Emily J. Sturdivant
Sara L. Zeigler
Benjamin T. Gutierrez
Kathryn M. Weber
20191220
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Myrtle Island, VA, 2014
1.0
vector digital data
data release
DOI:10.5066/P9V7F6UX
Woods Hole Coastal and Marine Science Center, Woods Hole, MA
U.S. Geological Survey, Coastal and Marine Hazards and Resources Program
https://doi.org/10.5066/P9V7F6UX
https://www.sciencebase.gov/catalog/item/5daa37d0e4b09fd3b0c9cedd
Emily J. Sturdivant
Sara L. Zeigler
Benjamin T. Gutierrez
Kathryn M. Weber
2019
Barrier island geomorphology and shorebird habitat metrics: Sixteen sites on the U.S. Atlantic Coast, 2013–2014
1.0
data release
DOI:10.5066/P9V7F6UX
Reston, VA
U.S. Geological Survey
Suggested citation: Sturdivant, E.J., Zeigler, S.L., Gutierrez, B.T., and Weber, K.M., 2019, Barrier island geomorphology and shorebird habitat metrics—Sixteen sites on the U.S. Atlantic Coast, 2013–2014: U.S. Geological Survey data release, https://doi.org/10.5066/P9V7F6UX.
https://doi.org/10.5066/P9V7F6UX
https://www.sciencebase.gov/catalog/item/5d5ece47e4b01d82ce961e36
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.
These datasets measure positions of geomorphic features, specifically dune crests, dune toes, and mean high water (MHW) shoreline pertaining to sandy beaches at Myrtle Island, VA in 2014. They can be used to calculate beach width and height. The source data were created for the purpose of modeling coastal hazards related to dune overtopping.
Another version of these datasets is available at https://doi.org/10.5066/f7gf0s0z (Doran and others, 2017). The data were made available to this project prior to being released by Doran and others (2017). Slight differences between the two versions may be caused by data clean-up that was performed by this project in some cases.
20140108
20140727
Ground condition measured by source lidar data.
None planned
-75.82839272
-75.81686785
37.20430161
37.18513614
USGS Metadata Identifier
USGS:5daa37d0e4b09fd3b0c9cedd
ISO 19115 Topic Category
oceans
geoscientificInformation
None
Barrier Island
USGS
CMHRP
Geographic Information Systems
GIS
U.S. Geological Survey
Coastal and Marine Hazards and Resources Program
Woods Hole Coastal and Marine Science Center
St. Petersburg Coastal and Marine Science Center
MHW
Mean High Water
Coastal Hazards
Myrtle Island
Virginia Coast Reserve
USGS Thesaurus
geospatial datasets
geospatial analysis
geomorphology
transect sampling
None
Virginia
VA
Delmarva Peninsula
Myrtle Island
Virginia Coast Reserve
North America
United States
USA
Atlantic Ocean
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 (USGS) as the source of this information.
Sara L. Zeigler
U.S. Geological Survey
Mailing and Physical
384 Woods Hole Road
Woods Hole
MA
02543
United States
508-548-8700 x2290
szeigler@usgs.gov
https://www.sciencebase.gov/catalog/file/get/5daa37d0e4b09fd3b0c9cedd/?name=DC_DT_SLpts_asis_browse.png
Example geomorphology points (mean high water shoreline, dune toe, and dune crest) overlain on the DEM. This example is for Assateague Island, MD and may not represent this dataset.
PNG
Sara L. Zeigler
Emily J. Sturdivant
Benjamin T. Gutierrez
2019
Evaluating barrier island characteristics and piping plover (Charadrius melodus) habitat availability along the U.S. Atlantic coast—Geospatial approaches and methodology
Open-File Report
2019–1071
Reston, VA
U.S. Geological Survey
Details the methods used to process these data for use in barrier island and piping plover habitat modeling.
https://doi.org/10.3133/ofr20191071
Emily J. Sturdivant
2019
bi-transect-extractor
1.0
software release
DOI:10.5066/P915UYMY
Reston, VA
U.S. Geological Survey
Custom-built package used for data processing. The Jupyter notebook file distributed with these data were part of the processing to create these data. The notebook relies on this software package.
https://doi.org/10.5066/P915UYMY
https://code.usgs.gov/cmgp/bi-transect-extractor
Kathryn M. Weber
Jeffrey H. List
Karen L. M. Morgan
2005
An Operational Mean High Water Datum for Determination of Shoreline Position from Topographic Lidar Data
Open-File Report
2005-1027
Reston, VA
U.S. Geological Survey
Provides regional mean high water elevation used to determine shoreline position.
https://pubs.usgs.gov/of/2005/1027/
Kara J. Doran
Joseph W. Long
Justin J Birchler
Owen T. Brenner
Matthew W. Hardy
Karen L. M. Morgan
Hilary F. Stockdon
Miguel L. Torres
2017
Lidar-derived Beach Morphology (Dune Crest, Dune Toe, and Shoreline) for U.S. Sandy Coastlines
tabular digital data
Reston, VA
U.S. Geological Survey
Affiliated datasets created using the same methods. A version of this geomorphology points dataset is available as 14CNT01_morphology.zip. These data were made available to us prior to publication and as a result, processing steps may differ from what is described here.
https://doi.org/10.5066/F7GF0S0Z
Hilary F. Stockdon
Kara J. Doran
D. M. Thompson
K. L. Sopkin
Nathaniel G. Plant
Asbury H. Sallenger
2012
National assessment of hurricane-induced coastal erosion hazards: Gulf of Mexico
Open-File Report
2012–1084
Reston, VA
U.S. Geological Survey
Provides the methods for feature extraction (pp. 17–23).
https://pubs.usgs.gov/of/2012/1084/
Horizontal and vertical accuracy were estimated and recorded automatically during processing (see sections Positional Accuracy and Entity and Attribute Information). All output feature positions were manually verified against external aerial imagery and elevation data; positions deemed incorrect were manually deleted or relocated.
This dataset consists of three point shapefile datasets produced from elevation data and tidal datum values through an automated process described below. It was not explicitly checked for topological consistency, but feature locations were verified by displaying them with aerial imagery and digital elevation models. Incorrect feature positions were manually deleted or relocated. Alongshore gaps of feature positions exist where the feature could not be accurately located along the profile. Additionally, shoreline points were removed where groups of three or fewer consecutive points were separated from the shoreline trend in the surrounding areas.
Dune crest positions may indicate the peak of the berm rather than a dune crest. Dune toe position is only determined for a given profile if certain criteria are met (see first process step for details). The shoreline elevation is considered the elevation of mean high water (MHW) as documented by Weber and others (2005).
These data include dune crest positions and elevations (myr14_DCpts.shp), dune toe positions and elevations (myr14_DTpts.shp), and MHW shoreline positions (myr14_SLpts.shp). Processing attempted to locate positions every 10 m alongshore, but alongshore gaps greater than 10 m exist where features could not be accurately located along the cross-shore processing profile. Dune toe position is only determined for a given profile if certain criteria are met (see first process step for details). During post-processing, shoreline points were removed where groups of three or fewer consecutive points were separated from the shoreline trend in the surrounding areas.
Horizontal accuracy is dependent on the lidar point uncertainty and the density of and scatter in the lidar data points. For the shoreline points (myr14_SLpts.shp) cross-shore positional accuracy is estimated by calculating the 95% confidence interval of the linear regression of the shoreline position. It is reported in the field 'ci95_slx'.
Vertical accuracy is determined for each dune crest (myr14_DCpts.shp) feature and dune toe (myr14_DTpts.shp) feature based upon the scatter of data in the lidar grid cell. It is reported in the field 'z_error'.
Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Geodetic Survey (NGS), Remote Sensing Division
20170320
2014 NOAA Post Hurricane Sandy Topobathymetric LiDAR Mapping for Shoreline Mapping
https://coast.noaa.gov/htdata/lidar1_z/geoid12b/data/4800
digital data
20140108
20140727
ground condition
Lidar point cloud
Lidar survey that was used to estimate dune morphology variables.
A customized MATLAB routine was used to extract beach and dune morphology. The routine determines the position of the mean high water (MHW) shoreline and the position and elevation of dune toe and dune crest. The routine is summarized below. Refer to Stockdon and others (2012) for details and figures. A version of these data was released in Doran and others (2017).
Processing was performed in MATLAB version 2017a. Source lidar point clouds were adjusted to NAVD88 through a MHW-offset correction factor. The NAVD88 elevation of MHW is 0.34 m for the region encompassing Myrtle Island (Weber and others, 2005).
First, lidar point cloud data are interpolated to 10 m (alongshore) by 2.5 m (cross-shore) grids oriented parallel to a roughly shore-parallel reference line that is used for all such feature extractions (Doran and others, 2017). Interpolation uses a Hanning window that is twice as wide as the grid resolution to minimize noise. Automated routines then identify the position of the three features (dune crest, shoreline, and dune toe) for each elevation profile. Each step is performed by a separate MATLAB program.
To determine the dune crest position, the algorithm selects the peak of the most seaward sand dune. It does so by classifying inflection points in cross-shore slope as morphologic crests and troughs and identifying the highest crest elevation as the primary dune. In the absence of a dune, the beach berm was extracted. The selection is limited to areas within 200 m of the shoreline, seaward of built structures, less than 0.5 m vertical error, and higher than the MHW elevation.
For each profile, the position of the MHW shoreline is determined. The cross-shore location of the MHW shoreline is automatically extracted with the incorporation of the RMS error surface. The probability that a grid cell elevation value is equal to MHW elevation is estimated from a normal distribution of beach elevation. The grid cell with the highest probability within a defined distance of a prior shoreline is selected as the most likely shoreline. A more precise location of MHW is interpolated from a linear regression of the selected point and adjacent grid cells. A confidence interval for the estimate is defined from the regression error.
Once the dune crest position is established, the dune toe position is determined. First, if the dune crest position is understood to represent a beach berm because the elevation is less than the high water line (HWL), dune toe position is not determined for the given profile. In the remainder of cases, dune toe is identified as the point of maximum slope change between the shoreline and the dune crest unless the elevation of that point is within 0.5 m of the dune crest elevation or the curvature of the profile around the dune toe was negative.
The feature positions resulting from the automated routine are manually verified by overlaying the horizontal positions on high-resolution coastal imagery. Profiles with identified inconsistencies are viewed in a customized MATLAB Graphical User Interface (GUI) that displays the features with the lidar data (interpolated and point cloud) and allows the operator to relocate or delete feature positions. High density of built structures and complex topography often cause errors in the feature positions that require manual editing.
The positions are exported from Matlab with geographic coordinate values (WGS84) in a table of comma-separated values and converted to an Esri shapefile in NAD83 UTM Zone 18N (Make XY Event Layer tool in ArcGIS 10.5). Coordinates were transformed from WGS84 to NAD83 using the transformation WGS_1984_(ITRF00)_To_NAD_1983 (WKID: 108190, accuracy: 0.1 m).
Lidar point cloud
2017
Kara Doran
U.S. Geological Survey
mailing address
600 4th Street South
St. Petersburg
FL
33701
United States
727-502-8117
727-502-8182
kdoran@usgs.gov
Positions were converted from a table of comma-separated values to a shapefile using the function functions_warcpy.MorphologyCSV_to_FCsByFeature in the python package bi-transect-extractor (Sturdivant, 2019; version 1.0).
The dune crest, dune toe, and shoreline positions were overlaid on the DEM in ArcGIS 10.5 to check for incongruences between the morphology points and the elevation. Features that displayed logical inconsistency relative to the other features were flagged. For example, dune toe and crest points located seaward of shoreline points would be flagged and evaluated with reference to the DEM to determine which of the features were the more accurate. Shoreline points were removed where groups of three or fewer consecutive points (occupying 20 m or less alongshore) were separated from the shoreline trend in the surrounding areas (a general line suggested by the rest of the shoreline points and inferred by the operator). This is because sandy shorelines are expected to be generally linear features and these irregularities are often caused by an adjoining bar.
Finally, the points were converted from shapefile format to comma-separated text using the ArcGIS tool Export Table (version 10.5). Both the shapefile and the CSV files are included in this data release.
2018
Emily J Sturdivant
U.S. Geological Survey
mailing address
384 Woods Hole Road
Woods Hole
MA
02543
US
508-457-8700 x2230
508-457-2310
esturdivant@usgs.gov
Added keywords section with USGS persistent identifier as theme keyword.
20200810
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
Universal Transverse Mercator
18
0.9996
-75
0
500000.0
0
coordinate pair
0.6096
0.6096
meters
North_American_Datum_1983
GRS_1980
6378137.0
298.257222101
NAVD88
0.000001
meter
Attribute values
myr14_DCpts
Attribute values of 318 dune crest positions recorded in the Esri shapefile myr14_DCpts.shp.
USGS
FID
Internal feature number
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Feature geometry.
Esri
Coordinates defining the features.
state
State segment file identification (ID) number.
Producer defined
12
Virginia
Producer defined
seg
Segment ID number used in processing (also labeled "segment").
Producer defined
33
37
profile
Grid row number corresponding to a cross-shore profile location within the given segment.
Producer defined
1
94
lon
Longitude in WGS 84. Negative values indicate western hemisphere.
Producer defined
-75.828393
-75.81679
decimal degrees
lat
Latitude in WGS 84
Producer defined
37.185136
37.204282
decimal degrees
easting
Easting in NAD 83 UTM Zone 18N
Producer defined
426471.264295
427512.565393
meters
northing
Northing in NAD 83 UTM Zone 18N
Producer defined
4115731.720474
4117849.060002
meters
dhigh_x
Cross-shore feature location relative to the generalized reference line, only relevant during processing.
Producer defined
-934.851967
-270.564218
meters
dhigh_z
Feature elevation (NAVD88).
Producer defined
0.86518
1.913864
meters
z_error
Root mean squared vertical error of feature elevation (NAVD88).
Producer defined
0.01009
0.324658
meters
myr14_DTpts
Attributes for 32 dune toe positions recorded in the Esri shapefile myr14_DTpts.shp.
USGS
FID
Internal feature number
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Feature geometry.
Esri
Coordinates defining the features.
state
State segment file identification (ID) number.
Producer defined
12
Virginia
Producer defined
seg
Segment ID number used in processing (also labeled "segment").
Producer defined
34
36
profile
Grid row number corresponding to a cross-shore profile location within the given segment.
Producer defined
5
94
lon
Longitude in WGS 84. Negative values indicate western hemisphere.
Producer defined
-75.821064
-75.816539
decimal degrees
lat
Latitude in WGS 84
Producer defined
37.190334
37.197438
decimal degrees
easting
Easting in NAD 83 UTM Zone 18N
Producer defined
427126.739892
427534.678541
meters
northing
Northing in NAD 83 UTM Zone 18N
Producer defined
4116302.674986
4117087.390241
meters
dlow_x
Cross-shore feature location relative to the generalized reference line, only relevant during processing.
Producer defined
-548.775347
-376.100088
meters
dlow_z
Feature elevation (NAVD88).
Producer defined
1.012952
1.23232
meters
z_error
Root mean squared vertical error of feature elevation (NAVD88).
Producer defined
0.028808
0.139695
meters
myr14_SLpts
Attribute values for 165 shoreline positions recorded in the Esri shapefile myr14_SLpts.shp.
USGS
FID
Internal feature number
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Feature geometry.
Esri
Coordinates defining the features.
state
State segment file identification (ID) number.
Producer defined
12
Virginia
Producer defined
seg
Segment ID number used in processing (also labeled "segment").
Producer defined
33
36
profile
Grid row number corresponding to a cross-shore profile location within the given segment.
Producer defined
1
94
sl_x
Cross-shore feature location relative to the generalized reference line, only relevant during processing.
Producer defined
-573.999718
-305.391101
meters
ci95_slx
95% confidence interval for the shoreline position.
Producer defined
0.000346
0.264165
meters
slope
Mean beach slope calculated between dune toe and shoreline (NAVD88).
Producer defined
-0.088553
-0.004906
radians
easting
Easting in NAD 83 UTM Zone 18N
Producer defined
426541.838151
427597.773927
meters
northing
Northing in NAD 83 UTM Zone 18N
Producer defined
4115756.871306
4117199.927066
meters
MHW
Mean high water offset in meters.
Weber and others (2005)
0.34
0.34
meters
This section provides a separate detailed entity and attribute information section for each dataset described in these metadata. Each shapefile has a companion CSV file that contains the same information. The first row of the CSV is a header line and corresponds to the attributes described in the detailed entity and attribute section for that particular dataset. Fields may be reordered and the FID field may be replaced by a software-specific OBJECTID value, in which values do not directly match. The Shape attribute is unique to the shapefile format and is populated with NoData values in the CSV.
Methods Open-File Report by Zeigler and others, 2019
U.S. Geological Survey - ScienceBase
mailing address
Denver Federal Center, Building 810, Mail Stop 302
Denver
CO
80225
United States
1-888-275-8747
sciencebase@usgs.gov
These datasets contain three individual shapefile point and corresponding CSV datasets: Dune crest points (myr14_DCpts.shp and other shapefile components, myr14_DCpts.csv), dune toe points (myr14_DTpts.shp and other shapefile components, myr14_DTpts.csv) and shoreline points (myr14_SLpts.shp and other shapefile components, myr14_SLpts.csv). Additionally, the CSDGM FGDC metadata (myr14_DC_DT_SLpts_meta.xml) in XML format and the browse graphic (DC_DT_SLpts_asis_browse.png) in PNG format are included. These datasets can be downloaded individually or packaged on-demand in a zip file (see the Digital Transfer Option section).
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. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), and have been processed successfully on a computer system at the USGS, no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. The USGS or the U.S. Government shall not be held liable for improper or incorrect use of the data described and/or contained herein. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Shapefile
ArcGIS 10.5
Esri point shapefile and corresponding comma-separated values files
This dataset contains the point shapefiles and corresponding CSV files of the dune crest, dune toe, and shoreline positions. Also included is the CSDGM metadata and browse graphic.
0.1
https://www.sciencebase.gov/catalog/item/5daa37d0e4b09fd3b0c9cedd
https://www.sciencebase.gov/catalog/file/get/5daa37d0e4b09fd3b0c9cedd
https://doi.org/10.5066/P9V7F6UX
The first link is to the page containing the data. The second is a direct link to download all data available from the page as a zip file. The final link is to the publication landing page. The data page (first link) may have additional data access options, including web services.
None
To utilize these data, the user must have software capable of reading shapefile or CSV format.
20200810
Sara L. Zeigler
U.S. Geological Survey
Mailing and Physical
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700 x2290
(508) 457-2310
szeigler@usgs.gov
FGDC Content Standards for Digital Geospatial Metadata
FGDC-STD-001-1998