Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for northern North Carolina (NCnorth)

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Frequently anticipated questions:


What does this data set describe?

Title:
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for northern North Carolina (NCnorth)
Abstract:
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.
Supplemental_Information:
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.
  1. How might this data set be cited?
    U.S. Geological Survey, 2017, Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for northern North Carolina (NCnorth): data release DOI:10.5066/F74X55X7, U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

    This is part of the following larger work.

    Kratzmann, M.G., Himmelstoss, E.A., and Thieler, E.R., 2017, National Assessment of Shoreline Change— A GIS compilation of Updated Vector Shorelines and Associated Shoreline Change Data for the Southeast Atlantic Coast: data release DOI:10.5066/F74X55X7, U.S. Geological Survey, Reston, VA.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -78.543097
    East_Bounding_Coordinate: -75.460321
    North_Bounding_Coordinate: 36.548964
    South_Bounding_Coordinate: 33.841265
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 26-Sep-1997
    Ending_Date: 19-Aug-2009
    Currentness_Reference:
    ground condition
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: tabular digital data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
    2. What coordinate system is used to represent geographic features?
  7. How does the data set describe geographic features?
    NCnorth_shorelines_uncertainty
    uncertainty table (Source: U.S. Geological Survey)
    OID
    Internal feature number. (Source: 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. (Source: U.S. Geological Survey)
    Range of values
    Minimum:22
    Maximum:26107
    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. (Source: U.S. Geological Survey)
    Range of values
    Minimum:0.59
    Maximum:35.42
    Units: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. (Source: U.S. Geological Survey)
    Range of values
    Minimum:0
    Maximum:17.3
    Units: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. (Source: U.S. Geological Survey)
    Range of values
    Minimum:0
    Maximum:9.13
    Units:meters
    Entity_and_Attribute_Overview:
    The entity and attribute information provided here describes the tabular data associated with the dataset. Please review the individual attribute descriptions for detailed information.
    Entity_and_Attribute_Detail_Citation: U.S. Geological Survey

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • U.S. Geological Survey
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    U.S. Geological Survey
    Attn: E.A. Himmelstoss
    384 Woods Hole Road
    Woods Hole, MA
    USA

    508-548-8700 (voice)
    508-547-2310 (FAX)
    ehimmelstoss@usgs.gov

Why was the data set created?

This table includes: measurement and positional errors associated with the 1997 and 2009 lidar shorelines for North Carolina, 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 NCnorth_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.

How was the data set created?

  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
    Date: 13-Nov-2008 (process 1 of 7)
    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. The 1997 lidar data were processed in 2008 (20081113) and the 2009 lidar data were processed in 2014 (20140301). Person who carried out this activity:
    Amy Farris
    U.S. Geological Survey
    384 Woods Hole Road
    Woods Hole, MA
    USA

    508-548-8700 (voice)
    508-457-2310 (FAX)
    afarris@usgs.gov
    Date: 23-Mar-2010 (process 2 of 7)
    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 The 1997 lidar data were processed in 2010 (20100323) and the 2009 lidar data were processed in 2014 (20140317). Person who carried out this activity:
    E.A. Himmelstoss
    U.S. Geological Survey
    384 Woods Hole Road
    Woods Hole, MA
    USA

    508-548-8700 x2262 (voice)
    508-457-2310 (FAX)
    ehimmelstoss@usgs.gov
    Date: 2014 (process 3 of 7)
    The uncertainty table, which contains bias values for the entire state, was renamed for each subregion and the appropriate ID values were followed during the calculations for each subregion within the state. In North Carolina, bias values were averaged for the lidar shorelines included in the dataset. The measurement numbers (M-values) are the same from survey to survey, as they are based on the lidar profile extraction lines which are constant and do not change through time. Where the profile intersects the shorelines, it is the same ID number, therefore, the lidar shorelines are linear referenced to the same M-value. When the DSAS software calls to the uncertainty table, the same averaged bias value is used for the lidar shorelines at a given location. This process step and all subsequent process steps were performed by the same person: M.G. Kratzmann. Person who carried out this activity:
    M.G. Kratzmann
    U.S. Geological Survey
    384 Woods Hole Road
    Woods Hole, MA
    USA

    508-548-8700 (voice)
    508-457-2310 (FAX)
    mkratzmann@usgs.gov
    Date: 03-May-2016 (process 4 of 7)
    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.
    Date: 03-May-2016 (process 5 of 7)
    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.
    Date: 25-Aug-2017 (process 6 of 7)
    Keywords section of metadata optimized for discovery in USGS Coastal and Marine Geology Data Catalog. Person who carried out this activity:
    U.S. Geological Survey
    Attn: Alan O. Allwardt
    Contractor -- Information Specialist
    2885 Mission Street
    Santa Cruz, CA

    831-460-7551 (voice)
    831-427-4748 (FAX)
    aallwardt@usgs.gov
    Date: 10-Aug-2020 (process 7 of 7)
    Added keywords section with USGS persistent identifier as theme keyword. Person who carried out this activity:
    U.S. Geological Survey
    Attn: VeeAnn A. Cross
    Marine Geologist
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 x2251 (voice)
    508-457-2310 (FAX)
    vatnipp@usgs.gov
  3. What similar or related data should the user be aware of?
    Morton, Robert A., and Miller, Tara L., 2005, National Assessment of Shoreline Change: Part 2 Historical Shoreline Changes and Associated Coastal Land Loss along the U.S. Southeast Atlantic Coast: Open-File Report 2005-1401, U.S. Geological Survey, Reston, VA.

    Online Links:

    Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Ergul, A., 2009, Digital Shoreline Analysis System (DSAS) version 4.0 - An ArcGIS extension for calculating shoreline change: Open-File Report 2008-1278, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details: Current version of software at time of use was 4.3
    Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management, United States Geological Survey (USGS), and National Aeronautics and Space Administration (NASA), 20140121, 1997 Fall East Coast NOAA/USGS/NASA Airborne LiDAR Assessment of Coastal Erosion (ALACE) Project for the US Coastline: NOAA's Ocean Service, Office for Coastal Management, Charleston, SC.

    Online Links:

    Other_Citation_Details:
    Lidar data were obtained prior to the publication date listed in this citation.
    Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management (OCM), and Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX), 20141114, 2009 US Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) Lidar: Currituck, Dare, and Hyde Counties, North Carolina: NOAA's Ocean Service, Office for Coastal Management (OCM), Charleston, SC.

    Online Links:

    Other_Citation_Details:
    Lidar data were obtained prior to the publication date listed in this citation.
    Himmelstoss, E.A., Kratzmann, M.G., and Thieler, E.R., 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, U.S. Geological Survey, Reston, VA.

    Online Links:


How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
    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).
  2. How accurate are the geographic locations?
    The lidar shorelines from 1997 and 2009 have an average positional uncertainty of plus or minus 2.8 meters.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    The table only contains data where a Mean High Water shoreline point could be extrapolated from the lidar.
  5. How consistent are the relationships among the observations, including topology?
    Each row contains data associated with an individual vertex point along the lidar shorelines in NCnorth_shorelines.shp.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints: None.
Use_Constraints:
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.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey
    Denver Federal Center
    Denver, CO
    USA

    1-888-275-8747 (voice)
    sciencebase@usgs.gov
  2. What's the catalog number I need to order this data set?
  3. What legal disclaimers am I supposed to read?
    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.
  4. How can I download or order the data?
  5. What hardware or software do I need in order to use the data set?
    These data are available in dBase file format. The user must have software capable of reading or importing the dBase formatted data file.

Who wrote the metadata?

Dates:
Last modified: 10-Aug-2020
Metadata author:
M.G. Kratzmann
U.S. Geological Survey
384 Woods Hole Road
Woods Hole, MA
USA

508-548-8700 (voice)
508-457-2310 (FAX)
mkratzmann@usgs.gov
Metadata standard:
FGDC Content Standards for Digital Geospatial Metadata (FGDC-STD-001-1998)

This page is <https://cmgds.marine.usgs.gov/catalog/whcmsc/SB_data_release/DR_F74X55X7/NCnorth_shorelines_uncertainty.dbf.faq.html>
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