Joseph F. Terrano
Kathryn E.L. Smith
20210723
Transects with net change results for GPS and Worldview shorelines for the Grand Bay National Estuarine Research Reserve in Mississippi from 2013-2020
1.0
Vector Digital Data Set (Polyline)
Joseph F. Terrano
Kathryn E.L. Smith
Jonathan L. Pitchford
Michael Archer
Michael Brochard
20210723
Shorelines from High-resolution WorldView Satellite Imagery, Real-time Kinematic Global Positioning Data, and Aerial Imagery for 2013 to 2020 for Study Sites Within Grand Bay National Estuarine Research Reserve, Mississippi
U.S. Geological Survey data release
doi:10.5066/P9W8TNQM
St. Petersburg, Florida
U.S. Geological Survey - St. Petersburg Coastal and Marine Science Center
https://doi.org/10.5066/P9W8TNQM
Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into coastal management, including shoreline monitoring and change analysis. Geospatial shoreline data were created from a semi-automated methodology using WorldView (WV) satellite data between 2013 and 2020. The data were compared to contemporaneous field-surveyed Real-time Kinematic (RTK) Global Positioning System (GPS) data collected by the Grand Bay National Estuarine Research Reserve (GBNERR) and digitized shorelines from U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) orthophotos. Field data for shoreline monitoring sites was also collected to aid interpretation of results. This data release contains digital vector shorelines, shoreline change calculations for all three remote sensing data sets, and field surveyed data. The data will aid managers and decision-makers in the adoption of high-resolution satellite imagery into shoreline monitoring activities, which will increase the spatial scale of shoreline change monitoring, provide rapid response to evaluate impacts of coastal erosion, and reduce cost of labor-intensive practices. For further information regarding data collection and/or processing methods, refer to the associated journal article (Smith and others, 2021).
This dataset contains transects with net shoreline change calculations for GPS and WorldView shorelines. The purpose of these data is for the calculation of shoreline change for marsh shorelines of the GBNERR from 2013-2020.
20130919
20201117
ground condition
As needed
-88.465572
-88.391272
30.387934
30.325082
USGS Metadata Identifier
USGS:87a82118-e083-498d-8d60-91465a9c025a
None
shoreline data
shoreline map
global positioning system
USGS Thesaurus
coastal processes
aerial photography
digitization
ISO 19115 Topic Category
oceans
environment
boundaries
geoscientificInformation
None
Grand Bay National Estuarine Research Reserve
Gulf of Mexico
USA
Mississippi
MS
None
The U.S. Geological Survey requests to be acknowledged as originator of the data in future products or derivative research. This metadata record should be reviewed in its entirety to ensure specific data are suitable for other studies. WorldView imagery remains the property of Maxar Technologies and is not published in this data release (Maxar, 2021). Aerial imagery from Earth Explorer is publically avaliable and free to download (Earth Explorer, 2021). Shoreline change rates are influenced by availability and accuracy of shoreline data. Analyses of highly dynamic areas are particularly challenging, including 1) areas near inlets, where there are excessively dynamic depositional/erosional sand bars that may appear/disappear rapidly, and 2) tidal creek shorelines where the vegetation/water line is not easily distinguished. Transects were modified so they crossed the shorelines in a perpendicular direction, but some small peninsulas were difficult to determine a perpendicular direction. Users of this data should examine the variables and values closely to determine if the analyses are appropriate for their intended purpose.
U.S. Geological Survey St Petersburg Coastal and Marine Science Center
Joseph F. Terrano
Researcher III
Mailing
600 4th Street South
St. Petersburg
FL
33701
727-502-8047
727-502-8182
jterrano@contractor.usgs.gov
Acknowledgment of the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, as a data source would be appreciated in products developed from these data, and such acknowledgment as is standard for citation and legal practices. Sharing of new data layers developed directly from these data would also be appreciated by the U.S. Geological Survey staff. Users should be aware that comparisons with other datasets for the same area from other time periods may be inaccurate due to inconsistencies resulting from changes in photointerpretation, mapping conventions, and digital processes over time. These data are not legal documents and are not to be used as such. For access and pricing of imagery please contact Maxar Technologies.
Environment as of Metadata Creation: Microsoft Windows 10 Version 1909 (Build 18363.1441); Esri ArcGIS 10.5.1 (Build 7333) Service Pack N/A (Build N/A); AMBUR version 4.0.4
Jackson, C.W., Jr.
2010
Basic User Guide for the AMBUR package for R, version 1.0a.
Unknown
Unknown
User guide includes requirements for shorelines that are to be run through Analyzing moving Boundaries Using R (AMBUR)
http://ambur.r-forge.r-project.org/user/ambur%20basic%20user%20guide%201_0a.pdf.
Maglione, P., Parente, C. and Vallario, A.
2014
Coastline extraction using high resolution WorldView-2 satellite imagery
United Kingdom
European Journal of Remote Sensing
Defines an "apparent shoreline" on page 177.
https://doi.org/10.5721/EuJRS20144739
U.S. Geological Survey
2021
EarthExplorer
Reston, VA
U.S. Geological Survey
Repository used to acquire remotely sensed imagery. Commercial satellite imagery (such as WV) is only available to qualified Federal users at no cost and must contact the USGS Earth Resources Observation & Science Center (EROS) for requirements.
https://earthexplorer.usgs.gov/
Maxar Technologies
2021
Global Enhanced GEOINT Delivery (G-EGD)
Westminster, CO
Maxar Technologies (formerly DigitalGlobe Inc.)
Commercial satellite imagery repository. For access requirements please contact Maxar Technologies.
https://evwhs.digitalglobe.com/myDigitalGlobe/login
Smith, K.E.L., Terrano, J.F., Pitchford, J.L., Archer, M.
2021
Coastal wetland shoreline change monitoring: A comparison of shorelines from high-resolution WorldView satellite imagery, aerial imagery, and field surveys
Special Issue; New Insights into Ecosystem Monitoring Using Geospatial Techniques
Unknown
Basel, Switzerland
MDPI; Remote Sensing
Associated journal article with additional methodology, data analysis, and results.
Unknown
Shoreline change rates are influenced by availability and accuracy of shoreline data. Analyses of highly dynamic areas are particularly challenging, including 1) areas near inlets, where there are excessively dynamic depositional/erosional sand bars that may appear/disappear rapidly, and 2) tidal creeks, where the land/water line is hard to distinguish due to sporadic vegetation lines.
Vector features and attributes were checked for completeness and accuracy within ArcGIS. Linework is generated by the "Construct transects" and "Filter transects" algorithm in the AMBUR program and are generally perpendicular to the shorelines. However, where shorelines experience sharp bends, such as in small bays and narrow spits, the filter algorithm can create transects that are not perpendicular to the shoreline. Transects not covering a study area shoreline were removed as they would not calculate rates of change in AMBUR.
Dataset is considered complete for the information presented. GPS shorelines were only collected at specific sites and do not cover the entire study area. WV data was subject to image availability and not all dates cover the entire study area. Users are advised to read the rest of the metadata record carefully for additional details. This dataset contains transects with net shoreline change rates. To view shorelines and shoreline metadata please see the main data release page (https://doi.org/10.5066/P9W8TNQM).
A formal accuracy assessment of the horizontal positional information in the dataset has not been conducted. Elevation and water levels were not addressed in this study. For additional information on data collection techniques see the source metadata.
Several factors may influence the accuracy and uncertainty of shoreline position for vegetated shorelines, such as water level. Water level at the time of imagery collection was not taken into account when deriving shorelines. Published general uncertainty estimates for shorelines were used for all shorelines in this study based on the data source (satellite derived, GPS). WV imagery classifications were checked along study area shorelines to ensure the land/water classification was correct. WV shorelines cover extensive amounts of Grand Bay and not all shorelines beyond the transects were checked for detailed accuracy. The classification also has potential variations in shoreline positions from other published data due to image interpretation differences.
Joseph F. Terrano and Kathryn E.L. Smith
20210723
WorldView Shorelines of the Grand Bay National Estuarine Research Reserve from 2013 to 2020.
vector digital data
St Petersburg, Florida
U.S. Geological Survey
Shorelines derived from WorldView 2 or 3 and GPS data used to generate transects. Not all dates have complete study area coverage.
https://doi.org/10.5066/P9W8TNQM
digital data
20130919
20201117
ground condition
WV_GPS_NetChng_2013_2020.shp
Transects with net shoreline change calculations derived from GPS and WorldView shorelines.
For the methods used to derive the shorelines, please refer to the GPS and WorldView metadata records with this data release. Transects were generated by buffering the available shoreline datasets to create inner (land based) and outer (water based) baselines. The baselines form the start and end point for shoreline-perpendicular transects. Baselines were input into the AMBUR statistical package for R (version 4.0.4). AMBUR has several tools, which utilize shoreline parallel baselines to generate transects that are generally perpendicular to the shoreline. Transects were constructed at a sampling distance of 10 meters. Length varied depending on location, and so a length longer than the largest shoreline distance to ensure transects covered all dated shorelines. Once transects were created, the Filter Transects tool was used to adjust and even out the spread of transects. Where shorelines experience sharp bends, such as in small bays and narrow spits, transects may fall at a non-perpendicular angle. Please see the shoreline datasets to determine the estuarine shorelines analyzed. When necessary, final transects were checked and edited in ArcGIS ArcMap (version 10.5.1), to improve analysis results and improve shoreline coverage. Transects were manually edited to reduce errors in the analyses or to provide a more perpendicular intersection with the shorelines. Shoreline points and final statistical analyses were completed in AMBUR to generate the shoreline change rates. The following analysis parameters were used: first intersection (if transect intersects the same shoreline more than once, then by default it selected the first intersection), confidence level 95 (confidence level for the linear regression statistics), unit label m (the units of measure for the map is for Universal Transverse Mercator, in meters), analysis type is advanced (advanced includes additional statistics for a robust linear regression), and time unit for rates is "year" (utilizes years for calculating rates of shoreline change). More information on the AMBUR program can be obtained from Jackson (2010). Transects not covering study area shorelines were removed.
Transects with net shoreline change calculations derived from GPS and WorldView shorelines.
2021
Joseph F. Terrano
Researcher III
mailing and physical
600 4th Street South
St.Petersburg
FL
33701
USA
727-502-8047
jterrano@contractor.usgs.gov
Additional fields were added to the shapefile’s attribute table such as water level (wl) and year fraction (yr_frac). Water level was collected from the National Oceanic and Atmospheric Administration (NOAA) tides and currents webpage using the Dauphin Island station (https://tidesandcurrents.noaa.gov/waterlevels.html?id=8735180). Water level was collected for as close to the time the WorldView image was taken. Year fraction was calculated as the number of days between the GPS collection date and the WorldView date divided by 365 (leap years by 366). Due to having the GPS date as the starting date of the calculation, this often resulted in a negative value for the year fraction.
2021
Joseph F. Terrano
Researcher III
mailing and physical
600 4th Street South
St.Petersburg
FL
33701
USA
727-502-8047
jterrano@contractor.usgs.gov
Vector
String
1637
Universal Transverse Mercator
16
0.9996
-87.0
0.0
500000.0
0.0
coordinate pair
0.6096
0.6096
Meter
D_North_American_1983
GRS_1980
6378137.0
298.257222101
WV_GPS_NetChng_2013_2020.shp
Attribute table containing attribute information associated with the 2013 to 2020 Grand Bay, MS transects with net shoreline change calculations.
USGS
Transect
Number automatically generated by AMBUR as a unique identifier for each transect.
USGS
360
2442
Net_Chng
Net shoreline change measurement (NSM) between the GPS and Worldview shorelines calculated by AMBUR. If the NSM is negative, the transect hits the GPS shoreline before the WorldView shoreline. If the NSM is positive, the transect hits the WorldView shoreline before the GPS shoreline.
USGS
-31.068415
26.330462
Meters
year
4-digit year in which the imagery was collected. 2017 has three data sets so they are listed as 2017, 2017_2, and 2017_3.
USGS
2013
2020
Year
gps_date
Date the GPS data was collected in the mm/dd/yyyy format.
USGS
09/19/2013
11/13/2020
wv_date
Date the WorldView imagery was collected in the mm/dd/yyyy format.
USGS
12/17/2013
11/17/2020
wl
Water level at the Dauphin Island tidal station at the time the WorldView image was collected using "NAVD" as the datum. "NAVD" is refering to the NAVD88 datum.
USGS
-0.338
0.541
Meter relative to NAVD88
yr_fract
Year fraction was calculated as the number of days between the GPS collection date and the WorldView date divided by 365 (366 for leap years). Due to having the GPS date as the starting date of the calculation, this often resulted in a negative value for the year fraction.
USGS
-0.410959
0.106849
Site
Site the data was collected at.
USGS
BHM
Site at Bayou Heron Mouth.
GBNERR
MBN
Site at Middle Bay North.
GBNERR
MBS
Site at Middle Bay South.
GBNERR
MBW
Site at Middle Bay West.
GBNERR
GBE
Site at Grand Battures East.
GBNERR
BSI
Site at Bird Island.
GBNERR
SPAL
Site at North Jose Bay.
GBNERR
MET
Site at meterological station island.
GBNERR
PACN
Site at Point aux Chenes North.
GBNERR
PACM
Site at Point aux Chenes Middle.
GBNERR
PACS
Site at Point aux Chenes South.
GBNERR
U.S. Geological Survey St Petersburg Coastal and Marine Science Center
Joseph F. Terrano
Researcher III
Mailing
600 4th Street South
St. Petersburg
FL
33701
727-502-8047
727-502-8182
jterrano@contractor.usgs.gov
WV_GPS_NetChng_2013_2020.shp
This digital publication was prepared by an agency of the United States Government. Although these data have been processed successfully on a computer system at the U.S. Geological Survey, no warranty expressed or implied is made regarding the display or utility of the data on any other system, nor shall the act of distribution imply any such warranty. The U.S. Geological Survey shall not be held liable for improper or incorrect use of the data described and (or) contained herein. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof.
Shapefile
https://coastal.er.usgs.gov/data-release/doi-P9W8TNQM/data/WV_GPS_NetChng_2013_2020.zip
None. No fees are applicable for obtaining the dataset.
20210721
U.S. Geological Survey St Petersburg Coastal and Marine Science Center
Joseph F. Terrano
Researcher III
Mailing
600 4th Street South
St. Petersburg
FL
33701
727-502-8047
727-502-8182
jterrano@contractor.usgs.gov
Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998
local time