Conceptual marsh units for Jamaica Bay to western Great South Bay salt marsh complex, New York

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Frequently anticipated questions:

What does this data set describe?

Title:
Conceptual marsh units for Jamaica Bay to western Great South Bay salt marsh complex, New York
Abstract:
This data release contains coastal wetland synthesis products for the geographic region from Jamaica Bay to western Great South Bay, located in southeastern New York State. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and mean tidal range, are calculated for smaller units delineated from a Digital Elevation Model, providing the spatial variability of physical factors that influence wetland health. Through scientific efforts initiated with the Hurricane Sandy Science Plan, 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?
    Welk, Robert, Defne, Zafer, and Ganju, Neil, 2019, Conceptual marsh units for Jamaica Bay to western Great South Bay salt marsh complex, New York: data release DOI:10.5066/P9GAGLXB, U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

    This is part of the following larger work.

    Welk, Robert, Defne, Zafer, and Ganju, Neil, 2019, Coastal wetlands from Jamaica Bay to western Great South Bay, New York: data release DOI:10.5066/P9GAGLXB, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Welk, R., Defne, Z., and Ganju, N.K., 2019, Coastal wetlands from Jamaica Bay to western Great South Bay, New York: U.S. Geological Survey data release, https://doi.org/10.5066/P9GAGLXB.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -73.939947
    East_Bounding_Coordinate: -73.416415
    North_Bounding_Coordinate: 40.666277
    South_Bounding_Coordinate: 40.545976
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/5cfe97cbe4b0156ea5644fce?name=CMU.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: 2019
    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 (4619)
    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?
    CMU_JB
    Table containing attribute information associated with the dataset. (Source: U.S. Geological Survey)
    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 that represent the identification number for each 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:2784
    Units:none
    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.
    APGN_M2
    Surface area of the selected polygon type (vegetated or unvegetated). (Source: USGS)
    Range of values
    Minimum:1.049662
    Maximum:330917.399946
    Units:square meters
    ATOT_M2
    Total surface area of a marsh unit in square meters (Source: USGS)
    Range of values
    Minimum:9.009921
    Maximum:340675.207145
    Units:square meters
    FLG
    Marsh unit flag indicating anomalous marsh units based on absence of vegetation, elevation and surface area. 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; (-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:-1101
    Maximum:0
    Units:None
    Entity_and_Attribute_Overview:
    In this dataset, the salt marsh complex from Jamaica Bay to western Great South Bay has been delineated to conceptual salt marsh units to facilitate unit by unit evaluation of response and resiliency of 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)
    • Robert Welk
    • Zafer Defne
    • Neil Ganju
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    U.S. Geological Survey, Northeast Region
    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?

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 from Jamaica Bay to western Great South Bay was delineated to smaller, conceptual marsh units by 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?
    NED (source 1 of 4)
    U.S. Geological Survey, 2015, National Elevation Dataset: U.S. Geological Survey, Reston, VA.

    Online Links:

    Type_of_Source_Media: Digital
    Source_Contribution:
    Downloaded NED Digital Elevation Model from the National Map Projection was NAD 1983 UTM Zone 18N with the North American Vertical Datum of 1988 (NAVD 88). Download date was 2019/03/01.
    NAIP (source 2 of 4)
    U.S. Geological Survey, 2017, 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 1-meter resolution imagery from the USGS Earth Explorer. Projection was WGS 1984 Web Mercator Auxiliary Sphere. Download date was 2019/03/01.
    NWI (source 3 of 4)
    U.S. Fish and Wildlife Service, 2017, National Wetland Inventory New York Wetlands: U.S. Fish and Wildlife Service, Madison, WI.

    Online Links:

    Type_of_Source_Media: Digital
    Source_Contribution:
    Downloaded wetlands data for the state of New York in Shapefile format from the NWI download page. Projection was NAD 1983 Albers. Download date was 2019/03/01.
    NYSDEC (source 4 of 4)
    New England Interstate Water Pollution Control Commission Prepared by Cameron Engineering and Associates, LLP, 2015, Long Island Tidal Wetlands Trends Analysis.

    Online Links:

    Type_of_Source_Media: Digital
    Source_Contribution:
    Wetland polygon shapefile prepared for Long Island Tidal Wetlands Trends Analysis. Data available by request. Data acquired 2019/05/01.
  2. How were the data generated, processed, and modified?
    Date: 2019 (process 1 of 7)
    This process step and all subsequent process steps were performed by the same person, Robert Welk, in ArcMap (ver. 10.6.1) 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.
    Set the data frame coordinate system and projection to NAD 1983 UTM Zone 18N. Prepare elevation dataset to be clipped to the boundaries polygon. MOSAIC TO NEW RASTER(Pixel type= 32 bit float; Mosaic operator=Mean; Cellsize=1 m) all of the NED raster to a new raster dataset with 1 m resolution [elev_mosaic.tif]. Data sources used in this process:
    • NED
    Date: 2019 (process 2 of 7)
    Prepare mask polygon to define analysis boundaries. In order to account for the possible influence of the surrounding terrain on the analysis, first a mask area larger than the salt marsh extent is created [UVVR_mask]. At the end of the analysis the results are clipped to the boundaries of the salt marsh area [MU_mask]. Both UVVR_mask and MU_mask are edited to decide which interior polygons are removed.
    a) MERGE NWI wetland polygons with NYSDEC to obtain [NWI_DEC.shp].
    b) EXPORT features from NWI_DEC.shp 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, 2) Scrub-shrub, 3) Rooted vascular aquatic bed, 4) Organic unconsolidated shore classes [NWI_exclusive_select.shp].
    c) 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].

    d) 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. MULTIPART TO SINGLEPART to separate individual polygons [NWI_inclusive_single.shp].
    e) To exclude the voids in the NWI map during the analysis these interior polygons need to be removed from the mask. Create a rectangular polygon that covers the domain [extent.shp]. ERASE [NWI_excusive_select.shp] from [extent.shp] and MULTIPART TO SINGLEPART to get [NWI_voids_single.shp].
    f) 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.
    g) ERASE [erase_inside.shp] from [MU_mask01.shp] and [UVVR_mask01.shp] to obtain [MU_mask.shp] and [UVVR_mask.shp], respectively. Data sources used in this process:
    • NWI
    • NYSDEC
    Date: 2019 (process 3 of 7)
    Define preliminary boundaries for marsh units by basin analysis:
    a) EXTRACT BY MASK from mosaicked elevation dataset using [UVVR_mask.shp] polygon.
    b) FILL(no Z limit) sinks in extracted elevation raster.
    c) Calculate FLOW DIRECTION(do not force edge cells 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: 2019 (process 4 of 7)
    This step merges the "orphan marsh units", units that are less than 5000 m2 in area to the nearest to "parent marsh units", units that are larger than 5000 m2 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 m2 [lt5000.shp].
    b) Create parent marsh units features by exporting marsh units with an area greater than or equal to 5000 m2 [ge5000.shp].
    c) Run Python script (hydUnitloop.py). At each iteration step the script uses NEAR tool to find orphan marsh units within 1 m 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.
    d) The remaining orphan marsh units are those that are more than 1 m away from any parent. DISSOLVE them to create larger orphan units by grouping the orphans attached together into larger units.
    e) MULTIPART TO SINGLEPART to have single part polygons with unique identifiers.
    f) UNION(with gaps) single part features with parent units to obtain preliminary marsh units [pMUopt1.shp].
    g) SMOOTH POLYGON(Smoothing algorithm=PAEK; Smoothing tolerance=15 meters) to get the smoothed marsh units polygon [pMUopt1_smooth.shp].
    h) 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 m2, dissolve into the nearest parent units repeating the same steps above to obtain [pMUopt1_clip_final.shp]
    i) Compute the final marsh units by removing any artefacts 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 m2 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 artefacts.
    j) DISSOLVE the conceptual marsh units to get the final outlines for the marsh complex [CMU_mask_final.shp].
    Date: 2019 (process 5 of 7)
    Determine the vegetated and unvegetated areas by image processing.
    a) EXTRACT BY MASK from elevation raster [elev_mosaic.tif] 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 with4-bands (Near Infrared, Blue, Green, Red from the NAIP imagery and the rescaled elevation raster with 32 classes 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]. For marsh units with invalid elevation data, the classification was processed with imagery bands only and later merged with the rest of the dataset.
    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(Number of neighbors=4; Zone grouping method=Within; Add Link field to output) to get the [UVV_region.tif], and TEST("Count" less than 9) to set a threshold value of 9 raster cells [UVV_test.tif]. Use RASTER CALCULATOR to toggle the value of the Link field in the region raster, 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 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.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, Area_geo.SUM) 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.
    f) Add field "UVVR" and calculate unvegetated to vegetated ratio based on "TYP", "APGN_M2" and "ATOT_M2" fields. If the vegetated area is zero for a marsh unit set the value of UVVR to -1.
    g) Calculate the mean elevation for each marsh unit with ZONAL STATISTICS AS TABLE(Raster layer=[elev_mosaic.tif]; Zone features=[CMU.shp], Zone field=FID_CMU; Statistics type=Mean; Ignore Nodata=True) and JOIN with [CMU.shp] to get [mu_elev.shp]. Data sources used in this process:
    • NAIP
    Date: 2019 (process 6 of 7)
    Finalize the conceptual marsh units.
    a) Add field "FLG" to flag anomalous marsh units based on absence of vegetation, elevation and surface area. Set FLG to (-1) no vegetated area; (-10) marsh unit elevation higher than the 99.8 percentile; (-100) marsh unit elevation less than 0.2 percentile; (-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.
    b) Remove field "UVVR" and 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_JB.shp].
    Date: 07-Aug-2020 (process 7 of 7)
    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
  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, water and land boundaries inherit their accuracy from the accuracy of the U.S. Fish and Wildlife Service National Wetland Inventory (USFWS NWI) published in 2017. However, the lineage of the source data indicates that the underlying data span over 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 National Elevation Database (USGS NED) data from 2015. Vegetated and unvegetated polygons accuracy is based on the 1-meter resolution National Agriculture Imagery Program (NAIP) products from 2017. Any vegetated or unvegetated polygons less than 9 square meters were merged to the surrounding majority class. While creating marsh units conterminous polygons smaller than 900 square meters have been merged with the larger polygon of the same type. Small marsh island such as this are common in the geographic region from Jamaica Bay to western Great South Bay, so therefore many polygons in this dataset could not be merged with larger units.
  2. How accurate are the geographic locations?
    Horizontal accuracy is inherited from NED Digital Elevation Model. Vegetated and unvegetated polygons were based on the 1-meter resolution NAIP imagery. Although the analyses were performed at 1-meter resolution, the horizontal accuracy is superseded by NAIP imagery accuracy, +/-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 NWI dataset and the vertical accuracy of source elevation data, NED. NED 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 boundaries of the Jamaica Bay to western Great South Bay areas that include Estuarine intertidal areas of 1) Emergent, 2) Scrub-shrub, 3) Rooted vascular aquatic bed, 4) Organic unconsolidated shore, and 5) channels of open water that are wider 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 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 are checked for correct geometry and do not overlap. Small polygons (less than 9 square meters) 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. 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_JB.shp (and files associated with a shapefile), browse graphic (CMU.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: 19-Mar-2024
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. (updated on 20240319)
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_P9GAGLXB/CMU_JB_FGDC.faq.html>
Generated by mp version 2.9.51 on Wed Jun 26 15:25:06 2024