Development of a Vector-Based Method for Coastal Bluffline Mapping Using LiDAR Data and a Comparison Study in the Area of Lake Erie

Abstract

This paper introduces a new method for bluffline extraction based on analysis of surface normal vectors derived from a 2.5-dimensional Delaunay triangulation network generated using a set of LiDAR points. The developed method has been implemented and tested for the extraction of blufflines in a section of the Lake Erie coastline near Painesville, Ohio. Comparison of the research results with those generated by a method for bluffline extraction based on slope information along elevation profiles on transects shows an improvement in both horizontal and vertical accuracies in situations where the bluff has a relatively sharp edge formation.

Keywords:

• LiDAR (Light Detection and Ranging)
• bluffline
• bluff top
• bluff toe
• Delaunay triangulation
• normal vector
• DEM (Digital Elevation Model)

Acknowledgements

This research was supported in part by the NOAA Sea Grant College Program. Constructive comments from the reviewers were very helpful and are here acknowledged.