Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Event Hazards

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Frequently anticipated questions:

What does this data set describe?

Title:
Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Event Hazards
Abstract:
Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the likelihood of coastal change along the U.S coastline within the coming decade. The pilot study, conducted in the Northeastern U.S. (Maine to Virginia), is comprised of datasets derived from a variety of federal, state, and local sources. First, a decision tree-based dataset is built that describes the fabric or integrity of the coastal landscape and includes landcover, elevation, slope, long-term (>150 years) shoreline change trends, dune height, and marsh stability data. A second database was generated from coastal hazards, which are divided into event hazards (e.g., flooding, wave power, and probability of storm overwash) and persistent hazards (e.g., relative sea-level rise rate, short-term (about 30 years) shoreline erosion rate, and storm recurrence interval). The fabric dataset is then merged with the coastal hazards databases and a training dataset made up of hundreds of polygons is generated from the merged dataset to support a supervised learning classification. Results from this pilot study are location-specific at 10-meter resolution and are made up of four raster datasets that include (1) quantitative and qualitative information used to determine the resistance of the landscape to change, (2 & 3) the potential coastal hazards that act on it, (4) the machine learning output, or Coastal Change Likelihood (CCL), based on the cumulative effects of both fabric and hazards, and (5) an estimate of the hazard type (event or persistent) that is the likely to influence coastal change. Final outcomes are intended to be used as a first order planning tool to determine which areas of the coast may be more likely to change in response to future potential coastal hazards, and to examine elements and drivers that make change in a location more likely.
  1. How might this data set be cited?
    Sterne, Travis K., Pendleton, Elizabeth A., Lentz, Erika E., and Henderson, Rachel E., 20230228, Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Event Hazards: data release DOI:10.5066/P96A2Q5X, 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.

    Sterne, Travis K., Pendleton, Elizabeth A., Lentz, Erika E., and Henderson, Rachel E., 2023, Coastal Change Likelihood in the U.S. Northeast Region — Maine to Virginia: data release DOI:10.5066/P96A2Q5X, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Sterne, T.K., Pendleton, E.A., Lentz, E.E., and Henderson, R.E., 2023, Coastal Change Likelihood in the U.S. Northeast Region — Maine to Virginia: U.S. Geological Survey data release, https://doi.org/10.5066/P96A2Q5X.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -77.4828
    East_Bounding_Coordinate: -66.5998
    North_Bounding_Coordinate: 45.3000
    South_Bounding_Coordinate: 36.5148
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/61783250d34e4c6b7fe2a4a2?name=EvHaz_Graphic.jpg (JPEG)
    Outer Cape Cod with Event Hazard data layer.
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 2010
    Ending_Date: 2021
    Currentness_Reference:
    ground condition of source data
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: raster digital data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      This is a Raster data set. It contains the following raster data types:
      • Dimensions 128024 x 117988 x 1, type Grid Cell
    2. What coordinate system is used to represent geographic features?
      The map projection used is Mercator_1SP.
      Projection parameters:
      False_Easting: 0.0
      False_Northing: 0.0
      Latitude_of_Projection_Origin: 0.0
      Longitude_of_Central_Meridian: 0.0
      Standard_Parallel: 0.0
      Standard_Parallel: 0.0
      Planar coordinates are encoded using row and column
      Abscissae (x-coordinates) are specified to the nearest 10.0
      Ordinates (y-coordinates) are specified to the nearest 10.0
      Planar coordinates are specified in meters
      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?
    USGS_CCL_EventHazards_2022.tif
    Raster geospatial data file. (Source: U.S. Geological Survey)
    OID
    Internal object identifier. (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Value
    Unique numeric values contained in each raster cell. (Source: U.S. Geological)
    ValueDefinition
    1High tide flooding, wave power = 0 W/m, no overwash data
    11High tide flooding, wave power greater than 0 and less than or equal to 50 W/m, no overwash data
    21High tide flooding, wave power greater than 50 and less than or equal to 185 W/m, no overwash data
    31High tide flooding, wave power greater than 185 W/m, no overwash data
    100No high tide flooding, wave power = 0 W/m, overwash potential less than or equal to 25%
    101High tide flooding, wave power = 0 W/m, overwash potential less than or equal to 25%
    111High tide flooding, wave power greater than 0 and less than or equal to 50 W/m, overwash potential less than or equal to 25%
    121High tide flooding, wave power greater than 50 and less than or equal to 185 W/m, overwash potential less than or equal to 25%
    131High tide flooding, wave power greater than 185 W/m, overwash potential less than or equal to 25%
    200No high tide flooding, wave power = 0 W/m, overwash potential greater than 25% and less than or equal to 75%l
    201High tide flooding, wave power = 0 W/m, overwash potential greater than 25% and less than or equal to 75%
    211High tide flooding, wave power greater than 0 and less than or equal to 50 W/m, overwash potential greater than 25% and less than or equal to 75%
    221High tide flooding, wave power greater than 50 and less than or equal to 185 W/m, overwash potential greater than 25% and less than or equal to 75%
    231High tide flooding, wave power greater than 185 W/m, overwash potential greater than 25% and less than or equal to 75%
    300No high tide flooding, wave power = 0 W/m, overwash potential greater than 75%
    301High tide flooding, wave power = 0 W/m, overwash potential greater than 75%
    311High tide flooding, wave power greater than 0 and less than or equal to 50 W/m, overwash potential greater than 75%
    321High tide flooding, wave power greater than 50 and less than or equal to 185 W/m, overwash potential greater than 75%
    331High tide flooding, wave power greater than 185 W/m, overwash potential greater than 75%
    Count
    Number of raster cells with this value. (Source: Esri)
    Range of values
    Minimum:5051
    Maximum:276817125
    HTF
    High Tide Flooding: "Y" indicates a high likelihood that an area will become flooded during extreme tide events in the coming decade. "N" indicates a low relative likelihood to be affected by this potential hazard. (Source: U.S. Geological Survey)
    ValueDefinition
    Nindicates a low relative likelihood to be affected by high tide flooding
    Yindicates a high likelihood that an area will become flooded during extreme tide events in the coming decade
    Wave_Power
    Wave Power in Watts per meter (W/m). Value range indicates wave power in W/m that an area is likely to be exposed to in the coming decade. (Source: U.S. Geological Survey)
    ValueDefinition
    NoneNo wave power (0 W/m)
    LowWave power greater than 0 W/m, but less than 50 W/m
    ModerateWave power greater than or equal to 50 W/m, but less than 185 W/m
    HighWave power gretaer than 185 W/m
    Overwash
    Overwash potential for category 2 storm. Value refers to the probability that an area will experience overwash during a category 2 storm as described in Doran et al. (2020). (Source: U.S. Geological Survey)
    ValueDefinition
    NoDataNo Data
    LowProbability of storm overwash is less than 25 percent for a category 2 storm
    ModerateProbability of storm overwash is greater than 25 percent but less than 75 percent for a category 2 storm
    HighProbability of storm overwash is greater than 75 percent for a category 2 storm

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Travis K. Sterne
    • Elizabeth A. Pendleton
    • Erika E. Lentz
    • Rachel E. Henderson
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    U.S. Geological Survey
    Attn: Travis K Sterne
    384 Woods Hole Rd
    Woods Hole, MA

    (508) 548 8700 x2219 (voice)
    tsterne@usgs.gov

Why was the data set created?

Coastal Change Likelihood (CCL) is a first order planning tool that estimates the likelihood that an area of coast will experience change based on its inherit resistance to change, metrics associated with specific land cover types, and the hazards that impact a coast. The CCL Event Hazards dataset is a 10-meter-per-pixel (mpp) compilation of three event-driven coastal hazards (high-tide flooding, wave power, and overwash potential) used in building the final CCL product in geotiff format. Each raster cell is assigned a unique value based on the potential hazard scenario expected to occur in a given location. All relevant information pertaining to each grid cell is stored in the associated attribute table. This dataset covers the Northeast US coastline between +/- 10 meters elevation relative to mean high water (MHW) from Maine to Virginia.

How was the data set created?

  1. From what previous works were the data drawn?
    Shoreline Change - MA (source 1 of 5)
    Himmelstoss, E.A., Farris, A.S., and Weber, K.M., 20181126, Massachusetts Shoreline Change Project, 2018 Update: A GIS Compilation of Shoreline Change Rates Calculated Using Digital Shoreline Analysis System Version 5.0, With Supplementary Intersects and Baselines for Massachusetts.

    Online Links:

    Type_of_Source_Media: Digital and/or Hardcopy
    Source_Contribution: Shoreline Change Rates
    Shoreline Change - Not MA (source 2 of 5)
    Himmelstoss, E.A., Kratzmann, M., Hapke, C., Thieler, E.R., and List, J., 2010, 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.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Himmelstoss, E.A., Kratzmann, M., Hapke, C., Thieler, E.R., and List, J., 2010, 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: U.S. Geological Survey Open-File Report 2010–1119, available only online at https://pubs.usgs.gov/of/2010/1119.
    Type_of_Source_Media: Digital and/or Hardcopy
    Source_Contribution: Shoreline Change Rates
    PCOI (source 3 of 5)
    Doran, K.S., Birchler, J.J., Hardy, M.W., Bendik, K.J., Pardun, J.M., and Locke, H.A., 2020, National assessment of hurricane-induced coastal erosion hazards.

    Online Links:

    Other_Citation_Details:
    Doran, K.S., Birchler, J.J., Hardy, M.W., Bendik, K.J., Pardun, J.M., and Locke, H.A., 2020, National assessment of hurricane-induced coastal erosion hazards (ver. 2.0, February 2021): U.S. Geological Survey data release, https://doi.org/10.5066/P99ILAB9.
    Type_of_Source_Media: Digital and/or Hardcopy
    Source_Contribution: Dune Height, probability of overwash
    HTF (source 4 of 5)
    Sweet, W.V., Marcy, D., Dusek, G., Marra, J.J., and Pendleton, M., 2017, State of U.S. High Tide Flooding with a 2018 Outlook, National Oceanic and Atmospheric Administration (NOAA) Center for Operational Oceanographic Products and Services.

    Online Links:

    Type_of_Source_Media: Digital and/or Hardcopy
    Source_Contribution: High tide flooding potential
    Waves (source 5 of 5)
    Aretxabaleta, A.L., Defne, Z., Kalra, T.S., Blanton, B.O., and Ganju, N.K., 2022, Climatological wave height, wave period and wave power along coastal areas of the east coast of the United States and Gulf of Mexico.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Aretxabaleta, A.L., Defne, Z., Kalra, T.S., Blanton, B.O., and Ganju, N.K., 2022, Climatological wave height, wave period and wave power along coastal areas of the East Coast of the United States and Gulf of Mexico: U.S. Geological Survey data release, https://doi.org/10.5066/P9HJ0JIQ.
    Type_of_Source_Media: Digital and/or Hardcopy
    Source_Contribution: Wave Power
  2. How were the data generated, processed, and modified?
    Date: 2020 (process 1 of 5)
    This step and all the subsequent steps were completed by Elizabeth A. Pendleton or Travis K. Sterne using ESRI ArcGIS Pro geospatial software. Any steps that mention the use of “tools” or “functions” refer to geoprocessing tools utilized in ArcGIS Pro. The steps described in detail below are computed on the domain defined by the fabric dataset found in this data release. Each hazard dataset processed and included in this dataset has been clipped or modified to fit within the domain of the Northeast CCL study area. The final hazards raster (at end of step 4) presented here is a combination of three hazards that can be classified as event hazards because they occur intermittently. Event hazards include high tide flooding, storm overwash, and waves power (because the most damaging waves typically occur during storm events). Event hazard magnitudes are stored in according to place holder values, such that the ones place is occupied by high tide flooding, the tens place is occupied by wave power, and the hundreds place is occupied by storm overwash probability. Each event hazard has between 2 and 4 classes associated with its presence, thresholds, or magnitude defined either in this study or the source data publication. Details about the source data and processing for each hazard layer are described below.
    Date: 2020 (process 2 of 5)
    Step 1: High Tide Flooding: NOAA’s flood frequency layer was re-sampled to 10 mpp resolution (from the original resolution of 2.7 mpp) and NoData values were reclassified to 0 using the Reclassify tool. The resampled high tide flood layer extent was then clipped using the elevation mosaic created in the Fabric dataset, wherever elevation was less than 0 meters MHW using Raster Calculator. This created 2 classes for the high tide flooding hazard – 0 for absence, 1 for presence. Person who carried out this activity:
    Travis K Sterne
    U.S. Geological Survey, NORTHEAST REGION
    Geographer
    384 Woods Hole Road
    Woods Hole, MA
    US

    (508) 548 8700 x2219 (voice)
    tsterne@usgs.gov
    Data sources used in this process:
    • HTF
    Data sources produced in this process:
    • EventHazards1
    Date: 2020 (process 3 of 5)
    Step 2: Wave Power : Climatological wave power in Watts per meter (W/m) covering the East Coast on an irregular ADCIRC grid (Aretxabaleta and others, 2022) was rectilinearly gridded at 10 mpp resolution using the Points to Raster tool and the wave power was interpolated to the extent of the high tide flooding surface using the geoprocessing environment to match the processing extent of to the high-tide flood domain, so that wave power was propagated onto land in areas where flooding has occurred in the past. Wave power thresholds were divided into 4 classes (wave power value, reclassified value): greater than zero and less than or equal to10 W/m, 10; greater than 10 to 50 W/m, 20; greater than 50 to 185 W/m, 30; and greater than 185 W/m, 40. Person who carried out this activity:
    Elizabeth A. Pendleton
    U.S. Geological Survey, NORTHEAST REGION
    Geologist
    384 Woods Hole Road
    Woods Hole, MA
    US

    (508) 548 8700 x2259 (voice)
    ependleton@usgs.gov
    Data sources used in this process:
    • Waves
    Data sources produced in this process:
    • EventHazards2
    Date: 2021 (process 4 of 5)
    Step 3: Probability of Category 2 Storm Overwash: Storm overwash probability was derived from Doran and others (2020), and storm category 2 for overwash regime was chosen as the best fit for CCL. The Spatial Join function was used to append overwash probability values (0 to 100%) to the short-term shoreline change transects from Himmelstoss, Farris, and Weber (2018) and Himmelstoss and others (2010). Transect data were clipped to eliminate spatial overhang into inapplicable portions of the landscape such as back-bay areas of barrier islands using the Clip tool. Transects were then converted to raster format using the Feature to Raster tool and interpolated using two low-pass smoothing filters (Filter tool) in order to fill in data gaps between the 50-meter-spaced transects. Thresholds were defined and the raster layer was reclassified as follows (probability threshold, reclassified value): Less than or equal to 25% overwash probability, 100; 25-75%, 200; greater than 75%, 300. Data sources used in this process:
    • Shoreline Change - MA
    • Shoreline Change - Not MA
    • PCOI
    Data sources produced in this process:
    • EventHazards3
    Date: 2021 (process 5 of 5)
    Step 4: The individual event hazards layers were combined into a single geotiff using Raster Calculator by adding all previously compiled raster layers together (EventHazards1 + EventHazards2 + EventHazards3). The resultant grid had values between 1 and 331, representing the combination of hazards and their magnitudes that exist for a given area. The attribute table for this integer grid was updated to include a text descriptor field to help users identify the event hazards present for each grid value. See entity and attribute section for a list of grid value definitions. Data sources used in this process:
    • EventHazards1
    • EventHazards2
    • EventHazards3
    Data sources produced in this process:
    • EventHazardsComposite
  3. What similar or related data should the user be aware of?
    Thieler, E.R., and Hammar-Klose, E.S., 1999, National assessment of coastal vulnerability to sea-level rise; U.S. Atlantic Coast: Open-File Report 1999-593, U.S. Geological Survey, Reston, VA.

    Online Links:

    Pendleton, Elizabeth A., Lentz, Erika E., Sterne, Travis K., and Henderson, Rachel E., 2023, Development and application of a coastal change likelihood assessment for the northeast region, Maine to Virginia: Data Report 1169, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Pendleton, E.A., Lentz, E.E., Sterne, T.K., and Henderson, R.E., 2023, Development and application of a coastal change likelihood assessment for the northeast region, Maine to Virginia: U.S. Geological Survey Data Report 1169, 56 p., https://doi.org/10.3133/dr1169. The CCL data release (https://doi.org/10.5066/P96A2Q5X) is associated with the CCL Data Report (https://doi.org/10.3133/dr1169)

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

  1. How well have the observations been checked?
    All data values represent a compilation of coastal hazards likely to be present in the coming decade based on previous empirical research and expert opinion. The final output generated is the expected outcome based on this information.
  2. How accurate are the geographic locations?
    Horizontal coordinate information is referenced to the World Geodetic System of 1984 (WGS 1984) in a Geographic Coordinate System or WGS 1984 Web Mercator (auxiliary sphere) in a Projected Coordinate System. Source data were resampled to 10 mpp for use. There may be resampling errors associated with coarsening (e.g. high tide flooding data were resampled from ~5 mpp to 10 mpp) and rectilinear conversion of the finite element climatological wave data. Likewise some data, including storm overwash likelihood, were rasterized from a source vector, and there can be spatial inconsistencies associated with the rasterization of vector data. The horizontal accuracy of this dataset is assumed to be better than +/– 30 meters, but dynamic coastal areas may experience much higher rates of change during storms, and horizontal offset at the shoreline maybe much higher (+/- 100 meters) in certain areas.
  3. How accurate are the heights or depths?
    This dataset’s domain is defined by the z-values (elevation) domain of the Fabric dataset (of this publication), and as such has a horizontal positional uncertainty of up to 50 cm along the edge of the domain, which corresponds to + or – 10 meters MHW. However, this dataset has no explicit vertical depth values itself, and therefore there is no vertical position accuracy estimate except along the boundary of this dataset domain.
  4. Where are the gaps in the data? What is missing?
    CCL is a model for coastal landscapes in the Northeast United States. All output is "clipped" to an elevation domain; this dataset represents coastal hazards likely to be present in the coming decade from -10 to +10 meters MHW elevation, where data exists. Existing gaps in coverage for this dataset within this domain are a result of data gaps in source information.
  5. How consistent are the relationships among the observations, including topology?
    All data were checked for accuracy during processing. Any inconsistencies in the final data product are artifacts of source data.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints None. Please see 'Distribution Info' for details.
Use_Constraints Not to be used for navigation. Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. Please recognize the U.S. Geological Survey (USGS) as the source of this information. Additionally, there are limitations associated with coastal change hazard assessments. Although these data are published at a resolution of 10 mpp and are considered high resolution, the intended scale for use is around 1:24,000. Please read the associated data release (https://doi.org/10.3133/dr1169) for a list of caveats, applications, and use recommendations for these data.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey - ScienceBase
    Denver Federal Center, Building 810, Mail Stop 302
    Denver, CO
    US

    1-888-275-8747 (voice)
    sciencebase@usgs.gov
  2. What's the catalog number I need to order this data set? This dataset contains the raster data layer (.tif) and associated files (.sld, .ovr, .cpg, and .dbf) needed to view and edit the information it contains, as well as the FGDC CSDGM metadata in XML format. The .sld is a Service Layer Definition file used by ScienceBase to display the data, the .ovr file contains the pyramids used by a GIS to display the data at different scales the .cpg file is for charactersets, and the .dbf is a dBASE table file used to store data attributes.
  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 on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty.
  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 28-Feb-2023
Metadata author:
U.S. Geological Survey
Attn: Elizabeth A. Pendleton
Geologist
384 Woods Hole Rd
Woods Hole, MA

(508) 457 2259 (voice)
ependleton@usgs.gov
Metadata standard:
Content Standard for Digital Geospatial Metadata, FGDC-STD-001-1998 (FGDC-STD-001.1-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/whcmsc/SB_data_release/DR_P96A2Q5X/USGS_CCL_EventHazards_2022.faq.html>
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