Coastwards is an online Citizen Science platform launched in 2017 and funded by the Excellence Cluster 'The Future Ocean'. It aims at collecting data on coasts for research on the risks of sea-level rise.
Sea levels are projected to rise between 29 and 110 cm until the year 2100. Coastal regions will have to adapt to these changes, adaptation measures however cost money. Decisions on which coasts to protect and how to do so are often based on calculations of risk. These calculations are made by 'Integrated assessment models'. They take in huge amounts of data on coastal zones defined by hundreds of parameters.
One of these parameters is the coast material. It determines how vulnerable a given coast is to erosion. Sandy beaches erode more easily than rocky cliffs; erosion raises the risk.
And here lies the problem. Scientists do not have sufficient data for this parameter. The only comprehensive global dataset on coast material to be found was created in the year 1958. (And it was stolen from the library by the professor to be quickly scanned and then returned. True story.)
“Global assessments of vulnerability to climate-change induced sea-level rise and of its associated impacts are impeded by the severe lack of information on coastal physical characteristics.” Prof. A. Vafeidis (University of Kiel, Germany)
The platform was developed to collect this information with help of citizen scientists worldwide. Participation is anonymous and easy. A picture of a coast is uploaded and placed on a map. The coast in the picture is then classified by its coast material as one of the following: Sand, pebble, rock, mud, ice, coral or man-made. Every picture creates a data point which defines the coast material at that location. The more pictures are uploaded, the more defined the database becomes.
In an effort to be as inclusive as possible the platform was translated into 10 world languages and the design was kept as simple as possible.
The received data was evaluated for accuracy and consistency through comparison with existing spatial data of the mediterranean basin. Results of this evaluation show that 80% of the images of coasts uploaded were categorised correctly. Discrepancies in the remaining 20% can be attributed mainly to differences of the two databases in handling specific coastal types.
Overall, the results confirm the effectiveness of the platform to collect high quality data.
A second development phase has been defined and includes setting targets to promote better data coverage. The mediterranean basin, for example, could be sufficiently captured with 52.000 pictures (one per kilometer).