Volume 3                    Issue 1                    November  2007

Print Version   

Impacts of Transportation Infrastructure and Services on Urban Poverty and Land Development in Colombo, Sri Lanka

Amal S. Kumarage

1.  Introduction

The City of Colombo serves both as the national capital and the largest city in modern Sri Lanka.  Colombo and its metropolitan area—referred to as the Colombo Metropolitan Region (CMR) — fall within the Western Province, which is the most densely populated and economically active region within the country (see Table 1).  Transportation activity within this region is also the densest in Sri Lanka.

Table  SEQ Table \* ARABIC \s 1 1 : Summary of Vital Statistics of Colombo Metropolitan Region

Figure 1: Sri Lanka 

History: From ancient times, Sri Lanka has been largely an agricultural economy.  In recent history, particularly under colonial rule, the development of the Port of Colombo and the availability of suitable human resources led to the majority of industries locating within one hour travel distance from the port.  The growth of industries and the development of Colombo as the administrative capital and primary commercial center of the country have formed the basis of the physical expansion of Colombo and its environs.

The legacy of urbanization dating back to the 16^th century centered on the development of the Port of Colombo under Portuguese occupation. Under British occupation in 1871, the City had an extent of 2,449 hectares with a population of 98,847 persons. The density doubled by 1931 by which time the city grew to 3,368 hectares with population growing to 284,155 largely due to annexation of surrounding areas. This density doubled by 1981, by which time the land area had reached a near maximum of 3,711 hectares. The most recent strategic land use plan has proposed to reduce the extent of residential land use from 1,401 hectares to 691 hectares by 2010 in order to provide for more commercial development (UDA, 1998). 

Geographic: Colombo is a relatively small city with a resident population of around 700,000 with a day time inflow of a million persons. Its area is 3,730 hectares. The Colombo Metropolitan Region (CMR) which serves as the suburban feeder area for Colombo city has a population of over 5.3 million with a gross population density of 15 persons per hectare. In the City of Colombo itself the density is 188 persons per hectare.

Table 2: Population (2001)

Demographic: The land use distribution in the City of Colombo shows that residential use takes up 40%, of the available land, while transport & communications takes up 13%, with a further 30% presently developed for commercial and administrative purposes, with around 17% land bare or still under non-urban use. The residential densities within the city range from between 165 to 1,537 persons per hectare (UDA, 1998). The highest densities are accompanied by concentrations of people living in illegal squatter settlements that are badly overcrowded with respect to facilities available within them. These have, however, become popular forms of settlements for the poor in the absence of affordable public or private sector housing programs. It is estimated that at present about 35% of the city’s population lives in these settlements, which have semi permanent houses, shared toilets and poor sanitation conditions. This shortage of housing for the poorest sections of the city is commonly attributed to economic indicators, particularly affordability to the low income consumer to purchase or rent, scarcity of land and high land prices and high construction costs.

Transport: During the period 1961 to 1979, the traffic flows crossing the city boundary increased at the rate of 2.8% per annum. However it has increased at a much higher rate of 5.4% per annum over the last two decades. The passenger growth observed during the period 1985-95 was 4.7%, with bus transport growth at 4%, private vehicles growing at 11.8% and railways at 2.8%. It analyses the fact that these growth rates are inversely proportional to the cost of travel. In other words, the cheapest forms have had the lowest growth. In all, there are presently an estimated 2 million passenger crossings (both directions) per day in 315,504 vehicles of which 80% are private vehicles (Kumarage, 2000). The desire lines which indicate the direction, distance and volume of flow arriving at the centre, for the commuting trips to Colombo City can be illustrated as in Figure 2. This shows that commuting trips are rather short distances, with a few exceptions, where low cost railway travel is available.

Housing: It is estimated that around 25,000 to 30,000 new houses would be required to house these low income families adequately. The land that is presently occupied by these settlements can be used partially for this purpose. However, most resettlements would have to take place outside the city. The land values in Colombo City during the period 1985 to 1998 increased at the rate of 16.5% per annum (p.a.) in nominal terms and adjusted for inflation this is approximately 5% p.a.  (UDA, 1998) while that of the suburban areas increased by around 18% p.a where the real rate was around 6.5% p.a..  This makes purchase of land nearly impossible for poor people. The alternative areas for relocation are located at distances between 20 to 30 kilometres (kms) from the city centre.  The relocation of the poor to these locations will make accessing jobs in the city more difficult for them. It is most unlikely that they will move since it adversely affects their livelihood.

Income: Income Distribution for the Western Province, as calculated from the Sri Lanka Integrated Study (1999/2000) data, is given in Table 3.  This reinforces the position that two-thirds of the population is not engaged in income receiving occupations.  It seems that a significant proportion of income receiving (34%) fall within the lower half of income range of up to Rs 3,000/= per month (US$ 430), while 11% falls in the income range of over Rs. 10,000/= (US$ 1,430) per month.

 Table 3: Income Distribution (1999/2000)^[2]

2.  Objective & Scope of Paper

The Sri Lanka Transport Sector Strategy Study (World Bank, 1997) notes that poverty alleviation requires a transport policy that is focused on the poor.  The lack of such a policy and of relevant information has made it difficult to analyze how the transport sector is serving and helping the poor.  It has been assumed that the mobility needs of the poor could be resolved by improving transport networks and public transport services in both rural and urban areas. 

Policies should address, among other things, the best ways to provide adequate and affordable access for the poor to get to work, particularly in rural and marginal urban areas, opportunities for generating employment through the transport sector, and the strategic use of transport to reduce regional disparities. There are no studies where the transport needs of the poor have been studied specifically.

This paper examines the relationship between employment of the low income earners, their places of residence, and the transport linkages that are made available.

3.  Analysis of Income and Transport in the Western Province

This analysis is undertaken from aggregate socioeconomic data collected through Census and other household surveys and published from time to time. This data is not available for the City of Colombo. It does however exist for the Western Province. The objective of this analysis is to identify the patterns of (a) expenditure on transport and (b) of income of those living in the Western Province.

3.1  Individual Income and Distance of Travel to Work

Data from the Sri Lanka Integrated Survey (1999/2000) have been used to analyze the relationship between place of work and place of residence.  Table 4 shows results for the Western Province (WP) compared to the rest of the country where over half of people working, do so within their own community.  This could be interpreted in several ways.  First, it might suggest that population is so distributed that the majority of the employment opportunities are located outside the communities they live in.  Second, it might suggest a higher mobility for finding employment outside the local community, due to existence of acceptable transport services. 

Table 4: Relationship between Place of Work and Place of Residence

Table 5 gives the cross-relationship between income and place of work/place of residence for the Western Province.  These two tables show that there is a direct correlation between individual incomes and the propensity to seek employment in other communities. This is an interesting phenomenon that could be due to the fact:

(a)    That those who are able to commute outside their communities can get better incomes.

(b)    That those who have higher incomes tend to seek employment away from their own communities.

Table 5: Individual Income and Place of Work with Respect to Place of Residence – WP

In the case of (a) it relates to the availability and affordability of transport. This implies that poor transport will make people immobile and captive to their own communities, thus preventing them from accessing and holding employment that is higher paying. Both Tables 4 and 5 indicate that only those with incomes less than 1000/= per month appear to show a marked difference to other income categories with respect to the percentage of persons working within the same community.  The amount of income that falls within this category in all probability refers to part time employment which cannot be compared with the full time employment as the commuting distances would be very much less in the case of the former.

In the case of (b) above, it is a known social factor that higher paid employment is generally concentrated in centers (usually urban) and thus the average commuting distances would increase as people seek higher paying employment. This argument also can be used to explain why the percentage working in other urban areas increases with income and then begins to decrease  when monthly incomes increase beyond Rs. 10,000/=. This could possibly mean that relocation becomes more affordable when incomes are in that magnitude. The reverse inference of this observation is that when incomes are less than Rs 10,000/= per month, people are more likely to be constrained by the availability of transport facilities in seeking employment away from their community of residence.

A comparison of the two tables indicates that in the Western Province, there is higher mobility between residence and employment communities for the same income groups. This means that people have to commute further as residential and employment areas tend to be more separated in urban and suburban areas.

3.2  Occupation and Travel to Work

Table 6 gives the cross-relationship between type of occupation and place of work/place of residence for the Western Province.  There is relatively little mobility among those engaged in agriculture, as many people in this category are farming their own land or fishing, both activities generally being located close to residences.  Those in business, trade, and manufacturing activities also appear to be, in general, residing close to their places of employment - for example, family-based businesses where home and shop or home and trade are located within the same premises.  On the other hand, casual labour shows a somewhat higher propensity to seek employment in urban centers.  These might be persons who are engaged in construction or similar work and who might not actually be commuting on a daily basis - more because of distance than transport fare.  Salaried employees mostly travel outside their communities to urban communities for employment and show the highest degree of mobility.

Table 6: Type of Occupation and Place of Work with Respect to Place of Residence - WP

3.3  Income and Ownership of Vehicles

Ownership of all types of vehicles in the Western Province increases with income, as shown in Table 7.  All income groups own bicycles in significant numbers and bicycles are the most common vehicle owned. Motorcycles are also used by all income groups, although their ownership levels become significant only when household incomes rise above Rs 5,000 per month.  In the case of cars and vans, ownership is recorded even at low income levels, but becomes significant only when household incomes reach Rs 25,000 or more. 

 Table 7: Vehicle Ownership per 100 Households by Income (Rs/month) - WP

3.4  Percentage of Income Spent on Transport

The analysis of expenditure on public transport as a percent of expenditure on transport incurred by three different income groups is given in Table 8.  This clearly confirms the earlier trend but also provides information that the income group with less than Rs 3,500/= for monthly incomes are clearly captive to public transport, while this figure falls to around 50% to 60% percent of households when incomes are between Rs 3,500/= to Rs 10,000/=.

Table 8: Distribution of HH Income Groups by Expenditure on Public Transport (2000)

3.5  Expenditure on Public Transport and Income

Data from SLIS (1999/2000) have been tabulated in Table 9 to show the percentage of household expenditure spent on public transport by income group, for the Western Province.  The table shows that the percent of expenditure on transport is below 3 percent for the majority of households, irrespective of their level of income. The higher percentages are to be found among those households with higher incomes. However, it should be pointed out that the vast majority of public transport travel should be undertaken by those in the higher income categories. In this respect it should be noted that since the consideration is by household income and not individual incomes those households with several income-earning members would have a higher income but also a proportionately higher transport cost due to increased travel to work.

Table 9 does, however, indicate that the higher percentage expenditure on public transport is concentrated in the middle class households where incomes range between Rs 3,000/= to Rs 25,000/= per month. In the case of those households with incomes less than Rs 3,000/=, less than 2 percent of households incur more than 9 percent of their expenditure on pubic transport and less than 6 percent of the households incur more than 6 percent of expenditure on public transport. The respective values are higher and nearly double in the Western Province. This means that the urban poor appear to spend proportionately more on public transport than the rural poor do. This could be due to difficulties in using alternative modes of transport in urban areas, particularly bicycles; or else it could also be due to longer distances to work and school.

Table 9: Percent Expenditure on Public Transport by Income Group (WP)