Inventory of Managed Coastal Wetlands in Delaware Bay and Delaware's Inland Bays

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Frequently anticipated questions:

What does this data set describe?

Title:
Inventory of Managed Coastal Wetlands in Delaware Bay and Delaware's Inland Bays
Abstract:
This data release contains areas within Delaware Bay and Delaware Inland Bays that are within tidal elevations, as determined by the Highest Astronomical Tide (HAT), but that are classified as non-tidal or managed wetlands by the National Wetlands Inventory (NWI) or as non-estuarine by the 2016 Coastal Change Analysis Program (C-CAP) land cover dataset. These areas have been assigned the classification codes of NWI, where available, and C-CAP. These data are based on a 5m resolution elevation raster from Coastal National Elevation Database (CoNED), an interpolated surface from Highest Astronomical Tide (HAT) data from National Oceanographic and Atmospheric Administration (NOAA) tide gauges, and NWI and C-CAP digital wetland products. The area was determined by identifying non-tidal or non-wetland land covers at or below the interpolated HAT tidal elevation. The underlying wetland category from NWI or land cover type from C-CAP was then applied to the entire area to indicate areas for possible land or hydrologic management and assess current and future conditions of land within tidal elevations.
  1. How might this data set be cited?
    Nick, Sydney K., Defne, Zafer, and Kroeger, Kevin, 20230710, Inventory of Managed Coastal Wetlands in Delaware Bay and Delaware's Inland Bays: data release DOI:10.5066/P9VCYH3X, U.S. Geological Survey, Coastal and Marine Hazards and Resources Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Nick, S.K., Defne, Z., and Kroeger, K.D., 2023, Inventory of managed coastal wetlands in Delaware and Delaware's inland bays: U.S. Geological Survey data release, https://doi.org/10.5066/P9VCYH3X.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -75.7796
    East_Bounding_Coordinate: -74.6689
    North_Bounding_Coordinate: 40.2658
    South_Bounding_Coordinate: 38.5613
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/647f5975d34eac007b562495?name=MW_Browse.jpg&allowOpen=true (JPEG)
    Graphic that shows the extent of managed coastal wetlands
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 2023
    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 (73981)
    2. What coordinate system is used to represent geographic features?
      Horizontal positions are specified in geographic coordinates, that is, latitude and longitude. Latitudes are given to the nearest 0.0197509172. Longitudes are given to the nearest 0.0254454507. Latitude and longitude values are specified in Decimal seconds. The horizontal datum used is WGS_1984.
      The ellipsoid used is WGS 84.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257223563.
  7. How does the data set describe geographic features?
    managed_wetlands
    Table containing attribute information associated with the dataset. (Source: Producer Defined)
    FID
    Internal feature number. (Source: Esri) Sequential unique whole numbers that are automatically generated.
    Shape
    Feature geometry. (Source: Esri) Shape type.
    Acres
    Total area of polygon in U.S. Survey acres (Source: USGS)
    Range of values
    Minimum:1.08688573327e-09
    Maximum:799.059208239
    Units:U.S. Acres
    ATTRIBUTE
    NWI alpha-numeric wetland classification codes. (Source: USFWS) These are the attributes from the NWI source layer after removing the oligohaline modifier
    WETLAND_TY
    NWI Wetland Type as defined by NWI. (Source: USFWS)
    ValueDefinition
    empty cellNo underlying NWI data
    Freshwater Forested/Shrub WetlandForested swamp or wetland shrub bog or wetland.
    Freshwater Emergent WetlandHerbaceous marsh, fen, swale and wet meadow.
    RiverineRiverine wetland and deepwater.
    Estuarine and Marine WetlandVegetated and non-vegetated brackish and saltwater marsh, shrubs, beach, bar, shoal or flat.
    LakeLake or reservoir basin.
    Freshwater PondPond or aquatic bed.
    Estuarine and Marine DeepwaterOpen water estuary, bay, sound, open ocean.
    OtherFarmed wetland, saline seep and other miscellaneous wetland.
    ATTRIBUTE_
    NWI attributes, including the oligohaline modifier (Source: USFWS) These are the original attributes from the NWI source layer.
    NWI_TYPE
    NWI wetland type. If no NWI polygons intersected, the area was coded Undesignated Potential Wetland. (Source: USFWS)
    ValueDefinition
    Undesignated Potential WetlandNo underlying NWI wetlands.
    Freshwater Forested/Shrub WetlandForested swamp or wetland shrub bog or wetland.
    Freshwater Emergent WetlandHerbaceous marsh, fen, swale and wet meadow.
    RiverineRiver or stream channel.
    Estuarine and Marine WetlandVegetated and non-vegetated brackish and saltwater marsh, shrubs, beach, bar, shoal or flat.
    LakeLake or reservoir basin.
    Freshwater PondPond or aquatic bed.
    Estuarine and Marine DeepwaterOpen water estuary, bay, sound, open ocean.
    OtherFarmed wetland, saline seep and other miscellaneous wetland.
    gridcode_1
    CCAP source data raster code. Numerically identified and retained for table joining purposes. (Source: NOAA)
    Range of values
    Minimum:2
    Maximum:22
    CCAP_Categ
    CCAP land cover category in string format. (Source: NOAA)
    ValueDefinition
    Palustrine Scrub/Shrub WetlandIncludes tidal and nontidal wetlands dominated by woody vegetation less than 5m in height, and all such wetlands that occur in tidal areas in which salinity due to ocean-derived salts is below 0.05 percent (0.5 ppt). Total vegetation. coverage is greater than 20 percent. Species present could be true shrubs, young trees and shrubs, or trees that are small or stunted due to environmental conditions.
    Medium Intensity DevelopedContains areas with a mixture of constructed materials and vegetation or other cover. Constructed materials account for 50 to 79 percent of total area. This class commonly includes multi- and single-family housing areas, especially in suburban neighborhoods, but may include all types of land use.
    Developed Open SpaceContains areas with a mixture of some constructed materials, but mostly managed grasses or low-lying vegetation planted in developed areas for recreation, erosion control, or aesthetic purposes. These areas are maintained by human activity such as fertilization and irrigation, are distinguished by enhanced biomass productivity, and can be recognized through vegetative indices based on spectral characteristics. Constructed surfaces account for less than 20 percent of total land cover.
    Deciduous ForestContains areas dominated by trees generally greater than 5m tall and greater than 20 percent of total vegetation cover. More than 75 percent of the tree species shed foliage simultaneously in response to seasonal change.
    Low Intensity DevelopedContains areas with a mixture of constructed materials and substantial amounts of vegetation or other cover. Constructed materials account for 21 to 49 percent of total area. This subclass commonly includes single-family housing areas, especially in rural neighborhoods, but may include all types of land use.
    High Intensity DevelopedContains significant land area and is covered by concrete, asphalt, and other constructed materials. Vegetation, if present, occupies less than 20 percent of the landscape. Constructed materials account for 80 to 100 percent of the total cover. This class includes heavily built-up urban centers and large constructed surfaces in suburban and rural areas with a variety of land uses.
    Palustrine Forested WetlandIncludes tidal and nontidal wetlands dominated by woody vegetation greater than or equal to 5m in height, and all such wetlands that occur in tidal areas in which salinity due to ocean-derived salts is below 0.05 percent (0.5 ppt). Total vegetation coverage is greater than 20 percent.
    Scrub/ShrubContains areas dominated by shrubs less than 5m tall with shrub canopy typically greater than 20 percent of total vegetation. This class includes tree shrubs, young trees in an early successional stage, or trees stunted from environmental conditions.
    Palustrine Emergent WetlandIncludes tidal and nontidal wetlands dominated by persistent emergent vascular plants, emergent mosses or lichens, and all such wetlands that occur in tidal areas in which salinity due to ocean-derived salts is below 0.05 percent (0.5 ppt). Total vegetation cover is greater than 80 percent. Plants generally remain standing until the next growing season.
    CultivatedContains areas intensely managed for the production of annual crops. Crop vegetation accounts for greater than 20 percent of total vegetation. This class also includes all land being actively tilled.
    Mixed ForestContains areas dominated by trees generally greater than 5m tall, and greater than 20 percent of total vegetation cover. Neither deciduous nor evergreen species are greater than 75 percent of total tree cover. Both coniferous and broad-leaved evergreens are included in this category.
    Bare LandContains areas of bedrock, desert pavement, scarps, talus, slides, volcanic material, glacial debris, sand dunes, strip mines, gravel pits, and other accumulations of earth material. Generally, vegetation accounts for less than 10 percent of total cover.
    WaterIncludes areas of open water, generally with less than 25 percent cover of vegetation or soil.
    GrasslandContains areas dominated by grammanoid or herbaceous vegetation, generally greater than 80 percent of total vegetation. These areas are not subject to intensive management such as tilling but can be utilized for grazing.
    Unconsolidated ShoreIncludes material such as silt, sand, or gravel that is subject to inundation and redistribution due to the action of water. Substrates lack vegetation except for pioneering plants that become established during brief periods when growing conditions are favorable.
    Evergreen ForestContains areas dominated by trees generally greater than 5m tall and greater than 20 percent of total vegetation cover. More than 75 percent of the tree species maintain their leaves all year. Canopy is never without green foliage.
    Palustrine Aquatic BedIncludes tidal and nontidal wetlands and deepwater habitats in which salinity due to ocean-derived salts is below 0.05 percent (0.5 ppt) and which are dominated by plants that grow and form a continuous cover principally on or at the surface of the water. These include algal mats, detached floating mats, and rooted vascular plant assemblages. Total vegetation cover is greater than 80 percent.
    Pasture/HayContains areas of grasses, legumes, or grass-legume mixtures planted for livestock grazing or the production of seed or hay crops, typically on a perennial cycle and not tilled. Pasture/hay vegetation accounts for greater than 20 percent of total vegetation.
    Hectare
    Total area of polygon in hectares. (Source: USGS)
    Range of values
    Minimum:4.39848810404e-10
    Maximum:871.369323.369082349
    Units:Hectares
    Shape_Leng
    Esri populated number corresponding to the perimeter measurement, in meters, calculated in NAD83. (Source: Esri)
    Range of values
    Minimum:0.0102931074126
    Maximum:122399.581013
    Units:meters
    Shape_Area
    Esri populated number corresponding to area, in square meters, calculated in NAD83. (Source: Esri)
    Range of values
    Minimum:4.39848810404e-06
    Maximum:3233690.82349
    Units:square meters
    Entity_and_Attribute_Overview:
    This dataset contains managed tidal wetlands along the Delaware, New Jersey, and Pennsylvania regions of Delaware Bay. The landscape has been divided into individual polygons at tidal elevations and their corresponding NWI (where applicable), and C-CAP attributes are included. The size of these polygons may be smaller than our 1 acre threshold, as defined in the process, due to the splitting that occurred during the IDENTITY step.
    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)
    • Sydney K. Nick
    • Zafer Defne
    • Kevin Kroeger
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    Sydney K. Nick
    U.S. Geological Survey, Northeast Region
    Interdisciplinary Geographer/Geologist
    384 Woods Hole Road
    Woods Hole, MA
    US

    508-548-8700x2343 (voice)
    508-457-2310 (FAX)
    snick@usgs.gov

Why was the data set created?

The purpose of this dataset is to identify and calculate the area of various land cover categories that are at tidal elevations but are not mapped as tidal wetlands by NWI, estuarine by 2016 C-CAP land cover, or mapped as modified wetlands by NWI. This dataset provides important information about interpreted managed tidal wetland areas for federal, state, and local managers to assess restoration potential, barriers within migration corridors, greenhouse gas accounting, and sea level rise planning.

How was the data set created?

  1. From what previous works were the data drawn?
    USGS CoNED (source 1 of 4)
    Danielson, J., and Tyler, D., 20160501, Topobathymetric Model for Chesapeake Bay Region - Delaware and New Jersey 1859 to 2015: U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Region based Coastal National Elevation Database (CoNED) data were downloaded for the area of interest in October 2022. CoNED is a 1m resolution topobathymetric dataset for the coastal region. CoNED uses a variety of data sources to create this seamless elevation data, including LiDAR. Data were downloaded as Chesapeake Bay NJ_DE_Topobathy, NAD 1983 UTM Zone 18N with the North American Datum of 1988 (NAVD88). Download date was 01/29/2020.
    Type_of_Source_Media: Digital
    Source_Contribution: Elevation dataset
    NWI (source 2 of 4)
    U.S. Fish and Wildlife Service, 20210412, National Wetland Inventory: U.S. Fish and Wildlife Service, Madison, WI.

    Online Links:

    Other_Citation_Details:
    Downloaded wetlands data for Delaware, New Jersey, and Pennsylvania in shapefile format from the NWI download page. Projection was NAD 1983 Albers. Download date was 04/12/2021.
    Type_of_Source_Media: Digital
    Source_Contribution: Wetlands dataset
    NOAA HAT (source 3 of 4)
    National Oceanographic and Atmospheric Administration, 20220329, NOAA Tides and Currents Highest Astronomical Tide referenced to NAVD88, derived from NOAA Tides And Currents, 1983-2001 epoch.

    Online Links:

    Other_Citation_Details:
    R Studio (Version 2022.07.7+576) was used to pull metadata records for each station on 03/29/2022.
    Type_of_Source_Media: Digital
    Source_Contribution: Tidal datums
    CCAP (source 4 of 4)
    National Oceanographic and Atmospheric Administration, 20200301, 2016 Coastal Change Analysis Program Land Cover.

    Online Links:

    Other_Citation_Details: Downloaded 6/14/2021
    Type_of_Source_Media: Digital
    Source_Contribution: Land cover
  2. How were the data generated, processed, and modified?
    Date: 2022 (process 1 of 7)
    This process step and all subsequent process steps were performed by the same person, Sydney Nick, in ArcGIS Pro (ver. 3.0.2), 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 specified in the step. The input and output file names are provided in [square brackets] when necessary. All steps were performed with the map projection set to NAD_1983_Albers and inputs and outputs were stored as feature classes within a file geodatabase unless otherwise noted.
    This process step creates a spatial domain, converts Highest Astronomical Tide (HAT) data to NAVD88, interpolates a surface, and prepares CoNED elevation data.
    1. Create an area of interest polygon [aoi] that encompasses the Delaware Bay region that can be used to eliminate excess data. 2. Create a HAT surface: a) Download NOAA tide gauge data for gauges with both NAVD88 and HAT tidal datums. Identify the tidal gauges that have both NAVD88 and HAT values that encompass the entirety of the Delaware Bay region.
    b) Subtract the NAVD88 value from the HAT value for the 31 gauges within our Delaware Bay spatial domain ([aoi]).
    c) PROJECT tide gauge xy coordinates to NAD_1983_Albers [de_bay_tides.shp].
    d) Using the GEOSTATISTICAL WIZARD KRIGING tool and [de_bay_tides.shp], perform a simple kriging prediction, normal score transformation, covariance variogram, and set anisotropy as enabled. Use the defaults for all other variables. EXPORT resulting surface at a 5m resolution and NAD83 spatial reference [HAT_surface].
    3. Create an elevation dataset: a) Use PROJECT RASTER to project the CoNED raster to NAD_1983_Albers [njde_proj].
    b) RESAMPLE [njde_proj] to a 5m resolution using nearest neighbor resampling techniques [njde_5m]. The HAT surface was used as a snap raster to eliminate any cell misalignment during overlay. Person who carried out this activity:
    Sydney K Nick
    U.S. Geological Survey, Northeast Region
    Interdisciplinary Geographer/Geologist
    384 Woods Hole Road
    Woods Hole, MA
    US

    508-548-8700x2343 (voice)
    508-457-2310 (FAX)
    snick@usgs.gov
    Data sources used in this process:
    • NOAA HAT
    • USGS CoNED
    Data sources produced in this process:
    • njde_5m
    • aoi
    • HAT_surface
    Date: 2022 (process 2 of 7)
    This process step creates the Coastal Change Analysis Program (C-CAP) raster and polygon and National Wetlands Inventory (NWI) feature classes within the spatial domain.
    a) Use PROJECT RASTER to project the C-CAP raster to NAD_1983_Albers, using the HAT surface raster as a snap raster in the environment settings to produce [ccap_snap].
    b) Eliminate excess data beyond our spatial domain using EXTRACT BY MASK (input raster: ccap_snap; input raster or feature mask data: [aoi]; extraction area: Inside) to create [ccap_aoi].
    c) Create a polygon feature class of estuarine wetland areas as defined by C-CAP ([ccap_est_poly]) by using EXTRACT BY ATTRIBUTES (input raster: [ccap_aoi]; VALUE = 16 (estuarine forested wetland) OR VALUE = 17 (estuarine scrub shrub wetland) OR VALUE=18 (estuarine emergent wetland)) and perform RASTER TO POLYGON on the output.
    d) Convert C-CAP raster [ccap_aoi] to vector using RASTER TO POLYGON (input raster: [ccap_aoi]; field: Value; output polygon features: [ccap_poly], simplify polygons: FALSE, create multipart features: FALSE) to create a feature class of all C-CAP areas [ccap_poly].
    e) CLIP NWI polygons to aoi [nwi].
    f) Create an additional field in the [nwi] attribute table with the name "ATTRIBUTE_original" by using the CALCULATE FIELD (input table: [nwi]; field name: ATTRIBUTE_orginal; expression type: Python 3; Expression: ATTRIBUTE_original = !WETLAND_TYPE!).
    g) Because oligohaline in inconsistently used throughout the dataset, remove the oligohaline modifier by using CALCULATE FIELD (input table: [nwi]; field name: ATTRIBUTE_new; expression type: Python 3; Expression: NWI_TYPE=replace(!ATTRIBUTE!). code block: import re def replace(val): return re.sub ('6', '', val). This provides the user with the original NWI attribute if oligohaline modifier is desired.
    h) Create a feature class of the salt marshes as defined by NWI. SELECT BY ATTRIBUTE (ATTRIBUTE LIKE "E2EM%") from [nwi] EXPORT features [saltmarsh]).
    I) This step creates a polygonal feature class containing estuarine, marine, and fresh tidal, excluding those polygons with modifiers indicating they have been or are managed. To create [nwi_tidal] use the following sequence of three SQL statements on [nwi]: Create new selection: WETLAND_TYPE = 'Estuarine and Marine Deepwater' OR WETLAND_TYPE = 'Estuarine and Marine Wetland'; add to current selection: (ATTRIBUTE LIKE '%L%' AND ATTRIBUTE NOT LIKE 'L%' AND ATTRIBUTE NOT LIKE '%ML%') OR (ATTRIBUTE LIKE '%M%' AND ATTRIBUTE NOT LIKE '%EM%') OR ATTRIBUTE LIKE '%N%' OR (ATTRIBUTE LIKE '%P%' AND ATTRIBUTE NOT LIKE 'P%') OR ATTRIBUTE LIKE '%Q%' OR (ATTRIBUTE LIKE '%R%' AND ATTRIBUTE NOT LIKE '%RB%' AND ATTRIBUTE NOT LIKE '%RS%' AND ATTRIBUTE NOT LIKE 'R%') OR (ATTRIBUTE LIKE '%S%' AND ATTRIBUTE NOT LIKE '%SS%' AND ATTRIBUTE NOT LIKE '%US%' AND ATTRIBUTE NOT LIKE '%SB%') OR ATTRIBUTE LIKE '%T%' OR ATTRIBUTE LIKE '%V%'; remove from current selection: ATTRIBUTE LIKE '%b%' OR ATTRIBUTE LIKE '%d%' OR ATTRIBUTE LIKE '%f%' OR ATTRIBUTE LIKE '%h%' OR ATTRIBUTE LIKE '%m%' OR ATTRIBUTE LIKE '%r' OR ATTRIBUTE LIKE '%s%' OR ATTRIBUTE LIKE '%x%' EXPORT FEATURES. Data sources used in this process:
    • NWI
    • CCAP
    • aoi
    Data sources produced in this process:
    • ccap_snap
    • ccap_aoi
    • ccap_est_poly
    • ccap_poly
    • nwi
    • saltmarsh
    • nwi_tidal
    Date: 2022 (process 3 of 7)
    This process step, and the next two process steps, create a vegetation adjusted raster from [njde_5m]. This adjustment is to account for documented lidar inaccuracies in densely vegetated marshes, resulting in higher than ground elevations.
    a) RASTER CALCULATOR with the expression: Con("njde_5m" <= "HAT_surface",1) to create [con1].
    b) RASTER TO POLYGON (input raster: [con1]; field: Value, output polygon features: [con2]; simplify polygons: FALSE; create multipart features: FALSE).
    c) PAIRWISE ERASE (input features: [saltmarsh]; erase features: [con2]; output features: [misses]).
    d) POLYGON TO RASTER (input features: [misses]; value field: OBJECTID; output raster dataset: [missras]; cell assignment type: cell center; priority field: NONE; cell size: [HAT_surface]; environment snap raster: [HAT_surface]. i) RASTER TO POINT [missras]. ii) EXTRACT MULTI VALUES TO POINTS (fieldmap follows this format input raster: output field name. [HAT_surface]: hat; njde_5m: coned).
    g) SELECT LAYER BY ATTRIBUTE "coned IS NOT NULL" and export table to csv using TABLE TO TABLE [misspts.csv]. Data sources used in this process:
    • njde_5m
    • HAT_surface
    • saltmarsh
    Data sources produced in this process:
    • misspts.csv
    Date: 2022 (process 4 of 7)
    This process step uses R Studio (Version 2022.07.7+576) to identify the 75th percentile value between the CoNED elevation and HAT surface.
    a) Read [misspts.csv] into the RStudio environment with the read.csv function.
    b) Add a column and calculate the difference between CoNED and HAT using the syntax coned-hat.
    c) Calculate the 0.75 quantile of the differences between CoNED and HAT and use the resulting number in the following process step. For this data product, the adjustment factor was 0.25m. Data sources used in this process:
    • misspts.csv
    Data sources produced in this process:
    • 0.25 CoNED adjustment factor
    Date: 2022 (process 5 of 7)
    This process step uses the 75th quantile calculated in the previous step to adjust the CoNED elevation dataset in areas where NWI and C-CAP have mapped estuarine emergent wetlands.
    a) POLYGON TO RASTER [saltmarsh] using [HAT_surface] as both cell size and snap raster [sm_ras].
    b) EXTRACT BY ATTRIBUTES [ccap_aoi] with the query statement: "where VALUE is equal to 18" to create [ccap_est].
    c) MOSAIC TO NEW RASTER [ccap_est] and [sm_ras] to create [area2corr].
    d) TIMES [area2corr] with a constant value of 0 to create [area2corr_0].
    e) Add the vegetation adjustment factor (0.25 as the constant value) to [area2corr_0] using the PLUS tool and specifying in the processing environments both cell size and snap raster are set to [HAT_surface] to create [area2corr_25].
    f) Using MINUS, subtract [area2corr_25] from [njde_5m] to create [correction].
    g) Create the vegetation adjusted CoNED raster [coned_corr] by using MOSAIC TO NEW RASTER and listing the input rasters in the following order: [njde_5m], [correction] with the following parameters: spatial reference: [njde_5m]; pixel type: 32 bit float; number of bands: 1; mosaic operator: last. Data sources used in this process:
    • saltmarsh
    • HAT_surface
    • ccap_aoi
    • ccap_est_poly
    Data sources produced in this process:
    • coned_corr
    Date: 2023 (process 6 of 7)
    This process step uses the vegetation corrected CoNED [coned_corr] to create the tidal domain from which to identify managed tidal wetlands.
    a) Use RASTER CALCULATOR to create the tidal domain raster [Tidal], which will only include areas with elevations that are at or below the interpolated HAT surface. To do so, use the map algebra expression: Con( "coned_corr"<= "HAT_surface", "coned_corr"). This will result in a vegetation adjusted CoNED raster only in the areas that meet the expression criteria (elevation values maintained within the identified tidal domain, which can be used for further analyses).
    b) Use RASTER CALCULATOR to create the tidal domain raster [Tidal_simple] with the map algebra expression: Con( "coned_corr"<= "HAT_surface", 1). This will result in a simplified, binary 1/NoData raster of areas that have elevations at or below the interpolated HAT surface.
    c) Vectorize the tidal domain [Tidal_simple] using RASTER TO POLYGON (simplify features: FALSE; create multipart features: FALSE; [tidal_poly]. Data sources used in this process:
    • coned_corr
    • HAT_surface
    Data sources produced in this process:
    • tidal_poly
    Date: 2023 (process 7 of 7)
    This step uses the tidal domain [tidal_poly], [nwi_tidal], and [ccap_est_poly] to identify areas at tidal wetland elevations that are either mapped as non-tidal or managed tidal wetlands and assigns them both NWI (as ATTRIBUTE in the attribute table) and C-CAP attributes (as gridcode).
    a) ERASE (input features: [tidal_poly]; erase features: [nwi_tidal]) to create [tidal_nwi_erase].
    b) ERASE (input features: [tidal_nwi_erase]; erase features: [ccap_est_poly]) to create [mod].
    c) MULTIPART TO SINGLEPART [mod] to create [mod_single], Eliminate features smaller than our 1acre minimum size requirement by using SELECT BY ATTRIBUTE Shape_Area greater than or equal to 4046.8 (1 acre), EXPORT FEATURES to create [mod_sizemin].
    d) Using [mod_sizemin] as the input, [nwi] as the identity features, run IDENTITY to create [modnwi]
    e) SELECT BY ATTRIBUTE from [modnwi] ATTRIBUTE LIKE '%E1UBLx%' And Shape_Area > 500000 to eliminate the large human-made canals..
    f) Using [modnwi] as the input and [ccap_poly] as the identity features, run IDENTITY a second time to create [mod_wetlands]. The column named gridcode corresponds to C-CAP classifications.
    g) An additional field was created to maintain the original NWI WETLAND_TYPE field for users who may wish to use it in further analyses. This new field can be used for examining NWI wetland type versus areas not mapped by NWI and can used to provide C-CAP categories in subsequent steps via a table join from a csv of C-CAP labels. CALCULATE FIELD (input table: [mod_wetlands]; field name: NWI_TYPE; expression type: Python 3; Expression: NWI_TYPE=typ(!WETLAND_TYPE!). code block: def typ(p1): if len(p1)<2: return("Undesignated Potential Wetland") else: return(p1)
    h) Create and calculate geometry for fields acres and hectares.
    i)Project [mod_wetlands] to WGS84 using the WGS_1984_(ITRF00)_To_NAD_1983 geographic transformation.
    j) Keep only the following fields: FID, Shape, Orig_FID acres, ATTRIBUTE, WETLAND_TYPE, NWI_TYPE, gridcode_1, CCAP_Category, Hectares, Shape_Length, Shape_Area, before exporting to a shapefile [managed_wetlands]. Note that the fields will be shortened to the following when exported to a shapefile: FID, Shape, ORIG_FID_Acres, ATTRIBUTE, WETLAND_TY, ATTRIBUTE_, NWI_TYPE, gridcode_1, Hectare, Shape_Leng, Shape_Area. Data sources used in this process:
    • tidal_poly
    • nwi_tidal
    • ccap_est_poly
    • nwi
    • ccap_poly
    Data sources produced in this process:
    • managed_wetlands
  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?
    C-CAP land cover categories have stated accuracy of 85% overall and 80% per class. NWI polygons do not have stated accuracy. Managed tidal wetland polygon and attribute accuracy is based on 30m resolution C-CAP and NWI attributes.
  2. How accurate are the geographic locations?
    Horizontal accuracy is based on the input data and therefore is assumed to be +/- 30m, the most coarse of the input datasets.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    The managed coastal wetland polygonal dataset covers Delaware, Delaware Inland Bays, the Delaware Bay area of New Jersey, and the Delaware River areas of Pennsylvania and New Jersey as far north as Trenton, NJ.
    Sliver polygons of open salt water along the land/water boundary may also be included in some instances as a result of geoprocessing. Additionally, there are areas within polygons that have holes of varying sizes, and this is due to those areas being above HAT elevation or classified as estuarine or tidal wetland.
    Errors within the NWI data were retained (e.g., Project R05Y10P05).
    Topological errors in NWI polygons (overlaps) were retained but were negligible in calculations.
    Small area (less than 1 acre) polygons were created as a result of overlaying NWI and C-CAP attributes, therefore polygons smaller than the 4046.8m2 (1 acre) minimum size precision limitation stated the logical consistency report are in the final dataset.
    C-CAP is a raster with 30m resolution and therefore there may be some misclassified areas if the cell center coincided with an the edge of a land cover class in the source imagery used during creation. Additionally, the cell shape (30mx 30m square) was retained when converted to a vector and may not be coincident with NWI shape edges.
    The 1m resolution elevation dataset was resampled to a 5m resolution, using nearest neighbor resampling and therefore may be different than field measurements.
    All raster outputs were snapped to the interpolated surface raster and have no misalignment in the data that weren't inherent to the source data.
  5. How consistent are the relationships among the observations, including topology?
    There were topological errors (overlaps) in NWI polygons that accounted for a total area less than 1 acre and were therefore not corrected for this analysis and the data were used 'as is'. Small polygons (less than 1 acre) were removed from the managed coastal wetland vector dataset before assigning NWI and C-CAP attributes, however, once NWI and C-CAP values were assigned, smaller polygons were created and are in the final dataset. In the area of Supawna Meadows National Wildlife Refuge and Abbotts Meadows Wildlife Management Area (NWI project R05Y10P05), there are mapping errors in NWI that were not corrected for this dataset. Those areas should be noted and not used in further analyses.
    A visual comparison of polygons and Esri world imagery was performed at randomly selected sites to check for consistency. Polygons that were clearly misidentified due to resolution or alignment errors between NWI and C-CAP were manually removed, although some misidentified polygons may remain in the dataset.

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 The managed tidal wetland areas and associated land cover categories are 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
    USA

    1-888-275-8747 (voice)
    sciencebase@usgs.gov
  2. What's the catalog number I need to order this data set? managed_wetlands.zip (ZIP file contains a zip file for the shapefile managed_wetlands.shp and the additional shapefile components), the browse graphic, and FGDC CSDGM metadata in xml format.
  3. What legal disclaimers am I supposed to read?
    Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty.
  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 10-Jul-2023
Metadata author:
Sydney K. Nick
U.S. Geological Survey, Northeast Region
Interdisciplinary Geographer/Geologist
384 Woods Hole Road
Woods Hole, MA
US

508-548-8700x2343 (voice)
508-457-2310 (FAX)
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 the USGS.
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_P9VCYH3X/managed_wetlands.faq.html>
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