Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for southeastern Florida (FLse)

An operational Mean High Water (MHW) shoreline was extracted from the lidar surveys within MATLAB v7.6 using a method similar to the one developed by Stockdon et al. (2002). Shorelines were extracted from cross-shore profiles which consist of bands of lidar data 2 m wide in the alongshore direction and spaced every 20 m along the coast. For each profile, the seaward sloping foreshore points were identified and a linear regression was fit through them. The regression was evaluated at the operational MHW elevation to yield the cross-shore position of the MHW shoreline. If the MHW elevation was obscured by water points, or if a data gap was present at MHW, the linear regression was simply extrapolated to the operational MHW elevation. A lidar positional uncertainty associated with this point was also computed. The horizontal offset between the datum-based lidar MHW shoreline and the proxy-based historical shorelines nearly always acts in one direction and the "bias" value was computed at each profile (Ruggiero and List, 2009). In addition an uncertainty associated with the bias was also computed, which can also be thought of as the uncertainty of the HWL shorelines due to water level fluctuations. Repeating this procedure at successive profiles generated a series of X,Y points that contain a lidar positional uncertainty, a bias, and a bias uncertainty value. Ruggiero, P. and List, J.H., 2009. Improving Accuracy and Statistical Reliability of Shoreline Position and Change Rate Estimates. Journal of Coastal Research: v.25, n.5, pp.1069-1081. Stockdon, H.F., Sallenger, A.H., List, J.H., and Holman, R.A., 2002. Estimation of Shoreline Position and Change using Airborne Topographic Lidar Data: Journal of Coastal Research, v.18, n.3, pp.502-513.

The series of operational MHW points extracted from the cross-shore lidar profiles were converted to a .dbf file 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. For a detailed explanation of the method used to store bias and uncertainty data in a table, please refer to Appendix 2, section 12.3 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

The uncertainty table, which contains bias values for the entire state, was renamed for each subregion and the appropriate ID values were followed during the calculations for each subregion within the state. This process step and all subsequent process steps were performed by the same person: M.G. Kratzmann.

The shoreline uncertainty table (.dbf) was imported into a personal geodatabase in ArcCatalog v10 by right-clicking on the geodatabase > Import > Table (single). The uncertainty table was used with the Digital Shoreline Analysis System (DSAS) v4.3 software to perform rate calculations.

The shoreline uncertainty table was exported from the personal geodatabase back to a stand-alone dBase file using ArcCatalog v10 by right-clicking on the database file > Export > To dBase file (single) for publication purposes.

Keywords section of metadata optimized for discovery in USGS Coastal and Marine Geology Data Catalog.

Added keywords section with USGS persistent identifier as theme keyword.