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To measure the real impact of transport services, affordability needs to be part of the equation

Tatiana Peralta Quiros's picture

Differentiating between effective and nominal access

A couple of months ago, one of our urban development colleagues wrote about the gap between effective and nominal access to water infrastructure services. She explained that while many of the households in the study area were equipped with the infrastructure to supply clean water, a large number of them do not use it because of its price. She highlighted a “simple fact: it is not sufficient to have a service in your house, your yard, or your street. The service needs to work and you should be able to use it. If you can’t afford it or if features—such as design, location, or quality—prevent its use, you are not benefiting from that service.” To address this concern, the water practice has been developing ways to differentiate between “effective access” and “nominal access”—between having access to an infrastructure or service and being able to use it.

In transport, too, we have been exploring similar issues. In a series of blog posts on accessibility, we have looked at the way accessibility tools—the ability to quantify the opportunities that are accessible using a transit system—are reframing how we understand, evaluate, and plan transport systems. We have used this method that allows us to assess the effectiveness of public transport in connecting people to employment opportunities within a 60-minute commute.

Incorporating considerations of cost

Yet, time is not the only constraint that people face when using public transport systems. In Bogota, for example, the average percentage of monthly income that an individual spends on transport exceeds 20% for those in the lowest income group. In some parts of the city, this reaches up to 28%—well above the internationally acceptable level of affordability of 15%.

How does accessibility re-frame our projects?

Tatiana Peralta Quiros's picture
The increasing availability of standardized transport data and computing power is allowing us to understand the spatial and network impacts of different transportation projects or policies. In January, we officially introduced the OpenTripPlannerAnalyst (OTPA) Accessibility Tool. This open-source web-based tool allows us to combine the spatial distribution of the city (for example, jobs or schools), the transportation network and an individual’s travel behavior to calculate the ease with which an individual can access opportunities.

Using the OTPA Accessibility tool, we are unlocking the potential of these data sets and analysis techniques for modeling block-level accessibility. This tool allows anyone to model the interplay of transportation and land use in a city, and the ability to design transportation services that more accurately address citizens’ needs – for instance, tailored services connecting the poor or the bottom 40 percent to strategic places of interest.

In just a couple of months, we have begun to explore the different uses of the tool, and how it can be utilized in an operational context to inform our projects.
Employment Accessibility Changes in Lima,
Metro Line 2. TTL: Georges Darido

Comparing transportation scenarios
The most obvious use of the tool is to compare the accessibility impacts of different transportation networks. The tool allows users to upload different transportation scenarios, and compare how the access to jobs changes in the different parts of the city. In Lima, Peru, we were able to compare the employment accessibility changes that were produced by adding a new metro line. It also helped us understand the network and connectivity impacts of the projects, rather than relying on only travel times.

Understanding spatial form
However, the tool’s uses are not limited to comparing transport scenarios. Combining the tool with earth observation data to identify the location of slums and social housing, we are to explore the spatial form of a city and the accessibility opportunities that are provided to a city’s most vulnerable population.  We did so in Buenos Aires, Argentina, were we combined LandScan data and outputs from the tool to understand the employment accessibility options available to the city’s poorest population groups.

Rehabilitating roads.... one SMS at a time...

Chris Bennett's picture

The SMS message was “Drainage is not being done properly in the village Achajur. Please fix.” While it was disturbing to hear that there were problems in one of the projects I was responsible for, at the same time I was very encouraged since this proved the value of an SMS-based system we developed to facilitate local residents advising on social, environmental or engineering issues on our project.