Conceptual marsh units of Connecticut salt marshes

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Frequently anticipated questions:

What does this data set describe?

Title: Conceptual marsh units of Connecticut salt marshes
Abstract:
This data release contains coastal wetland synthesis products for the state of Connecticut. Metrics for resiliency, including the unvegetated to vegetated ratio (UVVR), marsh elevation, tidal range, wave power, and exposure potential to environmental health stressors 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. This project has been funded in part by the United States Environmental Protection Agency under assistance agreement DW-014-92531201-1 to N. Ganju.
  1. How might this data set be cited?
    Ackerman, Kate V., Defne, Zafer, and Ganju, Neil K., 20231023, Conceptual marsh units of Connecticut salt marshes: data release DOI:10.5066/P96QND48, 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., 2023, Geospatial characterization of salt marshes in Connecticut: data release DOI:10.5066/P96QND48, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Ackerman, K.V., Defne, Z., and Ganju, N.K., 2023, Geospatial characterization of salt marshes in Connecticut: U.S. Geological Survey data release, https://doi.org/10.5066/P96QND48.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -73.658477
    East_Bounding_Coordinate: -71.831904
    North_Bounding_Coordinate: 41.532199
    South_Bounding_Coordinate: 40.983874
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/64c40893d34e70357a33d41f/?name=CMU_CT_Browse.png&allowOpen=true (PNG)
    Graphic that shows the conceptual marsh units of Connecticut salt marshes.
  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 (4878)
    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_CT
    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) Feature geometry. Marsh units are polygon features.
    FID_CMU
    Unique whole numbers used to identify each conceptual marsh unit. These numbers are duplicated when a marsh unit has both vegetated and unvegetated sub-polygons. (Source: USGS)
    Range of values
    Minimum:0
    Maximum:2498
    Units:none
    APGN_M2
    Surface area of the selected polygon type (vegetated or unvegetated). (Source: USGS)
    Range of values
    Minimum:0.303985744294
    Maximum:476006.471534
    Units:square meters
    ATOT_M2
    Total surface area of a marsh unit. (Source: USGS)
    Range of values
    Minimum:164.768733548
    Maximum:511079.277486
    Units:square meters
    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 square meters; (-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 square meters. (Source: USGS)
    Range of values
    Minimum:-11200
    Maximum:0
    Entity_and_Attribute_Overview:
    In this dataset, the salt marsh complexes across Connecticut 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 Connecticut 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?
    CT DEM (source 1 of 3)
    Capitol Region Council of Governments, 2017, Connecticut Statewide Lidar 2016: State of Connecticut, Connecticut.

    Online Links:

    Other_Citation_Details:
    Downloaded 1-meter 2016 Lidar DEM. Projection was NAD 1983 UTM Zone 18N with the North American Vertical Datum of 1988 (NAVD88). Download date was 07/30/2021.
    Type_of_Source_Media: Digital
    Source_Contribution: Elevation dataset
    NAIP (source 2 of 3)
    U.S. Department of Agriculture, 2018, NAIP Digital Ortho Photo Image: USDA-FSA-APFO Aerial Photography Field Office, Salt Lake City, Utah.

    Online Links:

    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 01/29/2021.
    Type_of_Source_Media: Digital
    Source_Contribution: Aerial imagery dataset
    NWI (source 3 of 3)
    U.S. Fish and Wildlife Service, 20210501, National Wetland Inventory: U.S. Fish and Wildlife Service, Madison, WI.

    Online Links:

    Other_Citation_Details:
    Downloaded wetlands data for Connecticut in shapefile format from the NWI download page. Projection was NAD 1983 Albers. Download date was 10/05/2021.
    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. 2.8.8), 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 unless otherwise stated.
    a) Set the data frame coordinate system and projection to NAD 1983 UTM Zone 18N (2011).
    b) Prepare elevation dataset. Combine all downloaded tiles into one raster, using MOSAIC TO NEW RASTER, and PROJECT RASTER to NAD 1983 UTM Zone 18N (2011).
    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:
    • CT 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. From the NWI dataset of all wetlands for the area (referred to as [NWI_entire.shp]), select estuarine intertidal areas of 1) emergent wetland, 2) scrub-shrub area, 3) rooted vascular aquatic bed, and 4) organic unconsolidated shore classes (SELECT (ATTRIBUTE LIKE 'E2%EM%' OR ATTRIBUTE LIKE 'E2AB3%' OR ATTRIBUTE LIKE 'E2EM%' OR ATTRIBUTE LIKE 'E2SS%' OR ATTRIBUTE LIKE 'E2US4%'). EXPORT features (in the same coordinate system as the data frame) to create [NWI_exclusive_select.shp]. In some areas, erroneous line features were eliminated or modified to allow the salt marsh extent to be consistent with imagery.
    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) Create a shapefile of features that are not estuarine or are forested estuarine (SELECT (ATTRIBUTE NOT LIKE 'E%' OR ATTRIBUTE LIKE '%FO')) from the NWI dataset. EXPORT features to create [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 create the final mask shapefiles ([MU_mask.shp] and [UVVR_mask.shp]), areas that should not be included are removed (e.g., forest areas), and areas that should be included are incorporated (estuarine and marine wetland systems that are completely surrounded by salt marsh (e.g., interior ponds)):
    e)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.
    f) 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).
    g) 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].
    h) 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]).
    i) 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].
    j) 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]).
    k) 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 square meters) to the nearest "parent marsh units" (units that are larger than 5000 square meters) 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 square meters [inputfeatures.shp].
    b) Create parent marsh unit features by exporting marsh units with an area greater than or equal to 5000 square meters [nearfeatures.shp].
    c) Run Python script (hydUnitloop.py). At each iteration step, the script uses the 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. 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 square meters, 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 square meters 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].
    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.
    b) EXTRACT BY MASK from the elevation raster [elev_mosaic.tif] and the NAIP 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 500 cells. 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 DISSOLV (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.
    g) Visually inspect and manually remove marsh units that are fully forested due to polygon artifacts that are a result of buffering. Remove marsh units that are linear features (edges parallel to each other) and unattached to other marsh units (i.e., islands), as these are artifacts of the NWI dataset. Data sources used in this process:
    • NAIP
    • 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 square meters; (-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 square meters.
    c) Rearrange fields 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_CT]. Data sources used in this process:
    • UVV_poly_diss.shp
    Data sources produced in this process:
    • CMU_CT.shp
  3. What similar or related data should the user be aware of?

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

  1. How well have the observations been checked?
    Marsh units and water and land boundaries inherit their accuracy from the 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 (2016 CT Lidar DEM). Accuracy of the vegetated and unvegetated polygons is based on the National Agriculture Imagery Program (NAIP) products from 2018 (0.6-meter resolution). Any vegetated or unvegetated polygons less than 9 square meters 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 square meters 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 model (2016 CT Lidar DEM). Vegetated and unvegetated polygons were based on the 0.6-meter resolution NAIP imagery. Although the analyses were performed at 1-meter resolution, the horizontal accuracy is superseded by NAIP imagery accuracy which is +/-6 meters.
  3. How accurate are the heights or depths?
    Because the elevation values are averaged over delineated polygons, vertical accuracy depends on both the horizontal accuracy of the NWI dataset and the vertical accuracy of the source elevation dataset (1-meter 2016 CT Lidar DEM). The vertical accuracy is inherited from the source elevation dataset; it is reported to be 0.06 meters. 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 Connecticut's 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. 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 2172, 2402). In a few areas, there are no marsh units where there is visible marsh plain (e.g., northwest of marsh unit 1682), because the areas are classified in the NWI as estuarine intertidal unconsolidated shore, which is not included in our salt marsh boundaries. In a few locations, there may be areas that that are classified as unvegetated but are in fact very sparsely vegetated. A detailed on-the-ground analysis of a single site may result in a different interpretation of the wetland and marsh unit boundaries than those established through this analysis.
  5. How consistent are the relationships among the observations, including topology?
    Topological errors that occurred during geoprocessing were automatically removed by the topological rules used for the analysis. The polygons were checked for correct geometry and do not overlap. Small polygons (less than 9 square meters) were assumed to be marginal and were assigned the classification from the surrounding majority value.

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_CT.zip (ZIP file contains the shapefile CMU_CT.shp and the additional shapefile components), browse graphic (CMU_CT_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. The contents of this document do not necessarily reflect the views and policies of the Environmental Protection Agency. Not for navigational use.
  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 23-Oct-2023
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)
whsc_data_contact@usgs.gov
Contact_Instructions:
The metadata contact email address is a generic address in the event the person is no longer with USGS.
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/whcmsc/SB_data_release/DR_P96QND48/CMU_CT.faq.html>
Generated by mp version 2.9.51 on Mon Oct 23 17:02:49 2023