Development Density And Mix
- Summary
- Taxonomy & description
- First principles assessment
- Evidence on performance
- Policy contribution
- References
This measure was updated by INSTITUTE FOR TRANSPORT STUDIES (ITS) in 2014 under the CH4LLENGE project, financed by the European Commission.
Development densities and the mix of those developments have a key role to play in affecting both the level of travel and overall travel patterns. Higher densities of development may encourage shorter journeys and, thus, the use of walking and cycling. They may also help to make public transport more viable. In a similar manner, a better mix of developments can improve accessibility and hence reduce the need to travel.
Although neither terms are inextricably linked it is useful to consider them together. Development density refers to the number of people or jobs in a given area, whilst the development mix refers to how land uses are arranged in relation to each other. If common destinations are located close together, this type of mix is sometimes known as clustering.
The mechanisms through which density and mix have an impact on travel demand and travel patterns are:
- Accessibility - the number of potential destinations located within a geographical area tends to increase with population and employment density, reducing travel distances and the need for private travel. For example, in low-density areas a school may serve fifty square miles, requiring most students to travel by motor vehicle. In higher density areas, schools may serve just a few square miles, reducing average travelling distances and allowing more students to walk or cycle. Similarly, average travel distances for errands, commuting and business-to-business transactions can decline with density increases.
- Transport choice - Increased density tends to increase the numbers of transport options available in an area due to economics of scale. Higher density areas tend to have better pedestrian and bicycle facilities and better public transport service because increased demand makes them more cost-effective. As a result of these factors, higher density and clustered land use mix together tend to reduce per capita car ownership and use, and increased use of alternative modes.
Any impacts on travel demand and patterns arising from changes in the density and mix will depend upon: 1) the scale of the land use changes; 2) the design and type of changes, in terms of density and mix; 3) the speed with which the changes are affected.
It is also necessary to view changes in density and mix as being inextricably linked with a variety of other land use factors such as roadway connectivity and design, parking facility design, and building design, all of which will impact upon travel patterns.
Definition
Encouraging less motorised personal travel through land use involves the planning of new land use development and the management of existing land use in such a way as to bring origins and destinations closer together in order to help reduce private transport trips. This is normally done by increasing development densities or by organising the mix of lad use types, or both. Land use policy can also encourage a modal shift to public transport.
How can land use planning encourage less personal motorised travel?
Land use patterns affect travel behaviour. A variety of land use factors affect travel patterns including density, land use mix, roadway connectivity and design, parking facility design, and building design. Certain types of land use patterns are accessible by multiple modes, which reduces per capita car use, while others are car- orientated, which increases private car use. There are several strategies which involve changing land use patterns to increase multi-modal accessibility and reduce car use. (Online TDM encyclopaedia).
The full range of ways in which land use planning can encourage less personal motorised travel is as follows (TUE, p58). The list includes all types of land use instruments: the first two are covered in this section, the remaining six in other sections as shown.
1. increasing development densities - higher densities may encourage shorter journeys and, thus, the use of walking and cycling (and may help to make public transport more viable, see 3 below);
2. altering the development mix - a better mix of uses can improve accessibility and, hence, reduce the need to travel;
3. concentrating dense developments within transport corridors - where public transport can provide a viable alternative to the use of cars (see Encouraging Public Transport Use Through Land Use Planning);
4. reducing parking standards - this probably offers the single most direct impact on levels of car-use and can be used in trip-end restraint (see Parking Standards);
5. increasing developers' contributions for transport infrastructure, including public transport. Alternatively, the provision of public transport services can be required as part of the process of obtaining planning approval for new developments; (see Developer Contributions);
6. requiring commuted payments - these are a special type of developer contribution in which the normal requirements for private parking provision are waived in return for payment to a local authority of a charge per space, so that the Local Authority can make provision in public car parks or promote park-and-ride schemes (see Commuted Payments);
7. promoting travel-reduction ordinances/company transport plans - travel-reduction ordinances are used in the US and the Netherlands to require developers to produce a plan specifying ways in which they will reduce car-use to their development; this would require legislation in the UK. As an alternative, voluntary company travel plans could be developed.
How can land use density and land use mix encourage less personal motorised travel?
(based on Online TDM Encyclopaedia).
Density refers to the number of people or jobs in a given area. Mix refers to how land uses are arranged in relation to each other. If common destinations are located close together, this type of mix is sometimes known as 'clustering'.
An example of clustering is illustrated in the figure below:
A. This shows a conventional suburban development with buildings surrounded by parking and isolated from each other. There are often no paths connecting the buildings or sidewalks along the streets. Only car transport can effectively serve such destinations.
B. This shows the same buildings sited so they are clustered together and orientated toward the street, with main entrances that connect directly to the sidewalk rather than being located behind parking. This creates convenient pedestrian access between them, for example, making it easier for an employee in an office to visit an adjacent building, with a bank or shop for example (and for employees from two different buildings potentially to car share).
C. This shows eight buildings clustered around a park. As the cluster increases in size the efficiency of pedestrian improvements, car sharing and public transport services also increase, due to economies of scale.
D. This shows the eight-office building integrated into a park or campus, creating more convenient and attractive pedestrian connections between the buildings, further improving access and supporting transportation alternatives. It also creates a more enjoyable environment for employees and visitors compared with isolated buildings surrounded by parking.
Clustering At the Local Scale
Source: Online TDM Encyclopaedia
Density and mix can have significant impacts on travel demand and travel patterns through the following mechanisms:
- Accessibility: The number of potential destinations located within a geographical area tends to increase with population and employment density, reducing travel distances and the need for private travel. For example, in low-density areas a school may serve hundreds of square miles, requiring most students to travel by motor vehicle. In higher density areas, schools may serve just a few square miles, reducing average travel distances and allowing more students to walk or cycle. Similarly, average travel distances for errands, commuting and business-to-business transactions can decline with density.
- Transport choice: Increased density tends to increase the number of transport options available in an area due to economies of scale. Higher density areas tend to have better pedestrian and bicycle facilities and better public transport service because increased demand makes them more cost-effective.
As a result of these factors, higher density and clustered land use mix together tend to reduce per capita car ownership and use, and increased use of alternative modes (Jack Faucett Associates and Sierra Research, 1999).
International studies indicate that increased urban density significantly reduces per capita vehicle travel, as illustrated in the figure below (Newman, et al, 1997; Kenworthy and Laube, 1999). This occurs in both higher-income and lower-income regions.
Urban Density and Motor Vehicle Travel (Kenworthy and Laube, 1999)
Each point marked on the graph represents a major international city. Per capita vehicle use tends to decrease with density.
Holtzclaw (1994) found that average vehicle ownership, vehicle travel, and vehicle expenditure per household decline with increasing residential densities and proximity to public transport, holding constant other demographic factors such as household size and income.
Technology
This policy instrument is not dependent upon technology.
Why use land use planning to encourage less personal motorised travel?
The importance of the interactions between spatial (land use) planning and management, and the design, operation and use of transport systems, is fully recognised. Important aspects of this are (Cost 332):
- the spatial organisation engendered by the evolution of the production process increases personal mobility requirements (and those for goods movements),
- low density development, particularly in the suburbs, has encouraged the growth of travel and of multi-car households;
- the growing polarisation of commercial structures has also led to an increase in personal travel, particularly by car.
The reversal or reduction of these land use development trends will tend to reduce the need to travel in general and travel by car in particular. Land use changes, however, take quite a long time, so this is not a short-term policy instrument.
The trends listed above may be illustrated by the cases shown in the following table:
Relationship between transport and location of property development |
||
Location/land use |
Effect |
Source |
Out-of-town business parks, UK |
93% use car to travel to work |
RCEP, 1994 |
Gateshead MetroCentre, UK |
80% travel by car compared to 27% to the city centre |
TEST, 1989 |
Copenhagen insurance company moving from centre (near station) to suburbs |
Car commuting up from 26% to 54% |
ECMT and OECD, 1995 |
Supermarket on free-standing outer London site |
95% by car compared to 33% for inner London supermarket |
RCEP, 1994 |
Source: Lucas, Marsh and Jones, p.16.
The table below indicates how various land use design features are estimated to reduce per capita vehicle trip generation compared with conventional development that lacks these features (Online TDM Encyclopaedia).
Travel Impacts of Land Use Design Features (Dagang, 1995)
Design Feature |
Reduced Vehicle Travel |
Residential development around public transport nodes |
10% |
Commercial development around public transport nodes |
15% |
Residential development along public transport corridor. |
5% |
Commercial development along public transport corridor. |
7% |
Residential mixed-use development around public transport nodes |
15% |
Commercial mixed-use development around public transport nodes |
20% |
Residential mixed-use development along public transport corridors. |
7% |
Commercial mixed-use development along public transport corridors. |
10% |
Residential mixed-use development. |
5% |
Commercial mixed-use development. |
7% |
Source: Online TDM Encyclopaedia
Demand impacts
Increasing development densities and altering the development mix have an effect on demand in two ways:
- Reducing the need for motorised travel (especially private motorised travel) by ensuring origins and destinations are closer together (the topic of this section);
- Encouraging public transport use by improving conditions to enable public transport to operate more efficiently (dealt with separately under 'Encouraging Public Transport Use Through Land Use Planning' ;
It is the demand impact of the first of these which is the subject of the following table and the remainder of this section.
Responses and situations | ||
Response | Reduction in road traffic | Expected in situations |
Change of departure time is not an effect of this instrument | ||
Change of route is not an effect of this instrument | ||
Higher densities and more mixed land uses bring more destinations of a particular type within easier reach | ||
Higher densities and more mixed land uses bring more destinations of a particular type within easier reach | ||
Change of mode to public transport may occur where the change in land use makes the operation of public transport more viable, thus a better service | ||
Where a sufficient range of destinations is available within a short distance, a car may become less necessary and so some may sell it | ||
Encouraging moving house is not an objective of this instrument, nor is it a feasible outcome |
= Weakest possible response | = Strongest possible positive response | ||
= Weakest possible negative response | = Strongest possible negative response | ||
= No response |
Short and long run demand responses
Of all the instruments contained in these pages, land use instruments are perhaps the ones which, potentially at least, can have the greatest impact on reducing the amount of motorised travel. However, they are also the ones which take the longest to implement and thus to bear fruit. The greatest opportunities for change are in the circumstances of entirely new development, when land use densities and mixes may be specified in advance. Even in these conditions however, results will take years to materialise
Demand responses | |||||
Response | - | 1st year | 2-4 years | 5 years | 10+ years |
- | |||||
- | |||||
Change job location | |||||
- | Shop elsewhere | ||||
Compress working week | |||||
- | Trip chain | ||||
- | Work from home | ||||
- | Shop from home | ||||
Ride share | |||||
- | Public transport | ||||
- | Walk/cycle | ||||
- | |||||
- |
= Weakest possible response | = Strongest possible positive response | ||
= Weakest possible negative response | = Strongest possible negative response | ||
= No response |
Level of response
The amount of reduction in the amount of motorised travel in response to land use instruments, will depend on:
- the scale of the land use changes;
- the design and type of the changes, in terms of density and mix;
- the speed with which the changes are effected.
In all cases, there will be no response in the short term and very little in the medium term, as indicated in the table above.
One study of travel patterns in a North American suburb found the elasticity of transit (public transport) mode split with respect to land use density to be +0.10 to +0.51, depending on type of land use. This means that each 1.0% increase in density increases public transport use by 0.1-0.51% (Cervero (2002) in Online TDM Encyclopaedia).
Ewing and Cervero (2002) calculate the elasticity of per capita vehicle trips and vehicle travel with respect to various land use factors, as summarized in the table below. For example, this indicates that doubling neighbourhood density reduces per capita car travel by 5%. Similarly, doubling land use mix or improving land use design to support alternative modes also reduces per capita car travel by 5%. Although these factors may be small, they are cumulative. (Online TDM Encyclopaedia)
Typical Elasticities of Travel With Respect to the Built Environment (Ewing and Cervero, 2002) in Online TDM Encyclopaedia))
Factor |
Description |
Trips |
VMT |
Local Density |
Residents and employees divided by land area. |
-0.05 |
-0.05 |
Local Diversity (Mix) |
Jobs/residential population |
-0.03 |
-0.05 |
Local Design |
Sidewalk completeness/route directness and street network density. |
-0.05 |
-0.03 |
Regional Accessibility |
Distance to other activity centres in the region. |
-- |
-0.20 |
This table shows the elasticity values of Vehicle Trips and Vehicle Miles Travelled (VMT) with respect to various land use factors.
This suggests that neighbourhood design factors (density, mix and design) can reduce per capita vehicle travel on the order of 10-20%, while regional accessibility factors (i.e., where a neighbourhood is located with respect to the urban centre) can reduce car travel by 20-40%. (Online TDM Encyclopaedia)
Supply impacts
The supply implications are as follows:
- There will not be an increase in the supply of road space from land use instruments per se, though there might be additional local requirements, e.g. for access to new development, including by bus;
- If the land use policies are implemented on a regional scale, there could be a nett reduction in the need for road space (compared with doing nothing) in line with the decrease in the amount of travel;
- Higher density development could improve conditions for public transport and thus encourage greater public transport supply; (dealt with separately under 'Encouraging Public Transport Use Through Land Use Planning';
- Reduction in private motorised travel could encourage an increase in the supply of cycle and pedestrian facilities;
- Any reduction in car ownership would reduce the need for residential parking supply;
- Any reduction in 'motorised destinations' would reduce the need for non-residential parking supply.
Financing requirements
Though the costs of new development are considerable and land use solutions are, at their most extreme, the most expensive of the policy instruments contained in these pages, the cost usually falls in the main on the private sector (through investors, developers and occupiers). However, local authorities may have to bear some additional indirect costs (provision of extra traffic control, parking, public transport interchanges, etc).
Though it is difficult to cost this instrument, the range of possibilities being so large, some comments on cost can nevertheless be made.
Firstly, regarding individual developments, it has been estimated (Lucas, Marsh and Jones, p.19) that if development conforms to a standard to reflect sustainable development, construction costs will rise typically between 5 per cent and 20 per cent. Unfortunately the proportion of this extra cost related solely to attaining sustainable transport is not known but clearly there would be some additional cost if land use development had to conform to sustainable transport criteria.
There are ways of financing the extra costs of achieving a transport-friendly development policy, particularly where the extra cost would normally fall on the local authority. These ways include:
- Commuted payments
- Developer contributions
If development costs are looked at region-wide, an alternative picture on costs may occur, as illustrated in the following table (costs in Canadian dollars) (Online TDM Encyclopaedia)
Estimated 25 Year Public Costs for Three Development Options
(Blais, 1995)
Spread |
Nodal |
Central |
|
Residents per Ha |
66 |
98 |
152 |
Capital Costs (billion Canadian $ 1995) |
54.8 |
45.1 |
39.1 |
Op & Maint Costs (billion C$ 1995) |
14.3 |
11.8 |
10.1 |
Total Costs |
69.1 |
56.9 |
49.2 |
Percent Savings over status quo option |
0 |
17% |
29% |
This table shows substantial public savings for higher density land use patterns associated with transport-friendly development.
Finally, one interesting issue regarding financing is the possibility of higher land and property values arising from improved accessibility, and how the local authority can get its hands on a slice of it.
Expected impact on key policy objectives
Increasing land uses densities and modifying development mix encourage people to change their travel behaviour and in particular to travel less by car, through the mechanisms explained earlier. The resulting reduction in car travel can have significant effects on the various Konsult objectives as shown in the table below. Once again, these impacts are approximate as the scale of the effects depends largely on the scale of land use changes.
Contribution to objectives | ||
Objective |
Scale of contribution |
Comment |
By reducing motor traffic | ||
By reducing motor traffic | ||
By reducing motor traffic | ||
Through increased accessibility | ||
By reducing motor traffic | ||
More attractive location | ||
Uncertain effect |
= Weakest possible positive contribution | = Strongest possible positive contribution | ||
= Weakest possible negative contribution | = Strongest possible negative contribution | ||
= No contribution |
Expected impact on problems
The expected impacts of changes in land use density and mix on problem alleviation are summarised in the following table.
Contribution to alleviation of key problems | ||
Problem |
Scale of contribution |
Comment |
Congestion-related delay |
By reducing motor traffic in general | |
Congestion-related unreliability |
By reducing motor traffic in general | |
Community severence |
By reducing motor traffic in general | |
Visual intrusion |
By reducing motor traffic in general and the improved visual effect of "better" development | |
Lack of amenity |
By reducing motor traffic in general and the improved amenity effect of "better" development | |
CO2 emissions |
By reducing motor traffic in general and reducing congestion | |
Local air pollution |
By reducing motor traffic and congestion in local centres. Reduction in cold starts from fewer car trips. | |
Noise |
By reducing motor traffic and congestion in local centers | |
Reduction of green space |
By reducing motor traffic in general and the opportunity to incorporate green space in new development | |
Damage to environmentally sensitive sites |
By reducing motor traffic in general | |
Poor accessibility for those without a car and those with mobility impairments |
By encouraging a situation for more viable public transport and by easier movement in newly-designed centres | |
Disproportionate disadvantaging of particular social or geographic groups |
By encouraging a situation for more viable public transport, social and geographical groups are made more "accessibility equal" | |
Number, severity and risk of accidents |
By reducing motor traffic in general and in local centres (pedestrian safety) in particular | |
Suppression of the potential for economic activity in the area |
Insofar as land use planning maintains accessibility, the area should become more attractive as a location due to better amenity. If land use planning increases accessibility, this effect should be amplified. |
= Weakest possible positive contribution | = Strongest possible positive contribution | ||
= Weakest possible negative contribution | = Strongest possible negative contribution | ||
= No contribution |
Expected winners and losers
It is difficult to see how there can be any losers if policies of land use density and mix are wisely applied. This is because there should be a wider range of destinations within a given distance and public transport operations are made easier. There is no discouragement per se to any motorised mode: the reduction in traffic by reducing the need to travel will in fact benefit all motorised modes.
Winners and losers | ||
Group |
Winners/Losers |
Comment |
Large scale freight and commercial traffic |
Reduced congestion | |
Small businesses |
Reduced congestion, better public transport access for employees and customers | |
High income car-users |
Reduced congestion | |
People with a low income | Public transport access will improve | |
Low income car-users with poor access to public transport |
Public transport access will improve | |
All existing public transport users |
Public transport access will improve | |
People living adjacent to the area targeted |
They may benefit from reduced congestion and improved or increased public transport supply. | |
People making high value, important journeys |
Bus and car access improved | |
The average car user | Where they are able to travel more efficiently, saving time and money. Plus getting more exercise through modal shift to walking and cycling, and experiencing the community benefits, which accrue from these modes. |
= Weakest possible benefit | = Strongest possible positive benefit | ||
= Weakest possible negative benefit | = Strongest possible negative benefit | ||
= Neither wins nor loses |
Barriers to implementation
Scale of barriers | ||
Barrier | Scale | Comment |
Legal | Cities may not have powers to specify the requirements for a given density and mix of development. | |
Finance | New developments are expensive to provide. The scale of barrier depends on the source of finance for such developments. | |
Governance | Specifying development requirements requires an interaction between the city and the developers, who may well have other places in which to develop. In many cases the transport and planning authorities are separate. | |
Political acceptability | There will be some political opposition to imposing planning requirements, particularly if it is seen to restrict development. | |
Public and stakeholder acceptability | Opposition will come both from developers and in some cases from those living close to the development. | |
Technical feasibility | Strictly there are few technical barriers, but new development takes a considerable time to implement. |
= Minimal barrier | = Most significant barrier |
Though there are many case studies of schemes intended to reduce travel by land use planning there are few, if any, case studies which have quantified the real travel-reduction effect. The main reason for this is the difficulty of comparing before and after conditions for a measure that takes so long to implement and for effects to be felt. Most reported results relate to the comparison of existing developments with differing densities and mixes of development.
The TRANSLAND project summarised the key impacts:
- higher residential densities result in shorter trips and less car use;
- higher employment densities result in more public transport use, but longer trips;
- mixed development with traditional housing results in shorter trips and less car use;
- development more closely linked to public transport result in increased public transport use.
Contribution to objectives
Contribution to objectives | ||
Objective |
Scale of contribution |
Comment |
By reducing motor traffic | ||
By reducing motor traffic | ||
By reducing motor traffic | ||
Through increased accessibility | ||
By reducing motor traffic | ||
More attractive location | ||
Uncertain effect |
= Weakest possible positive contribution | = Strongest possible positive contribution | ||
= Weakest possible negative contribution | = Strongest possible negative contribution | ||
= No contribution |
Contribution to problems
Contribution to alleviation of key problems | ||
Problem |
Scale of contribution |
Comment |
Congestion | By reducing trip lengths and the proportion by car. | |
Community impacts | By increasing walking and cycling and the potential for community interaction. | |
Environmental damage | By reducing trip lengths and the proportion by car. | |
Poor accessibility | By reducing travel distances and increasing the viability of public transport. | |
Social and geographical disadvantage | By reducing travel distances and increasing the viability of public transport, walking and cycling. | |
Accidents | By reducing trip lengths and the proportion by car. | |
Economic growth | By increasing the viability of neighbourhood shops and local businesses. |
= Weakest possible positive contribution | = Strongest possible positive contribution | ||
= Weakest possible negative contribution | = Strongest possible negative contribution | ||
= No contribution |
Appropriate contexts
Appropriate area-types | |
Area type | Suitability |
City centre | |
Dense inner suburb | |
Medium density outer suburb | |
Less dense outer suburb | |
District centre | |
Corridor | |
Small town | |
Tourist town |
= Least suitable area type | = Most suitable area type |
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