Exposure potential of marsh plains to environmental health stressors in eastern Long Island salt marsh complex, New York (ver. 3.0, May 2026)

Frequently anticipated questions:

• What does this data set describe?
  1. How might this data set be cited?
  2. What geographic area does the data set cover?
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
  5. What is the general form of this data set?
  6. How does the data set represent geographic features?
  7. How does the data set describe geographic features?
• Who produced the data set?
  1. Who are the originators of the data set?
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
• Why was the data set created?
• How was the data set created?
  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
  3. What similar or related data should the user be aware of?
• How reliable are the data; what problems remain in the data set?
  1. How well have the observations been checked?
  2. How accurate are the geographic locations?
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
  5. How consistent are the relationships among the data, including topology?
• How can someone get a copy of the data set?
  1. Are there legal restrictions on access or use of the data?
  2. Who distributes the data?
  3. What's the catalog number I need to order this data set?
  4. What legal disclaimers am I supposed to read?
  5. How can I download or order the data?
• Who wrote the metadata?

What does this data set describe?

1. How might this data set be cited?
   Welk, Robert, Ackerman, Kate V., Defne, Zafer, and Ganju, Neil K., 20200331, Exposure potential of marsh plains to environmental health stressors in eastern Long Island salt marsh complex, New York (ver. 3.0, May 2026): data release 10.5066/P91H426U, U.S. Geological Survey, Coastal and Marine Hazards and Resources Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

   Online Links:

   • https://doi.org/10.5066/P91H426U
   • https://www.sciencebase.gov/catalog/item/5ddd98cde4b04a30051ac211

   This is part of the following larger work.
   Welk, Robert, Ackerman, Kate V., Defne, Zafer, and Ganju, Neil, 2020, Coastal wetlands of eastern Long Island, New York (ver. 3.0, May 2026): data release 10.5066/P91H426U, U.S. Geological Survey, Reston, VA.

   Online Links:

   • https://doi.org/10.5066/P91H426U
   • https://www.sciencebase.gov/catalog/item/5dd56511e4b0695797628ca6

   Other_Citation_Details:

   Suggested citation: Welk, R., Ackerman, K.V., Defne, Z., and Ganju, N.K., 2020, Coastal wetlands of eastern Long Island, New York (ver. 3.0, May 2026): U.S. Geological Survey data release, https://doi.org/10.5066/P91H426U.

2. What geographic area does the data set cover?

   West_Bounding_Coordinate: -72.748198
   East_Bounding_Coordinate: 71.885316
   North_Bounding_Coordinate: 41.291362
   South_Bounding_Coordinate: 40.766433
   

3. What does it look like?

   https://www.sciencebase.gov/catalog/file/get/5ddd98cde4b04a30051ac211?name=SCoRR_ELI_browse.png&allowOpen=true (PNG)

   Graphic that shows the exposure potential to environmental health stressors overlaying Esri basemap.

4. Does the data set describe conditions during a particular time period?

   Calendar_Date: 2020

   Currentness_Reference:

   Publication date of original release.

5. What is the general form of this data set?

   Geospatial_Data_Presentation_Form: Vector Digital dataset (Polygon)
   

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):
      • G-polygon (2752)
   2. What coordinate system is used to represent geographic features?
      The map projection used is WGS 1984 Web Mercator Auxiliary Sphere (ESRI Full Name: WGS_1984_Web_Mercator_Auxiliary_Sphere).
      

      Projection parameters:

      Standard_Parallel: 0.0
      Longitude_of_Central_Meridian: 0.0
      False_Easting: 0.0
      False_Northing: 0.0
      

      Planar coordinates are encoded using coordinate pair
      Abscissae (x-coordinates) are specified to the nearest 0.6096
      Ordinates (y-coordinates) are specified to the nearest 0.6096
      Planar coordinates are specified in Meter
      The horizontal datum used is D_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?

   mp_SCoRR_ELI

   Attribute information associated with the SCoRR ranks projected on to the marsh plains of the eastern Long Island salt marsh complex. (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.

   MP

   Unique whole number that represents the identification number for each polygon, or "marsh plain". In revision 3.0, this field was changed from "FID_CMU" to "MP." (Source: USGS)

   Range of values
   Minimum:	2
   Maximum:	3455

   MIN

   Minimum value of Sediment-bound Contaminant Resiliency and Response (SCoRR) rank within a marsh unit (Source: USGS)

   Range of values
   Minimum:	0
   Maximum:	14.654953
   Units:	None

   MAX

   Maximum value of SCoRR rank within a marsh unit (Source: USGS)

   Range of values
   Minimum:	0
   Maximum:	43.309837
   Units:	None

   MEAN

   Mean value of SCoRR rank within a marsh unit (Source: USGS)

   Range of values
   Minimum:	0
   Maximum:	15.520519
   Units:	None

   STD

   Standard deviation of SCoRR rank within a marsh unit (Source: USGS)

   Range of values
   Minimum:	0
   Maximum:	5.089573
   Units:	None

   FLG

   Marsh unit flag indicating anomalous marsh units based on elevation, surface area, and absence of vegetation. FLG values indicate: (-1) no vegetated area; (-10) marsh unit elevation higher than the 99.8 percentile; (-100) marsh unit elevation less than 0.2 percentile; (-200) greater than 25% of marsh unit has hydroflattened area and has -9999 as its elevation value; (-1000) marsh unit surface area less than 900 m2; and (0) no flag. Combination of negative values indicate combination of flags. For example, -1001 indicates no vegetated area and area less than 900 m2. (Source: USGS)

   Range of values
   Minimum:	-11201
   Maximum:	0
   Units:	None

   Entity_and_Attribute_Overview:

   In this dataset, exposure potential to environmental health stressors calculated with the SCoRR strategy is interpolated over the salt marsh units in the eastern Long Island salt marsh complex. A higher SCoRR rank indicates higher exposure potential to environmental health stressors. Raster cells that do not have a facility within a 2000 meter proximity are assigned a SCoRR rank of zero prior to clipping to the processing extent. Decimal values in the attribute table are a result of double precision calculations while significant digits are considered in defining the attribute measurement resolutions. Therefore, the smallest unit increment for exposure potential (SCoRR) values can be assumed to be a practical value such as 0.01.

   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)
   • Robert Welk
   • Kate V. Ackerman
   • Zafer Defne
   • Neil K. Ganju
2. Who also contributed to the data set?
3. To whom should users address questions about the data?
   U.S. Geological Survey

   Attn: Robert J Welk

   Hydrologic Technician

   2045 Route 112

   Coram, NY
   

   US

   631-736-0783 x141 (voice)

   rwelk@usgs.gov

Why was the data set created?

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: 2019 (process 1 of 12)

   This process step and all subsequent process steps were performed in ArcMap (ver. 10.7.1) using tools from ArcToolbox, unless otherwise stated. For complex operations, names of specific tools used are given in CAPITAL letters (any critical parameters used are given in parentheses, separated by a semicolon, immediately after the tool name). The input and output file names are provided in [square brackets] when necessary. Units for length and area calculations are meters (m) and square meters (m2) unless otherwise stated.
   a) CREATE CONSTANT RASTER(Constant value= 1; Output cell size: 0.003 degrees) that surpasses eastern Long Island boundaries, as defined in the conceptual marsh units layer.
   b) RASTER TO POINT to generate an array of points [scorr_pts.shp].
   c) Export point coordinates to an Excel table [contPts.xls]. Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Zafer Defne

   Ocean Scientist

   384 Woods Hole Rd.

   Woods Hole, MA
   

   USA

   508-458-8700 x2254 (voice)

   508-457-2310 (FAX)

   zdefne@usgs.gov

   Data sources produced in this process:

   • contPts.xls

   Date: 2016 (process 2 of 12)

   This step was performed by Daniel K. Jones following the SCoRR strategy (Reilly and others, 2015). ArcMap and tools from ArcToolbox were used for analysis unless otherwise stated. Names of specific tools used are given in CAPITAL letters (any critical parameters used are given in parentheses, separated by a semicolon, immediately after the tool name). Input and output file names are provided in [square brackets] when necessary. Apply SCoRR ranks to the gridded array of points [contPts.xls].
   a) Generate the list for facilities of concern from EPA's Toxic Release Inventory (TRI) data, and EPA's Facility Registry Service (FRS) data.
   TRI data were downloaded from https://www.epa.gov/toxics-release-inventory-tri-program/tri-basic-data-files-calendar-years-1987-2015 using the drop down menu for the year and state of interest. For this work, 2013 data for the state of New York were used. Each facility was assigned a rank value from 1 to 4 indicating its 'perceived contaminant hazard' based on i) a modified version of ranked contaminants from Olsen et al. 2013 (Reilly and others, 2015; Table 1), or ii) paneled expert opinion following methods outlined in Olsen et al. 2013.
   FRS data were downloaded from https://www.epa.gov/frs/frs-query for New York. Each facility was assigned a rank value from 1 to 4 based upon a questionnaire administered to the same expert panel mentioned above. Three attribute fields were utilized to assess the perceived contaminant hazard of each FRS facility: environmental program type, environmental interest type, and site type. Each of these fields provides details about regulations, uses, and potential hazards relevant to each facility.
   When relevant, historic storm vulnerabilities were used to weight each ranked FRS and TRI facility. Storm vulnerability datasets included Federal Emergency Management Agency's (FEMA) 100-year flood zones, National Oceanic and Atmospheric Administration’s Sea, Lake, and Overland Surges from Hurricanes (NOAA SLOSH) model-based inundation extents for hurricanes of category 1 to 5 in magnitude, and probabilities of storm impacts based on National Weather Service’s International Best Track Archive for Climate Stewardship (NWS IBTrACS) data. Overlay analysis was used to identify all facilities falling within 1 or more of these storm vulnerabilities. Equation 1 in Reilly and others (2015) was used to then weight each facility's perceived contaminant hazard rank based on the number of intersected storm vulnerabilities.
   b) Create a shapefile from the point coordinates and DEFINE PROJECTION(Coordinate System=WGS 84) as World Geodetic System 1984.
   c) GENERATE NEAR TABLE(Input Features=IN_FID; Near Features=NEAR_FID; Search radius= 2000 m) to identify facilities of concern within 2000 m of each point. Separate tables were generated for the TRI and FRS facilities. These were then recombined later during the inverse distance weighting procedure to arrive at the final rank at each location.
   d) Tables are imported into R software package and joined using the fields 'IN_FID' and 'NEAR_FID' to link facility attributes with each location using near table output.
   e) SCoRR rank at each location is calculated using the inverse distance-weighted average rank equation (Reilly and others, 2015; Equation 2) within a search radius of 2000 meters, based on the storm vulnerability-weighted potential contaminant hazard rank for each facility, and the distance to the facility location. Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Daniel K. Jones

   Geographer

   2329 Orton Circle

   Salt Lake City, UT
   

   USA

   240-620-7822 (voice)

   801-908-5001 (FAX)

   dkjones@usgs.gov

   Data sources used in this process:

   • contPts.xls

   Data sources produced in this process:

   • contPts.csv

   Date: 2016 (process 3 of 12)

   Remaining process steps were performed by Robert Welk, in ArcMap (ver. 10.7.1) using tools from ArcToolbox, unless otherwise stated. Names of specific tools used are given in CAPITAL letters (any critical parameters used are given in parentheses, separated by a semicolon, immediately after the tool name). Input and output file names are provided in [square brackets] when necessary. Units for length and area calculations are meters (m) and square meters (m2) unless otherwise stated.
   Establish marsh unit boundaries. DISSOLVE(Dissolve Fields= FID_CMU) features in marsh units layer based on the attribute identification numbers. FID_CMU is the unique identifier for each marsh unit. Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Robert Welk

   Hydrologic Technician

   2045 NY 112

   Coram, NY
   

   USA

   631-736-0783 x141 (voice)

   welk@usgs.gov

   Data sources used in this process:

   • CMU_ELI

   Data sources produced in this process:

   • mu

   Date: 2019 (process 4 of 12)

   Create a raster surface dataset from the feature points.
   a) Import points to ArcMap using MAKE XY EVENT LAYER [scorr.shp]. NoData values are converted to zero at this step.
   b) Create a raster surface with inverse distance weighting in Spatial Analyst toolbox. IDW.SpatialAnalyst(Output Cell Size=0.0003 degrees; Power=2; Search Radius=Variable; Number of Points=12) to obtain [scorr_idw.tif]. Data sources used in this process:

   • contPts.csv

   Data sources produced in this process:

   • scorr_idw.tif

   Date: 2019 (process 5 of 12)

   Clip the raster to marsh boundaries. A buffer zone is created around the marsh boundaries to facilitate alternative interpolation and clipping options in future studies.
   a) Create 250 m buffer around the marsh polygon [mu.shp] to create a clipping mask [mu_buff250m.shp]. BUFFER(Side type= Full; Method=Geodesic; Dissolve type= All).
   b) Clip the raster clipping mask. EXTRACT BY MASK to obtain [scorr_ELI.tif]. Data sources used in this process:

   • mu
   • scorr_idw.tif

   Data sources produced in this process:

   • scorr_ELI.tif

   Date: 2019 (process 6 of 12)

   PROJECT RASTER(Input raster= scorr_ELI.tif; Output raster= scorr_ELI.tif; Input coordinate system= GCS_WGS_1984; Output coordinate system= WGS_1984_Web_Mercator_Auxiliary_Sphere; Resampling technique= Nearest; Output cell size= 30 meters) to obtain [scorr_ELI.tif]. Data sources used in this process:

   • scorr_ELI.tif

   Data sources produced in this process:

   • scorr_ELI.tif

   Date: 2019 (process 7 of 12)

   Calculate values for each marsh unit. a) Clip the raster with the marsh units polygon by using EXTRACT BY MASK(Cell Size=3 m) to obtain [mu_scorr_idw.tif]. Cell size for raster analysis was reduced to 3 m to have smoother boundaries.
   b) ZONAL STATISTICS AS TABLE(Feature Zone Data=[mu]; Value Raster=[mu_scorr_idw.tif]; Output Table=mu_scorr_table; Statistics type=ALL)
   c) ADD JOIN(Layer name=[mu]; Input join field=FID_CMU; Join Table=mu_scorr_table; Output join field=FID_CMU) to marsh units layer based on the "FID_CMU" field
   d) Export dataset as a shapefile [mu_SCoRR_ELI.shp] and keep the 'MIN", 'MAX', "MEAN" and "STD" fields from the join operation. Data sources used in this process:

   • mu
   • scorr_ELI.tif

   Data sources produced in this process:

   • mu_SCoRR_ELI.shp

   Date: 06-Aug-2020 (process 8 of 12)

   Added keywords section with USGS persistent identifier as theme keyword. Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: VeeAnn A. Cross

   Marine Geologist

   384 Woods Hole Road

   Woods Hole, MA
   

   508-548-8700 x2251 (voice)

   508-457-2310 (FAX)

   vatnipp@usgs.gov

   Date: 16-Jan-2024 (process 9 of 12)

   Version 2 updates. Updates were performed in ArcGIS Pro 2.8.8. Duplicate marsh units were manually identified and compared to make sure the most appropriate duplicate marsh unit was deleted. Seventy-six duplicate marsh units were identified (out of 2828) in Mecox Bay, Sagaponack Pond and Georgica Pond and have been removed. After the duplicate marsh units were deleted, the elevation, hydroflattened percentage and elevation flag values were recalculated. Authorship was updated to include Kate Ackerman. Person who carried out this activity:
   

   Kate Ackerman

   U.S. Geological Survey

   Geologist

   384 Woods Hole Road

   Woods Hole, MA
   

   US

   508-548-8700 x2331 (voice)

   508-457-2310 (FAX)

   kackerman@usgs.gov

   Date: 01-May-2026 (process 10 of 12)

   Version 3 Updates. All updates were completed in ArcGIS Pro 3.4.3, using the version 2 of the dataset as the starting dataset. In the original dataset, each marsh plain was not subdivided into smaller parcels ("marsh units") because two processing steps were not completed. For Version 3, these processing steps were completed, resulting in each marsh plain being properly subdivided into these smaller marsh units. Using the new marsh units, UVVR and elevation values were recalculated. Tide range values were carried over from the original (larger) marsh plain polygons and applied to the new, smaller marsh units.
   However, exposure potential (SCoRR) values and shoreline change values could not be recalculated at the marsh unit scale. They remain unchanged and still represent the larger marsh plain polygons. In the SCoRR and shoreline change datasets, the field FID_CMU has been renamed to MP to indicate that those polygons correspond to marsh plains, not the newly created marsh units. In the title of the data release for exposure potential and shoreline change, the words "marsh units" were changed to "marsh plains." Throughout the exposure potential and shoreline change metadata, the term 'marsh unit' is still used, but readers should understand that it actually refers to the marsh plain. Previous versions of the data can be obtained by contacting whsc_data_contact@usgs.gov. Person who carried out this activity:
   

   Kate Ackerman

   U.S. Geological Survey

   Geologist

   384 Woods Hole Road

   Woods Hole, MA
   

   US

   508-548-8700 x2331 (voice)

   508-457-2310 (FAX)

   kackerman@usgs.gov

   Date: 2026 (process 11 of 12)

   Change the name of the FID_CMU field to "MP", for "marsh plain" since these polygons refer to marsh plains rather than marsh units. Also changed the name of the shapefile from "mu_SCoRR_ELI" to "mp_SCoRR_ELI." Person who carried out this activity:
   

   Kate Ackerman

   U.S. Geological Survey

   Geologist

   384 Woods Hole Road

   Woods Hole, MA
   

   US

   508-548-8700 x2331 (voice)

   508-457-2310 (FAX)

   kackerman@usgs.gov

   Date: 01-May-2026 (process 12 of 12)

   Removed the web services distribution formats in preparation for ScienceBase moving platforms and those services no longer being available. Person who carried out this activity:
   

   Kate Ackerman

   U.S. Geological Survey

   Geologist

   384 Woods Hole Road

   Woods Hole, MA
   

   US

   508-548-8700 x2331 (voice)

   508-457-2310 (FAX)

   kackerman@usgs.gov

3. What similar or related data should the user be aware of?
   Reilly, Timothy J., Jones, Daniel K., Focazio, Michael J., Aquino, Kimberly C., Carbo, Chelsea L., Kaufhold, Erika E., Zinecker, Elizabeth K., Benzel, William M., Fisher, Shawn C., Griffin, Dale W., Iwanowicz, Luke R., Loftin, Keith A., and Schill, William B., 2015, Strategy to evaluate persistent contaminant hazards resulting from sea-level rise and storm-derived disturbances-Study design and methodology for station prioritization: Open-File Report 2015-1188-A, U.S. Geological Survey, Reston, VA.

   Online Links:

   • https://doi.org/10.3133/ofr20151188A

   Olsen, Lisa D., Valder, Joshua F., Carter, Janet M., and Zogorski, John S., 2013, Prioritization of Constituents for National- and Regional-Scale Ambient Monitoring of Water and Sediment in the United States: Scientific Investigations Report 2012-5218, U.S. Geological Survey, Reston, VA.

   Online Links:

   • http://pubs.usgs.gov/sir/2012/5218/

   NOAA, 2016, VDatum (v3.5): NOAA, Silver Spring, MD.

   Online Links:

   • http://vdatum.noaa.gov

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

1. How well have the observations been checked?
   Water-land boundary and marsh unit boundaries inherit from accuracy of source data, conceptual marsh units. Exposure potential to environmental health stressors is calculated with the SCoRR strategy for a uniform grid with 0.003 degrees (~300 meters) resolution and resampled at a higher resolution of 0.0003 degrees (~30 meters) prior to averaging over each marsh unit.
2. How accurate are the geographic locations?
   Horizontal accuracy for the polygon boundaries is inherited from the source layer, conceptual marsh units, and is considered to be +/- 6 meters. The point cloud used for calculating tidal range with VDatum had a 0.0005 arc degree (~50-meter) resolution that was interpolated over a 0.0001 arc degree raster prior to clipping and calculating the mean value for each marsh unit.
3. How accurate are the heights or depths?
   
4. Where are the gaps in the data? What is missing?
   The boundaries of this dataset were created by expanding the outline boundaries of polygons created with a 250 meter exterior buffer around the source data, conceptual marsh units. Any polygons with an area smaller than 50 square meters were omitted in the source dataset.
5. How consistent are the relationships among the observations, including topology?
   By definition, SCoRR ranks cannot be a negative real number. Final values for each marsh unit were verified to be either zero or a positive real number.

How can someone get a copy of the data set?

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
   

   1-888-275-8747 (voice)

   sciencebase@usgs.gov
2. What's the catalog number I need to order this data set? mu_MN_SCoRR.shp (and other shapefile components), browse graphic, and CSDGM metadata in XML format.
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. 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?
   • Availability in digital form:

     Data format:	This zipped file contains a shapefile and associated metadata. in format Shapefile (version ArcGIS Pro 2.8.8) Size: 20
     Network links:	https://www.sciencebase.gov/catalog/file/get/5ddd98cde4b04a30051ac211 https://www.sciencebase.gov/catalog/item/5ddd98cde4b04a30051ac211 https://doi.org/10.5066/P91H426U

   • Cost to order the data: None. No fees are applicable for obtaining the dataset.

Who wrote the metadata?

Dates:

Last modified: 19-May-2026

Metadata author:

U.S. Geological Survey, Northeast Region

Attn: Robert J Welk

Hydrologic Technician

2045 Route 112

Coram, NY

US

631-736-0783 x141 (voice)

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 Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)