The lidar data were collected in projected coordinates (WGS 84 UTM zone 17N). The series of operational MHW points extracted from the cross-shore lidar profiles were converted into a calibrated route shapefile for use in ArcGIS using a Python script. The script generates a point shapefile, converts it to a polyline-M file, saves the uncertainty information in an accessory dBase (.dbf) file and finally generates a calibrated route for the newly-created polyline-M file. Calibration is based on the unique and sequential profile ID value provided with the point data and stored as the M-value. This value is also stored as an attribute in the uncertainty .dbf file and is used as the common attribute field linking the shoreline route file (shoreline.shp) to the uncertainty table (shorelines_uncertainty.dbf) storing the lidar positional uncertainty, the bias correction value, and the uncertainty of the bias correction for each point of the original lidar data.
During the rate calculation process DSAS uses linear referencing to retrieve the uncertainty and bias values stored in the associated table. Visually identified HWL-type proxy shorelines are virtually never coincident with datum-based MHW-type shorelines. In fact, HWL shorelines are almost universally estimated to be higher (landward) on the beach profile than MHW shorelines. Not accounting for this offset will cause shoreline change rates to be biased toward slower shoreline retreat, progradation rather than retreat, or faster progradation than in reality (for the typical case where datum-based shorelines are more recent data than the proxy-based shoreline dates), depending on actual changes at a given site.
Ruggiero, Peter, and List, J.H., 2009, Improving accuracy and statistical reliability of shoreline position and change rate estimates: Journal of Coastal Research, v. 25, no. 5, p. 1069–1081.
Ruggiero, Peter, Kaminsky, G.M., and Gelfenbaum, Guy, 2003, Linking proxy-based and datum-based shorelines on high-energy coastlines—Implications for shoreline change analyses: Journal of Coastal Research, special issue 38, p. 57–82.
For a detailed explanation of the method used to convert the lidar shoreline to a route, please refer to "Appendix 2- A case study of complex shoreline data" in the DSAS user guide:
Himmelstoss, E.A. 2009. "DSAS 4.0 Installation Instructions and User Guide" in: Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Ergul, Ayhan. 2009. Digital Shoreline Analysis System (DSAS) version 4.0 - An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2008-1278. https://woodshole.er.usgs.gov/project-pages/DSAS/version4/images/pdf/DSASv4_3.pdf