With an estimated population of about 5 million and an annual growth of 8 per cent, Dar es Salaam in Tanzania, is Africa’s fastest growing city. Over 70 per cent of the people live in informal, unplanned settlements with inadequate infrastructure. In addition, heavy rainfalls twice a year result in significant flood risks.
To reduce the risk of loss of lives, homes and property, a broad coalition of private sector, academic, humanitarian and development institutions looked at a combination of drones and community mapping to create risk maps and a hydrological model. Neither had been previously available due to a lack of high quality digital imagery.
Conventional methods that rely on qualitative data and satellite imagery with a resolution of 30 cm were available, but were severely limited. The city is growing and changing at such a rate that satellite imagery often becomes outdated within a year. Aerial images obtained with airplanes were often limited due to cloud cover.
The data was collected using fully automated eBee mapping drone manufactured by Sensefly and piloted by the non-profit organization Drone Adventures. Initially the drone mapped a section of several kilometers of the highway, the river and part of the Tandale neighborhood. The results were shared with local government officials and city planners, who then provided input for priority areas for the second mapping phase. During this second phase the majority of the data was obtained, including 20,000 optical images covering an area of 88 km2 with an average resolution of about 5 cm. In order to achieve this kind of coverage, 2-3 eBee drones were flying simultaneously operated by one pilot.
Data processing was done in Switzerland over a period of 6 weeks with high-memory speed processors that produced a total of 700 GB of data. The dataset was so large that it had to be mailed physically on a hard drive to Tanzania.
The Tanzania Commission for Science and Technology (COSTECH) made the data available to the public and published raw images on OpenAerialMap, a collection of openly licensed aerial imagery. The Humanitarian OpenStreetMap Team (HOT) organized local volunteers to first determine the respective communities’ mapping priorities and then digitized roofs, roads, drains, and trees and to mark businesses and roads. The result is a digital street map that shows businesses, and critical infrastructure with unprecedented accuracy.
It is too early to understand the full impact of having this kind of high quality imagery for decision-making and flood risk mitigation. However a few clear uses and advantages have already emerged:
- Local authorities are using the maps to inform urban planning decisions
- Public health officials are planning to use the detailed ward maps to improve their response to cholera outbreaks
- The exposure maps that include up-to-date buildings and infrastructure now enable planners to identify places that get flooded and to pinpoint where drainage systems need to be installed. This has even helped the city council acquire funding from the central government.
- Deterministic flood models have been created with the help of drone images. These can help understand potential inundation zones.
According to Mark Iliffe from the World Bank, “creating a flood inundation model is the holy grail but we have not been able to achieve this yet”. However, the work is still in progress.
Local authorities and communities were involved throughout the planning, data collection and data use phases and state officials were present every day of the drone flights.
Often little is known about community social acceptance on the use of drones for humanitarian or development purposes. However, in Dar es Salaam FHI 360 interviewed 14 high-level government officials and 208 community members who witnessed drone flights over the city. The study found that both “community witnesses and government officials were positive about the potential of [drone] technology in Tanzania”. Among many other potential uses, both community members and government officials noted disaster relief and the transport of medical supplies as promising applications. General concerns included the potential for accidents and for threats to national security. In addition, some of the latrines in the mapped communities do not have covers, raising concerns related to visual privacy among community members.
Both the Tanzanian government and the World Bank plan on continuing the use of drones for mapping purposes. The government is seeing the maps as a baseline to understand how the city is developing and changing following improvements to infrastructure and COSTEC has now developed the capacity to do follow-up mapping on their own. On the strength of the success of the initial mapping, the Tanzanian government is planning to complete mapping of the remaining areas in Dar es Salaam, as well as creating annual maps for change detection. The World Bank also intends to continue to use drones, however some concerns regarding the future regulatory environment have been expressed. This effort was only possible because of the close collaboration with the Tanzanian government and because there are no limiting regulations on the use of drones in place.
Over the next months, Droneblog will feature summaries of case studies that show how drones are already being used in disaster response operations worldwide. The case studies were produced under the leadership of the Swiss Foundation for Mine Action (FSD) and with funding from EU Humanitarian Aid. The goal of this research initiative is to identify use cases in which cases drones can improve the quality or increase the efficiency of humanitarian aid.
You can find more information about this and other case studies on http://drones.fsd.ch/
- How Drones Can Help in Humanitarian Emergencies - December 2, 2016
- How firefighters in the UK are pioneering the use of drones - November 8, 2016
- How Drones Can Help Improve Refugee Camps - October 26, 2016
- The benefits and limits of drones in search and rescue - October 24, 2016
- How Drones are Helping in Haiti - October 18, 2016