Long-term shoreline change rates for the Southern California coastal region using the Digital Shoreline Analysis System version 5.0

Metadata also available as - [Outline] - [Parseable text] - [XML]

Frequently anticipated questions:

What does this data set describe?

Title:
Long-term shoreline change rates for the Southern California coastal region using the Digital Shoreline Analysis System version 5.0
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 as part of the Coastal Change Hazards programmatic focus, formerly 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 this national scale 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.
In this release, three new tidal datum-based mean high water (MHW) shorelines extracted from 2009/2010/2011, 2015, and 2016 lidar elevation data are included in the analysis (coverage not necessarily continuous statewide). The full range of shoreline data is 1852 to 2016. The proxy-datum bias correction has been applied on a transect-by-transect basis to reconcile offsets between the MHW shorelines and proxy-based HWL shorelines for the entire California coastal region which is divided into three subregions: Northern California (NorCal), Central California (CenCal), and Southern California (SoCal). In the previous report (Hapke et al., 2006), the proxy-datum bias correction was only applied to regional shoreline averages.
This shoreline change update for California reports proxy-datum bias corrected rates when that information was computed while extracting shoreline positions from lidar data. In areas where the methods for delineating shorelines did not include computing bias correction values, the rates are reported without that correction. The proxy-datum bias concept is explained further in Ruggiero and List (2009) and in the process steps of the metadata file associated with the transect rates.
  1. How might this data set be cited?
    U.S. Geological Survey, 20240112, Long-term shoreline change rates for the Southern California coastal region using the Digital Shoreline Analysis System version 5.0: data release DOI:10.5066/P94J0K7Z, 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., and Himmelstoss, Emily A., 2024, National Shoreline Change—A GIS compilation of vector shorelines and associated shoreline change data from the 1800s to 2010s for the coast of California: data release DOI:10.5066/P94J0K7Z, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    suggested citation: Kratzmann, M.G., Farris, A.S., and Himmelstoss, E.A., 2024, National Shoreline Change—A GIS compilation of vector shorelines and associated shoreline change data from the 1800s to 2010s for the coast of California: U.S. Geological Survey data release, https://doi.org/10.5066/P94J0K7Z.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -119.998349
    East_Bounding_Coordinate: -117.123910
    North_Bounding_Coordinate: 34.455975
    South_Bounding_Coordinate: 32.534428
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/64adda95d34e70357a293282?name=BG_Socal_transects_rates_LT.jpg&allowOpen=true (JPEG)
    Map view of data
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 2024
    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 (6828)
    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?
    Socal_transects_rates_LT.shp
    Transects were automatically generated by DSAS at a 90 degree angle to the user-specified baseline using a user-specified smoothing algorithm to maintain roughly parallel transects that are orthogonal with respect to the baseline. These attributes are for long-term rates in Southern California (Socal). (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. (Source: U.S. Geological Survey)
    Range of values
    Minimum:3
    Maximum:unlimited
    SHAPE_Leng
    Length of feature in meter units (UTM zone 11N, WGS 84) (Source: Esri)
    Range of values
    Minimum:0
    Maximum:unlimited
    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 (shoreline advance) and negative values indicating erosion (shoreline retreat).
    A 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. (Source: U.S. Geological Survey) Decimal values may be positive or negative, which is used to indicate landward (negative) or seaward (positive) movement through time. 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 correction 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) movement through time. 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).
    A LR2 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. (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.
    A LSE 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. (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 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.
    A LCI90 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. (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.
    Bias_NB
    Describes whether or not the proxy-datum bias correction was applied at a given transect. There may be sections of coast with alternate combinations of shoreline type where the bias cannot be applied. For example, transects with only HWL shoreline intersections, or transects that include MHW shoreline intersections with no bias, will not have a bias correction applied. In DSAS v5.0, the bias correction is applied up to 2 kilometers beyond the last bias data point in the baseline flow direction. (Source: U.S. Geological Survey)
    ValueDefinition
    BiasThe proxy-datum bias correction was applied.
    NBThe proxy-datum bias correction was not applied.
    Entity_and_Attribute_Overview:
    The entity and attribute information provided here describes the tabular data associated with long-term (greater than 50 years, and typically greater than 100 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 11N WGS 84 projection.
    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?

Long-term (greater than 50 years, and typically greater than 100 years) shoreline change rates for the California coast are included in this dataset. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.0, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate based on available shoreline data for Northern California (Oregon border to Tomales Bay), Central California (Tomales Bay to El Capitán State Beach), and Southern California (El Capitán State Beach to the border with Mexico). 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 5)
    Transect features generated in a personal geodatabase using DSAS v5.0 for long-term rate calculations. Transects truncate at the landwardmost shoreline intersection.
    Long-term rate calculation parameters used: baseline layer=baseline_CA_[NorCal, CenCal, SoCal], baseline group field=NULL, baseline=midshore, transect spacing=50 meters, search distance=1000 meters, smoothing distance=900 meters, land direction=right, shoreline intersection=seaward, clip to extent=checked, File produced= transects_[Nor, Cen, So]_LT.
    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 5)
    Some transects were manually edited or deleted in an edit session using standard editing tools in ArcMap v10.7.
    Date: 2020 (process 3 of 5)
    Shoreline intersects and rate calculations performed for long-term rates with and without the proxy-datum bias correction. Parameters Used: shoreline layer=shorelines_CA_[Norcal, Cencal, Socal], shoreline date field=DATE_, shoreline uncertainty field name=Uncy, the default accuracy=15 meters, shoreline intersection=seaward, stats calculations=LRR, shoreline threshold=3, confidence interval=90%. File produced (Norcal)= transects_Nor_LT_rates_20200728_170343. File produced (Cencal)= transects_Cen_LT_rates_20200725_175846. File produced (Socal)= transects_So_LT_rates_20200729_163635.
    Date: 2020 (process 4 of 5)
    The rate feature classes were exported to shapefiles in ArcMap v10.7 by right-clicking the transect layer > data > export data. Files renamed [Norcal, Cencal, Socal]_transects_rates_LT.
    Date: 2020 (process 5 of 5)
    The exported rate shapefiles were projected in Esri's ArcToolbox (v10.7) > Data Management Tools > Projections and Transformations > Project. Parameters: input projection - UTM zone 10N (WGS84)(Norcal, Cencal), UTM zone 11N (WGS84)(Socal); output projection - geographic coordinates (WGS84); transformation = none.
  3. What similar or related data should the user be aware of?
    Kratzmann, Meredith G., 2024, National Shoreline Change—Summary Statistics of Shoreline Change From the 1800s To the 2010s for the Coast of California: data report 1187, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details: Data report associated with data release DOI:10.5066/P94J0K7Z.
    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 5.0): U.S. Geological Survey Software: software release version 5.0, U.S. Geological Survey, Reston, VA.

    Online Links:

    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:

    Hapke, Cheryl J., Reid, David, Richmond, Bruce M., Ruggiero, Peter, and List, Jeff, 2006, National Assessment of Shoreline Change Part 3: Historical Shoreline Change and Associated Coastal Land Loss Along Sandy Shorelines of the California Coast: Open-File Report 2006-1219, 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 long-term shoreline change rates for the region. Additional transects may have been generated but did not meet the required number of shorelines (at least three) or time period requirements (cannot be all historical shorelines or all modern lidar shorelines) and are not included here.
  5. How consistent are the relationships among the observations, including topology?
    These data were generated using DSAS v5.0. 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 v5.0 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?
    Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (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. Although these data have been processed successfully on a computer system at the U.S. Geological Survey (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.
  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: 12-Jan-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.
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_P94J0K7Z/Socal_transects_rates_LT_metadata.faq.html>
Generated by mp version 2.9.51 on Tue Oct 15 09:53:08 2024