Unvegetated to vegetated ratio of marsh units in Connecticut salt marshes

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Frequently anticipated questions:


What does this data set describe?

Title:
Unvegetated to vegetated ratio of marsh units in 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, Unvegetated to vegetated ratio of marsh units in 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/64c40901d34e70357a33d426/?name=UVVR_CT_Browse.png&allowOpen=true (PNG)
    Graphic that shows UVVR of conceptual marsh units in 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 (2499)
    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?
    mu_UVVR_CT.shp
    Table containing attribute information associated with the dataset. (Source: USGS)
    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. (Source: USGS)
    Range of values
    Minimum:0
    Maximum:2498
    ATOT_M2
    Total surface area of a marsh unit. (Source: USGS)
    Range of values
    Minimum:164.768733548
    Maximum:511079.277486
    Units:square meters
    AVEG_M2
    Surface area of the vegetated part of a marsh unit. (Source: USGS)
    Range of values
    Minimum:0.0
    Maximum:476006.471534
    Units:square meters
    UVVR
    Ratio of unvegetated surface area to vegetated surface area. Ordinarily, UVVR ranges from zero (completely vegetated) to infinity (completely unvegetated). However, it is assigned the value of -1 when completely unvegetated. (Source: USGS)
    Range of values
    Minimum:-1.0
    Maximum:534.580367571
    Units:none
    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
    Units:none
    Entity_and_Attribute_Overview:
    In this dataset, the salt marshes across Connecticut have been delineated to conceptual salt marsh units to facilitate unit by unit evaluation of response and resiliency of the marsh system to physical and biogeochemical drivers. Each unit is also analyzed based on the vegetated and unvegetated surface area coverage, the ratio of which can be an independent measure of marsh health for salt marshes on the Atlantic and Pacific coasts of the United States. UVVR is calculated as the ratio of unvegetated area to vegetated area in a marsh unit. 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 and UVVR is assumed to be 1 meter and 0.001, respectively.
    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 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

Why was the data set created?

The purpose of this shapefile is to calculate the ratio of unvegetated area to vegetated area in each marsh unit. Analysis of the unvegetated to vegetated marsh ratio (UVVR) is part of a comprehensive assessment to identify the factors and their weights in determining the vulnerability and resiliency of salt marshes. UVVR is defined as a potential indicator of the current state of a salt marsh unit. UVVR is calculated based on U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) 0.6-meter resolution imagery.

How was the data set created?

  1. From what previous works were the data drawn?
    CT DEM (source 1 of 4)
    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 4)
    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 4)
    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
    CMU_CT (source 4 of 4)
    Ackerman, K.V., Defne, Z., and Ganju, N.K., 2023, Conceptual marsh units of Connecticut salt marshes in Geospatial characterization of salt marshes in Connecticut: data release DOI:10.5066/P96QND48, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    This dataset (Conceptual marsh units of Connecticut salt marshes) is within the larger data release (Geospatial characterization of salt marshes in Connecticut). The first link below is to the conceptual marsh units data and the second link is to the data release.
    Type_of_Source_Media: Digital
    Source_Contribution:
    Used conceptual marsh units, generated as part of this data release, to delineate marsh unit boundaries.
  2. How were the data generated, processed, and modified?
    Date: 2022 (process 1 of 3)
    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) Establish marsh unit boundaries. Dissolve the vegetated and unvegetated classes in each marsh unit to have only one class for each marsh unit. DISSOLVE (Input features=[CMU_CT.shp]; Dissolve field=FID_CMU; Statistics field=ATOT_M2 and FLG with Statistics type= First). PROJECT (Input coordinate system=WGS 1984 Web Mercator Auxiliary Sphere; Output coordinate system=NAD 1983 UTM Zone 18N (2011)) the feature dataset to obtain dissolved marsh units [mu_diss.shp].
    c) 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).
    d) Create a polygon that covers the area of interest [extent.shp]. CLIP the mosaicked elevation dataset created in step (c) 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
    • mu_diss.shp
    Date: 2022 (process 2 of 3)
    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: 2023 (process 3 of 3)
    Compute 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 [mu_diss.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 [mu_diss.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.
    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.
    h) 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.
    i) DISSOLVE (Input features=[UVV_poly_diss.shp]; Dissolve fields=FID_CMU; Statistics field=UVVR, ATOT_M2 and FLG with Statistics type= First for all) to obtain [mu_UVVR_CT.shp].
    j) SELECT BY ATTRIBUTES FROM [CMU_CT.shp] where "TYP"= 'vegetated,' and join field "APGN_M2" from [CMU_CT.shp] to [mu_UVVR_CT.shp] and rename this field "AVEG_M2."
    k) 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.
    l) 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 UVVR for each marsh unit [mu_UVVR_CT.shp]. Data sources used in this process:
    • elev_mosaic.tif
    • NAIP
    Data sources produced in this process:
    • mu_UVVR_CT.shp
  3. What similar or related data should the user be aware of?
    Ganju, N.K., Defne, Z., and Fagherazzi, S., 2020, Are elevation and open-water conversion of salt marshes connected?: Geophysical Research Letters v. 47, issue 3.

    Online Links:

    Other_Citation_Details:
    For more information about the UVVR, please see this publication.
    Defne, Z., Aretxabaleta, A.L., Ganju, N.K., Kalra, T.S., Jones, D.K., and Smith, K.E.L., 2020, A geospatially resolved wetland vulnerability index: Synthesis of physical drivers: PLoS ONE 15 (1).

    Online Links:

    Other_Citation_Details:
    For more information about the UVVR, please see this publication.

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 for the polygon boundaries is inherited from the source layer, the conceptual marsh units, and is considered to be +/- 6 meters.
  3. How accurate are the heights or depths?
  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 The unvegetated to vegetated ratio for each marsh unit is 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? mu_UVVR_CT.zip (ZIP file contains the shapefile mu_UVVR_CT.shp and the additional shapefile components), a browse graphic (UVVR_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)

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