Coastal migration via satellite data (150k-250k)

Thanks to the public availability of satellite data (optical imagery of ESA Sentinel 2 and NASA Landsat 5, 7 & 8 with pixel resolutions of 10-30 metres and a revisit time of 1 to 2 weeks) and new analytical tools for processing big data (such as the Google Earth Engine), the EMODnet Geology team in collaboration with Deltares and TNO (Geological Survey of the Netherlands) were able to look at shoreline migration in a new way. Scripts for automated detection of the land-water boundary were used to separate land from water in annual image composites for the period 2007-2017. During this process, data points were generated for each part along the European shoreline. These points were then averaged by year and analysed for a decadal period.

Visualising pan-European shoreline change means making choices, like defining a stable shoreline for example. A mean rate of 0.5 metre per year was chosen, though this rate depends on the landscape: granite cliffs for example shows less decadal dynamics compared to a sandy barrier island.

The spatial resolution of the method, depending on the pixel resolution of the individual satellite images which is about 10 metres, is still limiting. Validations of abovementioned method have shown that the method is less accurate in case of bluffs, cliffs and muddy coasts, and as such further validations will need to take place. EMODnet Geology hopes that by releasing the satellite-based dataset now, coastal experts and other end users will be able to discover and communicate possibilities and limitations of automated methods for the extraction of shoreline position and quantification of annual to decadal change. To help in this process, a companion map showing shoreline migration on the basis of field data and expert is made available, thereby facilitating a first-order comparison.

Citation proposal
. Coastal migration via satellite data (150k-250k). https://services.mspdata.eu:/geonetwork/srv/api/records/d94fe678ac07466f6e9416642149db663be4f178