Final Q&A with the Humanitarian OpenStreetMap Team

Cristiano Giovando and Tyler Radford from the Humanitarian OpenStreetMap Team talk about the successes, challenges and next steps for their HIF-supported project to develop and implement an open sourced Humanitarian OpenAerialMap.

1. In layman’s terms can you describe what your HIF-funded project aimed to do and why is it innovative?

The OpenAerialMap (OAM) concept came about in 2007 when we noticed that although aerial and satellite imagery was being collected it was only available on different systems and to varying standards. Since then we have been trying to find a way to put that information in a common place – a single platform – that’s easy to access for mapping tasks. We designed the software to be open source and easily replicable, particularly in emergency settings where you need to get imagery quickly and easily from different sources in order to inform a response.

2. Did you achieve what you set out to?

Yes. The original idea was something that a group of students at San Diego University and members of the Open Street Map community envisioned in 2007. The Humanitarian OpenStreetMap Team (HOT) was founded after the Haiti disaster in 2010. With HIF funding in 2014 HOT began developing the OAM concept for humanitarian settings and how to make it all open sourced. Images collected from satellites and drones have been used and contributed to OAM. The original intention of the project was narrow but we are seeing people use the imagery for all sorts of humanitarian projects.

3. Can you give a specific example in practice of how OAM has improved humanitarian interventions?

The range of beneficiaries is broad. For example, a project sponsored by the World Bank focuses on flood risk modelling where local groups in Dar es Salaam, Tanzania, are collecting imagery and sharing it through OAM. This makes it available for thousands of local and online volunteers who are mapping roads, buildings and many other features. This gives us the most comprehensive map of Dar es Salaam which is useful because it’s an area prone to flooding, and the mapping has helped local groups to develop strategies for resilience.

HOT has also trained a number of local students and professionals to use the map data and they are beginning to use this in urban planning activities, although it may be too early for the full impact of the OAM to be realised.

Another example is rapid mapping after a disaster, such as the Nepal earthquake where maps derived from open imagery were used by humanitarian responders to plan logistics and coordinate response; these maps can be updated daily so responders can reach affected people even when a road has been cut off.

4. You mentioned in your final report that one of the challenges was that lessons learned were not circulated to humanitarian stakeholders and actors. How did you over come this or do you plan to disseminate your lessons learned?

The original schedule for the project was 12 months but due to a lack of capacity, scaling was late to take off. Since January 2015, thanks to a collaborative design process and development contributions by very skilled coders, OAM was swiftly created and published. The intense 8-month period of project development did not leave much time for wide diffusion of lessons learned, which instead only started in fall 2015 through a series of presentations at conferences and stakeholder meetings.

5. What were the main learnings? And what advice do you have for others embarking on similar projects?

The process was a learning experience from the start because of its open collaborative approach and community involvement. All communication and design has been open and public using chat platforms such as IRC and Gitter. I would recommend this method to others because they can easily get more feedback as the project is being developed. This was really beneficial.
One other thing that we learned was to include elements in the metadata of each imagery data set that is specific to humanitarian response e.g. why was the data collected. We initially wanted to keep the imagery search process simple, but realised that more metadata would ensure optimised and accurate search functions. For example by tagging all imagery collected for the 2015 Nepal earthquake response with a common metadata tag, it makes it easy to quickly retrieve all data available for that event.

We’ve also been learning from groups on the ground e.g. the World Bank team in Tanzania, and UAviators who are collecting data on Nepal with drones, and incorporated their feedback in the design process. We keep working with them to understand how they’re collecting imagery and how to easily bring it into OAM.

6. What would you do differently?

Sometimes open source software communities tend to be practical and develop prototype code without adhering to complex interoperability standards. These standards from the likes of ISO and OGC have been around for years but aren’t always practical for providers to use. Not using standards makes it difficult to find and share imagery efficiently. At the moment OAM uses an open API which allows for integration with most international standard interfaces, but it does not natively publish ISO compliant endpoints. In the end it worked out, but ideally standards should be implemented at all stages of development even if this slows down the process or makes it more difficult.

7. What are some of the main outcomes?

People can now use OpenAerialMap . Anyone can find and upload imagery to it. HOT has been supporting specific hosting of imagery for humanitarian scope, but at this stage it wouldn’t be sustainable to allow non humanitarian-related imagery in terms of infrastructure, capacity, and costs.

The OAM community is raising awareness about openly licenced imagery is a concept still not understood by many. People think that using imagery from Google Maps is legal for anything they want to do but it’s not. OAM is different from Google Maps and other proprietary mapping services for several reasons: it’s open source; legal to use for any scope; anyone can contribute imagery to it; it can be used to derive map features such as the footprint of a building or trace roads; and anyone can access the source imagery as GIS files, allowing for further image analysis.

8. What are the plans for OAM moving forward?

We want to focus on scalability, additional development, socialisation and awareness raising. We’d like to have better marketing materials and involve more communities who create and use open imagery. HOT gets requests from partners all the time to do mapping activities on the ground, so we need a dedicated coordinator to manage that and work on ingesting imagery from our partners. Many humanitarian organisations are already aware of OAM such as the Red Cross, MSF, and UN OCHA, but there is much more to be done to engage with large and small organisations particularly those that focus on preparedness, response and resilience. Often the challenge with local organisations is that they don’t have personnel trained to work with imagery, so we would like to provide simplified online tools to make it easier for these partners to extract information and do analysis from OAM imagery.

9. Do you have plans to take your project to scale?

We are actively seeking further funding. The project has been developed well so far but we have many more ideas for further development. We received a grant from Amazon to support the infrastructure until the end of 2016 . Now the challenge is how to diffuse the system, socialise the platform and raise awareness. To make this happen we need funding for a technical coordinator to facilitate obtaining, processing and getting the imagery into the platform. We have already been in talks with several donors to secure this funding. We are also considering whether we can integrate this with existing platforms to make it easier for people to contribute.