U.S. Geological Survey
2010
Shorelines of the Delmarva North coastal region from Cape Henlopen, Delaware to the southern end of Assateague Island, Virginia, used in shoreline change analysis (DelmarvaN_shorelines.shp)
vector digital data
Open-File Report
2010-1119
Woods Hole Coastal and Marine Science Center, Woods Hole, MA
U.S. Geological Survey, Coastal and Marine Geology Program
https://doi.org/10.3133/ofr20101119
http://pubs.usgs.gov/of/2010/1119/
http://pubs.usgs.gov/of/2010/1119/data/DelmarvaN_shorelines.zip
Emily A. Himmelstoss
Meredith G. Kratzmann
Cheryl J. Hapke
E. Robert Thieler
Jeffrey List
2010
National Assessment of Shoreline Change: A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for the New England and Mid-Atlantic Coasts
Open-File Report
2010-1119
Reston, VA
U.S. Geological Survey
http://pubs.usgs.gov/of/2010/1119/
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline data along open-ocean sandy shores of the conterminous United States and parts of Alaska and Hawaii under the National Assessment of Shoreline Change project.
There is no widely accepted standard for analyzing shoreline change. Existing shoreline data measurements and rate calculation methods vary from study to study and prevent combining results into state-wide or regional assessments. The impetus behind the National Assessment project was to develop a standardized method of measuring changes in shoreline position that is consistent from coast to coast. The goal was to facilitate the process of periodically and systematically updating the results in an internally consistent manner.
This dataset includes shorelines from 22 years ranging from 1845 to 2000 in the Delmarva North coastal region from Cape Henlopen, Delaware to the southern end of Assateague Island, Virginia. Shorelines were compiled from maps (U.S. Army Corps of Engineers Coastal Engineering Research Center), T-sheets (Maryland Department of Natural Resources, National Oceanic and Atmospheric Administration), and lidar (USGS).
Historical shoreline positions serve as easily understood features that can be used to describe the movement of beaches through time. These data are used to calculate rates of shoreline change for the U.S. Geological Survey's (USGS) National Assessment Project.
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 4.1. DSAS uses a measurement baseline method to calculate rate-of-change statistics. Transects are cast from the reference baseline to intersect each shoreline, establishing measurement points used to calculate shoreline change rates.
Cross-referenced citations are applicable to the dataset as a whole. Additional citations are located within individual process steps that pertain specifically to the method described in that step.
1845
2000
ground condition
None planned
-75.412170
-75.048033
38.804690
37.853614
USGS Metadata Identifier
USGS:5d9bcde9-1167-4c1d-a138-2f4ee5850235
None
Shoreline Change Rate
Linear Regression Rate
Endpoint Rate
Digital Shoreline Analysis System
DSAS
U.S. Geological Survey
USGS
Coastal and Marine Geology Program
CMGP
Woods Hole Coastal and Marine Science Center
WHCMSC
National Assessment of Shoreline Change Project
National Oceanic and Atmospheric Administration
NOAA
Coastal Services Center
CSC
U.S. Army Corps of Engineers
USACE
Coastal Engineering Research Center
CERC
Maryland Department of Natural Resources
MD DNR
ISO 19115 Topic Category
oceans
environment
geoscientificInformation
Marine Realms Information Bank (MRIB) Keywords
effects of coastal change
coastal processes
shoreline accretion
shoreline erosion
USGS Thesaurus
coastal processes
erosion
shoreline accretion
Coastal and Marine Ecological Classification Standard (CMECS)
Continental/Island Shore Complex
None
Atlantic Coast
United States
Mid-Atlantic
Delmarva
Delaware
Rehoboth Beach
Bethany Beach
Maryland
Ocean City
Assateague Island
Virginia
Chincoteague Island
Coastal and Marine Ecological Classification Standard (CMECS)
Virginian Ecoregion
Coastal and Marine Ecological Classification Standard (CMECS)
Substrate
None
Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. Please recognize the U.S. Geological Survey as the originator of the dataset.
U.S. Geological Survey
mailing and physical address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700
508-547-2310
Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 3; ESRI ArcCatalog 9.3.1.1850
Cheryl J. Hapke
Emily A. Himmelstoss
Meredith G. Kratzmann
Jeffrey List
E. Robert Thieler
2010
National Assessment of Shoreline Change: Historical Shoreline Change along the New England and Mid-Atlantic Coasts
Open-File Report
2010-1118
Reston, VA
U.S. Geological Survey
http://pubs.usgs.gov/of/2010/1118/
E.R. Thieler
E.A. Himmelstoss
J.L. Zichichi
A. Ergul
2009
Digital Shoreline Analysis System (DSAS) version 4.0 - An ArcGIS extension for calculating shoreline change
Open-File Report
2008-1278
Reston, VA
U.S. Geological Survey
Current version of software at time of use was 4.1
http://woodshole.er.usgs.gov/project-pages/DSAS/version4/index.html
http://woodshole.er.usgs.gov/project-pages/DSAS/
https://pubs.er.usgs.gov/publication/ofr20081278
Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Coastal Services Center (CSC)
Unknown
1996-2000 NOAA/USGS/NASA Airborne LiDAR Assessment of Coastal Erosion (ALACE) Project for the U.S. Coastline
Charleston, SC
NOAA's Ocean Service, Coastal Services Center (CSC)
Original online linkage, which no longer appears valid: http://www.csc.noaa.gov/ldart
National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS)
Unknown
Scanned National Ocean Service (NOS) Coastal Survey Maps (also known as Topographic Survey sheets, or T-sheets)
NOAA shoreline manuscripts (T-sheets)
Information unavailable from original metadata.
Washington, D.C.
National Oceanic and Atmospheric Administration
National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS)
U.S. Army Corps of Engineers (USACE), Coastal Engineering Research Center (CERC)
1988
Shoreline Movements Study: Cape Henlopen, Delaware to Cape Charles, Virginia
Washington, D.C.
National Ocean Service (NOS)
16 maps at 1:24,000 scale
Maryland Department of Natural Resources (MD DNR), Maryland Geological Survey, Coastal and Estuarine Geology Program
2000
Historical Shorelines, 1843-1989, Southern Coastal Bays, Maryland
Baltimore, Maryland
Maryland Geological Survey
The data provided here are a compilation of shorelines from multiple sources, spanning 155 years. The attributes are based on the requirements of the Digital Shoreline Analysis System (DSAS) software and have gone through a series of quality assurance procedures.
Adjacent shoreline segments do not overlap and are not necessarily continuous. Shorelines were quality checked for accuracy. Any slight offsets between adjacent segments due to georeferencing and digitizing error are taken into account in the uncertainty calculations included in the corresponding report (U.S. Geological Survey Open-file Report 2010-1118).
This shoreline file is complete and contains all shoreline segments used to calculate shoreline change rates along sections of the Delmarva North coastal region where shoreline position data were available. These data adequately represented the shoreline position at the time of the survey. Remaining gaps in these data, if applicable, are a consequence of non-existing data or existing data that did not meet quality assurance standards.
Shoreline data have been acquired from 1845 to 2000, the horizontal accuracy of which varies with respect to data source from which the shorelines were digitized, the lidar data from which the shorelines were extracted, and the time period. Shorelines prior to 1950 have an estimated positional uncertainty of plus or minus 10.8 meters. Shorelines from 1960-1980 have an estimated positional uncertainty of plus or minus 5.1 meters. Air photo-derived shorelines from 1990-2000s have an estimated positional uncertainty of plus or minus 3.2 meters. Lidar shorelines from 1997 and 2000 have an estimated positional uncertainty of plus or minus 2.3 meters. Please visit the 'Uncertainties and Errors' section in the corresponding USGS Open-File Report (http://pubs.usgs.gov/of/2010/1118/) for a complete explanation of the measurement uncertainties associated with these shorelines.
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.
2008
Emily Himmelstoss
U.S. Geological Survey
Geologist
mailing and physical address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700 x2262
508-457-2310
ehimmelstoss@usgs.gov
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. 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.
2008
Meredith Kratzmann
U.S. Geological Survey
Contractor
mailing address
384 Woods Hole Road
Woods Hole
MA
02543
USA
508-548-8700
mkratzmann@usgs.gov
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.
2009
Meredith Kratzmann
U.S. Geological Survey
Contractor
mailing address
384 Woods Hole Road
Woods Hole
MA
02543
USA
508-548-8700
mkratzmann@usgs.gov
Shorelines were 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 19N (NAD 83); transformation = none.
2009
Emily Himmelstoss
U.S. Geological Survey
Geologist
mailing and physical address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700 x2262
508-457-2310
ehimmelstoss@usgs.gov
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.
2009
Kathryn Weber
U.S. Geological Survey
Geologist
mailing and physical address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700
508-457-2310
kweber@usgs.gov
The lidar data were collected in projected coordinates (WGS 84 UTM zone 18N). 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 > 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 GeoWizard 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 ETGeoWizard > 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 (DelmarvaN_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 New England and Mid-Atlantic coasts 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. http://woodshole.er.usgs.gov/project-pages/DSAS/version4/images/pdf/DSASv4.pdf
This process step and all subsequent process steps were performed by the same person - Emily Himmelstoss.
2009
Emily Himmelstoss
U.S. Geological Survey
Geologist
mailing and physical address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700 x2262
508-457-2310
ehimmelstoss@usgs.gov
Historic shoreline positions were projected in ESRI's ArcToolbox (v.9.3) > Data Management Tools > Projections and Transformations > Feature > Project. Parameters: input projection = UTM zone 19N (NAD 83); output projection = geographic coordinates (WGS84); transformation = NAD_1983_To_WGS_1984_1. Shorelines from all sources were then 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, Quad, Uncertainty (Uncy), Source, and Year). These fields are required for the Digital Shoreline Analysis System (DSAS), which was used to calculate shoreline change rates.
2009
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) v4.1 software to perform rate calculations.
2009
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.
2010
The data were projected in ArcToolbox v9.3 > Data Management Tools > Projections and Transformations > Feature > Project. Parameters: input projection = UTM zone 18N (WGS 84); output projection = geographic coordinates (WGS84); transformation = none.
2010
Edits to the metadata were made to fix any errors that MP v 2.9.34 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 an online link to the data in the identification section. Fixed cross-reference online links. Fixed a link in a process step. Minor fixes to the attribute format for some attributes were needed. The distribution format name was modified in an attempt to be more consistent with other metadata files of the same data format. 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.
20161116
U.S. Geological Survey
VeeAnn A. Cross
Marine Geologist
Mailing and Physical
384 Woods Hole Road
Woods Hole
MA
02543
508-548-8700 x2251
508-457-2310
vatnipp@usgs.gov
Keywords section of metadata optimized for discovery in USGS Coastal and Marine Geology Data Catalog.
20170207
U.S. Geological Survey
Alan O. Allwardt
Contractor -- Information Specialist
mailing and physical address
2885 Mission Street
Santa Cruz
CA
95060
831-460-7551
831-427-4748
aallwardt@usgs.gov
Added keywords from Coastal and Marine Ecological Classification Standard (CMECS) to metadata.
20180426
U.S. Geological Survey
Alan O. Allwardt
Contractor -- Information Specialist
mailing and physical address
2885 Mission Street
Santa Cruz
CA
95060
831-460-7551
831-427-4748
aallwardt@usgs.gov
Crossref DOI link was added as the first link in the metadata.
20191118
U.S. Geological Survey
VeeAnn A. Cross
Marine Geologist
Mailing and Physical
384 Woods Hole Road
Woods Hole
MA
02543-1598
508-548-8700 x2251
508-457-2310
vatnipp@usgs.gov
Added keywords section with USGS persistent identifier as theme keyword.
20200908
U.S. Geological Survey
VeeAnn A. Cross
Marine Geologist
Mailing and Physical
384 Woods Hole Road
Woods Hole
MA
02543-1598
508-548-8700 x2251
508-457-2310
vatnipp@usgs.gov
Vector
String
722
0.000001
0.000001
Decimal degrees
D_WGS_1984
WGS_1984
6378137.000000
298.257224
DelmarvaN_shorelines
Vector shorelines
U.S. Geological Survey
FID
Internal feature number.
ESRI
Sequential unique whole numbers that are automatically generated.
Shape
Feature geometry.
ESRI
Coordinates defining the features.
RouteID
Route identification value assigned to individual lidar shoreline line segments. A unique cross-shore profile identification value is stored at each vertex of the lidar route and serves as a common attribute to the shoreline uncertainty table (DelmarvaN_shorelines_uncertainty.dbf).
USGS
0
Short integer field where zeros are "no data" and automatically filled in for the remaining shoreline polylines not derived from lidar.
Information unavailable from original metadata.
Date_
Date of shoreline position; date of survey as indicated on source material. A default date of 07/01 was assigned to shorelines where only the year was known (month and day unknown). Using July, the mid-point month of the calendar year, minimizes the potential offset to the actual shoreline date by a maximum of six months.
USGS
Character string of length 10
Uncy
Estimate of shoreline position uncertainty. Actual shoreline position is within the range of this value (plus or minus, meters). The uncertainty was determined by Equation 2 in USGS Open-File Report (OFR) 2010-1118 (cross-referenced in this metadata file). The historic shoreline uncertainty values contain all of the measurement errors listed in Table 5 of OFR 2010-1118, except for the uncertainty of the High Water Line (HWL). The HWL uncertainty listed in Table 5 was averaged for the entire study region. However, the uncertainty of the HWL at an individual transect can be determined with more precision along the shoreline route. The HWL uncertainty was added to the historic shoreline uncertainty stored in the shoreline attribute table during the DSAS rate calculation process to better account for uncertainty at individual transects alongshore as opposed to using a regionally averaged value. This was done using linear referencing that interpolates a value based on data stored in the shoreline_uncertainty dBase file (.dbf) at a specific transect/shoreline intersect alongshore. The lidar shoreline position uncertainty is also stored in the associated shoreline_uncertainty.dbf file and values are interpolated at specific transect/shoreline intersections using the same linear referencing method. The lidar uncertainty attribute field was filled with null values while residing in the geodatabase. Upon exporting the shoreline feature class to a shapefile for publication, the null values in the lidar uncertainty field were automatically converted to zero values.
USGS
0
Zeros are "no data" and serve as place fillers for the lidar shorelines. Actual uncertainty values for lidar are stored in shoreline uncertainty dBase (.dbf) file.
USGS
Source
Agency that provided shoreline feature or the data source used (e.g. T-sheet) to digitize shoreline feature.
USGS
Information unavailable from original metadata.
Shape_Leng
Length of feature in meters units (UTM zone 19N, WGS 84)
ESRI
0.824284
31432.676981
Year_
Four digit year of shoreline
USGS
1845
2000
Default_D
Differentiates between shorelines that have known month and day attributes and those that use the default value of 07/01 when only the year is known.
USGS
0
Shoreline month and day are known.
U.S. Geological Survey
1
Shoreline month and day are unknown and default value of 07/01 was used.
U.S. Geological Survey
U.S. Geological Survey
mailing and physical address
Woods Hole Coastal and Marine Science Center
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700
508-547-2310
Downloadable Data: USGS Open-File Report 2010-1119
Neither the U.S. Government, the Department of the Interior, nor the USGS, nor any of their employees, contractors, or subcontractors, make any warranty, express or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, nor represent that its use would not infringe on privately owned rights. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the USGS in the use of these data or related materials.
Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Shapefile
ArcGIS 9.3
ESRI polyline shapefile
This WinZip (version 9.0) file contains a shapefile of historic shorelines from 1845 to 2000 for the sandy shorelines of Delmarva North from Cape Henlopen, Delaware to Chincoteague Inlet, Virginia.
Use WinZip or pkUnzip
0.814
http://pubs.usgs.gov/of/2010/1119/data/DelmarvaN_shorelines.zip
Data are downloadable via the World Wide Web (WWW).
None
This zip file contains data available in Environmental Systems Research Institute (ESRI) polyline shapefile format. The user must have ArcGIS or ArcView 3.0 or greater software to read and process the data file. In lieu of ArcView or ArcGIS, the user may utilize another GIS application package capable of importing the data. A free data viewer, ArcExplorer, capable of displaying the data is available from ESRI at www.esri.com.
20240318
Emily Himmelstoss
U.S. Geological Survey
Geologist
mailing and physical address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700 x2262
508-547-2310
whsc_data_contact@usgs.gov
The metadata contact email address is a generic address in the event the person is no longer with USGS. (updated on 20240318)
FGDC Content Standards for Digital Geospatial Metadata
FGDC-STD-001-1998
local time