2014 profile-derived mean high water shorelines of Cape Cod Bay, MA used in shoreline change analysis

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Frequently anticipated questions:


What does this data set describe?

Title:
2014 profile-derived mean high water shorelines of Cape Cod Bay, MA used in shoreline change analysis
Abstract:
The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using 2008-2009 color aerial orthoimagery and 2007 topographic LIDAR lidar datasets obtained from NOAA's Ocean Service, Coastal Services Center.
This 2018 update includes two new mean high water (MHW) shorelines for the Massachusetts coast extracted from lidar data collected between 2010-2014. The first new shoreline for the state includes data from 2010 along the North Shore and South Coast from lidar data collected by the U.S. Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX). Shorelines along the South Shore and Outer Cape are from 2011 lidar data collected by the U.S. Geological Survey's (USGS) National Geospatial Program Office. Shorelines along Nantucket and Martha’s Vineyard are from a 2012 U.S. Army Corps of Engineers Post Sandy Topographic lidar survey. The second new shoreline for the North Shore, Boston, South Shore, Cape Cod Bay, Outer Cape, South Cape, Nantucket, Martha’s Vineyard, and South Coast west of Buzzards Bay is from 2013-2014 lidar data collected by the U.S. Geological Survey's (USGS) Coastal and Marine Geology Program. Shorelines were extracted from these lidar surveys using several different methods dependent on the location of the shoreline and whether or not wave data were available.
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.
When this datum-based MHW shoreline is compared to historical proxy-based high water line (HWL) shorelines (e.g., when calculating shoreline change rates), the result may be affected by an offset between the two types of shorelines. Ruggiero and List (2009, citation in second process step of this metadata file) showed that for open-ocean sandy beaches, historical, proxy-based HWL shorelines tend to be landward of datum-based MHW shorelines. While this proxy-datum bias was estimated and corrected for in other datasets in this project, it has not been calculated for these data (hence the “NB” for no bias in the filename). Since there is no nearby buoy from which to gather wave data, the run-up equations used to estimate a proxy-datum bias value cannot be run. However, this shoreline extent tends to have lower wave energy than an open-ocean beach, which would result in less run-up and yield a smaller offset between a proxy-based HWL shoreline and this datum-based MHW shoreline than would occur along open-ocean coasts. This shoreline data has an associated uncertainty table that quantifies the measurement and positional errors associated with this lidar shoreline. The dataset contains a common attribute with the M-values stored for the lidar data within the CapeCodBay_pShorelineNB_2014_uncertainty.dbf. These data are used in conjunction with the shoreline file to calculate rates of shoreline change.
  1. How might this data set be cited?
    U.S. Geological Survey, 2018, 2014 profile-derived mean high water shorelines of Cape Cod Bay, MA used in shoreline change analysis: data release DOI:10.5066/P9O7S72B, 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.

    Himmelstoss, Emily A., Farris, Amy S., and Weber, Kathryn M., 2018, Massachusetts Shoreline Change Project: A GIS Compilation of Vector Shorelines for the 2018 update: data release DOI:10.5066/P9O7S72B, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Himmelstoss, E.A., Farris, A.S., and Weber, K.M., 2018, Massachusetts shoreline change project—A GIS compilation of vector shorelines for the 2018 update: U.S. Geological Survey data release, https://doi.org/10.5066/P9O7S72B.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -70.239774
    East_Bounding_Coordinate: -70.002113
    North_Bounding_Coordinate: 42.061834
    South_Bounding_Coordinate: 41.726787
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/5bd86584e4b0b3fc5ce9d9d0/?name=CapeCodBay_pShorelineNB_2014_browse.png (PNG)
    Map vie of the data
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 04-Apr-2014
    Ending_Date: 06-Apr-2014
    Currentness_Reference:
    ground condition of the data these shorelines are based on.
  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 (53)
    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 0.0197424726. Longitudes are given to the nearest 0.0261783948. Latitude and longitude values are specified in Decimal seconds. The horizontal datum used is WGS_1984.
      The ellipsoid used is WGS_84.
      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?
    CapeCodBay_pShorelineNB_2014.shp
    Table containing attribute information associated with the data set. (Source: U.S. Geological Survey)
    FID
    Internal feature number. (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: Esri) Coordinates defining the features.
    Route_ID
    Route identification value assigned to individual lidar shoreline line segments. A unique cross-shore profile identification value is stored at each vertex of the lidar route and serves as a common attribute to the shoreline uncertainty table CapeCodBay_pShorelineNB_2014_uncertainty.dbf (Source: U.S. Geological Survey)
    Range of values
    Minimum:6
    Maximum:65
    Date_
    Date of shoreline position; date of survey as indicated on source material. A default date of 07/01 was assigned to shorelines where only the year was known (month and day unknown). Using July, the mid-point month of the calendar year, minimizes the potential offset to the actual shoreline date by a maximum of six months. (Source: U.S. Geological Survey) Date of the shoreline in mm/dd/yyyy
    Uncy
    The estimate of shoreline position uncertainty for these data. A zero value indicates the uncertainty is stored in the associated uncertainty database file (CapeCodBay_pShorelineNB_2014_uncertainty.dbf). This field is only preserved for shoreline change analysis. The shoreline change software (DSAS ) uses linear referencing to interpolate an uncertainty value at the measurement location along the shoreline based on data stored in the uncertainty file. (Source: U.S. Geological Survey)
    ValueDefinition
    0.0Place holder in field. Actual values are stored in separate table.
    Source
    Agency that provided shoreline feature. (Source: U.S. Geological Survey)
    ValueDefinition
    lidar-USGSThe data were derived by the U.S. Geological Survey from lidar.
    Source_b
    Method of deriving shoreline feature. (Source: U.S. Geological Survey)
    ValueDefinition
    profile no biasThe mean high water shoreline was extracted from lidar data using a profile method. Due to the shoreline location and lack of wave buoy data, no bias was calculated.
    ATTRIBUTE
    The vertical shoreline reference. (Source: U.S. Geological Survey)
    ValueDefinition
    MHWmean high water
    Year_
    Four digit year of shoreline. (Source: U.S. Geological Survey)
    ValueDefinition
    2014The calendar year of the source data from which the shoreline feature was extracted.
    Default_D
    In historic shoreline data the exact month and day of a shoreline are unknown. This field is used to indicate when a default month and day are used. It does not apply to this dataset, but is preserved for merging this shoreline feature with other historic shoreline data for change analysis. (Source: U.S. Geological Survey)
    ValueDefinition
    0False. No default month and day were used.
    Shape_Leng
    Length of shoreline in meter units (WGS84, UTM zone 19N) calculated via Xtools Pro (v.16.1.2431). (Source: U.S. Geological Survey)
    Range of values
    Minimum:20.0096834552
    Maximum:8417.1098253
    Units:meters

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: Emily A. Himmelstoss
    384 Woods Hole Road
    Woods Hole, MA
    USA

    508-548-8700 x2262 (voice)
    508-547-2310 (FAX)
    ehimmelstoss@usgs.gov

Why was the data set created?

Shoreline positions serve as easily understood features that can be used to describe the movement of beaches through time. This particular shoreline dataset is a mean high water (MHW) datum-based shoreline extracted using a profile method. These data are used in conjunction with other shoreline files to calculate rates of shoreline change. Accompanying this dataset is an uncertainty table that quantifies the measurement and positional errors associated with this shoreline. See the first process step for essential information to understand these data and other shoreline change related data.

How was the data set created?

  1. From what previous works were the data drawn?
    2013-2014 lidar (source 1 of 1)
    Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management (OCM), and Woolpert, 20150615, 2013-2014 U.S. Geological Survey CMGP Lidar: Post Sandy (MA, NH, RI): NOAA's Ocean Service, Office for Coastal Management (OCM), Charleston, SC.

    Online Links:

    Type_of_Source_Media: online
    Source_Contribution:
    The LAS format (lidar data exchange file format) was used. Using the cart method to download the data, the data were downloaded in the UTM Zone 19 projection with the NAD83 horizontal datum and NAVD88 vertical datum with horizontal and vertical units in meters.
  2. How were the data generated, processed, and modified?
    Date: 2016 (process 1 of 5)
    Explanation of the methods used to delineate shoreline features that are a part of this update for the Massachusetts Office of Coastal Zone Management Shoreline Change Project:
    This data release has two methods of shoreline extraction: the profile method and the contour method. The profile method is further broken down into two varieties: shorelines that are extracted along open-ocean coasts and those that are sheltered.
    Profile open-ocean coast (bias): datum-based mean high water (MHW) shoreline. The elevation of MHW was obtained from Weber and others (2005). These data have an associated uncertainty table that provides the horizontal uncertainty associated with the shoreline, a proxy-datum bias value describing the unidirectional horizontal offset between the MHW shoreline and the historical proxy-based high water line (HWL) shorelines, and the uncertainty associated with the calculated proxy-datum bias value. These shorelines are polyline-M shapefiles.
    Profile not open-ocean (no bias): datum-based mean high water (MHW) shoreline. Since Weber and others (2005) only covers open-ocean coast, all MHW elevations for these data come from NOAA's vdatum (version 3.8; https://vdatum.noaa.gov/). These data have an associated uncertainty table that provides the horizontal uncertainty associated with the shoreline. These shorelines are polyline-M shapefiles.
    Contour method: this method is used along sections of the coast that were too crenulated for the for the profile method. The elevation of MHW was used from Weber and others, 2005 when available. In areas not covered by Weber and others (2005), NOAA's vdatum (version 3.8; https://vdatum.noaa.gov/) is used to determine MHW. Once this value is determined, the contour line of that value is extracted from the DEM surface in the area of interest. These shorelines are polyline shapefiles.
    Not included in this data release is another method of shoreline delineation. A brief explanation of this method is provided to convey the importance of the information contained in the uncertainty tables, even if that information is not actively used in all cases in this data release.
    Proxy-based historical shorelines: Vector shorelines digitized from georegistered T-sheets using standard editing tools in ArcMap provide a proxy-based high water line (HWL) feature that is not tidally-referenced. Individually these shorelines are stored as polyline shapefiles. In previous analyses (see Himmelstoss and others, 2011 listed in cross references) these data were published as a merged file with profile method data extracted from lidar. Therefore the published data are all polyline-M, but the historic HWL shorelines contain no linear referencing. Visually identified HWL-type proxy shorelines are virtually never coincident with datum-based MHW-type shorelines. In fact, HWL shorelines are almost universally estimated to be higher (landward) on the beach profile than MHW shorelines. Not accounting for this offset will cause shoreline change rates to be biased toward slower shoreline retreat, progradation rather than retreat, or faster progradation than in reality (for the typical case where datum-based MHW shorelines are more recent data than the proxy-based HWL shoreline dates).
    The Digital Shoreline Analysis System software (Himmelstoss and others, 2018) used to compute rates detects when proxy-based and datum-based shorelines are present and uses linear referencing to retrieve the information on bias and uncertainty stored in the DBF table associated with the profile method shorelines and correct for the proxy-datum bias offset.
    Date: 2016 (process 2 of 5)
    Whenever possible, a profile method was used to extract the operational Mean High Water (MHW) shoreline from the lidar point cloud data, using a Matlab-based approach (Matlab version 2015b) similar to the one developed by Stockdon and others (2002). Elevation values for the height of MHW were determined from vdatum (version 3.8) provided by NOAA (https://vdatum.noaa.gov/). We continued the practice set out by Weber and others, (2005) of using one MHW value for a continuous section of coast (as opposed to using a continuously varying value). We chose this value such that it is always within 15 cm of the value returned by vdatum at any point along the coast. For example, we used MHW = 0.6 m for all of Buzzards Bay even though vdatum shows it varying slightly over the basin. For the shorelines in this region we used an average MHW elevation of 1.44 meters. This profile method uses a coast-following reference line with 20 m spaced profiles. All lidar data points that are within 1 m of each profile are associated with that profile. All work is done on the 2 m wide profiles, working on a single profile at a time.
    For each profile, a linear regression was fit through data points on the foreshore and the regression was evaluated at the MHW elevation to yield the cross-shore position of the MHW shoreline. If there was a data gap at MHW or if the MHW elevation was obscured by water points, the linear regression was simply extrapolated to the MHW elevation. Foreshore beach slope is defined as the slope of the regression line.
    Each MHW shoreline point that was extracted using this profile method has an uncertainty associated with it. This uncertainty includes three components: 1) the 95% confidence interval on the linear regression estimate of the shoreline position; 2) the uncertainty associated with the elevation of the raw lidar data and; 3)the uncertainty due to extrapolation. These three components of uncertainty were added in quadrature to yield a total error for each shoreline point. For details on each component, see pp.12-13 under the section titled Lidar-Derived MHW Shoreline Position Uncertainty in Hapke and others (2011).
    There is a known horizontal offset between the datum-based lidar MHW shoreline and the proxy-based historical shorelines on open-ocean sandy beaches that nearly always acts in one direction (Ruggiero and List, 2009). In order to estimate the bias between these two types of shorelines, wave data from a nearby buoy is needed to calculate wave run-up. Many of the sheltered areas within the Massachusetts study area do not have nearby buoy data and a proxy-datum bias value cannot be calculated in these areas. Therefore when this new datum-based MHW shoreline is compared to historic proxy-based HWL shorelines in these sheltered areas, there may be some artificial landward offset of the historic data that has not been quantified and could potentially influence the rates. The north facing shoreline of Martha's Vineyard tends to have lower wave energy, which would result in less run-up and yield a smaller offset between a proxy shoreline and a datum shoreline than would occur along open-ocean coasts.
    Hapke, C.J., Himmelstoss, E.A., Kratzmann, M.G., List, J.H., and Thieler, E.R., 2011, National assessment of shoreline change—Historical shoreline change along the New England and Mid-Atlantic coasts: U.S. Geological Survey Open-File Report 2010-1118, 57 p., https://pubs.usgs.gov/of/2010/1118/.
    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, no. 5, p. 1069-1081. [Also available at https://www.jstor.org/stable/27752753]
    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, no. 3, p. 502-513. [Also available at https://www.jstor.org/stable/4299097] Person who carried out this activity:
    Amy S. Farris
    U.S. Geological Survey
    Oceanographer
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 x2344 (voice)
    afarris@usgs.gov
    Date: 2016 (process 3 of 5)
    The series of points representing the shoreline were converted into a calibrated route shapefile for use in ArcGIS using a Python script (for Python v2.7.12). The script generates a point shapefile, converts it to a polyline-M file, saves the uncertainty information in an accessory dBase (.dbf) file and finally generates a calibrated route for the newly-created polyline-M file. Calibration is based on the unique and sequential profile ID value provided with the point data and stored as the M-value. This value is also stored as an attribute in the uncertainty .dbf file and is used as the common attribute field linking the shoreline route file (filename_pshorelineNB.shp) to the uncertainty table (filename_pshorelineNB_uncertainty.dbf where filename indicates the area of work, such as MarthasVineyard, the p indicates the profile method, and the NB indicates that there is no proxy-datum bias information) storing the lidar positional uncertainty. This process step and all subsequent process steps, unless otherwise noted, were performed by the same person - Emily Himmelstoss. Person who carried out this activity:
    Emily A. Himmelstoss
    U.S. Geological Survey
    Geologist
    384 Woods Hole Road
    Woods Hole, MA

    508-458-8700 x2262 (voice)
    ehimmelstoss@usgs.gov
    Date: 2018 (process 4 of 5)
    The shoreline polyline-M shapefile was projected in Esri's ArcToolbox (v.10.5) > Data Management Tools > Projections and Transformations > Feature > Project.Parameters: input projection – NAD 83 UTM 19N; output projection - geographic coordinates (WGS 84); transformation - WGS_1984_To_NAD_1983_1.
    Date: 17-Nov-2021 (process 5 of 5)
    Added keywords section with USGS persistent identifier as theme keyword (20200810). Tweaked a thesaurus name (20211117). 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?
    Thieler, E.R., and Smith, T.L., 2013, Massachusetts Shoreline Change Mapping and Analysis Project, 2012 Update: Open-File Report 2012-1189, U.S. Geological Survey, Reston, VA.

    Online Links:

    Smith, Theresa L., Himmelstoss, Emily A., and Thieler, E. Robert, 2013, Massachusetts Shoreline Change Project: A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for the 2012 update: Open-File Report 2012-1183, U.S. Geological Survey, Reston,VA.

    Online Links:

    Thieler, E. Robert, O'Connell, James F., and Schupp, Courtney A., 2001, The Massachusetts Shoreline Change Project: 1800s to 1994 Technical Report: U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

    Himmelstoss, Emily A., Kratzmann, Meredith G., Hapke, Cheryl J., Thieler, E. Robert, and List, Jeffrey H., 2011, The National Assessment of Shoreline Change: A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for the New England and Mid-Atlantic Coasts: Open-File Report 2010-1119, U.S. Geological Survey, Reston, VA.

    Online Links:

    Weber, Kathryn M., List, Jeffrey H., and Morgan, Karen L.M., 2005, An operational mean high water datum for determination of shoreline position from topographic Lidar data: Open-File Report 2005-1027, U.S. Geological Survey, Reston, VA.

    Online Links:

    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:


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

  1. How well have the observations been checked?
    The attributes are based on the requirements of the Digital Shoreline Analysis System (DSAS) software, please refer to cross reference for citation.
  2. How accurate are the geographic locations?
    Each MHW shoreline point extracted using the profile method has an uncertainty associated with it. This uncertainty includes three components:
    1) the 95% confidence interval on the linear regression estimate of the shoreline position;
    2) the uncertainty associated with the elevation of the raw lidar data which is stated as 0.1 m RMS in the lidar metadata;
    3) the uncertainty due to extrapolation if the shoreline point was determined by extrapolation.
    These three components of uncertainty were then added in quadrature, yielding a total error for each shoreline point which is stored in the shoreline uncertainty DBF file associated with these data. Averaging these points for this region results in a positional uncertainty of plus or minus 2.02 meters.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    Although not a continuous shoreline for Cape Cod Bay, this shoreline file is complete. It contains all shoreline segments where shoreline position data could be extracted using the profile method. This dataset does not include any proxy-datum bias information because wave data were unavailable in this region. These data adequately represented the shoreline position at the time of the survey. Shorelines derived using a different method could potentially fill in the gaps. Remaining gaps in these data, if applicable, are a consequence of non-existing data or existing data that did not meet quality assurance standards.
  5. How consistent are the relationships among the observations, including topology?
    Adjacent shoreline segments do not overlap and are not necessarily continuous. Shorelines were visually assessed in map view to verify that no erroneous data were included.

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 - 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 shapefile of shoreline data derived from a profile method, (CapeCodBay_pShorelineNB_2014.shp and other shapefile components), browse graphic (CapeCodBay_pShorelineNB_2014_browse), and the FGDC CSDGM metadata in XML and TEXT format.
  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 a polyline-M 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:
Emily A. Himmelstoss
U.S. Geological Survey
384 Woods Hole Road
Woods Hole, MA
USA

508-548-8700 x2262 (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)

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