Short-term shoreline change rates for the Georgia coastal region using the Digital Shoreline Analysis System version 5

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Frequently anticipated questions:

What does this data set describe?

Title:
Short-term shoreline change rates for the Georgia coastal region using the Digital Shoreline Analysis System version 5
Abstract:
During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion along the southeast US coastline and implications for vulnerability to future storms.
  1. How might this data set be cited?
    U.S. Geological Survey, 20210929, Short-term shoreline change rates for the Georgia coastal region using the Digital Shoreline Analysis System version 5: data release DOI:10.5066/P9J3CVN4, U.S. Geological Survey, Coastal and Marine Hazards and Resources Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

    This is part of the following larger work.

    Kratzmann, Meredith G., Farris, Amy S., Weber, Kathy M., Henderson, Rachel E., and Himmelstoss, Emily A., 2021, USGS National Shoreline Change: A GIS compilation of Updated Vector Shorelines (1800s - 2010s) and Associated Shoreline Change Data for the Georgia and Florida Coasts: data release DOI:10.5066/P9J3CVN4, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    suggested citation: Kratzmann, M.G., Farris, A.S., Weber, K.M., Henderson, R.E., and Himmelstoss, E.A., 2021, USGS National Shoreline Change: A GIS compilation of Updated Vector Shorelines (1800s - 2010s) and Associated Shoreline Change Data for the Georgia and Florida Coasts: U.S. Geological Survey data release, https://doi.org/10.5066/P9J3CVN4
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -81.461035
    East_Bounding_Coordinate: -80.840820
    North_Bounding_Coordinate: 32.024230
    South_Bounding_Coordinate: 30.714825
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/614a7d82d34e0df5fb9756fe?name=BG_GA_transects_rates_ST.jpg (jpg)
    Map view of data
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 2021
    Currentness_Reference:
    publication date
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: vector digital data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      This is a Vector data set. It contains the following vector data types (SDTS terminology):
      • String (2628)
    2. What coordinate system is used to represent geographic features?
      Horizontal positions are specified in geographic coordinates, that is, latitude and longitude. Latitudes are given to the nearest 0.0000001. Longitudes are given to the nearest 0.0000001. Latitude and longitude values are specified in Decimal degrees. The horizontal datum used is WGS_1984.
      The ellipsoid used is WGS_1984.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257223563.
  7. How does the data set describe geographic features?
    GA_transects_rates_ST.shp
    Transects were automatically generated by DSAS at a 90 degree angle to the user-specified baseline using a smoothing algorithm to maintain roughly parallel transects that are orthogonal with respect to the baseline. These attributes are for short-term rates in Georgia (GA). Count = 2628. (Source: U.S. Geological Survey)
    FID
    Internal feature number used as a unique identifier of an object within a table primarily used in shapefiles. (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: Esri) Coordinates defining the features.
    TransectID
    A unique identification number for each transect. Values may not increment sequentially alongshore. (Source: U.S. Geological Survey) Sequential unique whole numbers that are automatically generated.
    BaselineID
    Unique identification number of the baseline segment. If BaselineID=0 no transects will be generated. Used by DSAS to determine transect ordering alongshore if multiple baseline segments exist. (Source: U.S. Geological Survey)
    Range of values
    Minimum:1
    Maximum:unlimited
    TransOrder
    Assigned by DSAS based on ordering of transects along the baseline. Used to allow user to sort transect data along the baseline from baseline start to baseline end. (Source: U.S. Geological Survey)
    Range of values
    Minimum:0
    Maximum:unlimited
    Azimuth
    Assigned by DSAS to record the azimuth of the transect measure in degrees clockwise from North. If a transect position has been adjusted during the editing process, the azimuth value in the attribute table is updated automatically. (Source: U.S. Geological Survey)
    Range of values
    Minimum:0
    Maximum:360
    Units:degrees
    ShrCount
    Number of shorelines used to compute shoreline change metrics. If ShrCount = 2 only an end point rate (EPR) is computed since there are not enough shorelines to compute a linear regression rate (LRR). (Source: U.S. Geological Survey)
    Range of values
    Minimum:2
    Maximum:unlimited
    SHAPE_Leng
    Length of feature in meter units (UTM zone 17N, WGS 84) (Source: Esri)
    Range of values
    Minimum:0
    Maximum:unlimited
    EPR
    The end point rate is calculated by dividing the distance of shoreline movement by the time elapsed between two shorelines, the oldest and most recent only. The rate is reported in meters per year with positive values indicating accretion and negative values indicating erosion. (Source: U.S. Geological Survey) Decimal values may be positive or negative, which is used to indicate landward (negative) or seaward (positive) direction from baseline origin. Reported in meters per year.
    NB_EPR
    End point rate-of-change statistic as described in the attribute EPR but without the proxy-datum bias applied. NB=no bias. (Source: U.S. Geological Survey) Decimal values may be positive or negative, which is used to indicate landward (negative) or seaward (positive) direction from baseline origin. Reported in meters per year.
    EPRunc
    Describes the uncertainty of the reported end point rate in meters. The shoreline uncertainties for the two positions used in the end point calculation are each squared, then added together (summation of squares). The square root of the summation of squares is divided by the number of years between the two shorelines. This result is reported as the confidence of the end point rate calculation (EPRunc). (Source: U.S. Geological Survey) Positive decimal values in meters.
    NB_EPRunc
    The uncertainty of the reported end point rate in meters as described in the attribute EPRunc for rates without the proxy-datum bias applied (NB_EPR). NB=no bias. (Source: U.S. Geological Survey) Positive decimal values in meters.
    LRR
    A linear regression rate-of-change statistic was calculated by fitting a least-squares regression line to all shoreline points for a particular transect. Any shoreline points that are referenced to HWL were adjusted by the proxy-datum bias distance (meters) along the transect to correct for the offset between proxy-based HWL and datum-based MHW shorelines. The best-fit regression line is placed so that the sum of the squared residuals (determined by squaring the offset distance of each data point from the regression line and adding the squared residuals together) is minimized. The linear regression rate is the slope of the line. The rate is reported in meters per year with positive values indicating accretion and negative values indicating erosion.
    For short-term (ST) rates, an LRR value of 9999 in the attribute table means that value is Null. ArcGIS automatically changes Null values to zero values when a feature class is exported from a geodatabase to a shapefile. Zero values were changed to 9999 to clearly identify Null values. This scenario occurs when ShrCount = 2 and only an EPR rate is calculated. (Source: U.S. Geological Survey) Decimal values may be positive or negative, which is used to indicate landward (negative) or seaward (positive) direction from baseline origin. Reported in meters per year.
    NB_LRR
    A linear regression rate-of-change statistic as described in the attribute LRR but without the proxy-datum bias applied. NB=no bias. (Source: U.S. Geological Survey) Decimal values may be positive or negative, which is used to indicate landward (negative) or seaward (positive) direction from baseline origin. Reported in meters per year.
    LR2
    The R-squared statistic, or coefficient of determination, is the proportion of variance in the data that is explained by a regression. It is a dimensionless index that ranges from 1.0 to 0.0 and measures how successfully the best-fit line accounts for variation in the data. The smaller the variability of the residual values around the regression line relative to the overall variability, the better the prediction (and closer the R-squared value is to 1.0).
    For short-term (ST) rates, an LR2 value of 9999 in the attribute table means that LR2 is Null. ArcGIS automatically changes Null values to zero values when a feature class is exported from a geodatabase to a shapefile. Zero values were changed to 9999 to clearly identify Null values. This scenario occurs when ShrCount = 2 and only an EPR rate is calculated. (Source: U.S. Geological Survey)
    Range of values
    Minimum:0
    Maximum:1
    NB_LR2
    The R-squared statistic, or coefficient of determination, as described in the attribute LR2 but for NB (no bias) rates. (Source: U.S. Geological Survey)
    Range of values
    Minimum:0
    Maximum:1
    LSE
    This quantity is the standard error of the regression, also known as the standard error of the estimate. To calculate it, the distance between each data point and the regression line is calculated. These distances are squared then summed. The sum is divided by the number of data point minus two. The square root is taken of the result.
    For short-term (ST) rates, an LSE value of 9999 in the attribute table means that LSE is Null. ArcGIS automatically changes Null values to zero values when a feature class is exported from a geodatabase to a shapefile. Zero values were changed to 9999 to clearly identify Null values. This scenario occurs when ShrCount = 2 and only an EPR rate is calculated. (Source: U.S. Geological Survey) Positive decimal values in meters.
    NB_LSE
    The standard error as described in the attribute LSE but for NB (no bias) rates. (Source: U.S. Geological Survey) Positive decimal values in meters.
    LCI90
    The standard error of the slope with confidence interval describes the uncertainty of the reported rate. The LRR rates are determined by a best-fit regression line for the shoreline data at each transect. The slope of this line is the reported rate of change (in meters/year). The confidence interval (LCI) is calculated by multiplying the standard error (also called the standard deviation) of the slope by the two-tailed test statistic at the user-specified 90 percent confidence. This value is often reported in conjunction with the slope to describe the confidence of the reported rate. For example: LRR = 1.2 LCI90 = 0.7 could be reported as a rate of 1.2 (+/-) 0.7 meters/year.
    For short-term (ST) rates, an LCI90 value of 9999 in the attribute table means that LCI90 is Null. ArcGIS automatically changes Null values to zero values when a feature class is exported from a geodatabase to a shapefile. Zero values were changed to 9999 to clearly identify Null values. This scenario occurs when ShrCount = 2 and only an EPR rate is calculated. (Source: U.S. Geological Survey) Positive decimal values in meters.
    NB_LCI90
    The 90 percent confidence interval as described in the attribute LCI90 but for NB (no bias) rates. (Source: U.S. Geological Survey) Positive decimal values in meters.
    Entity_and_Attribute_Overview:
    The entity and attribute information provided here describes the tabular data associated with short-term (approximately 30 years) shoreline change rates, as well as rates that incorporate the known unidirectional offset between proxy-based high water line features and datum-based mean high water line features (the proxy-datum bias), and rates that did not have the necessary information to correct for this offset (no bias). Please review the individual attribute descriptions for detailed information. All calculations for length are in meter units and were based on the UTM zone 17N WGS 84 projection. This region, Georgia, has two shapefiles describing rates: long-term (LT) and short-term (ST).
    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: Meredith G. Kratzmann
    384 Woods Hole Road
    Woods Hole, MA
    USA

    508-548-8700 (voice)
    508-457-2310 (FAX)
    mkratzmann@contractor.usgs.gov

Why was the data set created?

Shoreline positions were compiled prior to and following Hurricane Irma along the sandy shorelines of the Gulf of Mexico and Atlantic coasts of Florida and the coast of Georgia. Shoreline positions from the mid-1800s through 2018 were used to update the shoreline change rates for Florida and Georgia using the Digital Shoreline Analysis System (DSAS) software. The shoreline positions and updated shoreline change rates provide actionable information to homeowners, coastal communities, and managers of public and private properties to improve resiliency for long-term hazards.
Short-term (~30 years) shoreline change rates for the Georgia (GA) coastal region are included in this dataset. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate based on available shoreline data for Georgia. An end point rate was calculated also. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline, establishing measurement points which provide location and time information used to calculate rates of change. This dataset consists of shoreline change rates stored as a new transect layer.

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: 2020 (process 1 of 6)
    Transect features generated in a personal geodatabase using DSAS v5 for short-term rate calculations. Transects truncate at the landwardmost shoreline intersection.
    Short-term rate calculation: Transect features generated in a personal geodatabase using DSAS v5 using selected shoreline data (Year >= 1970) for short-term rate calculations. Short-term transects were cast separately due to the truncation (clipping) process since the end location is likely different when using a selection of the shorelines. Parameters Used: baseline layer=GA_baseline, baseline group field=NULL, baseline=midshore, transect spacing=50 meters, search distance=2000 meters, smoothing distance=900 meters, land direction=left, shoreline intersection=seaward, clip to extent=checked, File produced=GA_transectsST.
    For additional details on parameters, please see the DSAS help file distributed with the DSAS software, or visit the USGS website at: https://www.usgs.gov/centers/whcmsc/science/digital-shoreline-analysis-system-dsas
    This process step and all other process steps were performed by the same person - Meredith Kratzmann. Person who carried out this activity:
    U.S. Geological Survey
    Attn: Meredith Kratzmann
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 (voice)
    508-457-2310 (FAX)
    mkratzmann@contractor.usgs.gov
    Date: 2020 (process 2 of 6)
    Some transects were manually edited or deleted in an edit session using standard editing tools in ArcMap v10.7.
    Date: 2020 (process 3 of 6)
    Shoreline intersects and rate calculations performed for short-term rates with and without bias. Parameters Used: shoreline layer=GA_shorelines, shoreline date field=DATE_, shoreline uncertainty field name=Uncy, the default accuracy=5.1 meters, shoreline intersection=seaward, stats calculations=LRR, EPR, shoreline threshold=2, confidence interval=90%. File produced (GA)= GA_transectsST_rates_20201130_160032.
    Date: 2020 (process 4 of 6)
    The rate feature classes were exported to shapefiles in ArcMap v10.7 by right-clicking the transect layer > data > export data. File renamed GA_transects_rates_ST.
    Date: 2020 (process 5 of 6)
    The exported rate shapefiles were projected in Esri's ArcToolbox (v10.7) > Data Management Tools > Projections and Transformations > Project. Parameters: input projection - UTM zone 17N (WGS84); output projection - geographic coordinates (WGS84); transformation = none.
    Date: 27-Apr-2022 (process 6 of 6)
    Updated the cross-reference information with regards to the related Data Report (20220427). The metadata available from a harvester may supersede metadata bundled with the dataset. Compare the metadata dates to determine which metadata file is most recent. Person who carried out this activity:
    U.S. Geological Survey
    Attn: VeeAnn A. Cross
    384 Woods Hole Road
    Woods Hole, MA
    USA

    (508) 548-8700 x2251 (voice)
    508-457-2310 (FAX)
    vatnipp@usgs.gov
  3. What similar or related data should the user be aware of?
    Kratzmann, Meredith G., 2022, U.S. Geological Survey National Shoreline Change: Summary Statistics for Updated Vector Shorelines (1800s - 2010s) and Associated Shoreline Change Data for the Georgia and Florida Coasts: Data Report 1156, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Data Report associated with this data release: Kratzmann, M.G., Farris, A.S., Weber, K.M., Henderson, R.E., and Himmelstoss, E.A., 2021, USGS national shoreline change-A GIS compilation of updated vector shorelines (1800s - 2010s) and associated shoreline change data for the Georgia and Florida Coasts: U.S. Geological Survey data release, https://doi.org/10.5066/P9J3CVN4.
    Himmelstoss, Emily A., Farris, Amy S., Henderson, Rachel E., Kratzmann, Meredith G., Ergul, Ayhan, Zhang, Ouya, and Zichichi, Jessica L., 2018, Digital Shoreline Analysis System (version 5): U.S. Geological Survey Software: software release version 5, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details: Current version of software at time of use was 5.1
    Himmelstoss, Emily A., Henderson, Rachel E., Kratzmann, Meredith G., and Farris, Amy S., 2018, Digital Shoreline Analysis System (DSAS) Version 5.0 User Guide: Open-File Report 2018-1179, U.S. Geological Survey, Reston, VA.

    Online Links:

    Himmelstoss, Emily, Kratzmann, Meredith, and Thieler, E. Robert, 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:

    Himmelstoss, Emily, Kratzmann, Meredith, and Thieler, E. Robert, 2017, National Assessment of Shoreline Change: A GIS compilation of Updated Vector Shorelines and Associated Shoreline Change Data for the Gulf of Mexico Coast: Data release doi:10.5066/F78P5XNK, U.S. Geological Survey, Reston, VA.

    Online Links:

    Himmelstoss, Emily, Kratzmann, Meredith, and Thieler, E. Robert, 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:

    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:

    Miller, Tara L., Morton, Robert A., and Sallenger, Asbury H., 2005, The National Assessment of Shoreline Change: A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for the U.S. Southeast Atlantic Coast: Open-File Report 2005-1326, U.S. Geological Survey, Reston, VA.

    Online Links:

    Morton, Robert A., Miller, Tara L., and Moore, Laura J., 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, U.S. Geological Survey, Reston, VA.

    Online Links:

    Miller, Tara L., Morton, Robert A., Sallenger, Asbury H., and Moore, Laura J., 2004, The National Assessment of Shoreline Change: A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for the U.S. Gulf of Mexico: Open-File Report 2004-1089, U.S. Geological Survey, Reston, VA.

    Online Links:

    Ruggiero, Peter, and List, Jeffrey H., 200909, Improving Accuracy and Statistical Reliability of Shoreline Position and Change Rate Estimates: Journal of Coastal Research vol. 255, Coastal Education and Research Foundation, n/a.

    Online Links:

    Other_Citation_Details: pp. 1069-1081

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

  1. How well have the observations been checked?
    The attributes of this dataset are based on the field requirements of the Digital Shoreline Analysis System and were automatically generated by the software during the generation of the transect layer or during the calculation of shoreline change rates performed by the software.
  2. How accurate are the geographic locations?
    The uncertainty of the linear regression rate is estimated by the elements LR2, LSE and LCI90. See the attribute definition of each for more information.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    This dataset contains the transects automatically generated by the DSAS software application that were used to calculate short-term shoreline change rates for the region. Additional transects may have been generated but did not meet the required number of shorelines or time period requirements.
  5. How consistent are the relationships among the observations, including topology?
    These data were generated using DSAS v5. The transects automatically generated by the software were visually inspected along with the shoreline data prior to rate calculations. Sometimes transect positions were manually edited within a standard ArcMap edit session to adjust the position at which an individual transect intersected the shorelines to better represent an orthogonal position to the general trend of the coast over time.

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 These data were automatically generated using the DSAS v5 software applications. 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. These data are not to be used for navigation.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey - ScienceBase
    Federal Center, Building 810, MS 302
    Denver, CO
    USA

    1-888-275-8747 (voice)
    sciencebase@usgs.gov
  2. What's the catalog number I need to order this data set? The dataset contains the polyline rates of shoreline change data, (SHP and other shapefile components), browse graphic, and the FGDC CSDGM metadata.
  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. 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, 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 a polyline shapefile format. The user must have software to read and process the data components of a shapefile.

Who wrote the metadata?

Dates:
Last modified: 19-Mar-2024
Metadata author:
Meredith G. Kratzmann
U.S. Geological Survey
384 Woods Hole Road
Woods Hole, MA
USA

508-548-8700 (voice)
508-457-2310 (FAX)
whsc_data_contact@usgs.gov
Contact_Instructions:
The metadata contact email address is a generic address in the event the person is no longer with USGS. (updated on 20240319)
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_P9J3CVN4/GA_transects_rates_ST_metadata.faq.html>
Generated by mp version 2.9.51 on Wed Jun 26 15:25:06 2024