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In data-scarce environments, disruptive thinking is needed: Freetown transport resilience

Fatima Arroyo Arroyo's picture


When our team started working in Freetown one year ago, we found very limited data on how people move or what are the public transport options to access jobs and services from different neighborhoods. How do you plan your public transport system when you do not have data? And what if you are also constrained by a highly vulnerable environment to natural disasters and poverty? Keep reading: Disruptive thinking has the answer.

Context

Freetown, Sierra Leone’s capital city, is a vibrant city with an increasing population and a growing economy—and probably the best beaches in the region. It is a densely populated, congested city situated on a hilly peninsula surrounded by the Atlantic Ocean, the estuary of the Sierra Leone River and mountains, with very little flat space. The city creates 30% of the country’s GDP, which evidences the importance for the national economy. Although Freetown is the main employment center in Sierra Leone, the access to jobs and services in the city is heavily impaired by inadequate transport services and infrastructure and a chronic congestion.  

The public transport services in Freetown are experiencing a rapid growth of unregulated, informal operators mainly minibuses (called poda-podas). Poda-podas, which are often not professionally driven or adequately maintained, are part of the solution to provide access to jobs, especially in the poorest areas of the city; and at the same time a great contributor to congestion, pollution and road safety issues.

Freetown is one of the most vulnerable cities in the world to climate change and natural disasters, especially to flash-floods and landslides. The urban transport system is at very significant risk from climate impacts, exacerbated by poorly engineered and constructed roads and drainage structures in very poor condition due to deficient maintenance. Climate change is going to aggravate this risk as projections indicate an increase of the maximum 1- and 5-day rainfall especially during July-September. This risk was evidenced by the August 2017 terrible landslide and floods.

Disruptive thinking: how to plan a more resilient urban transport system and how to make these ideas a reality?

Our goal is to support the Government of Sierra Leone to plan its transport infrastructure and transport services to become a more resilient city. We had in mind three main ideas: (i) let’s understand how flooding impacts transport services; (ii) let’s compare how people move different in rainy season and out of rainy season (comparison of mobility patterns); and (iii) let’s analyze the changes on accessibility due to climate impact. And we started thinking how best we could make use of technology in this data-scare environment…

We only had a hint of the impacts to start with…financial documents from the Transport Corporation suggested a reduction on fare collection of about 20% during the rainy season!

(i) let’s understand how flooding impacts transport services

First, we decided to map all the bus routes in the city – formal routes and poda-poda routes – to create the first comprehensive map of the bus network. Thanks to the DataCollaboratives Initiative, we partnered with WhereIsMyTransport for this task. A group of bright and motivated students from Fourah Bay College made this mapping possible. They used mobile phones to map all routes and gather other information, such as fares and bus frequency.

Second, we mapped all the areas in the city that suffer recurrent flooding during the rainy season. The same group of smart local civil engineering students used Roadlab app to map the locations and gather data about drainage and culverts state.

Having data on bus routes and flooding locations, we plan to understand how transport services are affected by weather related events.

(ii) let’s compare how people move different in rainy season and out of rainy season (comparison of mobility patterns)

With the first question we could see how, where and when the supply of public transport is affected by climate impacts but how does that translate to the demand of public transport? How does its mobility patterns change during rainy season?

Again, with limited budget and almost no-date we needed to push creative thinking again. Using similar approaches as in other countries, we partnered with the Ministry of Communications to make use of CDR data. CDR has been using recently to identify origin-destination matrices that are the basis of mobility studies. Here, we are going a step forward. Splitting the data into two, rainy season and dry season, we are seeing substantial difference on number of trips and reached destination.

But what areas of the city see the largest impacts? What are the poverty rates and job opportunities there? How longer does it take to reach same destination during rainy season? These questions led us to the third main idea: (iii) let’s analyze change in accessibility due to climate impact.

Our work in not done yet and the colleagues in the Big Data team, and top-notched researchers at University of California Berkley are helping us to find those answers to make the transport service provision in Freetown more resilient, because we believe that if the transport services are less impacted by flooding, people will be less impacted to access economic opportunities and social services.
 

This work is funded by the Global Facility for Disaster Reduction and Recovery (GFDRR)Resilience to Climate Change.
 

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