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How scientists are using drones to help predict coastal erosion
A large chunk of chalk recently collapsed into the sea from the Seven Sisters cliffs, a world-renowned beauty spot located on England’s East Sussex coastline. To many, they are a quintessentially English landmark – and the British press was quick to show concern. The usual questions that follow these types of events involve the rate at which the coastline is eroding and potential risks to the public.
Answering these questions is difficult from a scientific perspective – sets of data regarding rock fall are often not available and those that are available are often incomplete.
Approximately 53% of England and Wales’ coastline exhibit cliffs and shore platforms. These cliffs retreat through episodic rock falls that can range in size from small pebbles to hundreds of thousands of cubic metres. Analysis of historical aerial photographs can go some way to establishing the rate of retreat over decades. However, this approach does not provide information on individual rock fall events.
Since the turn of the millennium, the evolution of sea cliffs has received greater attention from earth scientists. The interaction of the local climate, waves and tidal range with cliff materials makes changes in these land forms difficult to predict over large areas.
In order to develop an understanding of the relative frequency of rock fall events of differing magnitudes, an inventory of events through time is required. This can then be used to both predict future change as well as establish the potential risk posed by rock falls to both the public and to infrastructure. The way forward therefore seems to involve mapping technology that is capable of capturing both large and small rock falls as they occur along a section of coast.
This kind of high-precision monitoring has improved our understanding of the rates of cliff erosion by measuring volumetric change between extremely detailed 3D models of the cliff face. These data have typically been acquired through change detection between sequential datasets using terrestrial laser scanning (TLS), a time-of-flight laser system capable of reliably detecting rockfalls about the size of a fist at a range of several hundred meters.
This approach allows for a comprehensive understanding of cliff erosion and has been put to good use in experimental programs around the world. However, TLS is both extremely costly in terms of equipment and quite labour intensive.
An alternate way of collecting data with similar characteristics to TLS is known as digital photogrammetry. This method has the advantage of virtually instantaneous data capture and, when used in conjunction with unmanned aerial vehicle (UAV) technology – drones – offers the potential to provide high-resolution topographical information over large areas.
A pilot study undertaken at Telscombe Cliffs to the east of Brighton using an off-the-shelf multirotor UAV and a 36 mega-pixel digital camera has produced promising results with rockfall detection capabilities similar to those demonstrated by TLS. An example of the type of 3D model generated from these data is shown above.
Data used to create the model was collected during an eight-minute flight. The only real limit to the length of coastline that can be monitored in this way is the endurance of the UAV and the data storage capacity of the camera.
With high-endurance UAV platforms and camera systems it would seem feasible to map the undefended sea cliffs of England and Wales in their entirety at a relatively low cost. Repeat surveys taken annually over decades would then form the basis for a comprehensive rock fall inventory and could be used to answer the questions of risk management and cliff erosion that currently remain unanswered.
John Barlow receives funding from the EPSRC and Brighton and Hove council.
John Barlow, Lecturer in Applied Geomorphology (Geography), University of Sussex
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