Conceptual marsh units of Blackwater salt marsh complex, Chesapeake Bay, Maryland

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Frequently anticipated questions:

What does this data set describe?

Title:
Conceptual marsh units of Blackwater salt marsh complex, Chesapeake Bay, Maryland
Abstract:
This data release contains coastal wetland synthesis products for the geographic region of Blackwater, Chesapeake Bay, Maryland. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and others, are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands with the intent of providing Federal, State, and local managers with tools to estimate the vulnerability and ecosystem service potential of these wetlands. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their vulnerability and ecosystem services.
  1. How might this data set be cited?
    Ackerman, Kate V., Defne, Zafer, and Ganju, Neil K., 20210518, Conceptual marsh units of Blackwater salt marsh complex, Chesapeake Bay, Maryland: data release DOI:10.5066/P9M7H6XG, 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.

    Ackerman, Kate V., Defne, Zafer, and Ganju, Neil K., 2021, Coastal wetlands of the Blackwater region, Chesapeake Bay, Maryland: data release DOI:10.5066/P9M7H6XG, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Ackerman, K.V., Defne, Z., and Ganju, N.K., 2021, Coastal wetlands of the Blackwater region, Chesapeake Bay, Maryland: U.S. Geological Survey data release, https://doi.org/10.5066/P9M7H6XG.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -76.3333
    East_Bounding_Coordinate: -75.6812
    North_Bounding_Coordinate: 38.5053
    South_Bounding_Coordinate: 38.2175
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/608876f2d34e5611588fbcc6/?name=CMU_BW_Browse.png (PNG)
    Graphic that shows conceptual marsh units overlaying Esri basemap.
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 2021
    Currentness_Reference:
    Publication date
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: Vector Digital 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 (16752)
    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:
      False_Easting: 0.0
      False_Northing: 0.0
      Longitude_of_Central_Meridian: 0.0
      Standard_Parallel: 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 meters
      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?
    CMU_BW.shp Attribute Table
    Table containing attribute information associated with the dataset. (Source: Producer Defined)
    FID
    Internal feature number. (Source: Esri) Unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: Esri) Coordinates defining the features.
    FID_CMU
    Unique whole numbers used to identify each conceptual marsh unit. These numbers are duplicated when a marsh unit has both vegetated and unvegetated sub-polygons. (Source: USGS)
    Range of values
    Minimum:0
    Maximum:8532
    Units:none
    APGN_M2
    Surface area of the selected polygon type (vegetated or unvegetated). (Source: USGS)
    Range of values
    Minimum:0.41182997932
    Maximum:2284096.35511
    Units:m^2
    ATOT_M2
    Total surface area of a marsh unit. (Source: USGS)
    Range of values
    Minimum:142.611297122
    Maximum:3039925.37708
    Units:m^2
    TYP
    Classification of the polygon features in a marsh unit as vegetated or unvegetated. (Source: USGS)
    ValueDefinition
    unvegetatedUnvegetated part of the marsh unit.
    vegetatedVegetated part of the marsh unit.
    FLG
    Marsh unit flag indicating anomalous marsh units based on absence of vegetation, elevation and surface area. FLG values indicate: (-1) no vegetated area in the marsh unit; (-10) marsh unit elevation higher than the 99.8 percentile; (-100) marsh unit elevation less than 0.2 percentile; (-200) greater than 25 percent of the marsh unit elevation is hydro-flattened; (-1000) marsh unit surface area less than 900 m^2; and (0) no flag. Combination of negative values indicates a combination of flags; for example, -1001 indicates no vegetated area and area less than 900 m^2. (Source: USGS)
    Range of values
    Minimum:-1201
    Maximum:0
    Units:none
    COLORID
    Recycling sequential whole numbers (0-9) that are used for display purposes when plotting conceptual marsh units. These numbers are duplicated when a marsh unit has both vegetated and unvegetated sub-polygons. (Source: USGS)
    Range of values
    Minimum:0
    Maximum:9
    Units:none
    Entity_and_Attribute_Overview:
    In this dataset, the salt marsh complex in the Blackwater region has been delineated to conceptual salt marsh units to facilitate unit by unit evaluation of the response and resiliency of the marsh system to physical and biogeochemical drivers. Each unit is also analyzed based on the vegetated and unvegetated surface area coverage, the ratio of which can be an independent measure of marsh health for microtidal marshes on the Atlantic and Pacific coasts of the United States. 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 area values is assumed to be 1 meter.
    Entity_and_Attribute_Detail_Citation: USGS

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • 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?
    Kate V. Ackerman
    U.S. Geological Survey
    Geologist
    384 Woods Hole Rd
    Woods Hole, MA
    US

    508-548-8700 x2331 (voice)
    508-457-2310 (FAX)
    kackerman@usgs.gov

Why was the data set created?

These polygons were created to be used in evaluating the spatial variation of the response and resiliency of the salt marsh complex based on consistently defined marsh units while facilitating a better understanding of the relative importance of the processes involved. The salt marsh complex of the Blackwater region was delineated to smaller, conceptual marsh units by the geoprocessing of surface elevation data. Flow accumulation based on the relative elevation of each location is used to determine the ridge lines that separate each marsh unit while the surface slope is used to automatically assign each unit a drainage point, where water is expected to drain through.

How was the data set created?

  1. From what previous works were the data drawn?
    CoNED (source 1 of 3)
    Danielson, J., and Tyler, D., 20160501, Topobathymetric Model for Chesapeake Bay Region - District of Columbia, States of Delaware, Maryland, Pennsylvania, and Virginia, 1859 to 2015: U.S. Geological Survey, Reston, VA.

    Online Links:

    Type_of_Source_Media: Digital
    Source_Contribution:
    Downloaded CoNED Digital Elevation Model geodatabase. Projection was NAD 1983 UTM Zone 18N with the North American Vertical Datum of 1988 (NAVD 88). Download date was 2020/01/29.
    NAIP (source 2 of 3)
    U.S. Department of Agriculture, 2018, NAIP Digital Ortho Photo Image: USDA-FSA-APFO Aerial Photography Field Office, Salt Lake City, Utah.

    Online Links:

    Type_of_Source_Media: Digital
    Source_Contribution:
    Downloaded NAIP 0.6-meter resolution imagery from the USGS Earth Explorer. Projection was WGS 1984 Web Mercator Auxiliary Sphere. Download date was 2019/08/01.
    NWI (source 3 of 3)
    U.S. Fish and Wildlife Service, 20191001, National Wetland Inventory: U.S. Fish and Wildlife Service, Madison, WI.

    Online Links:

    Type_of_Source_Media: Digital
    Source_Contribution:
    Downloaded wetlands data for the state of Maryland in shapefile format from the NWI download page. Projection was NAD 1983 Albers. Download date was 2020/01/02.
  2. How were the data generated, processed, and modified?
    Date: 2020 (process 1 of 6)
    This process step and all subsequent process steps were performed by the same person, Kate Ackerman, 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 (m^2) unless otherwise stated.
    a) Set the data frame coordinate system and projection to NAD 1983 UTM Zone 18N.
    b) Create a rectangular polygon that covers the domain [extent.shp]. CLIP the CoNED elevation dataset by the boundaries polygon [elev_mosaic.tif]. 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
    Data sources used in this process:
    • CoNED
    Date: 2020 (process 2 of 6)
    Prepare a mask polygon to define analysis boundaries. In order to account for the possible influence of the surrounding terrain on the analysis, a mask area larger than the salt marsh extent is first created [UVVR_mask.shp]. At the end of the analysis the results are clipped to the boundaries of the salt marsh area [MU_mask.shp]. Both [UVVR_mask.shp] and [MU_mask.shp] are edited to determine which interior polygons are removed.
    a) EXPORT features (use the same coordinate system as the data frame) from NWI dataset after SELECT("ATTRIBUTE" LIKE 'E2%EM%' OR "ATTRIBUTE" LIKE 'E2AB3%' OR "ATTRIBUTE" LIKE 'E2EM%' OR "ATTRIBUTE" LIKE 'E2SS%' OR "ATTRIBUTE" LIKE 'E2US4%') to select from estuarine intertidal areas of 1) emergent wetland, 2) scrub-shrub area, 3) rooted vascular aquatic bed, 4) organic unconsolidated shore classes [NWI_exclusive_select.shp].
    b) BUFFER(Input features=[NWI_exclusive_select.shp]; Linear unit=5 meters; Dissolve type=All) to obtain the mask polygon [buff5m.shp] and ELIMINATE POLYGON PART(Condition=Percentage; Percentage=99; Eliminate contained part only) to obtain [UVVR_mask01.shp]. Apply buffer with -5 meters to obtain [MU_mask01.shp].
    c) EXPORT features from NWI dataset after SELECT("ATTRIBUTE" NOT LIKE 'E%' OR "ATTRIBUTE" LIKE '%FO') to obtain features that are not estuarine or are forested estuarine [NWI_inclusive_select.shp]. MULTIPART TO SINGLEPART to separate individual polygons [NWI_inclusive_single.shp].
    d) To exclude the voids in the NWI map during the analysis, these interior polygons need to be removed from the mask. ERASE [NWI_exclusive_select.shp] from [extent.shp] and MULTIPART TO SINGLEPART to get [NWI_voids_single.shp].
    e) SELECT BY LOCATION from [NWI_inclusive_single.shp] that are completely within the [MU_mask01.shp] and SELECT BY LOCATION from [NWI_voids_single.shp] that are completely within the [MU_mask01.shp]. If any of additional polygons need to be removed from the mask include them in a new feature layer [erase_mask_manual.shp]. MERGE all three feature sets to get polygons to be excluded [erase_inside.shp] from the final masks.
    f) ERASE [erase_inside.shp] from [MU_mask01.shp] to obtain [MU_mask.shp], and ERASE [erase_inside.shp] from [UVVR_mask01.shp] after BUFFER [erase_inside.shp] by -5 meters, to obtain [UVVR_mask.shp]. Data sources used in this process:
    • NWI
    Data sources produced in this process:
    • MU_mask
    • UVVR_mask
    Date: 2020 (process 3 of 6)
    Define preliminary boundaries for marsh units by basin analysis:
    a) EXTRACT BY MASK from elevation dataset [elev_mosaic.tif] using [UVVR_mask.shp] polygon.
    b) FILL(no Z limit) sinks in extracted elevation raster.
    c) Calculate FLOW DIRECTION(do not force edge cells to flow outward) raster.
    d) Calculate BASIN based on flow direction raster [basin_buff5m.tif].
    e) Apply MAJORITY FILTER(Number of neighbors=8) to clean the raster and convert RASTER TO POLYGON. CLIP the polygon with 1-meter buffered marsh units mask [MU_mask_buff1m.shp]. This additional buffer is necessary to prevent any polygon smoothing algorithm from changing the exterior boundaries and will be removed by clipping to the [MU_mask.shp] later. MULTIPART TO SINGLEPART and ADD GEOMETRY ATTRIBUTES(Geometry properties=Area_geodesic; Area unit=Square_meters) to get [basin_single.shp].
    Date: 2020 (process 4 of 6)
    This step merges the "orphan marsh units," units that are smaller than 5000 m^2 in area to the nearest to "parent marsh units," units that are larger than 5000 m^2 to obtain the preliminary marsh units. A Python script that iteratively calls a list of ArcMap tools to aggregate orphan units on parent units is used.
    a) Create orphan marsh units features by exporting marsh units with an area less than 5000 m^2 [inputfeatures.shp].
    b) Create parent marsh units features by exporting marsh units with an area greater than or equal to 5000 m^2 [nearfeatures.shp].
    c) Run Python script (hydUnitloop.py). At each iteration step, the script uses NEAR tool to find orphan marsh units within 1 meter of a parent marsh unit and merges them to the parent using UNION and DISSOLVE tools. The orphan units merged with a parent unit are removed from the orphan units dataset. Script will iterate until there is no change in the number of parent or orphan marsh units. The remaining orphan marsh units are those that are more than 1 meter away from any parent. DISSOLVE them to create larger orphan units by grouping the orphans attached together into larger units. MULTIPART TO SINGLEPART to have single part polygons with unique identifiers. UNION(with gaps) single part features with parent units to obtain preliminary marsh units [pMUopt1.shp]. SMOOTH POLYGON(Smoothing algorithm=PAEK; Smoothing tolerance=15 meters) to get the smoothed marsh units polygon [pMUopt1_smooth.shp].
    d) CLIP the extra buffer around the smoothed marsh units using the marsh units mask [MU_mask.shp]. If this results in any additional marsh units with an area less than 5000 m^2, dissolve into the nearest parent units repeating the same steps above to obtain [pMUopt1_clip_final.shp].
    e) Compute the final marsh units by removing any artifacts from [pMuOpt1_clip_final.shp] using ELIMINATE and REPAIR GEOMETRY tools. ELIMINATE(Expression="Area_geo" less than 900; Eliminating by border) polygon slivers smaller than 900 m^2 by merging them to the main polygon. MULTIPART TO SINGLEPART to get conceptual marsh units [CMU.shp]. This only applies to polygons that are bordering other polygons. Polygons that are not bordering other polygons are not affected as those are more likely to be real features as opposed to geoprocessing artifacts.
    f) DISSOLVE the conceptual marsh units to get the final outlines for the marsh complex [CMU_mask_final.shp].
    Date: 2020 (process 5 of 6)
    Determine the vegetated and unvegetated areas by image processing.
    a) EXTRACT BY MASK from elevation raster [elev_mosaic.tif] and the NAIP imagery using [UVVR_mask.shp] polygon. Rescale the elevation raster values to the same range with 8-bit NAIP imagery (0 to 255) using min-max scaling. Perform ISO CLUSTER UNSUPERVISED CLASSIFICATION with 5 input bands: the Near Infrared, Blue, Green, and Red from the NAIP imagery and the rescaled elevation raster; with 32 classes and a minimum class size of 5000 cells. RECLASSIFY the classified raster by visually comparing the NAIP imagery to obtain the unvegetated-vegetated raster [UVVc.tif].
    b) Dissolve unvegetated regions smaller than a threshold value to the surrounding vegetated regions and vice versa to clean the UVV raster. For this purpose, use the REGION GROUP(Number of neighbors=4; Zone grouping method=Within; Add Link field to output) to get the [UVV_region.tif], and TEST("Count" < 9) to set a threshold value of 9 raster cells [lt9.tif]. Use RASTER CALCULATOR to toggle the value of the Link field in the region raster [Map algebra expression=Con("%lt9.tif%", ~Lookup("%UVVc_region.tif%","LINK"),Lookup("%UVVc_region.tif%","LINK"))], where the test raster indicates regions with areas smaller than the threshold.
    c) RASTER TO POLYGON(Simplify polygons=False) and CLIP with the final marsh complex outline [CMU_mask_final.shp] to obtain [UVVc_filt_clip.shp].
    d) REPAIR GEOMETRY, ADD GEOMETRY ATTRIBUTES (Geometry properties=Area_geodesic; Area unit=Square_meters), CALCULATE FIELD (Python_9.3 expression; Field name=gridcode, Expression=filt(!gridcode!, !AREA_GEO!), Code Block= def filt(gridcode, AREA_GEO):/if gridcode== 0 and AREA_GEO < 9:/return 1/else:/return gridcode) and DISSOLVE(Create multipart features=False) to get filtered, clipped and dissolved unvegetated-vegetated polygons [UVVc_filt_clip_diss.shp].
    e) INTERSECT the final conceptual marsh units [CMU.shp] with unvegetated-vegetated polygons [UVVc_filt_clip_diss.shp], REPAIR GEOMETRY, and calculate the area of unvegetated and vegetated polygons in each marsh unit. To do this ADD GEOMETRY ATTRIBUTES(Geometry properties=Area_geodesic; Area unit=Square_meters) to get [UVV_poly.shp], and DISSOLVE(Input features=[UVV_poly.shp]; Dissolve fields=FID_CMU, gridcode; Statistics field=gridcode.MEAN) and REPAIR GEOMETRY to get [UVV_poly_diss.shp]. Edit the fields to have "TYP", "APGN_M2", and "ATOT_M2" fields for type of polygon indicating vegetated or unvegetated, surface area of the polygon, and total surface area of the marsh unit, respectively. Visually inspect and manually remove marsh units that are fully forested due to polygon artifacts that are a result of buffering. Data sources used in this process:
    • NAIP
    • elev_mosaic.tif
    Date: 2020 (process 6 of 6)
    Finalize the conceptual marsh units.
    a) Add field "COLORID" to cycle through integers from 0 to 9 to be used for coloring the marsh units. This field is used for display purposes only to distinguish between each marsh unit.
    b) Add field "FLG" to flag anomalous marsh units based on absence of vegetation, elevation and surface area. The flags are calculated in their respective shapefile (i.e., elevation flags are calculated in the elevation shapefile). Set FLG to (-1) no vegetated area in the marsh unit; (-10) marsh unit elevation higher than the 99.8 percentile; (-100) marsh unit elevation less than 0.2 percentile; (-200) greater than 25 percent of the marsh unit elevation is hydro-flattened; (-1000) marsh unit surface area less than 900 m^2; and (0) no flag. Combination of negative values indicates a combination of flags. For example, -1001 indicates no vegetated area and area less than 900 m^2.
    c) Rearrange field names and change the projection for better performance of web services with online base maps. PROJECT(Input coordinate system=NAD 1983 UTM Zone 18N; Output coordinate system=WGS 1984 Web Mercator Auxiliary Sphere; Geographic transformation=WGS 1984 (ITRF00) to NAD 1983) the feature dataset to obtain the final conceptual marsh units [CMU_BW.shp]. Data sources produced in this process:
    • CMU_BW.shp
  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?
    Marsh units and water and land boundaries inherit their accuracy from the 2020 U.S. Fish and Wildlife Service National Wetland Inventory (USFWS NWI). However, the lineage of the source data indicates that the underlying data span multiple years and the mapped features may have changed since the date of imagery. Accuracy of marsh unit delineation depends on the vertical and horizontal accuracy of the 1-meter resolution U.S. Geological Survey Coastal National Elevation Database (USGS CoNED) data from 2016. Accuracy of the vegetated and unvegetated polygons is based on the 0.6-meter resolution National Agriculture Imagery Program (NAIP) products from 2018. Any vegetated or unvegetated polygons less than 9 square meters (m^2) were merged with the surrounding majority class. When creating marsh units, conterminous polygons smaller than 900 m^2 were merged with the larger polygon of the same type.
  2. How accurate are the geographic locations?
    Horizontal accuracy is inherited from CoNED Digital Elevation Models. Vegetated and unvegetated polygons were based on the 0.6-meter resolution NAIP imagery. Although the analyses were performed at 1-meter resolution, the horizontal accuracy is superseded by NAIP imagery accuracy which is +/-6 meters.
  3. How accurate are the heights or depths?
    Because the elevation values are averaged over delineated polygons, vertical accuracy depends on both the horizontal accuracy of the NWI dataset and the vertical accuracy of the source elevation data, CoNED. CoNED vertical elevation accuracy was 0.2 meters.
  4. Where are the gaps in the data? What is missing?
    The marsh polygons are bound to the borders of the Blackwater estuarine intertidal areas that include; 1) emergent wetlands, 2) scrub-shrub areas, 3) rooted vascular aquatic beds, 4) organic unconsolidated shores, and 5) channels of open water that are narrower than 10 meters. Sliver polygons of open salt water along the marsh edges may also be included in some instances as a result of geoprocessing. A detailed on-the-ground analysis of a single site may result in a different interpretation of the wetland and marsh unit boundaries than those established through this analysis.
  5. How consistent are the relationships among the observations, including topology?
    Topological errors that occurred during geoprocessing were automatically removed by the topological rules used for the analysis. The polygons were checked for correct geometry and do not overlap. Small polygons (less than 9 m^2) were assumed to be marginal and were assigned the classification from the surrounding majority value. This resulted in polygons that were removed from the dataset and FID CMU values that are not sequential. In two areas (around marsh unit 3094 and marsh unit 4424), there are marsh units that have straight lines for boundaries; this is due to larger areas of hydro-flattened bathymetry/elevation values that do not allow the basin analysis to identify ridge lines between basins. Most of these marsh units have a flag that shows that the hydro-flattened area of the marsh unit is greater than 25 percent of the marsh unit area. In a few cases, there are hydro-flattened values on land, for example in the area of MU 4424.
    A visual comparison between NAIP imagery was performed at randomly selected sites to verify the land and water boundaries.

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 polygons are defined for scientific research purposes and should not be used as a sole source of reference for any regulations and policy making. 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 source of this information.
  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? CMU_BW.shp (and files associated with a shapefile), browse graphic (CMU_BW_Browse.png), and CSDGM metadata in XML 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. Not for navigational use.
  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 08-Jun-2021
Metadata author:
Kate V. Ackerman
U.S. Geological Survey
Geologist
384 Woods Hole Rd
Woods Hole, MA
US

508-548-8700 x2331 (voice)
508-457-2310 (FAX)
kackerman@usgs.gov
Metadata standard:
FGDC Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/whcmsc/SB_data_release/DR_P9M7H6XG/CMU_BW.faq.html>
Generated by mp version 2.9.50 on Tue Sep 21 18:18:56 2021