U.S. Geological Survey
2017
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Texas west (TXwest)
1
tabular digital data
data release
DOI:10.5066/F78P5XNK
Woods Hole Coastal and Marine Science Center, Woods Hole, MA
U.S. Geological Survey, Coastal and Marine Geology Program
https://doi.org/10.5066/F78P5XNK
https://www.sciencebase.gov/catalog/item/582ca551e4b04d580bd379a7
https://www.sciencebase.gov/catalog/file/get/582ca551e4b04d580bd379a7
E.A. Himmelstoss
M.G. Kratzmann
E.R. Thieler
2017
National Assessment of Shoreline Change— A GIS compilation of Updated Vector Shorelines and Associated Shoreline Change Data for the Gulf of Mexico Coast
1
data release
DOI:10.5066/F78P5XNK
Reston, VA
U.S. Geological Survey
https://doi.org/10.5066/F78P5XNK
https://www.sciencebase.gov/catalog/item/58055db4e4b0824b2d1c1ee2
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 table includes: measurement and positional errors associated with the 2000 and 2001 lidar shorelines for Texas west, a proxy-datum bias value that corrects for the unidirectional offset between the mean high water (MHW) elevation of the lidar and the high water line (HWL) shorelines, as well as a measurement uncertainty in the total water level.
The dataset contains a common attribute with the M-values stored for the lidar data within the TXwest_shorelines.shp. These data are used in conjunction with the shoreline file to calculate rates of shoreline change for the U.S. Geological Survey's (USGS) National Assessment of Shoreline Change Project.
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3. 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.
20000821
20011002
ground condition
None planned
-97.379029
-97.045221
27.834476
25.956466
USGS Metadata Identifier
USGS:582ca551e4b04d580bd379a7
None
lidar uncertainty
proxy-datum bias
high water line offsets
high water line uncertainty
Shoreline Change
Digital Shoreline Analysis System
DSAS
U.S. Geological Survey
USGS
Coastal and Marine Geology Program
CMGP
Woods Hole Coastal and Marine Science Center
National Assessment of Shoreline Change Project
National Oceanic and Atmospheric Administration
NOAA
Coastal Services Center
CSC
MHW
Mean High Water
HWL
High Water Line
Database IV format
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
None
Texas
TX
Aransas Pass
Port Aransas
Mustang Island
Padre Island
South Padre Island
Brazos Santiago Pass
Rio Grande
Gulf of Mexico
United States
North America
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
E.A. Himmelstoss
mailing and physical address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700
508-547-2310
ehimmelstoss@usgs.gov
Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.2.2.3552
Robert A. Morton
Tara L. Miller
Laura J. Moore
2004
National Assessment of Shoreline Change: Part 1 Historical Shoreline Changes and Associated Coastal Land Loss along the U.S. Gulf of Mexico
Open-File Report
2004-1043
Reston, VA
U.S. Geological Survey
https://pubs.usgs.gov/of/2004/1043/
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 4.3
https://woodshole.er.usgs.gov/project-pages/DSAS/version4/
https://woodshole.er.usgs.gov/project-pages/DSAS/
United States Geological Survey (USGS)
National Aeronautics & Space Administration (NASA)
Department of Commerce (DOC), National Oceanic & Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management (OCM)
20141114
2001 USGS/NASA Airborne Topographic Mapper (ATM) Lidar: Coastal Alabama, Florida, Louisiana, Mississippi, Texas
Charleston, SC
NOAA's Ocean Service, Office for Coastal Management (OCM)
Lidar data were obtained prior to the publication date listed in this citation.
https://coast.noaa.gov/dataviewer/index.html?action=advsearch&qType=in&qFld=ID&qVal=525
ftp://coast.noaa.gov/pub/DigitalCoast/lidar1_z/geoid12a/data/525
https://coast.noaa.gov/dataviewer
https://www.coast.noaa.gov
Texas Bureau of Economic Geology
unknown
Texas Bureau of Economic Geology Coastal Survey, San Bernard NWR, TX to Sabine Pass, LA
Austin, TX
Bureau of Economic Geology, The University of Texas at Austin
https://www.beg.utexas.edu/coastal.safe/2001%20final%20report.pdf
Peter Ruggiero
M.G. Kratzmann
E.A. Himmelstoss
E.R. Thieler
David Reid
2013
National Assessment of Shoreline Change: Historical Shoreline Change along the Pacific Northwest Coast
Open-File Report
2012-1007
Reston, VA
U.S. Geological Survey
https://pubs.usgs.gov/of/2012/1007/
E.A. Himmelstoss
M.G. Kratzmann
E.R. Thieler
2017
National Assessment of Shoreline Change: Summary Statistics for Updated Vector Shorelines and Associated Shoreline Change Data for the Gulf of Mexico and Southeast Atlantic Coasts
Open-File Report
2017-1015
Reston, VA
U.S. Geological Survey
https://doi.org/10.3133/ofr20171015
The attributes in this table record positional and measurement uncertainties and datum offsets calculated during the process of extracting an operational mean high water shoreline from the lidar data as described in the process steps. The field names are based on the requirements for use within the Digital Shoreline Analysis System (DSAS) software (USGS Open-File Report 2008-1278).
Each row contains data associated with an individual vertex point along the lidar shoreline in TXwest_shorelines.shp.
The table only contains data where a mean high water shoreline point could be extrapolated from the lidar.
The lidar shoreline has an average positional uncertainty of plus or minus 1.9 meters.
An operational Mean High Water (MHW) shoreline was extracted from the lidar surveys within MATLAB v7.6 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 20 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.
20081003
Amy Farris
U.S. Geological Survey
mailing and physical address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700
508-457-2310
afarris@usgs.gov
The series of operational MHW points extracted from the cross-shore lidar profiles were converted to a .dbf file 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.
For a detailed explanation of the method used to store bias and uncertainty data in a table, please refer to Appendix 2, section 12.3 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://woodshole.er.usgs.gov/project-pages/DSAS/version4/images/pdf/DSASv4_3.pdf
20090710
E.A. Himmelstoss
U.S. Geological Survey
mailing and physical address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700 x2262
508-457-2310
ehimmelstoss@usgs.gov
The shoreline uncertainty table (.dbf) was imported into a personal geodatabase in ArcCatalog v10.2 by right-clicking on the geodatabase > Import > Table (single). The uncertainty table was used with the Digital Shoreline Analysis System (DSAS) v4.3 software to perform rate calculations.
This process step and the subsequent process step was performed by the same person - M.G. Kratzmann.
20150908
M.G. Kratzmann
U.S. Geological Survey
mailing address
384 Woods Hole Road
Woods Hole
MA
02543
USA
508-548-8700
508-457-2310
mkratzmann@usgs.gov
The shoreline uncertainty table was exported from the personal geodatabase back to a stand-alone dBase file using ArcCatalog v10.2 by right-clicking on the database file > Export > To dBase file (single) for publication purposes.
20150909
Keywords section of metadata optimized for discovery in USGS Coastal and Marine Geology Data Catalog.
20170825
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 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
TXwest_shorelines_uncertainty
uncertainty table
U.S. Geological Survey
OID
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
ID
This field is case-sensitive and name specific. The field contains a cross-shore lidar profile ID stored as the M-value (measure value) at each vertex in the calibrated shoreline route. This serves as the link between the lidar shoreline and the uncertainty table and must be a unique number at each point.
U.S. Geological Survey
112
11215
UNCY
This field heading is case-sensitive and name specific. The field contains the plus/minus horizontal uncertainty (meters) in the lidar shoreline position at each cross-shore beach profile. For details on the components that make up this uncertainty, refer to the Methods section of USGS Open-File report 2012-1007 cross-referenced in the metadata.
U.S. Geological Survey
0
16.03
meters
BIAS
This field heading is case-sensitive and name specific. The field contains a proxy-datum bias value describing the unidirectional horizontal offset (in meters) between the MHW elevation of the lidar data and HWL shoreline positions.
U.S. Geological Survey
6.99
14.1
meters
UNCYB
This field heading is case-sensitive and name specific. The field contains the uncertainty in the calculated proxy-datum bias value (BIAS) in meters.
U.S. Geological Survey
2.829
7.301
meters
The entity and attribute information provided here describes the tabular data associated with the dataset. Please review the individual attribute descriptions for detailed information.
U.S. Geological Survey
U.S. Geological Survey
mailing and physical address
Denver Federal Center
Building 810
MS 302
Denver
CO
80225
USA
1-888-275-8747
sciencebase@usgs.gov
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.
dBase
IV
.dbf file format storing structured attribute data
This dBase file contains lidar positional and measurement uncertainties, proxy-datum bias offset values, and total water level uncertainties used when calculating rates in the Digital Shoreline Analysis System (DSAS) software with associated metadata.
no compression applied
0.822
https://www.sciencebase.gov/catalog/file/get/582ca551e4b04d580bd379a7
https://www.sciencebase.gov/catalog/item/582ca551e4b04d580bd379a7
https://www.sciencebase.gov/catalog/item/58055db4e4b0824b2d1c1ee2
https://doi.org/10.5066/F78P5XNK
The first link downloads the contents of the data page as a zip file, the second link is to the landing page of the data, the third and fourth links are to the main landing page of the data release.
None
These data are available in dBase file format. The user must have software capable of reading or importing the dBase formatted data file.
20200810
E.A. Himmelstoss
U.S. Geological Survey
mailing address
384 Woods Hole Road
Woods Hole
MA
02543-1598
USA
508-548-8700 x2262
508-457-2310
ehimmelstoss@usgs.gov
FGDC Content Standards for Digital Geospatial Metadata
FGDC-STD-001-1998
local time