Conceptual marsh units of Chesapeake Bay salt marshes

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What does this data set describe?

Title: Conceptual marsh units of Chesapeake Bay salt marshes
Abstract:
This data release contains coastal wetland synthesis products for Chesapeake Bay. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and tidal range 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., 20221103, Conceptual marsh units of Chesapeake Bay salt marshes: data release DOI:10.5066/P997EJYB, 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., 2022, Geospatial characterization of salt marshes in Chesapeake Bay: data release DOI:10.5066/P997EJYB, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Ackerman, K.V., Defne, Z., and Ganju, N.K., 2022, Geospatial characterization of salt marshes in Chesapeake Bay: U.S. Geological Survey data release, https://doi.org/10.5066/P997EJYB.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -77.374707
    East_Bounding_Coordinate: -75.593417
    North_Bounding_Coordinate: 39.589813
    South_Bounding_Coordinate: 36.374384
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/630f9b40d34e36012efa091d/?name=CMU_CB_Browse.png (PNG)
    Graphic that shows the conceptual marsh units of Chesapeake Bay salt marshes.
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 2022
    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 (90037)
    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 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?
    CMU_CB attribute table
    Table containing attribute information associated with the dataset. (Source: Producer Defined)
    OBJECTID
    Internal feature number. (Source: Esri) Sequential 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:1
    Maximum:46457
    Units:none
    APGN_M2
    Surface area of the selected polygon type (vegetated or unvegetated). (Source: USGS)
    Range of values
    Minimum:0.00293141849046
    Maximum:2877935.91808
    Units:m^2
    ATOT_M2
    Total surface area of a marsh unit. (Source: USGS)
    Range of values
    Minimum:12.9601064167
    Maximum:3202425.38166
    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.
    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
    FLG
    Marsh unit flag indicating anomalous marsh units based on absence of vegetation, elevation, surface area and tidal range extrapolation. 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 the 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; (-10000) mean tidal range of marsh unit is extrapolated; 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:-11201
    Maximum:0
    Entity_and_Attribute_Overview:
    In this dataset, the salt marsh complexes across Chesapeake Bay have 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 the marsh health of salt 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 salt marsh complexes based on consistently defined marsh units while facilitating a better understanding of the relative importance of the processes involved. The salt marshes of Chesapeake Bay were 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?
    USGS CoNED (source 1 of 8)
    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:

    Other_Citation_Details:
    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 01/29/2020.
    Type_of_Source_Media: Digital
    Source_Contribution: Elevation dataset
    NC DEM (source 2 of 8)
    NOAA Office for Coastal Management, 20211130, North Carolina Statewide Lidar DEM 2014 Phase 1: NOAA, Charleston, SC.

    Online Links:

    Other_Citation_Details:
    Downloaded Digital Elevation Model to be used for North Carolina. Projection was NAD 1983 UTM Zone 18N with the North American Vertical Datum of 1988 (NAVD 88). Download date was 04/04/2022.
    Type_of_Source_Media: Digital
    Source_Contribution: Elevation dataset for NC
    APG DEM (source 3 of 8)
    NOAA National Centers for Environmental Information, 2019, Continuously Updated Digital Elevation Model (CUDEM)-Ninth Arc-Second Resolution Bathymetric-Topographic Tiles: NOAA, Boulder, CO.

    Online Links:

    Other_Citation_Details:
    Downloaded Digital Elevation Model to be used for a small part of region CB08A (Aberdeen Proving Ground) that is not covered by CoNED. Tiles downloaded: chesapeake_bay/ncei19_n39x50_w076x25_2019v1.tif, chesapeake_bay/ncei19_n39x50_w076x50_2019v1.tif. Projection was NAD 1983 UTM Zone 18N with the North American Vertical Datum of 1988 (NAVD 88). Download date was 08/20/2021.
    Type_of_Source_Media: Digital
    Source_Contribution: Elevation dataset for Aberdeen Proving Ground
    NAIP (source 4 of 8)
    U.S. Department of Agriculture, 2018, NAIP Digital Ortho Photo Image (2018): USDA-FSA-APFO Aerial Photography Field Office, Salt Lake City, Utah.

    Online Links:

    Other_Citation_Details:
    Downloaded NAIP 4-band, 0.6-meter resolution imagery from the USGS Earth Explorer. Projection was NAD 1983 UTM Zone 18N. Download date was 01/17/2020. NAIP (2018) data was use in regions CB00, CB02, CB03, CB04, CB08, CB09, CB13, CB14A, CB15, and CB16.
    Type_of_Source_Media: Digital
    Source_Contribution: Aerial imagery dataset (2018)
    NAIP (source 5 of 8)
    U.S. Department of Agriculture, 2017, NAIP Digital Ortho Photo Image (2017): USDA-FSA-APFO Aerial Photography Field Office, Salt Lake City, Utah.

    Online Links:

    Other_Citation_Details:
    Downloaded NAIP 4-band, 1-meter resolution imagery from the USGS Earth Explorer. Projection was NAD 1983 UTM Zone 18N. Download date was 01/17/2020. NAIP (2017) data was used in regions CB07, CB10, and CB11.
    Type_of_Source_Media: Digital
    Source_Contribution: Aerial imagery dataset (2017)
    NAIP (source 6 of 8)
    U.S. Department of Agriculture, 2016, NAIP Digital Ortho Photo Image (2016): USDA-FSA-APFO Aerial Photography Field Office, Salt Lake City, Utah.

    Online Links:

    Other_Citation_Details:
    Downloaded NAIP 4-band, 1-meter resolution imagery from the USGS Earth Explorer. Projection was NAD 1983 UTM Zone 18N. Download date was 01/17/2020.NAIP (2016) data was used in regions CB05, CB11, CB12, and CB14B.
    Type_of_Source_Media: Digital
    Source_Contribution: Aerial imagery dataset (2016)
    Worldview-2 (source 7 of 8)
    Worldview-2 Maxar/DigitalGlobe, Inc., 2019, Worldview-2 Imagery: DigitalGlobe, Inc., Longmont, CO.

    Online Links:

    Other_Citation_Details:
    Downloaded Worldview-2 8-band, 1.85-meter resolution imagery from Maxar. Imagery (c) 2019 Maxar. Projection was WGS 1984 UTM Zone 18N. Download date was 07/01/2021. Worldview-2 imagery is commercially acquired by Maxar and is accessible through the website, https://evwhs.digitalglobe.com/myDigitalGlobe, by those who have access accounts. Worldview-2 data was used in region CB08A. Worldview-2 data was used in region CB08A.
    Type_of_Source_Media: Digital
    Source_Contribution: Satellite imagery dataset used for Aberdeen Proving Ground
    NWI (source 8 of 8)
    U.S. Fish and Wildlife Service, 20191001, National Wetland Inventory: U.S. Fish and Wildlife Service, Madison, WI.

    Online Links:

    Other_Citation_Details:
    Downloaded wetlands data for Virginia, Maryland and North Carolina in shapefile format from the NWI download page. Projection was NAD 1983 Albers. Download date was 01/02/2020.
    Type_of_Source_Media: Digital
    Source_Contribution: Wetlands dataset
  2. How were the data generated, processed, and modified?
    Date: 2022 (process 1 of 6)
    This process step and all subsequent process steps were performed by the same person, Kate Ackerman, in ArcGIS Pro (ver. 2.8.2), unless otherwise stated. For simple operations the name of the geoprocessing tool used is given in capital letters; for complex operations, the name of geoprocessing tool used is given in capital letters and 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.
    The Chesapeake Bay was split into 16 regions to complete this analysis, refer to the accompanying image (CB_regions.png) to see the location of the regions. The methodology from region to region was consistent, however small changes were made across Chesapeake Bay; the changes are noted in the process steps below.
    a) Set the data frame coordinate system and projection to NAD 1983 UTM Zone 18N.
    b) Prepare elevation dataset. For the NC DEM: RESAMPLE the raster to 1m. MOSAIC TO NEW RASTER the USGS CoNED raster and the NC DEM, with the USGS CoNED taking precedence over the NC DEM. For the small areas in region CB08A (Aberdeen Proving Ground, APG) that are not covered by USGS CoNED data, the APG DEM (resampled to 1m) was used to fill in these areas.
    c) Create a polygon that covers the area of interest [extent.shp]. CLIP the mosaicked elevation dataset created in step (b) by [extent.shp] to create [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:
    • USGS CoNED
    • NC DEM
    Data sources produced in this process:
    • elev_mosaic.tif
    Date: 2022 (process 2 of 6)
    This process step creates two mask polygons to define analysis boundaries over the area of interest. 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 created [UVVR_mask.shp]. This larger mask area is clipped to the boundaries of the salt marsh area to create [MU_mask.shp]. This process step explains how [UVVR_mask.shp] and [MU_mask.shp] are created and edited to determine which interior polygons are removed.
    a) Create a shapefile of the salt marshes as defined by NWI. EXPORT features (use the same coordinate system as the data frame) from NWI dataset of all wetlands for the area (referred to here as [NWI_entire.shp]) 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 to create [NWI_exclusive_select.shp]. For Colonial National Historic Park (in region CB14), palustrine emergent wetlands with freshwater tidal modifiers ('PEM1R'and 'PEM1S') were included.
    b) Create the preliminary masks that will be edited in the subsequent steps to make the final masks. BUFFER salt marsh classes (Input features=[NWI_exclusive_select.shp]; Linear unit=5 meters; Dissolve type=All) to obtain the mask polygon [buff5m.shp] and ELIMINATE POLYGON PART (Input features= [buff5m.shp]; Condition=Percentage; Percentage=99; Eliminate contained part only) to remove small interior polygons to obtain [UVVR_mask01.shp]. Apply BUFFER (Input features=[UVVR_mask01.shp]; Linear unit= -5 meters; Dissolve type= All) 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_exc_voids_single.shp].
    To remove areas that should not be included in the mask (e.g., forest areas) the following steps were implemented:
    d.1) An additional step was used for regions CB04-CB09 only: To find all of the interior features that should potentially be removed, run SYMMETRICAL DIFFERENCE (Input features=[buff5m.shp], Update features=[UVVR_mask01.shp], Join attributes= All) and MULTIPART TO SINGLEPART to obtain [UVVR_mask01_buff5m_diff_single.shp]. Do a SPATIAL JOIN (Target Features=[UVVR_mask01_buff5m_diff_single.shp], Join Features= [NWI_entire.shp]; Join operation=join one to one; Keep all target features; match option= intersect) to obtain [UVVR_nwi_sjoin.shp]. Select records that have a null value for the “attribute” field and generate a shapefile of the selected records [NWI_voids_single.shp].
    Depending on the region, the e.1, e.2 or e.3 methodology was used to create the [MU_mask.shp] and [UVVR_mask.shp] (the methodology changed very slightly as work progressed through the CB): (If you are using this metadata as instructions to generate marsh units, use the e.3 methodology (region CB16), as it represents the most up-to-date methodology).
    e.1) For regions CB00, CB02, CB04-CB13: SELECT BY LOCATION from [NWI_inclusive_single.shp] that are completely within the [MU_mask01.shp] and SELECT BY LOCATION from [NWI_exc_voids_single.shp] that are completely within the [MU_mask01.shp] (for regions CB04-CB09: and SELECT BY LOCATION from [NWI_voids_single.shp] that are completely within the [MU_mask01.shp]). If any additional polygons need to be removed from the mask, include them in a new feature layer [erase_mask_manual.shp]. MERGE all feature sets to get polygons to be excluded [erase_inside.shp] from the final masks. ERASE [erase_inside.shp] from [MU_mask01.shp] to obtain [MU_mask.shp]. To obtain [UVVR_mask.shp], BUFFER [erase_inside.shp] by -5 meters (side type= full; end type= round; method: geodesic; dissolve type: single feature) then ERASE [erase_inside.shp] from [UVVR_mask01.shp].
    e.2) For regions CB03, CB14, CB15: SELECT BY LOCATION from [NWI_inclusive_single.shp] that are completely within the [MU_mask01.shp] and SELECT BY LOCATION from [NWI_exc_voids_single.shp] that are completely within the [MU_mask01.shp]. If any additional polygons need to be removed from the mask, include them in a new feature layer [erase_mask_manual.shp]. MERGE all feature sets to get polygons to be excluded [erase_inside.shp] from the final masks. BUFFER [erase_inside.shp] by -5 meters, to obtain [erase_inside_buffback5m.shp] and ERASE [erase_inside_buffback5m.shp] from [UVVR_mask01.shp] to obtain [UVVR_mask.shp]. BUFFER [UVVR_mask.shp] by -5m to obtain [MU_mask.shp].
    e.3) For region CB16: This methodology incorporates estuarine and marine wetland systems that are completely surrounded by salt marsh (e.g., interior ponds):
    e.3a)SELECT BY LOCATION from [NWI_inclusive_single.shp] that are completely within the [MU_mask01.shp] and SELECT BY LOCATION from [NWI_exc_voids_single.shp] that are completely within the [MU_mask01.shp]. UNION all feature sets to get polygons to be excluded [erase_inside.shp] from the final masks.
    e.3b) Spatially join the [NWI_entire.shp] to [erase_inside.shp] in order to assign wetland attributes to the [erase_inside.shp] polygons. SPATIAL JOIN (target features= [erase_inside.shp]; join features= [NWI_entire.shp]; output feature class= [erase_inside_NWI_info.shp]; join operation= one to one; keep all target features; match option= intersect; search radius= -1 m).
    e.3c) Select the polygons that are marine or non-forested estuarine wetlands from [erase_inside_NWI_info.shp]: SELECT (ATTRIBUTE LIKE 'E1%' OR ATTRIBUTE LIKE 'E2AB%' OR ATTRIBUTE LIKE 'E2RF%' OR ATTRIBUTE LIKE 'E2SB%' OR ATTRIBUTE LIKE 'E2RS%' OR ATTRIBUTE LIKE 'E2US%' OR ATTRIBUTE LIKE 'E2EM%' OR ATTRIBUTE LIKE ‘E2SS%’ OR ATTRIBUTE LIKE ‘M1%’ OR ATTRIBUTE LIKE ‘M2%) to select all marine systems, estuarine subtidal systems, estuarine intertidal areas of aquatic bed, reef, streambed, rocky shore, unconsolidated shore, emergent or scrub-shrub [erase_inside_keepIntPonds.shp].
    e.3d) Remove the polygons from [erase_inside_NWI_info.shp] that should be retained (these are the interior ponds): ERASE (input feature= [erase_inside_NWI_info.shp]; erase feature= [erase_inside_keepIntPonds.shp]; output feature= [erase_inside_final.shp]).
    e.3e) If any additional polygons need to be removed from the mask, include them in a new feature layer [erase_mask_manual.shp] and MERGE with [erase_inside_final.shp].
    e.3f) Remove any unwanted polygons from the original [MU_mask01.shp] to make the final [MU_Mask.shp]: ERASE (input feature= [MU_mask01.shp]; erase feature= [erase_inside_final.shp]; output feature= [MU_mask.shp]).
    e.3g) BUFFER [MU_mask.shp] by 5m (side type= full; end type= round; method: geodesic; dissolve type: single feature) to obtain [UVVR_mask.shp]. Data sources used in this process:
    • NWI
    Data sources produced in this process:
    • MU_mask.shp
    • UVVR_mask.shp
    Date: 2022 (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 [basin_buff5m.tif] and convert RASTER TO POLYGON [basin_b5m_poly.shp]. Create a 1-meter buffered marsh units mask [MU_mask_buff1m.shp] and use this to CLIP the polygon to create [basin_b5m_polyclip.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. Using [basin_b5m_polyclip.shp] as the input, MULTIPART TO SINGLEPART and ADD GEOMETRY ATTRIBUTES(Geometry properties=Area_geodesic; Area unit=Square_meters) to get [basin_single.shp]. Data sources used in this process:
    • elev_mosaic.tif
    Data sources produced in this process:
    • basin_single.shp
    Date: 2022 (process 4 of 6)
    This step merges the "orphan marsh units," units that are smaller than 5000 m^2, 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 ArcGIS tools to aggregate orphan units on parent units is used.
    a) Create orphan marsh unit features by exporting marsh units from [basin_single.shp] with an area less than 5000 m^2 [inputfeatures.shp].
    b) Create parent marsh unit 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. The 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. To [CMU.shp], ADD FIELD “FID_CMU” and CALCULATE FIELD as FID_CMU= FID x 1. Delete fields from [CMU.shp] so that only area_geo and FID_CMU remain. REPAIR GEOMETRY of [CMU.shp]. In region CB08A (APG), there were a lot of marsh units with straight-edge boundaries, perhaps due to poor elevation data quality. These were merged with adjacent marsh units to eliminate these boundaries.
    f) DISSOLVE the conceptual marsh units to get the final outlines for the marsh complex [CMU_mask_final.shp]. Data sources used in this process:
    • basin_single.shp
    Data sources produced in this process:
    • CMU_mask_final.shp
    Date: 2022 (process 5 of 6)
    Determine the vegetated and unvegetated areas by image processing.
    a) MOSAIC TO NEW RASTER the NAIP tiles (for region CB08A, Worldview-2 tiles).
    b) EXTRACT BY MASK from the elevation raster [elev_mosaic.tif] and the NAIP (and Worldview-2) imagery raster using [UVVR_mask.shp] polygon and append “UVVR_mask” to the file name. Rescale the elevation raster values to the same range with 8-bit NAIP imagery (0 to 255) using min-max scaling in RASTER CALCULATOR (map algebra expression: (("elev_mosaic_UVVR_mask.tif"-(min value of the input raster))*(255-0)/(max value of the input raster)-( min value of the input raster)))+0). 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. (For region CB08A, the ISO CLUSTER UNSUPERVISED CLASSIFICATION was performed with the Worldview-2 8 bands and the rescaled elevation raster.) RECLASSIFY the classified raster by visually comparing the NAIP imagery to obtain the unvegetated-vegetated raster [UVVc.tif]. In some regions, a couple of the 32 classes are classified as vegetated in one area but unvegetated in another area. For these classes, the area can be split into separate sections to allow one section to be classified as vegetated and the other as unvegetated.
    c) 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.
    d) RASTER TO POLYGON(Simplify polygons=False) and CLIP with the final marsh complex outline [CMU_mask_final.shp] to obtain [UVVc_filt_clip.shp].
    e) 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].
    f) 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]. Add fields "TYP", "APGN_M2", and "ATOT_M2" for type of polygon indicating vegetated or unvegetated, surface area of the polygon, and total surface area of the marsh unit, respectively, and calculate "APGN_M2" and "ATOT_M2" areas. 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
    • Worldview-2
    • elev_mosaic.tif
    Data sources produced in this process:
    • UVV_poly_diss.shp
    Date: 2022 (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 marsh units.
    b) Add field "FLG" to flag anomalous marsh units based on absence of vegetation, elevation, surface area and tidal range extrapolation. 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 the 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; (-10000) mean tidal range of marsh unit is extrapolated; 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(Output coordinate system=WGS 1984 Web Mercator Auxiliary Sphere) the feature dataset to obtain the final conceptual marsh units [CMU_CB].
    d) Since exporting the CMU_CB feature class to a shapefile would result in a shapefile greater than the 2 GB limit, it is released as a GeoPackage. The GeoPackage was created using CREATE SQLITE DATABASE (Output database name= CMU_CB.gpkg; Spatial Type = GeoPackage), then FEATURE CLASS TO FEATURE CLASS (Input features=CMU_CB; Output location= CMU_CB.gpkg; Output Name= CMU_CB). The CMU_CB.gpkg can be opened in any open-source GIS software. The CMU_CB feature class is also released as a Esri service definition file [CMU_CB.sd], so WMS/WFS can be enabled. The service definition file was generated in ArcGIS Desktop 10.7.1, following the instructions found on the ScienceBase website, https://www.sciencebase.gov/about/content/sciencebase-geospatial-services (accessed 10/19/22). Data sources used in this process:
    • UVV_poly_diss.shp
    Data sources produced in this process:
    • CMU_CB.gpkg
    • CMU_CB.sd
  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 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 elevation data (primarily: USGS CoNED, secondarily for NC only: NOAA NC DEM). Accuracy of the vegetated and unvegetated polygons is based on the National Agriculture Imagery Program (NAIP) products from 2018 (0.6-meter resolution), 2017 (1-meter resolution), and 2016 (1-meter resolution). Any vegetated or unvegetated polygons less than 9 square meters (m^2) were merged with the surrounding majority class unless they are at the edge of a marsh unit. 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 the Digital Elevation Models (primarily: USGS 1m CoNED, for NC only: NOAA NC 1.5m DEM). Vegetated and unvegetated polygons were based on the 0.6-meter and 1-meter resolution NAIP imagery (and in region CB08A, the polygons are based on the 1.85-meter resolution Worldview-2 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 datasets (primarily: USGS 1m CoNED, for NC only: NOAA NC 1.5m DEM). The vertical accuracy is inherited from the source elevation datasets; it is reported to be 0.2 meters for the 1-meter CoNED dataset, and is reported as 0.06 meters for the 1.5-meter NOAA North Carolina DEM dataset. No additional accuracy assessment of the vertical accuracy has been conducted.
  4. Where are the gaps in the data? What is missing?
    The marsh polygons are bound to the borders of the Chesapeake Bay 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 (e.g., marsh unit 36608).
    In a few cases, linear marsh unit features that are artifacts of the NWI dataset are retained (e.g., marsh units 17309, 17310, 20453).
    Occasionally, marsh units are retained in this dataset even though the imagery displayed extreme change (e.g., partially or completely converted to water) from the NWI wetland delineation (e.g., marsh units 18150, 36504).
    In some marsh units there are small sliver gaps due to coupling of artifacts of the NWI (e.g., NWI polygons for ditches that are classified as riverine) and geoprocessing when the marsh polygons were closer than 10 meters at a specific section that is followed by a wider distance (e.g., access roads, fringing forests, etc.). The effect of these sliver gaps on the calculations is negligible (e.g., south of marsh unit 19742).
    In a few marsh units there are small gaps that inadvertently did not get incorporated into the marsh unit; the effect of these gaps on the calculations is negligible (e.g., marsh unit 33957).
    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.
    At Colonial National Historic Park, Virginia, palustrine emergent persistent wetlands (with freshwater tidal modifiers) were included to ensure complete coverage of the estuarine and palustrine emergent wetlands within the Park boundaries.
    In region CB16 (at the VA-NC border), the methodology was changed slightly to include estuarine and marine wetland polygons that are completely surrounded by salt marsh (see process step e.3).
    In region CB08A (Aberdeen Proving Ground, in northern Chesapeake Bay), Worldview-2 imagery was used due to the unavailability of NAIP imagery.
  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. In two areas (around marsh units 4028 and 5358), 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.

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? In order to have WMS/WFS, the data is released as a service definition file, CMU_CB.sd, since it is too large to be released as a shapefile. The GeoPackage file, CMU_CB.gpkg, can be imported into any GIS software. Also included are an image of the regions used to complete the analyses (CB_regions.png), a browse graphic (CMU_CB_Browse.png) and FGDC CSDGM metadata in xml format.
  3. What legal disclaimers am I supposed to read?
    Although these data have been processed successfully on a computer system at the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. The USGS or the U.S. Government shall not be held liable for improper or incorrect use of the data described and/or contained herein. 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. Any use of trade, firm, or product 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: 03-Nov-2022
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:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/whcmsc/SB_data_release/DR_P997EJYB/CMU_CB.faq.html>
Generated by mp version 2.9.51 on Thu Nov 3 17:37:57 2022