VA Bias_Feature – Feature class containing Virginia proxy-datum bias information to be used in the Digital Shoreline Analysis System.

Step 1: GATHERING SLOPE DATA FORM POINT CLOUD LIDAR DATA. The proxy datum bias calculation is made possible by utilizing data acquired in the processing for the profile method of shoreline extraction similar to the one developed by Stockdon and others (2002). This method extracts an elevation-based shoreline from point cloud lidar data using a Matlab-based approach (Matlab version 2015b). Using a coast-following reference line with 20 m spaced cross shore profiles, lidar data is analyzed within a two meter swath around each profile. This method is used to extract the mean high water (MHW) shoreline, as well as slope, and uncertainty information. For Virginia, the slope and uncertainty information at each profile was averaged over time using data from the years 1997, 2010 and 2017 where available.
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, no. 3, p. 502-513. [Also available at https://www.jstor.org/stable/4299097]

Step 2: CALCULATING THE PROXY DATAUM BIAS. There is a known horizontal offset between the datum-based lidar MHW shoreline and the proxy-based historical shorelines on open-ocean sandy beaches that nearly always acts in one direction (Ruggiero and List, 2009). This bias is called the proxy-datum bias (PDB). The PDB is primarily due to wave run-up and thus is affected by the slope of the foreshore and the movement of water (waves, tides) onto the foreshore, see equation for the PDB and the PDB uncertainty in Ruggiero and List, 2009. These equations require beach slope and wave data. Ideally data collected at the time the proxy-based shoreline was collected would be used, however, for our purposes the PDB is estimated by averaging all available slope data (described in step 1) and averaging at least 10 years of historical wave data from a nearby buoy (https://www.ndbc.noaa.gov/) and the U.S. Wave Information Study (WIS - https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00071) The resulting PDB and PDB uncertainty is stored to a point shapefile at the intersection of the each profile with the coast-following reference line.
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, no. 5, p. 1069-1081. [Also available at https://www.jstor.org/stable/27752753]
National Data Buoy Center, National Oceanic and Atmospheric Administration (NOAA) Stennis Space Center, MS 39529 https://www.ndbc.noaa.gov/
U.S. Wave Information Study, DOC/NOAA/NESDIS/NCEI National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce, https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00071

Step 3: BIAS CONVERSION FROM POINT TO POLYLINE. To be used with DSAS, the data from the bias points must be connected to a shapefile that is near or adjacent to the DSAS baseline. However, the resulting bias points from the lidar shoreline extraction do not always fall near the baseline. The following steps (Step 4 - Step 9) detail how a series of transects are created to connect the point bias data to a coast following polyline feature. The following process steps were performed by the same person, Rachel E. Henderson.

Step 4. A personal geodatabase was created and the baseline and sample shorelines for the project area were added (see larger work citation for data). Using DSAS v5.1, the default parameters were set for midshore baseline. Transects were cast using 20-meter spacing, a search distance of 1000, and smoothing distance of 2000. Once cast, the transects were evaluated with the original bias points to ensure the transects overlapped with the bias points and baseline. If needed, the transects were recast with a larger search distance.

Step 5. The data from the original bias points are transferred to the transects, using the ArcTool “Spatial Join” (ArcToolbox > Analysis Tools > Overlay > Spatial Join). The resulting Bias_transect contains all the original bias information. The Bias_transect is then converted to a midpoint using the ArcTool "Feature Vertices to Points" (ArcToolbox > Data Management Tools > Features > Feature Vertices to Points) and selecting the midpoint option. As the transects were cast with the midshore baseline options, the midpoint will intersect the baseline. The resulting Bias_midpoint, contains all the original bias information.

Step 6. A copy of the baseline is created, and split into 20 meter increments, to match the spacing and detail of the bias_midpoint feature. Points spaced at 20 meters along the original baseline were created using the ArcTool "Generate Points along Lines" at a distance of 20 meters. Then the ArcTool "Split Line at Point" was used with the copy of the baseline, to generate a new feature that has 20 meter segments: Feature_20m.

Step 7. The data from Bias_midpoint are transferred to the new baseline Feature_20m, using the ArcTool “Spatial Join” (ArcToolbox > Analysis Tools > Overlay > Spatial Join) resulting in a new polyline feature (Feature_wbias) containing all the original bias information, at 20 meter increments.

Step 8. The ArcTool "Unsplit Line" (ArcToolbox > Data Management Toolbox > Features > Unsplit Line) was used to reconnect any adjacent 20 meter segment with the same bias, and bias uncertainty values, reducing the number of small segments of bias feature. The final bias feature shapefile holds the bias and the bias uncertainty. These components are used by DSAS v5.1 to apply the proxy-datum bias correction to shoreline change calculations.

Step 9. The Bias_Feature was imported into a personal geodatabase in ArcCatalog v10.5 by right-clicking on the geodatabase > Import > Feature class (single). The feature class is used with the Digital Shoreline Analysis System (DSAS) v5.1 software to apply the proxy-datum bias to rate calculations.

Step 10. The bias_feature was exported from a personal geodatabase in ArcCatalog v10.5 by right-clicking on the geodatabase > Export > Feature class (single). Coordinate System: UTM Zone 18N (WGS84)