Urban Density

Defining Density

The term urban density is multifaceted and covers a broad range of urban characteristics. The relationshi
p between Transit Oriented Development (TOD) and urban density is critical. TOD concentrates most growth and development within a short walk of frequent transit stops and stations giving rise to concept of an active node with mixed economic and commercial market-from-charni-roadactivities. The form of development varies from community to community based on local goals, character, and needs and there is no ‘one-size-fits-all’ approach to achieving an appropriate level of density to support transit. Different studies have highlighted different types and appropriate levels of densities and their relation with various factors including the transit system and travel pattern.


Density, precisely mean the mass or number per unit area, focusing on utilising the available land resource efficiently. Traditionally density has been measured/mapped using built density, residential density and population density.

Measuring Density

To understand the impact Transit Oriented Development has on an urban area, it is critical to measure its impact on urban density over a period of time. To achieve the same there are multiple methods actively followed to calculate it efficiently and effectively, based on the urban context, activities generated as a result, and other concerned factors.

Vancouver Transit oriented community design guideline 2012 suggests concentrating and intensifying activities near frequent transit; focus density in urban centres and around frequent transit corridors and nodes to support a strong demand for transit service; and plan for density that supports community character and promotes quality of life. The strategy for development involves using the valuable land near high-demand transit facilities as efficiently as possible.

Measuring Built-up Area: Floor Space Index (FSI) or Floor Area Ratio (FAR) is the ratio of built-up area of all floors on a plot to the total area of the plot. Built density defines the urban fabric or the form of development; higher this value taller is the built form of the city, other things remaining constant. Builtup area is measured as FSI in Indian cities. FSI values are traditionally capped within Indian cities by using the development control regulations, resulting in a low rise urban form within the cities. To capitalise on the development opportunities in TOD, it is recommended to concentrate the built-up area density (through use of higher FSI) within a walking distance (500 to 800 metres or roughly a 10 minute walk) or a bikable distance (1 km to 1.5 km, roughly about 10 minute bike ride) from the transit stations.

Measuring Households (Residential Density): The number of households (HHs) or dwelling units (DUs) per unit area defines the residential density. It helps to estimate the land area required to accommodate a given population. This measure generally forms a part of the housing strategy with the city planning process. Increasing residential density gives an opportunity to improve affordability of land by distributing the cost of development among a greater number of households and lead to an efficient use of the associated resource and services. London uses the concept of measuring and increasing the residential densities in areas well served by transportation infrastructure. The housing strategy for London recommends densities varying from 30 DUs per hectare in suburban areas to 435 DUs per hectare in central London (Greater London Authority, 2003).
This estimate guides the provision of infrastructure and services for present and future population and indicates where densities may need to be regulated to achieve an optimum level.

Measuring Population: By measuring the number of persons per unit area, population densities estimate the space available or consumed per person. Population density is often further classified into day-time and night-time densities to distinguish between the number of visitors, workers and residents within the area. Higher the difference between day-time and night-time densities, higher is the imbalance in mix of land-uses. Moreover a high number of households and a high value of night time density indicates higher number of people per household. This helps define the capacity of the existing infrastructure and guides the provision of infrastructure and services for future population.


Measuring employment/ jobs: For any TOD, jobs available per household near the transit station is an important parameter to guide the level of density and manage the travel demand. Jobs/HH is a measure of non-residential area needed to support the economic productivity of a space. Mixed-use developments with significant jobs per households ratio will improve diversity. State of Florida, Department of transportation density guideline matrix suggests a range of 15 jobs/HH in urban core (predominantly non-residential) areas having commuter rail or LRT and 4 jobs per household in areas having equal mix of residential and non-residential uses, served by bus. In this standard jobs/ sq. km varies from 40,000 to 2,00,000 jobs based on mode of public transport. Similarly, Ottawa’s comprehensive plan suggests 20,000 to 25,000 jobs/ sq. km for any mixed use development.

Employment density / job density also refers to average floor space available per employee. It is often used as a measure of intensity of use and an indicator of space available per person within a workplace. Employment densities are significant as they have a direct influence on the utilisation of the commercial spaces, thus defining the economic productivity of the space. The City of London has around 97,000 employees/ sq. km, and Canary Wharf, has around 2,32,000 employees/ sq. km (Buchanan, 2008). The employment density depends on the nature of activity. For example, in an industrial space it will be different from that in a space with service sector. Employment density measures can be used to estimate the level of gross employment that can be accommodated within an area.

Cities are complex systems and thereby require multiple views of urban densities at different scales of urban fabric. Indian cities have relied entirely on FSI to regulate densities thereby ignoring the other important parameters. This has therefore deterioriated both the housing and the infrastructure (including public spaces) within the cities. Density regulations for TOD has to be based on high builtup density, high household density and high population density provided that other mitigating elements such as open space provision, pedestrian circulation networks and public transportation corridors are available.

Built Density and Population Density

Dharavi has low FAR: 2, high du/ha: 630 and high population density – 3148 ppH.
Kwong Ming Court, Hong Kong has high FAR – 12.5, high du/ha – 1507, high population density – 4910 ppH.
The Esplanade has high FAR – 9.6, low du/ha – 361, low population
density – 591 ppH.


Kwong Ming Court,
housing estate Hong

Cambridge, MA, The,


Densities, FSI and Crowding

In Mumbai a family averages about 5 people, living typically in an apartment of 25 sq m. That is 5 sq m per person. In Manhattan the apartment size is typically 1,000 sq ft (about 90 sq.m) and occupancy averages 1.7 persons. The average floor space there works out to 55 sq.m per person. Each Manhattan resident occupies 11 times as much floor space as a Mumbai resident. So for the same plot area, FSI 11 will have 11 times the built-up floor area as FSI 1. But because of the space each family takes up, FSI 11 in Manhattan will have the same number of people at FSI 1 in Mumbai. Similarly, in terms of head count, FSI 15 in Manhattan corresponds to FSI 1.33 in Mumbai. These apparently very different FSI values of 15 in one place and 1.33 in another, will give us identical levels of street crowding in both cities. So when you compare FSI in different cities you need to also remember how much floor space each resident occupies in each of those cities (Praja, 2014)

Sirish B. Patel, proposes using crowding as an alternative measure. Indoor crowding, park crowding and amenity crowding. He advocated that FSI alone cannot be a tool for density mapping. He defines Indoor Crowding (IC) as occupants per hectare of built-up area and Street Crowding (SC) as occupants per hectare of street area.

So, instead of saying that in Mumbai people live in 5 sq.m per capita, and in Manhattan occupy 55 sq.m per capita, we can say that in Mumbai Residential Crowding is 2,000 persons per hectare (a hectare is 10,000 sq.m), and in Manhattan Residential Crowding is 182 persons per hectare of built-up residential area. It is an inversion of the residential space taken up per capita (Praja, 2014).

Successful TODs such as Canary Wharf and King’s Cross consider all views of urban densities discussed above. Even Indian cities, such as Delhi have recently recognised these relationships for housing, transportation and infrastructure provision. This can be seen in the Draft TOD policy of Delhi Development Authority from 2012, which mandates that 50% units of size ranging between 32 to 40 sq.m and the balance 50% comprising of homes ≤ 65 sq.m.

These discussed measures alone are not the only ways to measure and regulate density but depends on multiple other factors such as social construct of the urban area, proposed or existing urban policies and projects for the city, existing economic growth magnets and possible target areas for development. Thus, apart from these there are other measures that can be used to map density. These includes street crowding, an indicator of footfall on street and in public places; and availability of open spaces per person, addressing quality of life.

Density in Indian Cities
Over 377 million people live in about 8000 urban centres in India. As per Census of India 2011, there are 3 cities with population greater than 10 million and 53 cities with population greater than 1 million. Top 10 cities having 8% of the total urban population live in just 0.1% of the total land and 53 million plus cities have 13.3% of urban population in 0.2% of the land area in India. Pushkarev and Zupan in 1977 prescribed minimum residential densities ranging between 5400 persons/sq.km to 9000 persons/sq.km (Victoria Transport Policy Institute, 2016) depending on the mode of transit for a TOD. Similarly, State of Florida transport prescribes gross population densities ranging from 10000 persons/sq.km to 20000 persons/sq.km in TOD zones based on mode of transit. In the 33 smart cities announced in the first year of Indian Smart Cities Mission, average city densities varies from values as low as 980 person/ sq. km (Dharamshala) to values as high as 26,555 person/ sq. km (Chennai). Analysis of densities in these 33 cities reveal that even the 75th percentile is only 8719 persons/ sq. km (Bhagalpur) and the average density in is 5916 persons/sq.km. Therefore, in case of tier 3 cities like Dharamshala, Panaji, and most of the tier 2 cities such as Raipur, Ranchi etc., there is a definite need to increase densities to support transit investments, pcrowd-167074rovided that other parameters such as housing, public transportation, pedestrian and NMT infrastructure, and urban design are improved. In tier 1 cities of India such as Mumbai and Chennai, densities are high and sufficient for transit, therefore requiring interventions in other aspects of TOD so as to improve the quality of the urban space. The second highest density in the smart cities of first year amounts to only 13,304 persons/ sq. km (Surat), which is considerable lower than the highest density (Chennai).
Even though average densities are low in most of the Indian cities, their core areas have sufficient densities which can generate a demand for public transit system, which may vary from bus based systems to heavy rail depending on the density. In areas in the cities where the densities are low, re-densification together with improvements in urban space (NMT and pedestrian infrastructure, housing and urban design) becomes an important tool. TOD therefore is a tool to optimise densities to improve quality of life.