Journal of Coastal Conservation

, Volume 19, Issue 6, pp 831–845 | Cite as

Application of airborne LiDAR to investigate rates of recession in rocky coast environments

  • Claire S. EarlieEmail author
  • Gerd Masselink
  • Paul E. Russell
  • Robin K. Shail


Coastal cliff erosion is a widespread problem that threatens property and infrastructure along many of the world’s coastlines. Rates of erosion used for shoreline management are generally based on analysis of historic maps and aerial photographs which, in rocky coast environments, does not wholly capture the detail in the processes and the failures occurring across the cliff face. This study uses airborne LiDAR (Light Detection and Ranging) data to gain a quantitative understanding of cliff erosion along rocky coastline where recession rates are relatively low (c. 0.1 m yr−1).

It was found that three-dimensional volumetric changes on the cliff face and linear rates of retreat can be reliably calculated from consecutive digital elevation models (DEMs) several years apart. Furthermore, the accuracy of the data on sloping surfaces was tested by applying a threshold below which data that could be construed as error were removed. Using a vertical change threshold of 0.5 m had limited effect on the computed rates of retreat. The spatial variability in recession rates around the coastline was considered in terms of the relationship with the varying boundary conditions (rock mass characteristics, cliff geometries, beach morphology) and forcing parameters (wave climate and wave exposure). Recession rates were statistically correlated with significant wave height (H s ), rock mass characteristics (GSI) and the ratio between the two (GSI/H s ).

The current method of assessing rocky cliff recession using maps and aerial photographs tends to not only miss the detail in the three-dimensional nature of the cliff evolution, but may also be too coarse a resolution to capture the small scale changes that contribute to the overall failure. LiDAR data, although limited in its temporal extent due to it being a relatively new technology, is a suitable method of evaluating cliff erosion on a time scale of 3–4 years and provides additional insight into the process occurring in slowly eroding environments.


Cliff erosion Airborne LiDAR Rocky coastlines Digital elevation model 



The work described in this publication was supported by the European Social Fund Combined Universities in Cornwall Studentship project number 11200NC05. The author would like to thank the National Trust and the Channel Coastal Observatory for information and data provided.


  1. Adams JC, Chandler JH (2002) Evaluation of LiDAR and medium scale photogrammetry for detecting soft-cliff coastal change. Photogramm Rec 17:405–418CrossRefGoogle Scholar
  2. Adams PN, Storlazzi CD, Anderson RS (2005) Nearshore wave-induced cyclical flexing of sea cliffs. J Geophys Res 110Google Scholar
  3. Ashton AD, Walkden MJA, Dickson ME (2011) Equilibrium responses of cliffed coasts to changes in the rate of sea level rise. Mar Geol 284:217–229CrossRefGoogle Scholar
  4. Austin, M. J., Scott, T. M., Russell, P. E., Masselink, G., 2013. Rip current prediction: development, validation, and evaluation of an operational tool. Journal of Coastal ResearchGoogle Scholar
  5. Bird, E. C. F., 1998. The Coasts of Cornwall: Scenery and Geology with an Excursion Guide. Alexander AssociatesGoogle Scholar
  6. Brock JC, Purkis SJ (2009) The emerging role of LiDAR remote sensing in coastal research and resource management. J Coast Res Spec Issue 53:1–5CrossRefGoogle Scholar
  7. Brooks SM, Spencer T (2010) Temporal and spatial variations in recession rates and sediment release from soft rock cliffs, Suffolk coast, UK. Geomorphology 124:26–41CrossRefGoogle Scholar
  8. Brooks SM, Spencer T, Boreham S (2012) Deriving mechanisms and thresholds for cliff retreat in soft-rock cliffs under changing climates: rapidly retreating cliffs of the Suffolk coast, UK. Geomorphology 153–154:48–60CrossRefGoogle Scholar
  9. CCO, 2012. Channel Coastal Observatory, Map viewer and data catalogue. Retrieved 01/01/2012, from
  10. Cosgrove ARP, Bennett MR, Doyle P (1998) The rate and distribution of coastal cliff erosion in England: a cause for concern? In: Bennett MR, Doyle P (eds) Issues in environmental geology: a British perspective. The Geological Society, LondonGoogle Scholar
  11. Damgaard JS, Dong P (2004) Soft cliff recession under oblique waves: physical model tests. J Waterw Port Coast Ocean Eng 130:234–242CrossRefGoogle Scholar
  12. Dawson RJ, Dickson ME, Nicholls RJ, Hall JW, Walkden MJA, Stansby PK, Mokrech M, Richards J, Zhou J, Milligan J, Jordan A, Pearson S, Rees J, Bates PD, Koukoulas S, Watkinson AR (2009) Integrated analysis of risks of coastal flooding and cliff erosion under scenarios of long term change. Clim Chang 95:249–288CrossRefGoogle Scholar
  13. Dewez TJB, Rohmer J, Regard V, Cnudde C (2013) Probabilistic coastal cliff collapse hazard from repeated terrestrial laser surveys: case study from Mesnil Val (Normandy, northern France). In: Conley DC, Masselink G, Russell PE, O’Hare TJ (eds) Proceedings 12th international coastal symposium (Plymouth, England), journal of coastal research, vol 65, Special Issue No., pp 702–707Google Scholar
  14. Dickson ME, Pentney R (2012) Micro-seismic measurements of cliff motion under wave impact and implications for the development of near-horizontal shore platforms. Geomorphology 151–152:27–38CrossRefGoogle Scholar
  15. Dong P, Guzzetti F (2005) Frequency-size statistics of coastal soft-cliff erosion. Ocean Eng 131:37–42Google Scholar
  16. Dornbusch, U. and Robinson, D., 2005, Controls on chalk cliff erosion in the eastern channel. BAR Phase 1 report, University of SussexGoogle Scholar
  17. Earlie C, Masselink G, Russell P, Shail R (2013) Proceedings 12th International Coastal Symposium. In: Conley DC, Masselink G, Russell PE, O’Hare TJ (eds) J Coast Res. Special Issue No. 65, Plymouth, England, pp 470–475Google Scholar
  18. ESRI, 2011. Mapping and analysis for understanding our world. Retrieved 01/03/2012, from
  19. Geomatics Group, 2012. Geomatics Group; Integrated spatial data. Retrieved 01/02/2012, from
  20. Hall JW, Meadowcroft IC, Lee ME, van Gelder PHAJM (2002) Stochastic simulation of episodic soft coastal cliff recession. Coast Eng 46:159–174CrossRefGoogle Scholar
  21. Hladik C, Alber M (2012) Accuracy assessment and correction of a LIDAR-derived salt marsh digital elevation model. Remote Sens Environ 121:224–235CrossRefGoogle Scholar
  22. Hoek E, Marinos P, Benissi M (1998) Applicability of the Geological Strength Index (GSI) classification for very weak and sheared rock masses. The case of the Athens Schist Formation. Bull Eng Geol Environ 57:151–160CrossRefGoogle Scholar
  23. Jaboyedoff M, Oppikofer T, Abellan A, Derron MH, Loye A, Metzger R, Pedrazzini A (2012) Use of LIDAR in landslide investigations: a review. Nat Hazards 61:5–28CrossRefGoogle Scholar
  24. Kidner DB, Thomas M, Leight C, Oliver R, Morgan C (2004) Coastal monitoring with LiDAR: Challenges, problems and pitfalls. Remote Sensing for Environmental Monitoring, Gis Applications, and Geology Iv. Edited by M. Ehlers, F. Posa, H. J. Kaufmann, U. Michel and G. DeCarolis. Bellingham Spie-Int Soc Opt Eng 5574:80–89Google Scholar
  25. Lee EM (2008) Coastal cliff behaviour: observations on the relationship between beach levels and recession rates. Geomorphology 101:558–571CrossRefGoogle Scholar
  26. Leigh CL, Kidner DB, Thomas MC (2009) The use of LiDAR in digital surface modelling: issues and errors. Trans GIS 13:345–361CrossRefGoogle Scholar
  27. Leveridge B, Hartley AJ (2006) The Variscan Orogeny: the development and deformation of Devonian/Carboniferous basins in SW England and South Wales. In: Brenchley PJ, Rawson PF (eds) The Geology of England and Wales. Geological Society of London, London, pp 225–255Google Scholar
  28. Leveridge BE, Shail RK (2011) The Gramscatho basin, south Cornwall, UK: Devonian active margin successions. Proc Geol Assoc 122:568–615CrossRefGoogle Scholar
  29. Lim M, Rosser NJ, Allison RJ, Petley DN (2010) Erosional processes in the hard rock coastal cliffs at Staithes, North Yorkshire. Geomorphology 114:12–21CrossRefGoogle Scholar
  30. Lim M, Rosser NJ, Petley DN, Keen M (2011) Quantifying the controls and influence of tide and wave impacts on coastal rock cliff erosion. J Coast Res 27:46–56CrossRefGoogle Scholar
  31. Met Office, 2012. South-west England: Climate. Retrieved 01/09/2012, from
  32. Naylor L, Stephenson W, Trenhaile AS (2010) Rock coast geomorphology: recent advances and future research directions. Geomorphology 114:3–11CrossRefGoogle Scholar
  33. Nunes, M., Ferreira, O., Loureiro, C. and Baily, B., 2011. Beach and cliff retreat induced by storm groups at Forte Novo, Algarve (Portugal). Journal of Coastal Research, (SI 64), 795–799Google Scholar
  34. Orford, J., Burgess, K., Dyer, K., Townend, I. and Balson, P. 2002, ‘FUTURECOAST -- The Integration of Knowledge to Assess Future Coastal Evolution at a National Scale’ Paper presented at 28th International Conference on Coastal Engineering, Cardiff, pp. 3221–3233Google Scholar
  35. Pethick J (1984) An introduction to coastal geomorphology. Arnold, LondonGoogle Scholar
  36. Pethick JS, Crooks S (2000) Development of a coastal vulnerability index: a geomorphological perspective. Environ Conserv 27:35–367CrossRefGoogle Scholar
  37. Ridgewell J, Walkden M (2009) Cornwall and Isles of Scilly SMP2 Sub-cells review of coastal processes and geomorphology. Royal Haskoning Ltd, PeterboroughGoogle Scholar
  38. Rogers J, Baptiste A, Jeans K (2009) Proceedings of the 44th flood and coastal risk management conference. UK, Telford, National Coastal Erosion Risk Mapping – The final furlongGoogle Scholar
  39. Rosser NJ, Petley DN, Lim M, Dunning SA, Allison RJ (2005) Terrestrial laser scanning for monitoring the process of hard rock coastal cliff erosion. Q J Eng Geol Hydrogeol 38:363–375CrossRefGoogle Scholar
  40. Rosser N, Lim M, Petley D, Dunning S, Allison R (2007) Patterns of precursory rockfall prior to slope failure. J Geophys Res Earth Surf 112Google Scholar
  41. Sallenger AH Jr, Krabill WB, Swift RN, Brock J, List J, Hansen M, Holman RA, Manizade S, Sontag J, Meredith A, Morgan K, Yunkel JK, Frederick EB, Stockdon H (2003) Evaluation of Airborne Topographic LiDAR for quantifying beach changes. J Coast Res 19:125–133Google Scholar
  42. Schmidt KA, Hadley BC, Wijekoon N (2011) Vertical accuracy and use of topographic LIDAR data in coastal marshes. J Coast Res 27:116–132CrossRefGoogle Scholar
  43. Scott T, Masselink G, Russell P (2011) Morphodynamic characteristics and classification of beaches in England and Wales. Mar Geol 286:1–20CrossRefGoogle Scholar
  44. Shail RK, Coggan JS (2010) Godrevy coastal recession baseline survey 2009–2010. University of Exeter, Camborne School of MinesGoogle Scholar
  45. Shail, R., Coggan, J., and Stead, D., 1998. Coastal landsliding in Cornwall, UK: Mechanisms, modelling and implications. Proceedings of the eighth International Congress of the International Association for Engineering Geology and the Environment,(Vancouver, Canada), 1323 – 1330Google Scholar
  46. Stephenson WJ (2006) Coastal geomorphology. Prog Phys Geogr 30:122–132CrossRefGoogle Scholar
  47. Sunamura T (1992) Geomorphology of Rocky Coasts. John Wiley and Sons Ltd., ChichesterGoogle Scholar
  48. UKHO, 2012. UK Hydrographic Office; Products and Services. Available online at: (Accessed: 01/03/2012 2012)
  49. USGS. 2012. Digital Shoreline Analysis System. Available online at: (Accessed: 01/04/2012 2012)
  50. Westgate BM, Coggan JS, Pine RJ (2003) Development of a risk-based approach to coastal slope instability assessment in Cornwall. Geosci south-west England 10:390–396Google Scholar
  51. Wood JD, Fisher PF (1993) Assessing interpolation accuracy in elevation models. Comput Graph Appl IEEE 13:48–56CrossRefGoogle Scholar
  52. Wyllie DC, Mah CW (2004) Rock slope engineering: civil and mining, 4th edn. Spon Press, LondonGoogle Scholar
  53. Xhardé, R., Long, B. F., and Forbes, D. L., 2006. Accuracy and limitations of airborne LiDAR surveys in coastal environments. In 2006 International Geoscience and Remote Sensing Symposium pp. 2412–2415. Denver, CO: IEEEGoogle Scholar
  54. Young AP, Ashford SA (2006) Application of airborne LIDAR for seacliff volumetric change and beach-sediment budget contributions. J Coast Res 22:307–318CrossRefGoogle Scholar
  55. Young AP, Flick RE, Gutierrez R, Guza RT (2009) Comparison of short-term seacliff retreat measurement methods in Del Mar, California. Geomorphology 112:318–323CrossRefGoogle Scholar
  56. Young AP, Guza RT, O’Reilly WC, Flick RE, Gutierrez R (2011a) Short-term retreat statistics of a slowly eroding coastal cliff. Nat Hazards Earth Syst Sci 11:205–217CrossRefGoogle Scholar
  57. Young AP, Adams P, O’Reilly WC, Flick RE, Guza RT (2011b) Coastal cliff ground motions from local ocean swell and infragravity waves in southern California. J Geophys Res 116Google Scholar
  58. Zhang K, Whitman D, Leatherman S, Robertson W (2005) Quantification of beach changes caused by hurricane Floyd along Florida’s Atlantic coast using airborne laser surveys. J Coast Res 21:123–134CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Claire S. Earlie
    • 1
    Email author
  • Gerd Masselink
    • 1
  • Paul E. Russell
    • 1
  • Robin K. Shail
    • 2
  1. 1.School of Marine Science and EngineeringPlymouth UniversityPlymouthUK
  2. 2.Camborne School of MinesUniversity of ExeterCornwallUK

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