Shorelines of the Oregon coastal region used in shoreline change analysis (OR_shorelines.shp)

Shoreline data were sought in an effort to compile as many quality shorelines as possible for the region. Digital shorelines, if available from another agency, were acquired. If no digital shorelines were available or if a data set was incomplete, T-sheets were requested from NOAA and received as scanned raster images.

An operational Mean High Water (MHW) shoreline was extracted from the lidar surveys within MATLAB 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 40 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.

T-sheets were geo-registered using ERDAS Imagine geographic imaging software (v.9.3) by placing 10-20 well-spaced ground control points at gridline intersections. Some T-sheets may have required additional coordinate transformation information from NOAA to account for datum offsets between historical datums (USSD) and modern datums (NAD27 or NAD83). Datum transformations were applied to GCP coordinates prior to registration. T-sheets that were already geo-registered were quality checked. Total RMS error for the rectification process was maintained below 1 pixel, which translates to approximately 4 meters at a scale of 1:20,000 and 1.5 meters at a scale of 1:10,000. This process step and all subsequent process steps were performed by the same person - Meredith Kratzmann.

Vector shorelines were digitized from the georegistered T-sheets using standard editing tools in ArcMap v9.3. Quality assessments were performed and shorelines were edited to remove any overlap between adjacent shorelines. No edgematching between adjacent shorelines was attempted.

Historical shorelines were merged in ESRI's ArcToolbox (v.9.3), Data Management Tools > General > Merge. Then the merged file was projected in ESRI's ArcToolbox (v.9.3) > Data Management Tools > Projections and Transformations > Feature > Project. Parameters: input projection = geographic (NAD 83); output projection = UTM zone 10N (WGS 84); transformation = NAD_1983_To_WGS_1984_1.

The lidar data were collected in projected coordinates (WGS 84 UTM zone 10N). The series of operational MHW points extracted from the cross-shore lidar profiles were converted to a point feature class within a geodatabase in ArcCatalog by right-mouse clicking the point data file > Create Feature Class > From XY table. The point feature class was converted to a polyline-M file by connecting adjacent profile points to form a vector shoreline feature using ET GeoWizards (v.9.8) > Convert > Point to Polyline Z (M). The lidar profile ID value was stored as the M-value. The lidar vector shoreline was then converted to a route using ArcToolbox v9.3 Linear Referencing Tools > Create Routes. Parameters: Input Line Features = polyline M file; Route Identifier Field = ET_ID (created by ET GeoWizards when constructing polyline-M field), Measure Source = Length, default values for rest. The unique cross-shore profile ID is stored as the M-value at each vertex. The route was calibrated using ETGeoWizards (v.9.8) > LinRef tab > Calibrate routes with points. Parameters: Attribute Field selected, Point layer = original point shapefile, Route ID field = RouteID, Measure Field = ID (lidar profile ID), Input search tolerance = 40, Interpolation between points checked, Recalculate measures using calibration points and shortest path distance between vertices checked, every other option unchecked. The calibration assigns interpolated measure values from the start to the end of the route based on the known profile IDs stored at each vertex. This profile ID is used as the common attribute field between the route file and an uncertainty table (OR_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. The calculation of these values is explained in detail in the full report, National Assessment of Shoreline Change for the Pacific Northwest Coast, cross-referenced in this metadata file. Please refer specifically to the methods section titled "The Proxy-Datum Bias Correction between HWL and MHW shorelines." 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://pubs.er.usgs.gov/publication/ofr20081278

Historic shorelines were appended to the lidar route data in ArcToolbox > Data Management Tools > General > Append to produce a single shoreline file for the region. The final shoreline dataset was coded with attribute fields (ID, Date, Uncertainty (Uncy), Source, and Year). These fields are required for the Digital Shoreline Analysis System (DSAS), which was used to calculate shoreline change rates.

The appended shoreline file and the shoreline uncertainty table (.dbf) were imported into a personal geodatabase in ArcCatalog v9.3 by right-clicking on the geodatabase > Import (feature class for shoreline file and table for uncertainty table) for use with the Digital Shoreline Analysis System (DSAS) v4.2 software to perform rate calculations.

The shoreline feature class was exported from the personal geodatabase back to a shapefile in ArcCatalog v9.3 by right-clicking on the shoreline file > Export > To Shapefile (single) for publication purposes.

The data were projected in ArcToolbox v9.3 > Data Management Tools > Projections and Transformations > Feature > Project. Parameters: input projection = UTM zone 10N (WGS84); output projection = geographic coordinates (WGS84); transformation = none.

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

Added keywords from Coastal and Marine Ecological Classification Standard (CMECS) to metadata.

Edits to the metadata were made to fix any errors that MP v 2.9.46 flagged. This is necessary to enable the metadata to be successfully harvested for various data catalogs. In some cases, this meant adding text "Information unavailable" or "Information unavailable from original metadata" for those required fields that were left blank. Other minor edits were probably performed (title, publisher, publication place, etc.). Added a landing page link as the first link in the identification section. The distribution format name was modified in an attempt to be more consistent with other metadata files of the same data format. Fixed cross-referece information. Minor fixes to the attribute format for some attributes were needed. Attempted to modify http to https where appropriate. The metadata date (but not the metadata creator) was edited to reflect the date of these changes. The metadata available from a harvester may supersede metadata bundled within a download file. Compare the metadata dates to determine which metadata file is most recent.

Added keywords section with USGS persistent identifier as theme keyword.