Sara L. Zeigler
Emily J. Sturdivant
Benjamin T. Gutierrez
20191220
ElevMHW: Elevation adjusted to local mean high water: Smith Island, VA, 2014
1.0
raster digital dataset
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/5daa3801e4b09fd3b0c9cf17
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.
This digital elevation model (DEM) represents the elevation (adjusted for mean high water tidal datum) for each 5x5 m cell within the boundaries of the Smith Island, Virginia study area as measured by lidar collected in 2014. See Zeigler and others (2019) for additional details.
The DEM is part of a series of spatial datasets used to describe characteristics of barrier islands found along the North American Atlantic coast in order to identify habitat for the federally protected piping plover (Charadrius melodus). Information contained in these spatial datasets was used within a Bayesian network to model the probability that a specific set of landscape characteristics would be associated with piping plover habitat.
For additional information on processing and use of this geospatial dataset, see the USGS Open-File report by Zeigler and others (2019).
201311
201406
Collection period of the source lidar data.
None planned
-75.92738691
-75.82825409
37.18136655
37.10935845
USGS Metadata Identifier
USGS:5daa3801e4b09fd3b0c9cf17
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 Habitat
Smith Island
Virginia Coast Reserve
ISO 19115 Topic Category
oceans
elevation
USGS Thesaurus
geospatial datasets
geospatial analysis
geomorphology
digital elevation models
lidar
topography
None
Virginia
VA
Delmarva Peninsula
Smith Island
North America
United States
USA
Atlantic Ocean
Virginia Coast Reserve
None. Please see 'Distribution Info' for details.
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.
U.S. Geological Survey
Sara L. Zeigler
mailing address
384 Woods Hole Road
Woods Hole
MA
02543
US
508-548-8700 x2290
508-457-2310
szeigler@usgs.gov
https://www.sciencebase.gov/catalog/file/get/5daa3801e4b09fd3b0c9cf17/?name=Elev_cei_browse.png
Example DEM. This example is for Cedar Island, VA and does 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
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
https://pubs.usgs.gov/of/2005/1027/
This file consists of raster data produced from elevation data and tidal datum values through a semi-automated process described below. No further logical accuracy tests were conducted on the present dataset.
This dataset is clipped to a custom boundary and may not include the entire spatial extent of the original source datasets as they are published in original form. However, the custom boundary spans the entire coverage of the Smith Island site relevant to the broader research program (see Zeigler and others, 2019 for more details). This dataset is therefore considered complete for the information presented as described in the abstract section. Users are advised to read the rest of the metadata record carefully for additional details.
The horizontal accuracy of the raster inherited the accuracy of the source digital elevation model (DEM), which was dependent on the accuracy of the source lidar. Refer to source contribution below for details. No projection transformations were required, because the source DEM was downloaded in NAD83 UTM Zone 18N. As such, horizontal accuracy was not affected by reprojection. The source DEM was resampled to 5-m resolution using bilinear interpolation. We estimate the accuracy of this elevation raster to be within 1 m horizontally.
No formal accuracy assessments were conducted on the final DEM.
The vertical accuracy of the raster inherited the accuracy of the source digital elevation model (DEM), which was dependent on the accuracy of the source lidar. Refer to source contribution below for details. The source DEM was resampled to 5-m resolution using the ‘Resample’ tool with bilinear interpolation in ArcToolbox version 10.4.1. Elevation values were adjusted to the operational mean high water (MHW) value for the region as determined by Weber and others (2005) (refer to processing descriptions below). According to Weber and others (2005), tidal datums used to calculate location-specific offsets are accurate within 6 cm.
We estimate an overall conservative vertical accuracy of the final DEM within 1 m. However, areas with abrupt changes in elevation (e.g., a raster cell with a very low elevation adjacent to a cell with a very high elevation) may experience degraded vertical accuracy due to resampling.
No formal accuracy assessments were conducted on the final DEM.
Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Geodetic Survey (NGS), Remote Sensing Division
Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management (OCM)
20151220
2014 NOAA Post-Sandy Topobathymetric LiDAR: Void DEMs South Carolina to New York
map
Silver Spring, MD
NOAA's Ocean Service, National Geodetic Survey (NGS)
https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=4967
https://coast.noaa.gov/htdata/raster2/elevation/Post_Sandy_DEM_2014_4967
https://coast.noaa.gov/dataviewer
https://inport.nmfs.noaa.gov/inport/item/48367
digital data
201311
201406
ground condition
DEM
Source elevation dataset used directly to produce this MHW elevation raster. Source data were downloaded from https://coast.noaa.gov/dataviewer in horizontal datum NAD 1983 (2011), UTM Zone 18N, vertical datum NAVD88. Downloaded on 4/8/2016.
Full methods and justification are provided in the associated Methods OFR (Zeigler and others, 2019).
Starting with the lidar-based source digital elevation model (DEM) for the study area, we converted the GeoTIFF file to a raster grid in ArcGIS (version 10.4.1) in the study area’s extent (as set in the geoprocessing Environment Settings). The study area boundaries were previously set using a polygon vector layer, a custom boundary that includes the entire Smith Island site relevant to the broader research program (see Zeigler and others, 2019 for more details). The study area extent has no further impacts on data contained in the final dataset presented here.
We then resampled the resolution of the DEM (in Esri raster grid format) from 1 m to 5 m using the Resample tool in ArcToolbox version 10.4.1. In the Resample tool, we employed the bilinear resampling technique, which calculates the value of each pixel by averaging (weighted for distance) the values of the surrounding four cells.
In Raster Calculator in ArcToolbox, we subtracted the mean high water (MHW) offset (0.34) for the Smith Island study area, as previously determined by Weber and others (2005). This process adjusts the source DEM’s original NAVD88-referenced elevation values so that 0 m elevation is MHW based on regional tidal values. See Weber and others (2005) for additional information.
Finally, we reclassified all NoData cells in the study area to a fill value of ‘9999’. All cells outside the study area were given a NoData value of -9999, and these cells were excluded from all subsequent analyses. The distinction between fill values and NoData values allowed us to include cells with missing values–denoted by fill values–in subsequent analyses. Cells with NoData values were excluded (Zeigler and others, 2019).
No projection transformations were required, because the source DEM was downloaded in NAD83 UTM Zone 18N.
2017
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
Raster
Grid Cell
1746
1614
1
Universal Transverse Mercator
18
0.9996
-75
0.0
500000.0
0.0
row and column
5.0
5.0
meters
North_American_Datum_1983
GRS 1980
6378137.0
298.2572221010042
Mean High Water tidal datum from Weber and others (2005)
0.01
meters
Explicit elevation coordinate included with horizontal coordinates
Smi14_ElevMHW.tif
Raster geospatial data file.
Producer defined
Value
Elevation in meters corrected to the MHW datum published by Weber and others (2005). See Weber and others (2005) for additional information on operational offsets for adjusting elevation values MHW tidal datum relative to NAVD88. Cells within the study area extent that were missing values were given a fill value of ‘9999’. Cells outside the study area extent were given a NoData value of ‘-9999’.
Producer defined
-2.12273
4.15863
The raster layer (5x5 m resolution) depicts a given location's elevation above sea-level, corrected for mean high water offset (Weber and others, 2005). This elevation layer is derived from aerial lidar. Please review Zeigler and others (2019) for detailed information. A fill value of ‘9999’ indicates cells within the study area with missing values. A NoData value of '-9999' applies to all cells outside the study area extent. Cells with fill values (9999) were used in subsequent analyses and those with NoData values (-9999) were excluded from analysis (Zeigler and others, 2019).
Methods Open-File Report by Zeigler and others (2019)
U.S. Geological Survey - ScienceBase
mailing and physical address
Denver Federal Center, Building 810, Mail Stop 302
Denver
CO
80225
USA
1-888-275-8747
sciencebase@usgs.gov
These data files comprise a GeoTIFF (Smi14_ElevMHW.tif) file with a continuous elevation value for each 5x5 m cell. Additionally, the CSDGM FGDC metadata (Smi14_ElevMHW.tif.xml) and the browse graphic (elev_cei_browse.png) are included. These data 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.
GeoTIFF
ArcGIS 10.4
32-bit GeoTIFF
A 32-bit GeoTIFF, a browse PNG image, and FGDC CSDGM metadata in XML format.
16.5
https://www.sciencebase.gov/catalog/item/5daa3801e4b09fd3b0c9cf17
https://www.sciencebase.gov/catalog/file/get/5daa3801e4b09fd3b0c9cf17
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 a 32-bit GeoTIFF format.
20200810
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
FGDC Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998