A transect-based method described in Farris and others (2018) was used to estimate the slope of the foreshore of the beach using Matlab (version 2019b). This method utilized 20 meter spaced transects oriented perpendicular to a coast-following reference line. All lidar data points within 1 meter of each transect were associated with that transect. All processing was done on the 2 meter wide transects, working on a single transect at a time. For each transect, points on the foreshore were identified and a linear regression was fit through them. Foreshore beach slope was defined as the slope of the regression line. The regression was evaluated at the elevation of Mean High Water (MHW) to yield the location of the shoreline.
The height of Mean High Water was determined from Weber and others (2005).
The shoreline position on each transect has an estimated uncertainty associated with it. This uncertainty includes four components: 1) the 95% confidence interval on the linear regression estimate of the shoreline position; 2) the vertical error of the raw lidar data as reported in the lidar data’s metadata; 3) a 15 cm vertical error in our chosen value of MHW, and; 4) the uncertainty due to extrapolation (if the shoreline was determined using extrapolation). These four components of uncertainty were added in quadrature to yield a total error for each shoreline point.
The accompanying data files (referenceLine_WestCoast.csv and referenceLine_WestCoast.shp) contain information about the reference baseline, transects and the MHW values used to estimate the shoreline location.
This step was completed by several people: Dave Reid, Kathryn M. Weber and Amy S. Farris.
Farris, A.S., Weber, K.M., Doran, K.S., and List, J.H., 2018, Comparing methods used by the U.S. Geological Survey Coastal and Marine Geology Program for deriving shoreline position from lidar data: U.S. Geological Survey Open-File Report 2018–1121, 13 p.,
https://doi.org/10.3133/ofr20181121
