prefer suburban housing, but the features respondents value most are neighborhood security, quality schools and neighborhood quality. This suggests that some households would choose higher density, multi-modal locations if they had such amenities.
Demand for New Urbanist communities, loft apartments and urban infill is strong, provided that they offer personal security, school quality and prestige comparable to suburbs. A study by Eppli and Tu (2000) found that homes in New Urbanist communities sold for an average of $20,189 more than otherwise comparable homes in more conventional communities, an 11% increase in value. One survey found that 43% of homebuyers who currently choose rural and suburban locations are good candidates for higher density, traditional neighborhood developments (Heart and Biringer, 2000). Similarly, a survey of the Puget Sound region housing market found that although the majority of respondents prefer a detached home, most care more about the quality of their neighborhood and owning their own home than about housing type, and more than 90% would willingly trade low-density housing for a medium- or high-density home if it had other desirable features (Decisions Data, 1994).
Many families already choose relatively higher-density housing, but it is not clustered with other common destinations and so does not increase accessibility. For example Moudon and Hess (2000) found that 40% of residents in suburban areas of Puget Sound live in medium- to high-density, multi-family housing. Yet, these developments often lack pedestrian access to nearby retail and public services, forcing residents to drive rather than walk for errands. Better integration between land use and transportation can significantly reduce automobile use without changing housing type or density.
Table 3 Good and Bad Density (Clark and Moir 2015)
|
Characteristics of ‘Good’ Density |
Characteristics of ‘Gad’ Density |
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Mixed use of land. Combining residential, commercial, retail, transport and green space creates a vibrant urban landscape which is used at all times of day and by different groups. |
Monotonous. Dense single land use appears to prevent the advantages of density from being leveraged and fosters negative externalities instead. |
|
Connected. Includes high volume reliable public transport and leverages existing infrastructure. 80% of ULI members surveyed identified good infrastructure as an essential component of successful density |
Isolated. Without transport infrastructure density is not able to fulfil its key role of facilitating access, and can lead to unmanageable traffic challenges. |
|
Planned in advance and incremental in pace. Good density is the product of an overarching strategic vision about place-making and specific / explicit project choices. |
Occurs at a rapid and unmanaged pace. Places and people become overwhelmed by rapid density which prevents assimilation and the investment needed to make density work. |
|
Cohesive. Meets social needs as well as economic needs. The aim of good density is not just to create capital assets but to serve people who live and work in the city. |
The concentration of single income populations (whether high income or low income) or single ethnic groups. If density is combined with income or ethnic segregation, it can have the unintended effect on increasing ‘ghettoisation’ or spatial inequality. |
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Liveable. Enhances quality of life and liveability for residents. Good density mitigates the liveability stresses caused by concentration and takes advantage of the opportunities it creates to enhance public services and quality of life. |
Unliveable. Without good public and private services density can become monolithic, scary, and imprisoning. Bad density can breed crime and insecurity, making dense spaces fearsome and unattractive. |
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Spacious. Good density provides public and open spaces for citizens to decompress regardless of their income. |
Absence of public and open space / connectivity. Without the space to decompress density can become oppressive and feel crowded. |
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Has flexibility. Good density can be increased or added to incrementally. |
Lack of adaptability to changing economic and social circumstances. Dense buildings that are inflexible can prevent a whole district or neighbourhood from adapting. It can have a blighting effect. |
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Has design built into it. High density does not always have to mean high rise, but should always mean high quality urban design. |
The absence of good urban design. Density can be created in ways which are perceived to be ugly. |
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Green. Has an environmental benefit and uses energy, waste, water and transport systems more efficiently. Encourages shared facilities and services. |
Polluting. Traffic congestion and heat island effects stemming from poorly planned density can be detrimental to the environment. |
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Appropriate. Minimises impact on existing settled neighbourhoods and places. Good density reflects and accentuates the local character of existing neighbourhoods. Planners take measures to accommodate and provide for existing residents. |
Conspicuous and inappropriate to existing scale of buildings and character of city scape. The blend of buildings in the same neighbourhood is key, each city or district has its own vernacular or narrative that dense buildings need to be in tune with. |
This table summarizes ways that development density can be good or bad overall.
Clustering is usually implemented by local governments and developers. Clustering often requires changes to development policies and practices that allow and encourage higher densities and more flexible parking requirements.
Special effort is often required to increase density and clustering. Incremental increases can be achieved by expanding existing buildings, for example, by adding rooms and secondary suites. Urban redevelopment, such as conversion of commercial buildings to residential, or redevelopment of old industrial areas, can be an opportunity to increase density and land use mix.
Because existing residents often oppose density increases, special care may be required to provide address concerns and provide incentives. For example, developers may be required to help fund community amenities, and Residential Parking Permits may be applied to insure that existing residents have access to onstreet parking spaces. Many of the objections to increased density can be addressed through good design and mitigation (New Urbanism).
Density and clustering tend to reduce per capita automobile travel (Land Use Impacts on Transportation) by reducing travel distances to common destinations and by improving transportation Options, particularly walking, ridesharing and public transit by increasing the demand for such services (Kuzmyak and Pratt, 2003; Turcotte, 2008).
In an extensive review of studies Ewing (1997) concludes, “that doubling urban densities results in a 25-30% reduction in VMT, or a slightly smaller reduction when the effects of other variables are controlled.” Even greater travel reductions are possible if clustering is implemented with other TDM strategies, including Pedestrian Improvements, Parking Management, Commute Trip Reduction programs, Ridesharing, Transit Improvements and Traffic Calming. The This View of Density Calculator produced by the San Francisco League of Conservation Voters (www.sflcv.org/density) predicts the effects of clustering on land consumption and travel behavior. Campoli and MacLean (2002) provide information and illustrations that can help decision-makers better understand different densities and development patterns.
Density at both origins and destinations affect travel behavior. Work trips and shopping trips are affected by population and employment densities. One study found that increasing urban residential population density to 40 people per acre increased transit use from about 2% to 7%, while increasing densities in commercial centers to 100 employees per acre resulted in an additional 4% increase in transit use, to an 11% total mode share (Frank and Pivo, 1995). Barnes and Davis (2001) also found that densities at employment centers are particularly important for encouraging transit and ridesharing. Glaeser and Kahn (2008) found that per capita vehicle travel, energy consumption and pollution emissions tend to be lower in denser city centers than in suburbs.
Aesthetically-pleasing urban character and amenities at worksites, such as shops and restaurants within walking distance, can reduce errand trips and increase transit and rideshare use, because without these, employees may feel the need to have a car to run errands during breaks (Cambridge Systematics 1994). One study found that the presence of worksite amenities such as banking services, on-site childcare, a cafeteria, a gym, and postal services could reduce average weekday car travel by 14%, due to a combination of reduced errand trips and increased ridesharing (Davidson 1994).
Table 4 Travel Impact Summary
|
Objective |
Rating |
Comments |
|
Reduces total traffic. |
3 |
Reduces travel distances and supports alternative modes. |
|
Reduces peak period traffic. |
3 |
" |
|
Shifts peak to off-peak periods. |
0 |
|
|
Shifts automobile travel to alternative modes. |
3 |
Supports alternative modes. |
|
Improves access, reduces the need for travel. |
3 |
|
|
Increased ridesharing. |
2 |
|
|
Increased public transit. |
3 |
|
|
Increased cycling. |
2 |
|
|
Increased walking. |
3 |
|
|
Increased Telework. |
0 |
|
|
Reduced freight traffic. |
2 |
|
Rating from 3 (very beneficial) to –3 (very harmful). A 0 indicates no impact or mixed impacts.
Density and clustering can provide a variety of economic, social and environmental benefits (Forman, et al. 2003, p. 332; Litman 2004).
Density and clustering improve Accessibility (by reducing the average distance between common destinations) and Transportation Options (walking improvements and transit services are tend to be most feasible and cost effective with clustered land use), encourage use of alternative modes, and reduce per capita automobile costs and impervious surface. Clustering reduces the costs of providing public infrastructure and services such as roads, utility lines, policing and schools (Land Use Evaluation). This can help reduce regional traffic congestion, road and parking facility costs, consumer transportation costs, crashes, energy consumption, pollution emissions and urban sprawl, which protects openspace. These benefits tend to be greatest if complementary land uses are mixed and supported by other TDM and land use management strategies, such as Smart Growth.
Density and clustering tend to provide agglomeration benefits, which consist of the accessibility and network effects that increase economic efficiency and productivity (Coffey and Shearmur, 1997). Published research indicates that doubling urban population density produces approximately 6% increase in productivity (Haughwout, 2000; Harris and Ioannides, 2000). This explains why cities and commercial centers develop and are so important for economic development: clustering of common destinations reduces the costs of activities that require frequent interactions. These benefits can be very large, as indicated by the much higher land values that occur in major commercial centers.
Clustering can increase Livability if it is implemented in conjunction with pedestrian and cycling improvements, traffic calming and other Streetscape enhancements. It can increase opportunities for neighborhood interaction and community cohesion. However, clustering can also increase exposure to noise and air pollution.
Density and clustering increase some costs, including some types of infrastructure costs (such as some utility costs), local traffic congestion, although regional traffic and pollution emissions tend to decline if clustering reduces total vehicle use. Although clustering may increase local traffic congestion, and therefore reduce average vehicle travel speeds, it tends to bring common destinations closer together, so total travel costs are reduced. Reduced automobile use and improved opportunities for Parking Management can reduce road and parking facility costs.
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Do Clustering and Density Cause Social Problems?
Many higher-density urban neighborhoods have higher rates of social problems (crime and poverty) than lower-density suburban neighborhoods. Some people assume that this indicates that clustering and density cause social problems. But, although studies find an association between crowding (density measured in residents per residential room, an indication of poverty) and social problems, there is no such association with density measured in residents per acre (1000 Friends of Oregon, 1999). For example, there are also high crime rates in some rural areas with low densities but high poverty, and therefore crowding.
This indicates that the association between density and social problems reflects the tendency of distressed households to concentrate in higher-density, urban neighborhoods, not that higher-density development causes social problems. This suggests that clustering does not increase social problems, and urban infill could reduce such problems if distressed households become less segregated (Litman, 2001). |
Density and clustering tend to reduce the amount of greenspace in a particular area, although they can increase total regional greenspace by reducing per capita road, parking and building area requirements. Most of these negative impacts can be reduced with appropriate design features (such as noise insulation and carefully located parks), but these mitigation activities may also involve additional costs.
Table 5 Benefit Summary
|
Objective |
Rating |
Comments |
|
Congestion Reduction |
1 |
Can increase local congestion but reduces regional congestion. |
|
Road & Parking Savings |
2 |
Reduces road and parking requirements. |
|
Consumer Savings |
2 |
|
|
Transport Choice |
3 |
|
|
Road Safety |
2 |
|
|
Environmental Protection |
2 |
|
|
Efficient Land Use |
3 |
|
|
Community Livability |
1 |
|
Rating from 3 (very beneficial) to –3 (very harmful). A 0 indicates no impact or mixed impacts.
Density and clustering can have a variety of equity impacts. Changes to development policies and practices may benefit some people and disadvantage others. In particular, it can add value to urban land values and keep urban fringe land from appreciating in value as quickly as would occur otherwise. Policies that support clustering often involve reducing cross-subsidies for low-density, urban-fringe development (Litman, 1999). Policies that reduce residential parking requirements and improve transportation choice can be progressive (Location Efficient Development). Clustering can be particularly beneficial to people who are transportation disadvantaged, and improve Basic Mobility.
Table 6 Equity Summary
|
Criteria |
Rating |
Comments |
|
Treats everybody equally. |
0 |
|
|
Individuals bear the costs they impose. |
1 |
|
|
Progressive with respect to income. |
1 |
|
|
Benefits transportation disadvantaged. |
3 |
|
|
Improves basic mobility. |
3 |
|
Rating from 3 (very beneficial) to –3 (very harmful). A 0 indicates no impact or mixed impacts.
Density and clustering can be applied under most geographic conditions, although design, scale and magnitude may differ. For example, a rural cluster may be quite different than a suburban or urban cluster. Federal and state governments can encourage clustering in their own facilities and transportation investments. Regional and municipal governments can encourage clustering with supportive transportation and land use policies. Developers, businesses and campuses can implement clustering directly.
Table 7 Application Summary
|
Geographic |
Rating |
Organization |
Rating |
|
Large urban region. |
3 |
Federal government. |
1 |
|
High-density, urban. |
3 |
State/provincial government. |
2 |
|
Medium-density, urban/suburban. |
3 |
Regional government. |
3 |
|
Town. |
3 |
Municipal/local government. |
3 |
|
Low-density, rural. |
2 |
Business Associations/TMA. |
3 |
|
Commercial center. |
3 |
Individual business. |
2 |
|
Residential neighborhood. |
3 |
Developer. |
3 |
|
Resort/recreation area. |
3 |
Neighborhood association. |
2 |
|
College/university communities. |
3 |
Campus. |
3 |
Ratings range from 0 (not appropriate) to 3 (very appropriate).
Clustering is a Land Use Management strategy.
Density and clustering support and are supported by Transportation Demand Management. They are an important component of Access Management, Location Efficient Development, New Urbanism and Smart Growth. Clustering tends to facilitate Pedestrian Improvements, and since most transit trips include walking links, it is important for efficient Transit. If located near transit stations or corridors it results in Transit Oriented Development. Clustering becomes more feasibility with Parking Management, particularly Shared Parking, to reduce the amount of land needed for parking facilities around buildings. The efficiency of Transportation Management Associations, Ridesharing and other Commute Trip Reduction strategies increases if worksites are clustered together.
Major stakeholders for implementing clustered development include local officials, developers, existing nearby residents, future residents and employees and transit agencies.
Existing development policies and practices often favor lower-density, dispersed development. Transportation planning practices often favor road and parking facility investments which lead to lower-density, automobile-oriented land use patterns, over pedestrian and transit investments that lead to more clustered land use.
· Public agencies should encourage clustering in their land use and transportation policies, including the location and design of their own facilities.
· Existing policies that discourage land use clustering (such as single-use zoning, excessive building setbacks and parking requirements) should be eliminated or made more flexible.
· Clusters should include an appropriate mix of activities. For example, employment centers should also include shops and services that workers frequent during their breaks, and residential centers should include schools, shops and public services.
· Special care should be taken to create convenient and attractive walking conditions, and clusters should include bicycle, ridesharing and transit improvements as appropriate.
· Clustering should be implemented as part of overall land use management strategies such as
· Clustering should be implemented with other TDM strategies that encourage vehicle travel reductions and shifts to alternative modes.
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Thanks to their many miles of super highways, gas stations and drive through restaurants, the modern suburb is a wonderful place to drive – as long as you don’t what to stop. |
An important part of Smart Growth is using land more efficiently and preserving those lands that are most environmentally sensitive. By building in a more compact way, these goals can be achieved. Compact development also reduces development costs through more efficient use of infrastructure, which in turn makes housing more affordable.
Compact development can encompass the following:
Cluster development produces very attractive and marketable communities and makes it easier for developers to preserve environmentally sensitive lands such as wetlands and forests by allowing lots to be grouped on certain portions of a site, rather than spread uniformly across a site, so that other areas of the site may remain undisturbed as open space. Yet many localities make it difficult or impossible to develop in this manner.
Higher density development uses land more wisely by building more homes on the land. Higher density housing could include single-family homes on smaller lots, or it could include attached homes or apartment buildings. Many people enjoy the affordability and ease of maintenance of higher density housing. Higher densities also create cost-savings through greater efficiencies in infrastructure. Zoning codes that prohibit this type of development should be changed.
Mixed-use development can produce diverse and convenient communities that can have the added benefit of reducing traffic. By integrating different uses such as residences, offices, and shopping, many daily vehicle trips can be eliminated or reduced in length. Zoning was established to separate different uses that created nuisances, such as separating factories from residences. But today most workplaces are clean and quiet and can be built closer to homes without adverse effects. Many employers also find that locating workplaces near shops, banks, dry cleaners, and restaurants can save their employees time. Zoning needs to address our modern condition and make these kind of developments possible.
Traditional Neighborhood Developments are a type of community that mixes uses and housing types to create a form more like the towns of the past than the automobile dominated suburbs we have come to know. These new communities are built for walking, and ideally allow residents to walk to shops, schools, places of worship, parks, and eventually transit stops. There are now over 200 traditional neighborhood projects under way or in the planning stages. Examples include Celebration, near Orlando, Florida; Harbor Town in Memphis; and Kentlands, in Gaithersburg, Maryland. Again, zoning often prohibits this type of development, but some communities are adopting new zoning codes to permit it.
What Needs To Be Done
Change your
development ordinances.
If these types of
development are to be built, your community’s laws must permit them to occur.
It may be necessary to adopt new ordinance language that permits and encourages
cluster development, higher densities, and mixed uses. Narrower street widths,
varied yard setbacks, alternative stormwater and wastewater systems, and
altered approaches to utility installation may all need to be considered to
make compact development possible and successful. If each developer must go
through a complex and costly process of obtaining special waivers and
approvals, special use permits, or planned unit development approval to achieve
compact development, the developer will probably find it makes more business
sense to keep building conventional large-lot subdivisions.
Provide more
certainty in the approval process.
The second thing that must
be done is to assure the developer of more certainty in the development
approval process. Too often, even when a community’s comprehensive plan or
zoning ordinance calls for compact development, a developer is thwarted by
opposing citizens or an uncooperative government. If your community decides
through its democratic process to support compact development—whatever they
have agreed this term means in terms of lot sizes and allowable
densities--measures should be taken to ensure that these plans are carried out.
Community discussions about the appropriateness of cluster development, higher
densities, or mixed uses should take place during the comprehensive planning
process, not on a project-by-project basis.
To streamline the development approval process and give developers more certainty in building compact development, the following suggestions are made:
Plan for
compact development.
To permit and promote compact communities, citizens, planners, and public
officials must be willing to challenge the conventional wisdom of the past and
accept that new goals may require new tools. But allowing compact development
and helping it get approved are not enough. Communities need to help pave the
way by planning for and helping provide the necessary infrastructure to support
compact development — be that streets and highways, or water and wastewater systems.
Developers and communities need to work in partnership to make compact
communities a reality and achieve Smart Growth.
The Smart Growth Matrix is a tool to assist the Austin City Council in analyzing development proposals within the Desired Development Zone. It is designed to measure how well a development project meets the City's Smart Growth goals such as: 1) the location of development; 2) proximity to mass transit; 3) urban design characteristics; 4) compliance with nearby neighborhood plans; 5) increases in tax base, and other policy priorities.
If a development project, as measured by the matrix, significantly advances the City's goals, financial incentives may be available to help offset the high cost of developing in urban areas. These incentives may include waiver of development fees and public investment in new or improved infrastructure such as water and sewer lines, streets or streetscape improvements, or similar facilities. These incentives require City Council review and approval.
Burlington, Vermont proposed to develop an eco-industrial park (EIP) on a 10 acre site, adjacent to which are already located a wood-burning co-generation power plant, a waste-wood depot, a community garden, and a compost facility. This brochure describes application of a suite of tools (Designing Industrial Ecosystems Tool, Facility Synergy Tool, and Reality Check) in a case study of Burlington. The case study illustrates how the screening models allow stakeholders to explore decisions, issues and tradeoffs in an interactive and flexible analytical framework. In addition to the information the tools provide (i.e., potential linkages, rough estimates of benefits, regulatory constraints), much of their value comes from the collaborative decision-making process they help to facilitate. As part of this incremental and collaborative process, in later stages of EIP planning, more detailed issues lying outside the three screening tools must be addressed, e.g., covenants, working relationships, engineering design specifications.
An extensive research project by the Centre for Livable Cities, based on experience in Singapore and other large cities, identified the following principles for creating livable high density cities:
The city of Vancouver’s EcoDensity will
create greater density throughout the city in order to reduce environmental
impacts, ensure necessary physical and social amenities, and supports new and
different housing types as a way to promote more affordability.
EcoDensity supports increasing density in a variety of contexts (i.e. in lower
density areas; along transit routes and nodes, neighbourhood centres,). The key
will be to support density that is high quality, attractive, more energy
efficient, and respects neighbourhood character, while lowering our footprint.
This requires reforming some existing policies, bylaws, incentives and zoning
to reduce barriers and promote ideas that will create communities that are
sustainable, livable and affordable.
EcoDensity involves an extensive research, planning and public consultation process. Some of the related issues are summarized below:
§ Do people want the city to allow more flexibility in our bylaws to promote sustainable building practices such as: use alternative energy sources (e.g., solar and geo-thermal energy systems); green roofs; use recycled rain water; recycled building materials?
§ Should the city make it easier for residents in single-family zoned areas to build a secondary suite above their garage, or convert their garage to a coach house?
§ How does the city encourage the creation of more secondary suites? Should we require that any new single family home rough in a secondary suite?
§ Do people want the city take more advantage of streets and nodes well served by transit or areas located around transit stations by increasing density significantly in those areas?
§ What aspects of our bylaws need to be changed in order to better accommodate or promote sustainable building practices such as energy-saving systems, recycling of grey water and rain water, green roofs, etc.
§ Should the city reduce its parking requirements on new developments, and if so, which type of developments? Should we require spaces for car sharing, or electric plugs in new underground garages to promote the use of electric vehicles? Should the city establish car free neighbourhoods?
§ How can the city help ensure that the necessary community amenities are included in areas where only smaller, incremental developments are built.
§ How could the city promote a greater range of types, sizes, locations and tenures of housing?
Richard Florida emphasizes the difference between regional gross density (people per square kilometer or mile) and concentrated density (the degree that people and economic activity are concentrated near the region’s center) when evaluating land use impacts. His analysis indicates that regional income, wages, economic output, education attainment, high tech industry, innovation (patients per capita), non-motorized and public transport commuting, and self-reported life satisfaction levels are positively correlated, and automobile commuting negatively correlated with concentrated density but much less so with gross density. Housing prices also tend to increase with concentrated density, making housing affordability a critical issue in such regions.
Westside Station Area Development -- About 7,000 dwellings and more than $505 million of residential and non-residential development have been built, permitted or proposed since 1990 within one-half mile of west side light rail stations. About 3,600 of the dwellings were completed in 1998. Over 3,000 of them are located in two station areas. One developer is building about 2,000 of these units in three station areas with backing from a pension fund.
Westside Station Area Planning -- A four year intergovernmental effort to update comprehensive plans, development regulations and capital improvement programs for areas within one-half mile of westside light rail stations. Hillsboro, Portland and Washington County adopted interim development regulations early in the process to minimize parking, increase density, prohibit inappropriate land uses, and require pedestrian oriented design. By 1998, new plans and development regulations had been adopted for almost all of the light rail station areas.
Sunset Transit Center -- Detailed design standards were adopted in October 1997 by
Washington County for an area including 190 acres under a single ownership. This was a major milestone in a debate that has lasted more than a decade on the best use of this property. The new plan and code was based on intensive discussions between adjacent neighborhoods, the property owner and county staff as well as urban design, market analysis and transportation consultants. A mixed use center is planned adjacent to the station and more than 2000 housing units in the balance of the area.
Beaverton Central Mixed Use Project -- One day the "The Round" will be the "jewel" of Westside Light Rail. Ground breaking was in October 1997 for this $100 million mixed-use project. The light rail station is in the middle of the site. The project includes a civic plaza with amphitheater, 154 for-sale dwellings, 152,000 square foot of class A office, 70,000 square foot of retail/office flex space, sister cities garden, 109 unit hotel, 10 screen movie theater, and 810 space parking garage. City staff are managing the project; regional technical and financial assistance is being provided. It took five years from the first study to ground breaking.
Murray West Master Plan -- A preliminary public/private master plan for a 120-acre area around the Beaverton Creek light rail station was completed in 1995. Trammell Crow Residential (TCR) completed construction of 830 dwelling units in 1998. Tri-Met's park & ride was relocated, redesigned and coordinated with TCR's project to create a pedestrian friendly environment. Nike plans to expand its world headquarters campus on 75 acres north of the station. City plan and code amendments for the 120-acre area were adopted in December 1997. Tri-Met managed the master plan effort. The City of Beaverton was lead on the plan/code amendments.
Hillsboro Light Rail Station Area Urban Design -- In 1993, this project dealt with issues that were not resolved during preliminary engineering and the draft EIS. There was concern that intergovernmental consensus would be difficult to achieve. In a five-week intensive effort, agreement was reached to remove two stations and redesign or relocate four others to reduce costs, improve access, and preserve opportunities for station area development. This was a joint effort with Metro, the City of Hillsboro and Washington County. Tri-Met was the lead agency. This is an excellent example of an interagency, interdisciplinary team approach with the right people with the right assignment at the right time.
Orenco/PacTrust Master Plan -- In January 1999, the National Home Builders selected "Orenco Station" out of nearly 1,000 entries for their "Master Planned Community of the Year" gold award. In 1998, it won the Governor's Livability Award. See www.orencostation.com for more information. More than 2,000 dwellings, a mixed use center, parks, and a sub-regional retail "power" center are planned, permitted or under construction between the light rail station and the new $2 billion Intel facility. The City of Hillsboro was the lead agency. Six-hundred apartments and the small lot single family home models were completed in 1997.
Downtown Hillsboro LID -- The City Council approved the Hillsboro Downtown Business Association petition for creation of a local improvement district (LID) in August 1996. The project implements the vision of the downtown (TOD) plan and began construction in summer 1997. The design for new sidewalks, curbs, decorative paving, street lamps, and greenery are complementary to light rail street improvements.
Portland TOD Property Tax Exemption Ordinance - It provides for a ten-year exemption for high density housing and mixed use projects. The City of Portland adopted an ordinance in October 1996 based on state legislation passed in 1995. Washington County and Tri-Met sought passage of the new state law; Tri-Met prepared a model ordinance.
Joint Development Projects -- Tri-Met has four projects in the Goose Hollow station area just west of downtown Portland. Arbor Vista ("Tree House" site) and Stadium Station Apartments ("Civic Stadium") are done; the project at Collins Circle is under construction; and the Butler Block project is in process. These projects pioneered the FTA waiver to the common grant rule for joint development; now all USA transit agencies can take advantage of these opportunities to increase ridership through TOD based on new regulations adopted in spring 1997 by FTA.
1000 Friends of Oregon (1999), “The Debate Over Density: Do Four-Plexes Cause Cannibalism” Landmark, 1000 Friends of Oregon (www.friends.org); at www.vtpi.org/1k_density.pdf.
Ryan Avent (2011), “One Path to Better Jobs: More Density in Cities,” New York Times Sunday Review (www.nytimes.com); 3 September 2011; at www.nytimes.com/2011/09/04/opinion/sunday/one-path-to-better-jobs-more-density-in-cities.html.
Gabriel M. Ahlfeldt and Elisabetta Pietrostefani (2019), The Economic Effects of Density: A Synthesis,” Journal of Urban Economics, Vol. 111, pp. 93-107 (https://doi.org/10.1016/j.jue.2019.04.006); at http://eprints.lse.ac.uk/100004/1/GA_EP_Economic_effects_of_density_CEPR.pdf.
Gary Barnes and Gary Davis (2001), Land Use and Travel Choices in the Twin Cities, Center for Transportation Studies, University of Minnesota (www1.umn.edu/cts), Report #6 in the Series: Transportation and Regional Growth Study.
Bob Bengford (2017), Visualizing Compatible Density, Municipal Research and Services Center (http://mrsc.org); at http://mrsc.org/Home/Stay-Informed/MRSC-Insight/April-2017/Visualizing-Compatible-Density.aspx.
Howard Blackson (2015), Density Is Just A Number: Stop Talking About Density And Start Talking About Place, Better! Cities & Towns (http://bettercities.net); at http://bettercities.net/news-opinion/blogs/howard-blackson/21453/density-just-number.
Marlon G. Boarnet and Susan Handy (2010), Draft Policy Brief on the Impacts of Residential Density Based on a Review of the Empirical Literature, for Research on Impacts of Transportation and Land Use-Related Policies, California Air Resources Board (http://arb.ca.gov/cc/sb375/policies/policies.htm).
Marlon G. Boarnet, Douglas Houston, Gavin Ferguson, and Steven Spears (2011), “Land Use and Vehicle Miles of Travel in the Climate Change Debate: Getting Smarter than Your Average Bear,” Climate Change and Land Policies (www.lincolninst.edu); draft version at http://economics.ucr.edu/spring11/Boarnet%20paper%20for%205%204%2011%20seminar.pdf.
Frances Bula (2017), “A Portrait of a Dense City. Once a Land of Spacious Abodes, Vancouver is Becoming Crowded – and Residents are Feeling the Squeeze,” Globe and Mail, (www.theglobeandmail.com); at www.theglobeandmail.com/news/british-columbia/vancouver-grapples-with-the-close-quarters-of-increasingdensity/article35703889.
Robert Burchell, et al (1998), The Costs of Sprawl – Revisited, TCRP Report 39, Transportation Research Board (www.trb.org).
Cambridge Systematics (1994), The Effects of Land Use and Travel Demand Management Strategies on Commuting Behavior, Travel Model Improvement Program, USDOT (www.bts.gov/tmip).
Julie Campoli and Alex MacLean (2002), Visualizing Density: A Catalog Illustrating the Density of Residential Neighborhoods, Lincoln Institute of Land Policy (www.lincolninst.edu); at www.lincolninst.edu/subcenters/visualizing-density.
Alex Cecchini (2015), A Primer on “Density”, Streets MM (http://streets.mn); at http://streets.mn/2015/05/06/a-primer-on-density.
Greg Clark and Emily Moir (2015), Density: Drivers, Dividends and Debates, Urban Land Institute (http://uli.org); at http://europe.uli.org/wp-content/uploads/sites/3/ULI-Documents/Density-Drivers-Dividends-Debates.pdf.
Greg Clark and Tim Moonen (2015), The Density Dividend: Solutions For Growing And Shrinking Cities, Urban Land Institute (http://uli.org); at http://europe.uli.org/wp-content/uploads/sites/3/ULI-Documents/ULI-TH-Density-Dividend-Report.pdf.
CLC (2013), 10 Principles for Liveable High-Density Cities: Lessons from Singapore, Urban Land Institute (www.uli.org) and the Centre for Livable Cities, Singapore (www.clc.gov.sg); at www.clc.gov.sg/documents/books/10PrinciplesforLiveableHighDensityCitiesLessonsfromSingapore.pdf.
William Coffey and Richard Shearmur (1997), “Growth and Location of High Order Services in the Canadian Urban System, 1971-1991,” Professional Geographer, Vol. 49, No. 4, Nov. 1997, pp. 404-418.
Diane Davidson (1994), Corporate Amenities, Trip Chaining and Transportation Demand Management, FTA-TTS-10, Federal Highway Administration (Washington DC).
Decisions Data (1994), Puget Sound Housing Preference Study, Puget Sound Regional Council (www.psrc.org).
Density Atlas (http://densityatlas.org) is a resource for measuring and comparing urban densities in cities around the world.
Eric Eidlin (2010), “What Density Doesn't Tell Us About Sprawl,” Access 37, University of California Transportation Center (www.uctc.net), pp. 1-9; at www.uctc.net/access/37/access37_sprawl.shtml.
Mark Eppli and Charles C. Tu (2000), Valuing the New Urbanism; The Impact of New Urbanism on Prices of Single-Family Homes, Urban Land Institute (www.uli.org).
Reid Ewing (1997), “Is Los Angeles-Style Sprawl Desirable?” Journal of the American Planning Association, Vol. 63. No. 1, Winter 1997, pp. 107-126.
Hao Audrey Fang (2008), “A Discrete–Continuous Model of Households’ Vehicle Choice and Usage, With an Application to the Effects of Residential Density,” Transportation Research Part B, Vol. 42, pp. 736–758; summary at www.sciencedirect.com/science/article/pii/S019126150800012X.
Richard Florida (2012), Cities With Denser Cores Do Better, The Atlantic Cities (www.theatlanticcities.com); at www.theatlanticcities.com/jobs-and-economy/2012/11/cities-denser-cores-do-better.
Richard T.T. Forman, et al (2003), Road Ecology: Science and Solutions, Island Press (www.islandpress.com).
Lawrence Frank and Gary Pivo (1995), “Impacts of Mixed Use and Density on Utilization of Three Modes of Travel: SOV, Transit and Walking,” Transportation Research Record 1466, TRB (www.trb.org), pp. 44-55.
Yonah Freemark (2016), Reorienting Our Discussion of City Growth, The Transport Politic (www.thetransportpolitic.com); at www.thetransportpolitic.com/2016/07/06/reorienting-our-discussion-of-city-growth.
Edward L. Glaeser and Matthew E. Kahn (2008), The Greenness Of Cities: Carbon Dioxide Emissions And Urban Development, Working Paper 14238, National Bureau Of Economic Research; at www.nber.org/papers/w14238; summarized in http://mek1966.googlepages.com/greencities_final.pdf.
Andrew F. Haughwout (2000), “The Paradox of Infrastructure Investment,” Brookings Review, Summer 2000, pp. 40-43.
Bennet Heart and Jennifer Biringer (2000), The Smart Growth - Climate Change Connection, Conservation Law Foundation (www.tlcnetwork.org).
Institute for Location Efficiency (www.locationefficiency.com) is an organization that works to encourage implementation of Location Efficient Development.
ITDP (2015), Density, Institute for Transportation and Development Policy (www.itdp.org); at www.itdp.org/wp-content/uploads/2015/09/Densify_ITDP.pdf.
JHK Associates (1995), Transportation-Related Land Use Strategies to Minimize Motor Vehicle Emissions: An Indirect Source Research Study, California Air Resources Board (www.arb.ca.gov); at www.sustainable.doe.gov/pdf/arb-report/arb-overview.htm.
Eric Damian Kelly (1994), “The Transportation Land-Use Link,” Journal of Planning Literature, Vol. 9, No. 2, November 1994, p. 128-145.
Jed Kolko (2011), Making the Most of Transit Density, Employment Growth, and Ridership around New Stations, Public Policy Institute of California (www.ppic.org); at www.ppic.org/content/pubs/report/R_211JKR.pdf.
Richard J. Kuzmyak and Richard H. Pratt (2003), Land Use and Site Design: Traveler Response to Transport System Changes, Chapter 15, Transit Cooperative Research Program Report 95, Transportation Research Board (www.trb.org).
Nico Larco (2010), Overlooked Density: Re-Thinking Transportation Options In Suburbia, OTREC-RR-10-03, Oregon Transportation Research and Education Consortium (www.otrec.us); at www.otrec.us/main/document.php?doc_id=1238.
Sherman Lewis (2017), “Neighborhood Density and Travel Mode: New Survey Findings for High Densities,” International Journal of Sustainable Development & World Ecology, pp. 1-14; at www.tandfonline.com/doi/full/10.1080/13504509.2017.1321052.
LGC (2003), Creating Great Neighborhoods: Density in Your Community, Local Government Commission, sponsored by the National Association of REALTORS (www.realtors.org); www.lgc.org/density-in-your-community.
LSE (2014), Urban Age Cities Compared, London School of Economics Cities Progromme (https://lsecities.net); at https://lsecities.net/media/objects/articles/urban-age-cities-compared/en-gb.
Todd Litman (2001), Evaluating Smart Growth and TDM; Social Welfare and Equity Impacts of Efforts to Reduce Sprawl and Automobile Dependency, VTPI (www.vtpi.org).
Todd Litman (2004), Evaluating Transportation Land Use Impacts, VTPI (www.vtpi.org); at www.vtpi.org/landuse.pdf.
Todd Litman (2006), Land Use Impacts On Transport, VTPI (www.vtpi.org); at www.vtpi.org/landtravel.pdf.
Todd Litman (2006), Smart Growth Policy Reforms, VTPI (www.vtpi.org); at www.vtpi.org/smart_growth_reforms.pdf.
Todd Litman (2006), Parking Management: Strategies, Evaluation and Planning, Victoria Transport Policy Institute (www.vtpi.org); at www.vtpi.org/park_man.pdf.
Todd Litman (2008), Recommendations for Improving LEED Transportation and Parking Credits, VTPI (www.vtpi.org); at www.vtpi.org/leed_rec.pdf.
Todd Litman (2011), “Can Smart Growth Policies Conserve Energy and Reduce Emissions?” Portland State University’s Center for Real Estate Quarterly (www.pdx.edu/realestate/research_quarterly.html), Vol. 5, No. 2, Spring, pp. 21-30; at www.vtpi.org/REQJ.pdf. Also see, Critique of the National Association of Home Builders’ Research On Land Use Emission Reduction Impacts, Victoria Transport Policy Institute (www.vtpi.org); at www.vtpi.org/NAHBcritique.pdf.
Todd Litman (2014), Analysis of Public Policies That Unintentionally Encourage and Subsidize Urban Sprawl, commissioned by LSE Cities (www.lsecities.net), for the Global Commission on the Economy and Climate (www.newclimateeconomy.net); at http://bit.ly/1EvGtIN.
Todd Litman (2016), Urban Sanity Understanding Urban Mental Health Impacts and How to Create Saner, Happier Cities, Victoria Transport Policy Institute (www.vtpi.org); at www.vtpi.org/urban-sanity.pdf.
Missing Middle Housing (www.missingmiddlehousing.com) describes why and how to create affordable, moderate-density housing suitable for urban infill development.
Frank R. Moretti (1999), Smart Growth: A Wolf in Sheep’s Clothing?, The Road Information Program (www.tripnet.org/smartgrowth.htm).
Anne Vernez Moudon and Paul Mitchell Hess (2000), “Suburban Clusters: The Nucleation of Multifamily Housing in Suburban Areas in the Central Puget Sound,” American Planning Association Journal, Vol. 66, No. 3, Summer 2000, pp. 243-263.
NAHB (1999), Consumer Survey on Growth Issues, National Association of Home Builders (www.nahb.com).
Garrett Nelson (2016), The Deception of Density: If We Think Carefully About the Flaws in Measuring How Dense a Place is, We Can Better Articulate What We Actually Value About Urbanism, City Labs (www.citylab.com); at www.citylab.com/tech/2016/10/the-deception-of-density/502646.
NHBA (2005), Talking Points On Compact Development, National Home Builders Association (www.nahb.org/generic.aspx?sectionID=628&genericContentID=17373&print=true).
John Ricco (2016), What Do 80,000 People in a Square Mile Look Like? Depends on Where You Put Them, Greater Greater Washington (http://greatergreaterwashington.org); at http://greatergreaterwashington.org/m/post/33093/what-do-80000-people-in-a-square-mile-look-like-depends-on-where-you-put-them.
Daniel Walter Rowlands (2017), The Way We Calculate Population Density is Wrong. Here’s What We Should do Instead, Greater Greater Washington (https://ggwash.org); at https://ggwash.org/view/65370/median-versus-average-population-density.
SFLCV (2003), This View of Density Calculator, San Francisco League of Conservation Voters (www.sflcv.org/density). This website illustrates various land use patterns, predicts their effects on travel behavior, and discusses various issues related to New Urbanist development. A spreadsheet version, called the ICLEI Density VMT Calculator, is available from the International Institute for Local Environmental Initiatives (www.icleiusa.org/library/documents/8-Density-VMT%20Calculator%20(2).xls).
simval84 (2015), Attached or Detached: Townhouses and Density, Urban Kchoze (http://urbankchoze.blogspot.ca); at http://urbankchoze.blogspot.ca/2015/04/attached-or-detached-townhouses-and.html.
Sidney Steele (1991), Reducing Trip Generation Through Project Design, ITE 1991 International Conference Compendium Paper, Institute of Transportation Engineers (www.ite.org).
Martin Turcotte (2008), “Dependence on Cars in Urban Neighbourhoods: Life in Metropolitan Areas,” Canadian Social Trends, Statistics Canada (www.statcan.ca); at www.statcan.ca/english/freepub/11-008-XIE/2008001/article/10503-en.htm.
ULI (2005), Higher-Density Development: MYTH AND FACT, Urban Land Institute (www.uli.org); at www.uli.org/Content/ContentGroups/PolicyPapers/MFHigher010.pdf.
Vancouver (2009), Secondary Suites in Apartments; Backgrounder/Information Sheet, EcoDensity Program, City of Vancouver (www.vancouver-ecodensity.ca); at www.vancouver-ecodensity.ca/webupload/File/Secondary%20Suites%20in%20Apartments%20Backgrounder%20Sheet.pdf.
Visualizing Density in Five Ontario Neighborhoods (www.visualizingdensity.ca) by the Canadian Urban Institute helps planners, designers, elected officials, residents’ groups, and private sector builders design more complete communities and adapt existing communities over time.
What is FAR (http://whatisfar.org). This game explains the concept of Floor Area Ratio (FAR).
This Encyclopedia is produced by the Victoria Transport Policy Institute to help improve understanding of Transportation Demand Management. It is an ongoing project. Please send us your comments and suggestions for improvement.
Victoria Transport Policy Institute
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