Palaseanu-Lovejoy, M.; Danielson, J.; Thatcher, C.; Foxgrover, A.; Barnard, P.; Brock, J., and Young, A., 2016. Automatic delineation of seacliff limits using lidar-derived high-resolution DEMs in Southern California. In: Brock, J.C.; Gesch, D.B.; Parrish, C.E.; Rogers, J.N., and Wright, C.W. (eds.), Advances in Topobathymetric Mapping, Models, and Applications. Journal of Coastal Research, Special Issue, No. 76, pp. 162–173. Coconut Creek (Florida), ISSN 0749-0208.

Seacliff erosion is a serious hazard with implications for coastal management and is often estimated using successive hand-digitized cliff tops or bases (toe) to assess cliff retreat. Even if efforts are made to standardize manual digitizing and eliminate subjectivity, the delineation of cliffs is time-consuming and depends on the analyst's interpretation. An automatic procedure is proposed to extract cliff edges from high-resolution lidar-derived bare-earth digital elevation models, generalized coastal shoreline vectors, and approximate measurements of distance between the shoreline and the cliff top. The method generates orthogonal transects and profiles with a minimum spacing equal to the digital elevation model resolution. The method also extracts the xyz coordinates for each profile for the cliff top and toe, as well as second major inflections along the profile. Over 75% of the automated cliff top points and 78% of the toe automated points are within 95% confidence interval of the hand-digitized top and toe lines, and over 79% of the digitized top points and 84% of the digitized toe points are within the 95% confidence interval of the automated top and toe lines along a stretch of coast in Del Mar, California. Outlier errors were caused by either the failure to remove all vegetation from the bare-earth digital elevation model or errors of interpretation. The automatic method was further applied between Point Conception and Los Angeles Harbor, California. This automatic method is repeatable, takes advantage of detailed topographic information within high-resolution digital elevation models, and is more efficient than hand-digitizing.