Pilot project funded: Coastal Landslides

Innovative approaches to coastal landslide identification and mapping.

Landslide inventories are required for the assessment of susceptibility and for understanding risk. However inventories are, by their nature, a time- and resource-intensive activity. Recently methodologies for the automatic detection of landforms have made significant advances that may enable a more accurate and efficient approach to be taken.

Coastal_Landslides_Plate

Coastal Mass Movements: A failure on the north side of Brandon Head on the Dingle Peninsula, Ireland. Source: Google Earth Pro, Digital Globe. B – Coastal cliff failure at Nefyn Bay in Wales. C- Rockfalls at Porthkerry on the South Wales coast. D – Rockfall at the Cliffs of Moher in July 2015. Sources: A- Google Earth Pro, (2009); B and C BGS, ; D – Photo credit Jan Mlázovský.

Coastal landslides have not received sufficient treatment in Ireland due to the inaccessibility of most coastal environments. This is a concern as future climate change predictions for Ireland suggest that there may be an increase in the frequency of coastal landslides as both rainfall intensities and coastal storms are set to increase.
We propose to explore the use of machine learning algorithms and drone technology to enable more accurate mapping and therefore inventory building capability of coastal landslides. This approach will result in a more time-effective framework to produce coastal landslide inventories.

This Research is funded by the Geological Survey of Ireland research program (Short Calls).

Research Team:

Dr Bourke, Department of Geography, Trinity College, Dublin

Dr Pilla, School of Engineering, Trinity College, Dublin

Ms Cullen, Department of Geography, Trinity College, Dublin

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