SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Parramore Island, VA, 2014

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Metadata:

Identification_Information:
Citation:
Citation_Information:
Originator: Sara L. Zeigler
Originator: Emily J. Sturdivant
Originator: Benjamin T. Gutierrez
Publication_Date: 20191220
Title:
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Parramore Island, VA, 2014
Edition: 1.0
Geospatial_Data_Presentation_Form: raster digital dataset
Series_Information:
Series_Name: data release
Issue_Identification: DOI:10.5066/P9V7F6UX
Publication_Information:
Publication_Place: Woods Hole Coastal and Marine Science Center, Woods Hole, MA
Publisher:
U.S. Geological Survey, Coastal and Marine Hazards and Resources Program
Online_Linkage: https://doi.org/10.5066/P9V7F6UX
Online_Linkage: Larger_Work_Citation:
Citation_Information:
Originator: Emily J. Sturdivant
Originator: Sara L. Zeigler
Originator: Benjamin T. Gutierrez
Originator: Kathryn M. Weber
Publication_Date: 2019
Title:
Barrier island geomorphology and shorebird habitat metrics: Sixteen sites on the U.S. Atlantic Coast, 2013–2014
Edition: 1.0
Series_Information:
Series_Name: data release
Issue_Identification: DOI:10.5066/P9V7F6UX
Publication_Information:
Publication_Place: Reston, VA
Publisher: U.S. Geological Survey
Other_Citation_Details:
Suggested citation: Sturdivant, E.J., Zeigler, S.L., Gutierrez, B.T., and Weber, K.M., 2019, Barrier island geomorphology and shorebird habitat metrics—Sixteen sites on the U.S. Atlantic Coast, 2013–2014: U.S. Geological Survey data release, https://doi.org/10.5066/P9V7F6UX.
Online_Linkage: https://doi.org/10.5066/P9V7F6UX
Online_Linkage:
Description:
Abstract:
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.
Purpose:
These categorical raster files map 2014 substrate and vegetation characteristics in 5-m cells. The supervised classification raster (ParI14_SupClas.tif) depicts landcover attributes (for example, marsh, sand, water, herbaceous vegetation). It was created with a supervised classification of 2014 aerial imagery. Raster files ParI14_SubType.tif, ParI14_VegDen.tif, ParI14_VegType.tif were reclassified from the supervised classification raster with some manual modifications. ParI14_SubType.tif maps discrete substrate types; ParI14_VegDen.tif maps discrete categories of vegetation density; ParI14_VegType.tif maps discrete vegetation types. Raster file ParI14_GeoSet.tif maps discrete geomorphic settings (e.g. beach, dunes, washovers) and was digitized manually with reference to source datasets.
Information contained in these spatial datasets was used within a Bayesian network to model the probability that a specific set of landscape characteristics would be associated with piping plover habitat (Zeigler and others, 2019).
Supplemental_Information:
This metadata file describes five related datasets. For additional information on processing and use of this geospatial dataset, see the USGS Open-File report by Zeigler and others (2019).
Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 20140101
Ending_Date: 20140421
Currentness_Reference: Ground condition measured by source orthoimagery.
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -75.68469361
East_Bounding_Coordinate: -75.59655544
North_Bounding_Coordinate: 37.57821592
South_Bounding_Coordinate: 37.48224988
Keywords:
Theme:
Theme_Keyword_Thesaurus: USGS Metadata Identifier
Theme_Keyword: USGS:5daa37e9e4b09fd3b0c9cefb
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: Barrier Island
Theme_Keyword: USGS
Theme_Keyword: CMHRP
Theme_Keyword: Geographic Information Systems
Theme_Keyword: GIS
Theme_Keyword: U.S. Geological Survey
Theme_Keyword: Coastal and Marine Hazards and Resources Program
Theme_Keyword: Woods Hole Coastal and Marine Science Center
Theme_Keyword: St. Petersburg Coastal and Marine Science Center
Theme_Keyword: MHW
Theme_Keyword: Mean High Water
Theme_Keyword: Coastal Habitat
Theme_Keyword: Parramore Island
Theme_Keyword: Virginia Coast Reserve
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: oceans
Theme_Keyword: environment
Theme:
Theme_Keyword_Thesaurus: USGS Thesaurus
Theme_Keyword: geospatial datasets
Theme_Keyword: geospatial analysis
Theme_Keyword: image analysis
Theme_Keyword: scientific interpretation
Theme_Keyword: geomorphology
Theme_Keyword: coastal processes
Theme_Keyword: study areas
Theme_Keyword: geographic information systems
Theme_Keyword: erosion
Theme_Keyword: hazards
Theme_Keyword: sea-level change
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: Virginia
Place_Keyword: VA
Place_Keyword: Delmarva Peninsula
Place_Keyword: Parramore Island
Place_Keyword: North America
Place_Keyword: United States
Place_Keyword: USA
Place_Keyword: Atlantic Ocean
Place_Keyword: Virginia Coast Reserve
Access_Constraints: none
Use_Constraints:
Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. Please recognize the U.S. Geological Survey (USGS) as the source of this information.
Point_of_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey
Contact_Person: Sara L. Zeigler
Contact_Address:
Address_Type: mailing address
Address: 384 Woods Hole Road
City: Woods Hole
State_or_Province: MA
Postal_Code: 02543
Country: US
Contact_Voice_Telephone: 508-548-8700 x2290
Contact_Facsimile_Telephone: 508-457-2310
Contact_Electronic_Mail_Address: szeigler@usgs.gov
Browse_Graphic:
Browse_Graphic_File_Name: Browse_Graphic_File_Description:
Examples of substrate type, vegetation type, and vegetation density raster layers. These examples are for Rockaway Peninsula, NY and do not represent this dataset.
Browse_Graphic_File_Type: PNG
Cross_Reference:
Citation_Information:
Originator: Sara L. Zeigler
Originator: Emily J. Sturdivant
Originator: Benjamin T. Gutierrez
Publication_Date: 2019
Title:
Evaluating barrier island characteristics and piping plover (Charadrius melodus) habitat availability along the U.S. Atlantic coast—Geospatial approaches and methodology
Series_Information:
Series_Name: Open-File Report
Issue_Identification: 2019–1071
Publication_Information:
Publication_Place: Reston, VA
Publisher: U.S. Geological Survey
Other_Citation_Details:
Details the methods used to process these data for use in barrier island and piping plover habitat modeling.
Online_Linkage: https://doi.org/10.3133/ofr20191071
Cross_Reference:
Citation_Information:
Originator: Christopher Lea
Originator: Anthony C. Curtis
Publication_Date: 2010
Title:
Thematic accuracy assessment procedures: National Park Service vegetation inventory, version 2.0
Series_Information:
Series_Name: U.S. National Park Service report
Issue_Identification: Report NPS/2010/NRR-2010/204
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: U.S. National Park Service
Cross_Reference:
Citation_Information:
Originator: Klaus K.E. Neuendorf
Originator: James P. Mehl, Jr.
Originator: Julia A. Jackson
Publication_Date: 2011
Title: Glossary of geology. Fifth edition
Publication_Information:
Publication_Place: Alexandria, VA
Publisher: The American Geosciences Institute
Cross_Reference:
Citation_Information:
Originator: Emily J. Sturdivant
Originator: E. Robert Thieler
Originator: Sara L. Zeigler
Originator: Luke A. Winslow
Originator: Megan K. Hines
Originator: Jordan S. Read
Originator: Jordan I. Walker
Publication_Date: 2016
Title:
Biogeomorphic classification and images of shorebird nesting sites on the U.S. Atlantic coast
Series_Information:
Series_Name: data release
Issue_Identification: DOI: 10.5066/F70V89X3
Publication_Information:
Publication_Place: Reston, VA
Publisher: U.S. Geological Survey
Online_Linkage: https://doi.org/10.5066/F70V89X3
Cross_Reference:
Citation_Information:
Originator: Kara J. Doran
Originator: Joseph W. Long
Originator: Justin J Birchler
Originator: Owen T. Brenner
Originator: Matthew W. Hardy
Originator: Karen L. M. Morgan
Originator: Hilary F. Stockdon
Originator: Miguel L. Torres
Publication_Date: 2017
Title:
Lidar-derived Beach Morphology (Dune Crest, Dune Toe, and Shoreline) for U.S. Sandy Coastlines
Geospatial_Data_Presentation_Form: tabular digital data
Publication_Information:
Publication_Place: Reston, VA
Publisher: U.S. Geological Survey
Online_Linkage: https://doi.org/10.5066/F7GF0S0Z
Cross_Reference:
Citation_Information:
Originator: Paul J. Godfrey
Publication_Date: 1976
Title:
Comparative ecology of East Coast barrier islands—Hydrology, soil, vegetation, in Barrier islands and beaches
Series_Information:
Series_Name:
Technical proceedings of the 1976 Barrier Islands Workshop, Annapolis, Maryland, May 17–18, 1976
Issue_Identification: p. 5–31
Publication_Information:
Publication_Place: Washington, D.C.
Publisher: The Conservation Foundation
Cross_Reference:
Citation_Information:
Originator: U.S. Department of Agriculture (USDA)
Originator: USDA Natural Resources Conservation Service (NRCS)
Publication_Date: 2015
Title: The PLANTS Database (http://plants.usda.gov, 13 January 2014)
Publication_Information:
Publication_Place: Greensboro, NC
Publisher: National Plant Data Team
Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
The accuracies of the four derived thematic maps for geomorphic setting, substrate type, vegetation type, and vegetation density were assessed for 2014–2015 conditions at 15 study areas, including Parramore Island. These maps were derived in the same manner as those distributed here (derived for Parramore Island based on 2014 conditions). We assume that accuracy of maps of 2014–2015 conditions reflect the accuracy of our methods more generally, and accuracy values are therefore relevant for the files distributed here (ParI14_SubType.tif, ParI14_VegType.tif, ParI14_VegDen.tif, ParI14_GeoSet.tif).
Accuracy of the 2014–2015 derived raster layers at 15 study sites was assessed by comparing them against 482-501 ground validation points. The number of validation points used depended on the dataset examined. Validation points were subset from the iPlover dataset (Sturdivant and others, 2016). We followed the methodology recommended by the National Park Service (Lea and Curtis, 2010) to produce statistics for overall accuracy, chance agreement, and a kappa coefficient. Classifications were not altered when a difference between a ground validation point and the underlying raster cell was found.
For geomorphic setting (501 validation points), overall accuracy was 46% and chance agreement was 23%, resulting in a kappa coefficient of 0.30. For substrate type (490 validation points), overall accuracy was 96% and chance agreement was 51%, resulting in a kappa coefficient of 0.92. For vegetation type (482 validation points), overall accuracy was 93% and chance agreement was 46%, resulting in a kappa coefficient of 0.88. For vegetation density (490 validation points), overall accuracy was 85% and chance agreement was 39%, resulting in a kappa coefficient of 0.76. See Zeigler and others (2019) for more details on this validation exercise.
Logical_Consistency_Report:
These raster layers (ParI14_SubType.tif, ParI14_VegType.tif, ParI14_VegDen.tif) show discrete landcover classes and were produced based on a supervised classification of aerial imagery (ParI14_SupClas.tif). Geomorphic settings contained in ParI14_GeoSet.tif were hand-digitized with reference to the orthoimagery and DEM (see Source Information). An area is considered developed (in all applicable raster layers) if it includes human development or is completely surrounded by development (from ParI14_Development.shp). The data were reviewed using standard USGS review procedures. No checks for topological consistency in addition to those described in the Attribute Accuracy Report were performed on these data.
Completeness_Report:
This dataset is clipped to a custom boundary and may not include the entire spatial extent of the original source dataset. However, the custom boundary spans the entire coverage of the study area relevant to the broader research program (see Zeigler and others, 2019 for more details). The data are therefore considered complete for the information presented as described in the abstract section. Users are advised to read the rest of the metadata record carefully for additional details.
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
The assumed positional accuracy of these raster coverages is 5 m.
The horizontal accuracy of these layers inherits the accuracy of the source datasets. The orthoimage was used as a source dataset for all five layers. ParI14_GeoSet.tif was digitized from the source DEM, beach geomorphic feature positions (see larger work), and shoreline polygons (see larger work), in addition to aerial imagery.
The horizontal root-mean-square-error (RMSE) of the orthoimage was 0.53 m. Subsequent datum transformation (see source contribution information) may have added about 0.1 m of uncertainty.
During supervised classification, polygons were hand-digitized, combined and ultimately resampled from 0.35 m to 5 m resolution using a majority moving window. Some positional accuracy loss is expected in the final classified image as a result of changes in resolution size. In particular, we notice the omission of thin, linear features (for example, coastal walls and small roads that would have been classified as development).
ParI14_GeoSet.tif: Source elevation data were compiled to meet the 1.0 m RMSE horizontal accuracy specification. No projection transformations were required, because the source DEM was downloaded in NAD83 UTM Zone 18N.
The location of shoreline and dune points (Doran and others, 2017) was determined at 10-m intervals parallel to the shore. Accuracy estimates are included in the source dataset. We reprojected source shoreline and dune points using the ‘Project’ tool in ArcToolbox with the datum transformation "WGS_1984_(ITRF00)_To_NAD_1983" (WKID: 108190, accuracy: 0.1 m). Additional steps were taken as part of a semi-automated process to produce a full shoreline for the study area (see pari14_shoreline.shp in the larger work), which was used to delineate the boundaries of some geomorphic settings. In addition to the sources of error inherited from the source datasets, some geomorphic settings were manually digitized as polygons and then converted to raster format with 5x5 m resolution. The rasterization process tends to decrease the precision of the resulting data.
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator:
Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Geodetic Survey (NGS), Remote Sensing Division
Publication_Date: 20150501
Title:
2014 NOAA Ortho-rectified Mosaic of Hurricane Sandy Coastal Impact Area
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Silver Spring, MD
Publisher: NOAA's Ocean Service, National Geodetic Survey (NGS)
Online_Linkage: Online_Linkage: https://coast.noaa.gov/htdata/raster1/imagery/Sandy_2014_4885
Online_Linkage: https://coast.noaa.gov/dataviewer
Online_Linkage: https://inport.nmfs.noaa.gov/inport/item/48588
Type_of_Source_Media: digital data
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 20140101
Ending_Date: 20140421
Source_Currentness_Reference: ground condition
Source_Citation_Abbreviation: Orthoimage
Source_Contribution:
The orthoimage was used to classify the scene into landcover types. Source data were distributed at 0.35 m pixel resolution, in horizontal datum NAD83. Downloaded on 2/21/2017. Data were projected to UTM Zone 18N (EPSG:26918) using the ‘Project Raster’ tool in ArcToolbox (version 10.4.1).
Source_Information:
Source_Citation:
Citation_Information:
Originator:
Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Geodetic Survey (NGS), Remote Sensing Division
Originator:
Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management (OCM)
Publication_Date: 20151220
Title:
2014 NOAA Post-Sandy Topobathymetric LiDAR: Void DEMs South Carolina to New York
Geospatial_Data_Presentation_Form: map
Publication_Information:
Publication_Place: Silver Spring, MD
Publisher: NOAA's Ocean Service, National Geodetic Survey (NGS)
Online_Linkage: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=4967
Online_Linkage: Online_Linkage: https://coast.noaa.gov/dataviewer
Online_Linkage: https://inport.nmfs.noaa.gov/inport/item/48367
Type_of_Source_Media: digital data
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 201311
Ending_Date: 201406
Source_Currentness_Reference: ground condition
Source_Citation_Abbreviation: DEM
Source_Contribution:
Elevation data used for visual reference while digitizing dunes and geomorphic feature types. Source data were downloaded from https://coast.noaa.gov/dataviewer in horizontal datum NAD 1983 (2011), UTM Zone 18N, vertical datum NAVD88. Downloaded on 4/8/2016.
Process_Step:
Process_Description:
ParI14_SupClas.tif
Using the orthoimage, we conducted a supervised classification to delineate substrate and vegetation characteristics. Full methods are provided in the associated Methods OFR (Zeigler and others, 2019). For additional information and example figures, see Zeigler and others (2019). All steps were undertaken in ArcGIS and ArcToolbox version 10.4.1.
Because the signatures of some features closely resembled those of others (e.g., water and the reflection from buildings), we ran the classification in three stages and combined results into a single classification of landcover. We created sub-classifications for (1) bare sand and water, (2) marsh, and (3) vegetation and other features in the barrier’s interior.
To divide the landscape into these three sub-classifications, we hand-digitized masking polygons in ArcGIS. All digitization was performed with the orthoimage for reference. For the marsh classification, we hand-digitized polygons of marsh platforms. For vegetation and inland features, we hand-digitized a polygon that encompassed vegetation and the barrier’s interior by delineating the boundary of open sand and vegetation. Finally, we hand-digitized polygons to encompass areas of human development (ParI14_Development.shp in larger work). ‘Human development’ could include housing communities, commercial infrastructure, recreational facilities, major roads, and shoreline armoring (e.g., jetties). In sites without any human development, such as in the Virginia Coast Reserve, we omitted the development component of the following steps.
We then conducted the classification for marsh. We used the Classification toolbar to hand-digitize training polygons for the following classes: (1) Water; (2) Marsh, vegetation or unknown cover; (3) Marsh, unvegetated sediment; and (4) Marsh, shrub or forest. We ran the interactive supervised classification routine in the Classification toolbar and clipped the resulting classification image along the boundaries of the marsh mask. In the Image Analysis window, we masked out areas that overlapped with development polygons, if present. The resulting image matched the extent of the marsh polygons and contained cells at the original resolution of the orthoimage (0.35 m) with one of the four values represented by the training polygons.
Next, we created training polygons in the same manner that represented different types of vegetation in the inland portion of the barrier. Training samples represented the following classes: (1) Water; (2) Sand; (3) Herbaceous Vegetation or Shrub, assumed sparse to moderate cover (< 20% cover); (4) Herbaceous Vegetation or Shrub, assumed moderate to dense cover (>20% cover); and (5) Shrub or Forest, assumed moderate to dense cover. We ran the interactive supervised classification routine in the Classification toolbar and clipped the resulting classification image along the boundaries of the vegetation mask. In the Image Analysis window, we masked out areas that overlapped with the marsh or development mask. The resulting image matched the extent of the vegetation mask, minus areas overlapping with marsh and development, and contained cells at the original resolution (0.35 m) of the orthoimage. Cells had one of the five values represented by the training polygons.
We created training polygons in the same manner for the final sub-classification. These samples represented the following classes: (1) Water and (2) Sand. We ran the interactive supervised classification routine in the Classification toolbar. We masked out areas that overlapped with the marsh, development, or vegetation masks in the Image Analysis window. The resulting image covered areas not already covered by the marsh, vegetation, or development and contained cells at the aerial imagery’s original resolution (0.35 m) with a value for either sand or water.
Using the Merge tool in the Image Analysis window in ArcGIS, we combined the rasters for (1) marsh, (2) vegetation, (3) sand/water sub-classifications with the (4) rasterized development layer into a single raster (hereafter, the ‘supervised classification’). We changed the supervised classification’s resolution from the aerial imagery’s original cell size (0.35 m) to a 5 m cell size with the Resample tool in ArcToolbox. We used ‘majority’ as the resampling technique, where the new 5 m cell took on the most common value within the 5x5 m area.
In many instances, cells took on the value of ‘NoData’ around the boundaries of the marsh, vegetation, and development masks when we merged individual sub-classifications. We replaced these NoData values using statistical information from surrounding cells according to the following code in the Raster Calculator tool in ArcToolbox:
CON(isnull([raster]), FOCALMAJORITY([raster], rectangle, 5, 5), [raster]).
This code indicates that, if the value of a cell in the supervised classification is NoData, then replace that value with the value held by the majority of cells in the surrounding 5x5 cell window.
The final supervised classification was a raster layer with a 5 m cell size clipped to the extent of the study area with cells taking on one of nine possible values: (1) water, value = 1; (2) sand, value = 2; (3) herbaceous vegetation or low shrub, sparse to moderate cover, value = 9; (4) herbaceous vegetation or low shrub, moderate to dense cover, value = 3; (5) high shrub or forest, moderate to dense cover, value = 4; (6) marsh, sediment, value = 11; (7) marsh, vegetation or unknown cover, value = 7; (8) marsh, high shrub or forest, value = 14; and (9) development, value = 10. Note, this list contains all possible values in the supervised classification we considered within the larger research program (see Zeigler and others, 2019). Not all values may be represented in this supervised classification specifically.
Process_Date: 2018
Process_Step:
Process_Description:
Geomorphic settings raster (ParI14_GeoSet.tif)
We created the geomorphic settings raster dataset (ParI14_GeoSet.tif) by first delineating the boundaries of individual features (e.g., the edges of washover fans), combining these features into a single shapefile, and converting that shapefile to a raster. Each individual geomorphic feature was given a value for identification purposes (‘value’) as well as a priority number (‘priority’) on which to base the merging of all features into a single layer.
For additional information and example figures, see Zeigler and others (2019). All steps were conducted in ArcGIS and ArcToolbox version 10.4.1.
We began by hand-digitizing the boundaries for marsh (value = 6, priority = 6) based on the visual inspection of the orthoimage. The rear-edges of marsh boundaries were drawn such that they extended out past the study area boundary and included areas of open water that were directly across from marsh platforms.
We created a polygon for beach (value = 1, priority = 5) using the shoreline (pari14_shoreline.shp in the larger work) and custom study area boundary polygons. The custom study area boundary spans the entire coverage of the Parramore Island site relevant to the broader research program (see Zeigler and others, 2019 for more details). The boundary polygon’s spatial extent does not affect the quality or completeness of the dataset.
To create the beach polygon, we used the ‘Erase’ tool in ArcToolbox to mask out the shoreline polygons and the hand-digitized marsh polygons from a copy of the full study area polygon. This process essentially removed the features of marsh and anything interior of the shoreline from the study area boundary, leaving only the beach geomorphic setting in the final polygon. Together, the beach and marsh polygons covered the outermost edges of the study area.
We also hand-digitized the boundaries of dunes (value = 3, priority = 7) using the DEM (displayed in 1 m intervals), dune crest and dune toe points (pari14_DCpts.shp and pari14_DTpts.shp in larger work and Doran and others, 2017), and the orthoimage as guides. We digitized the rear of dune complexes such that the boundary fell landward of dune crest points (if present) and along a clear decrease in elevation (according to visual inspection of the source DEM). The front of the dune was also drawn such that the boundary fell along a clear decrease in elevation and passed through dune toe points. We used the ‘Snapping’ feature in the Editing toolbar of ArcGIS to ensure that the front boundary of dune complexes coincided with the dune toe points. In some instances, particularly in washovers, dune crest points were present without obvious changes in elevation (in the DEM) or the presence of dune toe points. In these cases, we hand-digitized the dune boundary such that it tightly encompassed dune crest points.
Boundaries of the remaining geomorphic features were hand-digitized according to visual inspection of the orthoimage and in reference to boundaries already created for beach, marsh, and dunes. The rear, landward boundary of the backshore (value = 2, priority = 4) was digitized such that it overlapped with dune polygons (but did not extend past the landward-most boundary of the dune). When dunes were not present, the landward boundary of the backshore was drawn where non-vegetated sand ended and dense vegetation began. We extended the backshore polygon boundary seaward beyond the shoreline (or the boundary of marsh in the case of the back-barrier).
The characteristic fan-shaped boundaries of washovers (value = 4, priority = 3) were hand-digitized such that they overlapped with the boundaries of marsh along the back-barrier and with the boundaries of dune complexes on the seaward shore. In instances where dunes were not present seaward of a washover, we digitized the washover boundary along wrack if visible in the orthoimage.
We hand-digitized polygons for ridge/swale complexes (value = 7, priority = 2), when present, at the boundary of open sand and vegetation according to the orthoimage. Note: this geomorphic setting was not present at all sites and may not be represented.
For barrier interior (value = 5, priority = 1), the final geomorphic setting, we used the Erase tool in ArcToolbox to remove all other geomorphic settings (i.e., beach, backshore, dune, washover, marsh, and ridge/swale) from a copy of the study area polygon (not published). In this way, the barrier interior setting occurred only in the absence of any other geomorphic features.
Using the Merge tool in ArcToolbox, we combined the individual polygon shapefiles for beach, backshore, dune, washover, barrier interior, marsh, and ridge/swale into a single shapefile. We used the Integrate tool in ArcToolbox (distance = 1 m) to close small gaps between polygons.
We then converted the merged polygon shapefile to a raster with a 5 m cell size, using the priority value for each geomorphic setting type in the attribute table to determine which geomorphic setting type took precedence when two or more settings overlapped (where a raster cell takes the value of the feature with the highest priority value). We selected ‘maximum area cell assignment’ to determine cell values. The extent was set to the study area extent in the geoprocessing Environment Settings window so that the converted raster would be clipped to the extent of the study area.
The final raster provided a categorical map of geomorphic features with every 5x5 m cell categorized as one of the seven possible geomorphic settings.
Process_Date: 2018
Process_Step:
Process_Description:
Reclassification for the substrate type layer (ParI14_SubType.tif):
All steps were undertaken in ArcGIS and ArcToolbox version 10.4.1. For additional information and example figures, see Zeigler and others (2019).
Each of the classes contained in the supervised classification is associated with a substrate type, vegetation type, and vegetation density for later use in creating raster coverages for these characteristics. For substrate type, we reclassified the original supervised classification value to the following substrate types and associated values:
(1) water -> Water, 4444; (2) sand -> Sand or ShellGravelCobble, 7777; (3) herbaceous or shrub, sparse to moderate cover -> Sand or ShellGravelCobble, 7777; (4) herbaceous or shrub, moderate to dense cover -> Sand or ShellGravelCobble, 7777; (5) shrub or forest -> Unknown, 9999; (6) marsh, sediment -> Sand or MudPeat, 1000; (7) marsh, vegetation or unknown cover -> MudPeat, 3333; (8) marsh, shrub or forest -> Unknown, 9999; (9) development -> Development, 6666.
Note, this list contains all possible values for substrate types considered within the larger research program (see Zeigler and others, 2019). Not all values may be represented for this site.
We made one manual change to the reclassification of the supervised classification to create the substrate type layer. For raster cells that were classified as ‘beach’ in the geomorphic settings layer (ParI14_GeoSet.tif), we manually reclassified the substrate type for these cells to ‘Water’ with 'None' for both vegetation density and vegetation type. The beach geomorphic setting represented all raster cells outside of the shoreline polygons (pari14_shoreline.shp in larger work), and we assumed that these areas would be underwater at some point depending on the tide. We reclassified everything outside of the full shoreline polygons as Water to maintain consistency in landcover classifications relative to tide fluctuations.
Process_Date: 2018
Process_Step:
Process_Description:
Reclassification for the vegetation density layer (ParI14_VegDen.tif):
All steps were undertaken in ArcGIS and ArcToolbox version 10.4.1. For additional information and example figures, see Zeigler and others (2019).
For vegetation density, we reclassified the original supervised classification value to the following vegetation densities and associated values:
(1) water -> None, 111; (2) sand -> None or Sparse, 666; (3) herbaceous or shrub, sparse to moderate cover -> Sparse or Moderate, 777; (4) herbaceous or shrub, moderate to dense cover -> Moderate or Dense, 888; (5) shrub or forest -> Moderate or Dense, 888; (6) marsh, sediment -> None or Sparse, 666; (7) marsh, vegetation or unknown cover -> Unknown, 9999; (8) marsh, shrub or forest -> Moderate or Dense, 888; (9) development -> Development, 555.
Note, this list contains all possible values for vegetation density classes considered within the larger research program (see Zeigler and others, 2019). Not all values may be represented in this dataset.
We made one manual change to the reclassification of the supervised classification to create the vegetation density layer. For raster cells that were classified as ‘beach’ in the geomorphic settings layer (ParI14_GeoSet.tif), we manually reclassified the substrate type for these cells as ‘Water’ with 'None' for both vegetation density and vegetation type. The beach geomorphic setting represented all raster cells outside of the shoreline polygons (pari14_shoreline.shp in larger work), and we assumed that these areas would be underwater at some point depending on the tide. This also reduced misclassifications where beach wrack (or dead materials washed up on to the beach) was incorrectly identified as vegetation, which was a common issue in the supervised classification process. Thus, we reclassified everything outside of the shoreline polygons as 'None', or lacking terrestrial vegetation.
Process_Date: 2018
Process_Step:
Process_Description:
Reclassification for the vegetation type layer (ParI14_VegType.tif):
All steps were undertaken in ArcGIS and ArcToolbox version 10.4.1. For additional information and example figures, see Zeigler and others (2019).
For vegetation type, we reclassified the original supervised classification value to the following vegetation types and associated values:
(1) water -> None, 11; (2) sand -> None or Herbaceous, 77; (3) herbaceous or shrub, sparse to moderate cover -> Herbaceous or Shrub, 88; (4) herbaceous or shrub, moderate to dense cover -> Herbaceous or Shrub, 88; (5) shrub or forest -> Shrub or Forest, 99; (6) marsh, sediment -> None or Herbaceous, 77; (7) marsh, vegetation or unknown cover -> Unknown, 9999; (8) marsh, shrub or forest -> Shrub or Forest, 99; (9) development -> Development, 55.
Note, this list contains all possible values for vegetation types considered within the larger research program (see Zeigler and others, 2019). Not all values may be represented for this site.
We made one manual change to the reclassification of the supervised classification to create the vegetation type layer. For raster cells that were classified as ‘beach’ in the geomorphic settings layer (ParI14_GeoSet.tif), we manually reclassified the substrate type for these cells as ‘Water’ with 'None' for both vegetation density and vegetation type. The beach geomorphic setting represented all raster cells outside of the shoreline polygons (pari14_shoreline.shp in larger work), and we assumed that these areas would be underwater at some point depending on the tide. We reclassified everything seaward of the full shoreline as Water to maintain consistency in landcover classifications relative to tide fluctuations. This also reduced misclassifications where beach wrack (or dead materials washed up on to the beach) was incorrectly identified as vegetation, which was a common issue in the supervised classification process. For these reasons, we reclassified everything outside of the shoreline polygons as none, or lacking in terrestrial vegetation.
Process_Date: 2018
Process_Step:
Process_Description:
Added keywords section with USGS persistent identifier as theme keyword.
Process_Date: 20200810
Process_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey
Contact_Person: VeeAnn A. Cross
Contact_Position: Marine Geologist
Contact_Address:
Address_Type: Mailing and Physical
Address: 384 Woods Hole Road
City: Woods Hole
State_or_Province: MA
Postal_Code: 02543-1598
Contact_Voice_Telephone: 508-548-8700 x2251
Contact_Facsimile_Telephone: 508-457-2310
Contact_Electronic_Mail_Address: vatnipp@usgs.gov
Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Grid Cell
Row_Count: 2140
Column_Count: 1543
Vertical_Count: 1
Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Planar:
Grid_Coordinate_System:
Grid_Coordinate_System_Name: Universal Transverse Mercator
Universal_Transverse_Mercator:
UTM_Zone_Number: 18
Transverse_Mercator:
Scale_Factor_at_Central_Meridian: 0.9996
Longitude_of_Central_Meridian: -75
Latitude_of_Projection_Origin: 0.0
False_Easting: 500000.0
False_Northing: 0.0
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: row and column
Coordinate_Representation:
Abscissa_Resolution: 5.0
Ordinate_Resolution: 5.0
Planar_Distance_Units: Meter
Geodetic_Model:
Horizontal_Datum_Name: D_North_American_1983
Ellipsoid_Name: GRS_1980
Semi-major_Axis: 6378137.0
Denominator_of_Flattening_Ratio: 298.257222101
Entity_and_Attribute_Information:
Detailed_Description:
Entity_Type:
Entity_Type_Label: ParI14_SupClas values attribute table
Entity_Type_Definition:
Values attribute table (ParI14_SupClas.tif.vat.dbf), which indicates the landcover classification of every cell in the raster (ParI14_SupClas.tif). These metadata list all possible values; some of the values described may not be present in this dataset.
Entity_Type_Definition_Source: Producer defined
Attribute:
Attribute_Label: VALUE
Attribute_Definition:
Categorical identifier for landcover characteristics (describing vegetation and substrate).
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 1
Enumerated_Domain_Value_Definition:
Water: Any location that (i) is always submerged (e.g., locations several meters into the ocean, bay, or inland water body) or (ii) was submerged at the time source aerial imagery was captured (i.e., intertidal regions of beaches).
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 2
Enumerated_Domain_Value_Definition:
Open Sand: Areas lacking visible vegetation and containing some type of sandy substrate.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 3
Enumerated_Domain_Value_Definition:
Herbaceous or Shrub vegetation (moderate to dense): Areas containing herbaceous vegetation or short shrubby vegetation at moderate (20-90% vegetation cover in a 5x5 m area) to dense (greater than 90% vegetation cover) densities.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 4
Enumerated_Domain_Value_Definition:
Shrub or Forest (moderate to dense): Areas containing tall shrubs or trees at moderate (20-90% vegetation cover in a 5x5 m area) to dense (greater than 90% vegetation cover) densities.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 7
Enumerated_Domain_Value_Definition:
Marsh (vegetation or unknown cover): Marsh areas containing mud/peat substrates and either herbaceous vegetation or unknown vegetation cover.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 9
Enumerated_Domain_Value_Definition:
Herbaceous or shrub vegetation (sparse to moderate): Areas containing herbaceous vegetation or short shrubby vegetation at sparse (less than 20% vegetation cover in a 5x5 m area) to moderate (20-90% vegetation cover) densities.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 10
Enumerated_Domain_Value_Definition:
Development: Any location that fell within areas obviously influenced by anthropogenic activities (e.g., housing developments, paved roads or parking lots, recreational sports fields, etc.).
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 11
Enumerated_Domain_Value_Definition:
Marsh (sediment): Marsh areas containing sandy or mud/peat substrates as well as no to sparse vegetation.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 14
Enumerated_Domain_Value_Definition:
Marsh (shrub or forest): Marsh areas containing unknown substrate and either shrubby vegetation or forests.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute:
Attribute_Label: COUNT
Attribute_Definition: Number of 5x5 m cells in the given landcover type.
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 59776
Range_Domain_Maximum: 383082
Attribute_Units_of_Measure: number of grid cells
Attribute:
Attribute_Label: TYPE
Attribute_Definition:
Definitions of categorical identifiers for landcover characteristics (describing vegetation and substrate) found on Parramore Island.
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Development
Enumerated_Domain_Value_Definition:
(10) Development: Any location that fell within areas obviously influenced by anthropogenic activities (e.g., housing developments, paved roads or parking lots, recreational sports fields, etc.).
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Herbaceous vegetation or Shrub
Enumerated_Domain_Value_Definition:
(3) Herbaceous or shrub vegetation (moderate to dense): Areas containing herbaceous vegetation or short shrubby vegetation at moderate (20-90% vegetation cover in a 5x5 m area) to dense (greater than 90% vegetation cover) densities.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Herbaceous or Shrub (sparse to moderate)
Enumerated_Domain_Value_Definition:
(9) Herbaceous or shrub vegetation (sparse to moderate): Areas containing herbaceous vegetation or short shrubby vegetation at sparse (less than 20% vegetation cover in a 5x5 m area) to moderate (20-90% vegetation cover) densities.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Marsh (sediment)
Enumerated_Domain_Value_Definition:
(11) Marsh (sediment): Marsh areas containing sandy or mud/peat substrates as well as no to sparse vegetation.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Marsh (shrub or forest)
Enumerated_Domain_Value_Definition:
(14) Marsh (shrub or forest): Marsh areas containing unknown substrate and either shrubby vegetation or forests.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Marsh
Enumerated_Domain_Value_Definition:
(7) Marsh (vegetation or unknown cover): Marsh areas containing mud/peat substrates and either herbaceous vegetation or unknown vegetation cover.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Sand
Enumerated_Domain_Value_Definition:
(2) Open Sand: Areas lacking visible vegetation and containing some type of sandy substrate.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Shrub or Forest
Enumerated_Domain_Value_Definition:
(4) Shrub or Forest (moderate to dense): Areas containing tall shrubs or trees at moderate (20-90% vegetation cover in a 5 m area) to dense (greater than 90% vegetation cover) densities.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Water
Enumerated_Domain_Value_Definition:
(1) Water: Any location that (i) is always submerged (e.g., locations several meters into the ocean, bay, or inland water body) or (ii) was submerged at the time source aerial imagery was captured (i.e., intertidal regions of beaches).
Enumerated_Domain_Value_Definition_Source: Producer defined
Detailed_Description:
Entity_Type:
Entity_Type_Label: ParI14_GeoSet values attribute table
Entity_Type_Definition:
Values attribute table (ParI14_GeoSet.tif.vat.dbf), which indicates the geomorphic setting classification of every cell in the raster (ParI14_GeoSet.tif). These metadata list all possible values; some of the values described may not be present in this dataset.
Entity_Type_Definition_Source: Producer defined
Attribute:
Attribute_Label: VALUE
Attribute_Definition:
Coded identifier of geomorphic setting type (see Zeigler and others, 2019 for more details).
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 1
Enumerated_Domain_Value_Definition:
Beach: The relatively thick and temporary accumulation of loose, water-borne material (usually well-sorted sand and pebbles, accompanied by mud, cobbles, boulders, and smoothed rock and shell fragments) that is in active transit along, or deposited on, the shore zone between the limits of low water and high water (Neuendorf and others, 2011). In this study, the beach geomorphic setting occurred from the shoreline seaward to the study area boundary.
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 2
Enumerated_Domain_Value_Definition:
Backshore: The upper, usually dry, zone of the shore or beach, lying between the mean high water shoreline of mean spring tides and the upper limit of shore-zone processes; it is acted upon by waves or covered by water only during exceptionally severe storms or unusually high tides (Neuendorf and others, 2011). In this study, the backshore geomorphic setting occurred between the mean high water shoreline and either (i) the dune toe, (ii) the edge of developed areas, or (iii) the edge of dense vegetation (or forest).
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 3
Enumerated_Domain_Value_Definition:
Dune complex: A low mound, ridge, bank, or hill of loose, windblown granular material (generally sand), either bare or covered by vegetation, capable of movement from place to place but retaining its characteristic shape (Neuendorf and others, 2011). In this study, “dune” also describes low-lying areas between dunes (or “interdune” regions) that are part of the larger dune complex.
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 4
Enumerated_Domain_Value_Definition:
Washover (or overwash): A fan of material deposited from the ocean landward on a mainland beach or barrier island, produced by storm waves breaking over low parts of the mainland beach or barrier and depositing sediment either landward (mainland beaches) or across a barrier island into the bay or sound (barrier islands). A washover typically displays a characteristic fan-like shape (Neuendorf and others, 2011).
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 5
Enumerated_Domain_Value_Definition:
Barrier Interior: the geomorphic setting described all areas spanning the interior boundary of the dunes (or backshore in the absence of dunes) on the ocean-side to the interior boundary of the marsh, dunes, or backshore on the back-barrier side. This setting was typically used to describe areas that did not fall into any other geomorphic setting (e.g., washovers, ridge or swale complexes).
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 6
Enumerated_Domain_Value_Definition:
Marsh: A relatively flat, low-lying, intermittently water-covered area with generally halophytic grasses existing landward of a barrier island (Neuendorf and others, 2011).
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 7
Enumerated_Domain_Value_Definition:
Ridge/Swale complex: Long subparallel ridges and swales aligned obliquely across the regional trend of the contours (Neuendorf and others, 2011).
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute:
Attribute_Label: COUNT
Attribute_Definition:
Number of 5x5 m cells pertaining to the applicable geomorphic setting.
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 52128
Range_Domain_Maximum: 439684
Attribute_Units_of_Measure: number of grid cells
Attribute:
Attribute_Label: TYPE
Attribute_Definition:
Geomorphic setting type (see Zeigler and others, 2019 for more details).
Attribute_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Backshore
Enumerated_Domain_Value_Definition:
(2) The upper, usually dry, zone of the shore or beach, lying between the mean high water shoreline of mean spring tides and the upper limit of shore-zone processes; it is acted upon by waves or covered by water only during exceptionally severe storms or unusually high tides (Neuendorf and others, 2011). In this study, the backshore geomorphic setting occurred between the shoreline and either (i) the dune toe, (ii) the edge of developed areas, or (iii) the edge of dense vegetation (or forest).
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Barrier Interior
Enumerated_Domain_Value_Definition:
(5) The barrier interior geomorphic setting described all areas spanning the interior boundary of the dunes (or backshore in the absence of dunes) on the ocean-side to the interior boundary of the marsh, dunes, or backshore on the back-barrier side. This setting was typically used to describe areas that did not fall into any other geomorphic setting (e.g., washovers, ridge or swale complexes).
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Beach
Enumerated_Domain_Value_Definition:
(1) The relatively thick and temporary accumulation of loose, water-borne material (usually well-sorted sand and pebbles, accompanied by mud, cobbles, boulders, and smoothed rock and shell fragments) that is in active transit along, or deposited on, the shore zone between the limits of low water and high water (Neuendorf and others, 2011). In this study, the beach geomorphic setting occurred from the shoreline seaward to the study area boundary.
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Dune Complex
Enumerated_Domain_Value_Definition:
(3) A low mound, ridge, bank, or hill of loose, windblown granular material (generally sand), either bare or covered by vegetation, capable of movement from place to place but retaining its characteristic shape (Neuendorf and others, 2011). In this study, “dune” also describes low-lying areas between dunes (or “interdune” regions) that are part of the larger dune complex.
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Marsh
Enumerated_Domain_Value_Definition:
(6) A relatively flat, low-lying, intermittently water-covered area with generally halophytic grasses existing landward of a barrier island (Neuendorf and others, 2011).
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Ridge/Swale complex
Enumerated_Domain_Value_Definition:
(7) Long subparallel ridges and swales aligned obliquely across the regional trend of the contours (Neuendorf and others, 2011).
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Washover
Enumerated_Domain_Value_Definition:
(4) A fan of material deposited from the ocean landward on a mainland beach or barrier island, produced by storm waves breaking over low parts of the mainland beach or barrier and depositing sediment either landward (mainland beaches) or across a barrier island into the bay or sound (barrier islands). A washover typically displays a characteristic fan-like shape (Neuendorf and others, 2011).
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Detailed_Description:
Entity_Type:
Entity_Type_Label: ParI14_SubType values attribute table
Entity_Type_Definition:
Values attribute table (ParI14_SubType.tif.vat.dbf), which indicates the substrate type classification of every cell in the raster (ParI14_SubType.tif). These metadata list all possible values; some of the values described may not be present in this dataset.
Entity_Type_Definition_Source: Producer defined
Attribute:
Attribute_Label: VALUE
Attribute_Definition: Coded identifier for discrete substrate type.
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 1000
Enumerated_Domain_Value_Definition:
Sand or Mud/Peat: In this study, wet, sandy substrates could not be differentiated from mud/peat in marshy areas. Therefore, we identified substrate as being either of these two types in the Substrate raster layer. Mud/Peat is a sticky, fine-grained, predominantly clay- or silt-sized marine detrital sediment (Neuendorf and others, 2011). Sand included rock or mineral grains with diameters between 0.074 and 4.76 mm (Neuendorf and others, 2011).
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 1111
Enumerated_Domain_Value_Definition:
Sand: predominantly sandy substrates that contain rock or mineral grains with diameters between 0.074 and 4.76 mm (Neuendorf and others, 2011) with no discernible shells fragments or large rock fragments.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 2222
Enumerated_Domain_Value_Definition:
Shell/Gravel/Cobble: substrates containing a mixture of sand, shell or rock fragments, or large rocks.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 3333
Enumerated_Domain_Value_Definition:
MudPeat: A sticky, fine-grained, predominantly clay- or silt-sized marine detrital sediment (Neuendorf and others, 2011).
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 4444
Enumerated_Domain_Value_Definition:
Water: Any location that (i) is always submerged (e.g., locations several meters into the ocean, bay, or inland water body), (ii) was submerged at the time aerial imagery was captured (i.e., intertidal regions of beaches), or (iii) was not submerged at the time aerial imagery was captured but was seaward of the shoreline polygon.
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 6666
Enumerated_Domain_Value_Definition:
Development: Any location that fell within areas obviously influenced by anthropogenic activities (e.g., housing developments, paved roads or parking lots, recreational sports fields, etc.).
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 7777
Enumerated_Domain_Value_Definition:
Sand or ShellGravelCobble: In this study, predominantly sandy substrates could not be differentiated from substrates that were a mix of sand and ShellGravelCobble in the aerial imagery alone. Therefore, we identified substrate as being either of these two types in the substrate type raster layer. Sand included rock or mineral grains with diameters between 0.074 and 4.76 mm (Neuendorf and others, 2011) with no discernible shells fragments or large rock fragments. ShellGravelCobble described substrates containing a mixture of sand, shell or rock fragments, or large rocks.
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 9999
Enumerated_Domain_Value_Definition:
Unknown: Substrate type could not be determined based on aerial imagery
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute:
Attribute_Label: COUNT
Attribute_Definition:
Number of 5x5 m cells in the raster coverage that contain each substrate type.
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 159380
Range_Domain_Maximum: 424051
Attribute_Units_of_Measure: number of grid cells
Attribute:
Attribute_Label: TYPE
Attribute_Definition: Discrete substrate type.
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Development
Enumerated_Domain_Value_Definition:
(6666) Development: Any location that fell within areas obviously influenced by anthropogenic activities (e.g., housing developments, paved roads or parking lots, recreational sports fields, etc.).
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Sand
Enumerated_Domain_Value_Definition:
(111) Sand: predominantly sandy substrates that contain rock or mineral grains with diameters between 0.074 and 4.76 mm (Neuendorf and others, 2011) with no discernible shells fragments or large rock fragments.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: MudPeat
Enumerated_Domain_Value_Definition:
(3333) MudPeat: A sticky, fine-grained, predominantly clay- or silt-sized marine detrital sediment (Neuendorf and others, 2011).
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Sand or MudPeat
Enumerated_Domain_Value_Definition:
(1000) Sand or Mud/Peat: In this study, wet, sandy substrates could not be differentiated from mud/peat in marshy areas. Therefore, we identified substrate as being either of these two types in the Substrate raster layer. Mud/Peat is a sticky, fine-grained, predominantly clay- or silt-sized marine detrital sediment (Neuendorf and others, 2011). Sand included rock or mineral grains with diameters between 0.074 and 4.76 mm (Neuendorf and others, 2011).
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Sand or ShellGravelCobble
Enumerated_Domain_Value_Definition:
(7777) Sand or ShellGravelCobble: In this study, predominantly sandy substrates could not be differentiated from substrates that were a mix of sand and ShellGravelCobble. Therefore, we identified substrate as being either of these two types in the Substrate raster layer. Sand included rock or mineral grains with diameters between 0.074 and 4.76 mm (Neuendorf and others, 2011) with no discernible shells fragments or large rock fragments. ShellGravelCobble described substrates containing a mixture of sand, shell or rock fragments, or large rocks.
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: ShellGravelCobble
Enumerated_Domain_Value_Definition:
(222) Shell/Gravel/Cobble: substrates containing a mixture of sand, shell or rock fragments, or large rocks.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Unknown
Enumerated_Domain_Value_Definition:
(9999) Unknown: Substrate type could not be determined based on aerial imagery
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Water
Enumerated_Domain_Value_Definition:
(4444) Water: Any location that (i) is always submerged (e.g., locations several meters into the ocean, bay, or inland water body), (ii) was submerged at the time aerial imagery was captured (i.e., intertidal regions of beaches), or (iii) was not submerged at the time aerial imagery was captured but was seaward of the shoreline polygon.
Enumerated_Domain_Value_Definition_Source:
Producer defined, definition modified from Neuendorf and others (2011).
Detailed_Description:
Entity_Type:
Entity_Type_Label: ParI14_VegDen values attribute table
Entity_Type_Definition:
Values attribute table (ParI14_VegDen.tif.vat.dbf), which indicates the vegetation density classification of every cell in the raster (ParI14_VegDen.tif). These metadata list all possible values; some of the values described may not be present in this dataset.
Entity_Type_Definition_Source: Producer defined
Attribute:
Attribute_Label: VALUE
Attribute_Definition: Categorical identifier for discrete vegetation density classes.
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 111
Enumerated_Domain_Value_Definition:
None: Areas lacking terrestrial vegetation of any type. Such areas were most frequently associated with the beach geomorphic setting (found seaward of the study area shoreline) assumed to be covered by water.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 222
Enumerated_Domain_Value_Definition:
Sparse: areas where vegetation was apparent and covered less than 20% of the 5x5-m raster cell.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 333
Enumerated_Domain_Value_Definition:
Moderate: areas where vegetation appeared to cover 20–90% of the 5x5-m raster cell.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 444
Enumerated_Domain_Value_Definition:
Dense: areas where vegetation appeared to cover greater than 90% of the 5x5-m raster cell.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 555
Enumerated_Domain_Value_Definition:
Development: Any location that fell within areas obviously influenced by anthropogenic activities (e.g., housing developments, paved roads or parking lots, recreational sports fields, etc.).
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 666
Enumerated_Domain_Value_Definition:
None or Sparse: Areas lacking vegetation could not consistently be differentiated from areas containing sparse vegetation on open sandy areas (i.e., not covered by water) in the aerial imagery alone. Therefore, we identified vegetation density as being either none or sparse in the vegetation density raster layer. Areas described by these classes either appeared to lack vegetation completely in the aerial imagery or, if vegetation was apparent, covered less than 20% of the 5x5-m raster cell.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 777
Enumerated_Domain_Value_Definition:
Sparse or Moderate: In this study, areas with sparse vegetation could not consistently be differentiated from areas containing moderate vegetation in the orthoimagery alone. Therefore, we identified vegetation as being either of these two types in the Vegetation Density raster layer. Areas described as having 'Sparse' vegetation appeared to have vegetation that covered less than 20% of the 5x5-m raster cell. In areas described as 'Moderate', vegetation appeared to cover 20-90% of the 5x5-m raster cell.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 888
Enumerated_Domain_Value_Definition:
Moderate or Dense: In this study, areas with moderate vegetation could not consistently be differentiated from areas containing dense vegetation in the aerial alone. Therefore, we identified vegetation as being either of these two classes in the vegetation density raster layer. Areas described by these classes either appeared to have vegetation covering 20-90% or > 90% of the 5x5-m raster cell.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 9999
Enumerated_Domain_Value_Definition:
Unknown: Vegetation density could not be determined based on the aerial imagery
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute:
Attribute_Label: COUNT
Attribute_Definition:
Number of 5x5 m cells in the raster coverage that contain each vegetation density class.
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 159380
Range_Domain_Maximum: 424051
Attribute_Units_of_Measure: number of grid cells
Attribute:
Attribute_Label: TYPE
Attribute_Definition: Discrete vegetation density classes found on Parramore Island.
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Dense
Enumerated_Domain_Value_Definition:
(444) Dense: areas where vegetation appeared to cover greater than 90% of the 5x5-m raster cell.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Development
Enumerated_Domain_Value_Definition:
(555) Development: Any location that fell within areas obviously influenced by anthropogenic activities (e.g., housing developments, paved roads or parking lots, recreational sports fields, etc.).
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Moderate
Enumerated_Domain_Value_Definition:
(333) Moderate: areas where vegetation appeared to cover 20–90% of the 5x5-m raster cell.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Moderate or Dense
Enumerated_Domain_Value_Definition:
(888) Moderate or Dense: In this study, areas with moderate vegetation could not consistently be differentiated from areas containing dense vegetation in the aerial alone. Therefore, we identified vegetation as being either of these two classes in the vegetation density raster layer. Areas described by these classes either appeared to have vegetation covering 20-90% or > 90% of the 5x5-m raster cell.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: None
Enumerated_Domain_Value_Definition:
(111) None: Areas lacking terrestrial vegetation of any type. Such areas were most frequently associated with the beach geomorphic setting (found seaward of the study area shoreline) assumed to be covered by water.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: None or Sparse
Enumerated_Domain_Value_Definition:
(666) None or Sparse: In this study, areas lacking vegetation could not consistently be differentiated from areas containing sparse vegetation on open sandy areas (i.e., not covered by water) in the aerial imagery alone. Therefore, we identified vegetation density as being either none or sparse in the vegetation density raster layer. Areas described by these classes either appeared to lack vegetation completely in the aerial imagery or, if vegetation was apparent, covered less than 20% of the 5x5-m raster cell.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Sparse or Moderate
Enumerated_Domain_Value_Definition:
(777) Sparse or Moderate: In this study, areas with sparse vegetation could not consistently be differentiated from areas containing moderate vegetation in the orthoimagery alone. Therefore, we identified vegetation as being either of these two types in the Vegetation Density raster layer. Areas described as having 'Sparse' vegetation appeared to have vegetation that covered less than 20% of the 5x5-m raster cell. In areas described as 'Moderate', vegetation appeared to cover 20-90% of the 5x5-m raster cell.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Sparse
Enumerated_Domain_Value_Definition:
(222) Sparse: areas where vegetation was apparent and covered less than 20% of the 5x5-m raster cell.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Unknown
Enumerated_Domain_Value_Definition:
(9999) Unknown: Vegetation density could not be determined based on aerial imagery.
Enumerated_Domain_Value_Definition_Source: Producer defined
Detailed_Description:
Entity_Type:
Entity_Type_Label: ParI14_VegType values attribute table
Entity_Type_Definition:
Values attribute table (ParI14_VegType.tif.vat.dbf), which indicates the vegetation type classification of every cell in the raster (ParI14_VegType.tif). These metadata list all possible values; some of the values described may not be present in this dataset.
Entity_Type_Definition_Source: Producer defined
Attribute:
Attribute_Label: VALUE
Attribute_Definition: Categorical identifier for discrete vegetation types.
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 11
Enumerated_Domain_Value_Definition:
None: Areas lacking terrestrial vegetation of any type. Such areas were associated with the beach geomorphic setting (found seaward of the study area shoreline) assumed to be covered by water.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 22
Enumerated_Domain_Value_Definition:
Herbaceous: areas containing primarily herbaceous vegetation of the forb/herb growth habit (USDA, 2015) and lacking shrubs, trees, or any other vegetation with woody stems (Neuendorf and others, 2011). In this study, the Herbaceous vegetation type typically described the vegetation cover found in Godfrey’s (1976) (i) ‘grassland’ ecological zone along the backshore and dunes, dominated by beach grasses (e.g., Ammophila breviligulata) or (ii) ‘intertidal marsh’ ecological zone dominated by cordgrass (e.g., Spartina patens).
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 33
Enumerated_Domain_Value_Definition:
Shrub: Areas containing low (less than 5 m height), multi-stemmed woody plants of the subshrub or shrub growth habits (USDA, 2015). In this study, the Shrub vegetation type typically described vegetation cover found in Godfrey’s (1976) heath-like ‘shrublands’ ecological zone in stable dune systems.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 44
Enumerated_Domain_Value_Definition:
Forest: Areas containing trees and tall (> 5 m) shrubs of the tree growth habit (USDA, 2015). In this study, the Forest vegetation type typically described vegetation cover found in Godfrey’s (1976) ‘woodlands–forests’ ecological zone found in barrier island interiors and dominated by deciduous (e.g., Quercus velutina), pine (e.g., Pinus rigida), and juniper (e.g., Juniperus virginiana) species.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 55
Enumerated_Domain_Value_Definition:
Development: Any location that fell within areas obviously influenced by anthropogenic activities (e.g., housing developments, paved roads or parking lots, recreational sports fields, etc.).
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 77
Enumerated_Domain_Value_Definition:
None or Herbaceous: In this study, areas landward of the study area shoreline and lacking vegetation could not be differentiated from areas containing sparse vegetation in the aerial imagery alone. Therefore, we identified vegetation as being either of these two types in the vegetation type raster layer. Areas described as 'none' lacked vegetation of any type, while 'herbaceous' indicated areas containing primarily herbaceous vegetation of the forb/herb growth habit (USDA, 2015) and lacking shrubs, trees, or any other vegetation with woody stems. In this study, the herbaceous vegetation type typically described the vegetation cover found in Godfrey’s (1976) (i) ‘grassland’ ecological zone along the backshore and dunes, dominated by beach grasses (e.g., Ammophila breviligulata) or (ii) ‘intertidal marsh’ ecological zone dominated by cordgrass (e.g., Spartina patens).
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 88
Enumerated_Domain_Value_Definition:
Herbaceous or Shrub: In this study, areas with herbaceous vegetation could not consistently be differentiated from areas containing low shrubs in the aerial imagery alone. Therefore, we identified vegetation as being either of these two types in the vegetation type raster layer. Areas described as 'herbaceous' indicated areas containing primarily herbaceous vegetation of the forb/herb growth habit (USDA, 2015) and lacking shrubs, trees, or any other vegetation with woody stems. In this study, the herbaceous vegetation type typically described the vegetation cover found in Godfrey’s (1976) (i) ‘grassland’ ecological zone along the backshore and dunes, dominated by beach grasses (e.g., Ammophila breviligulata) or (ii) ‘intertidal marsh’ ecological zone dominated by cordgrass (e.g., Spartina patens). Areas described as 'shrub' indicated areas containing low (less than 5 m height), multi-stemmed woody plants of the subshrub or shrub growth habits (USDA, 2015). In this study, the shrub vegetation type typically described vegetation cover found in Godfrey’s (1976) heath-like ‘shrublands’ ecological zone in stable dune systems.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 99
Enumerated_Domain_Value_Definition:
Shrub or Forest: In this study, areas with tall shrubby vegetation could not consistently be differentiated from areas containing forests in the aerial alone. Therefore, we identified vegetation as being either of these two types in the vegetation type raster layer. Areas described as 'shrub' indicated areas containing tall (greater than 5 m height) multi-stemmed woody plants of the shrub growth habit (USDA, 2015). In this study, the shrub vegetation type typically described vegetation cover found in Godfrey’s (1976) heath-like ‘shrublands’ ecological zone in stable dune systems. Areas described as 'forest' contain plants of the tree growth habit (USDA, 2015). In this study, the forest vegetation type typically described vegetation cover found in Godfrey’s (1976) ‘woodlands–forests’ ecological zone found in barrier island interiors and dominated by deciduous (e.g., Quercus velutina), pine (e.g., Pinus rigida), and juniper (e.g., Juniperus virginiana) species.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 9999
Enumerated_Domain_Value_Definition:
Unknown: Vegetation type could not be determined based on aerial imagery
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute:
Attribute_Label: COUNT
Attribute_Definition:
Number of 5x5 m cells in the raster coverage that contain each vegetation type.
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Range_Domain:
Range_Domain_Minimum: 59694
Range_Domain_Maximum: 424051
Attribute_Units_of_Measure: number of grid cells
Attribute:
Attribute_Label: TYPE
Attribute_Definition: Discrete vegetation types found on Parramore Island
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Development
Enumerated_Domain_Value_Definition:
(55) Development: Any location that fell within areas obviously influenced by anthropogenic activities (e.g., housing developments, paved roads or parking lots, recreational sports fields, etc.).
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Forest
Enumerated_Domain_Value_Definition:
(44) Forest: Areas containing trees and tall (> 5 m) shrubs of the tree growth habit (USDA, 2015). In this study, the Forest vegetation type typically described vegetation cover found in Godfrey’s (1976) ‘woodlands–forests’ ecological zone found in barrier island interiors and dominated by deciduous (e.g., Quercus velutina), pine (e.g., Pinus rigida), and juniper (e.g., Juniperus virginiana) species.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Herbaceous vegetation
Enumerated_Domain_Value_Definition:
(22) Herbaceous: areas containing primarily herbaceous vegetation of the forb/herb growth habit (USDA, 2015) and lacking shrubs, trees, or any other vegetation with woody stems (Neuendorf and others, 2011). In this study, the Herbaceous vegetation type typically described the vegetation cover found in Godfrey’s (1976) (i) ‘grassland’ ecological zone along the backshore and dunes, dominated by beach grasses (e.g., Ammophila breviligulata) or (ii) ‘intertidal marsh’ ecological zone dominated by cordgrass (e.g., Spartina patens).
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Herbaceous vegetation or Shrub
Enumerated_Domain_Value_Definition:
(88) Herbaceous or Shrub: In this study, areas with herbaceous vegetation could not consistently be differentiated from areas containing low shrubs in the aerial imagery alone. Therefore, we identified vegetation as being either of these two types in the vegetation type raster layer. Areas described as 'herbaceous' indicated areas containing primarily herbaceous vegetation of the forb/herb growth habit (USDA, 2015) and lacking shrubs, trees, or any other vegetation with woody stems. In this study, the herbaceous vegetation type typically described the vegetation cover found in Godfrey’s (1976) (i) ‘grassland’ ecological zone along the backshore and dunes, dominated by beach grasses (e.g., Ammophila breviligulata) or (ii) ‘intertidal marsh’ ecological zone dominated by cordgrass (e.g., Spartina patens). Areas described as 'shrub' indicated areas containing low (less than 5 m height), multi-stemmed woody plants of the subshrub or shrub growth habits (USDA, 2015). In this study, the shrub vegetation type typically described vegetation cover found in Godfrey’s (1976) heath-like ‘shrublands’ ecological zone in stable dune systems.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: None
Enumerated_Domain_Value_Definition:
(11) None: Areas lacking terrestrial vegetation of any type. Such areas were associated with the beach geomorphic setting (found seaward of the study area shoreline) assumed to be covered by water.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: None or Herbaceous
Enumerated_Domain_Value_Definition:
(77) None or Herbaceous: In this study, areas landward of the study area shoreline and lacking vegetation could not be differentiated from areas containing sparse vegetation in the aerial imagery alone. Therefore, we identified vegetation as being either of these two types in the vegetation type raster layer. Areas described as 'none' lacked vegetation of any type, while 'herbaceous' indicated areas containing primarily herbaceous vegetation of the forb/herb growth habit (USDA, 2015) and lacking shrubs, trees, or any other vegetation with woody stems. In this study, the herbaceous vegetation type typically described the vegetation cover found in Godfrey’s (1976) (i) ‘grassland’ ecological zone along the backshore and dunes, dominated by beach grasses (e.g., Ammophila breviligulata) or (ii) ‘intertidal marsh’ ecological zone dominated by cordgrass (e.g., Spartina patens).
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Shrub
Enumerated_Domain_Value_Definition:
(33) Shrub: Areas containing low (less than 5 m height), multi-stemmed woody plants of the subshrub or shrub growth habits (USDA, 2015). In this study, the Shrub vegetation type typically described vegetation cover found in Godfrey’s (1976) heath-like ‘shrublands’ ecological zone in stable dune systems.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Shrub or Forest
Enumerated_Domain_Value_Definition:
(99) Shrub or Forest: In this study, areas with tall shrubby vegetation could not consistently be differentiated from areas containing forests in the aerial alone. Therefore, we identified vegetation as being either of these two types in the vegetation type raster layer. Areas described as 'shrub' indicated areas containing tall (greater than 5 m height) multi-stemmed woody plants of the shrub growth habit (USDA, 2015). In this study, the shrub vegetation type typically described vegetation cover found in Godfrey’s (1976) heath-like ‘shrublands’ ecological zone in stable dune systems. Areas described as 'forest' contain plants of the tree growth habit (USDA, 2015). In this study, the forest vegetation type typically described vegetation cover found in Godfrey’s (1976) ‘woodlands–forests’ ecological zone found in barrier island interiors and dominated by deciduous (e.g., Quercus velutina), pine (e.g., Pinus rigida), and juniper (e.g., Juniperus virginiana) species.
Enumerated_Domain_Value_Definition_Source: Producer defined
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: Unknown
Enumerated_Domain_Value_Definition:
Unknown: Vegetation type could not be determined based on aerial imagery
Enumerated_Domain_Value_Definition_Source: Producer defined
Overview_Description:
Entity_and_Attribute_Overview:
This section provides a separate detailed entity and attribute information section for each dataset described in these metadata. These datasets comprise five individual raster files in GeoTiff format, which each have an associated values attribute table with discrete attribute values for each 5x5 m cell. The values attribute file is a necessary component of the dataset.
Entity_and_Attribute_Detail_Citation: Methods Open-File Report by Zeigler and others, 2019
Distribution_Information:
Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey - ScienceBase
Contact_Address:
Address_Type: mailing and physical address
Address: Denver Federal Center, Building 810, Mail Stop 302
City: Denver
State_or_Province: CO
Postal_Code: 80225
Country: USA
Contact_Voice_Telephone: 1-888-275-8747
Contact_Electronic_Mail_Address: sciencebase@usgs.gov
Resource_Description:
These datasets comprise five individual raster files in GeoTiff format (ParI14_SupClas.tif, ParI14_GeoSet.tif, ParI14_SubType.tif, ParI14_VegDen.tif, ParI14_VegType.tif), which each have an associated values attribute table with discrete attribute values for each 5x5 m cell (ParI14_SupClas.tif.vat.dbf, ParI14_GeoSet.tif.vat.dbf, ParI14_SubType.tif.vat.dbf, ParI14_VegDen.tif.vat.dbf, ParI14_VegType.tif.vat.dbf). Additionally, the CSDGM FGDC metadata (ParI14_SupClas_GeoSet_SubType_VegDen_VegType_meta.xml) and the browse graphic (supclas_rock_browse.png) are included. These datasets can be downloaded individually or packaged on-demand in a zip file (see the Digital Transfer Option section).
Distribution_Liability:
Neither the U.S. Government, the Department of the Interior, nor the USGS, nor any of their employees, contractors, or subcontractors, make any warranty, express or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, nor represent that its use would not infringe on privately owned rights. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the USGS in the use of these data or related materials. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), and have been processed successfully on a computer system at the 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. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: GeoTIFF
Format_Version_Number: ArcGIS 10.4
Format_Specification: GeoTIFF
Format_Information_Content:
This dataset contains 8-bit and 16-bit GeoTIFF files and associated GeoTIFF components of land cover classifications. Also included is the CSDGM metadata and browse graphic.
Transfer_Size: 50.8
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information: Access_Instructions:
The first link is to the page containing the data. The second is a direct link to download all data available from the page as a zip file. The final link is to the publication landing page. The data page (first link) may have additional data access options, including web services.
Fees: None
Technical_Prerequisites:
To utilize these data, the user must have software capable of reading a 16-bit GeoTIFF with associated values attribute table.
Metadata_Reference_Information:
Metadata_Date: 20240319
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Sara L. Zeigler
Contact_Organization: U.S. Geological Survey
Contact_Address:
Address_Type: Mailing and Physical
Address: 384 Woods Hole Road
City: Woods Hole
State_or_Province: MA
Postal_Code: 02543
Country: United States
Contact_Voice_Telephone: 508-548-8700 x2290
Contact_Electronic_Mail_Address: whsc_data_contact@usgs.gov
Contact_Instructions:
The metadata contact email address is a generic address in the event the person is no longer with USGS. (updated on 20240319)
Metadata_Standard_Name: FGDC Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998

This page is <https://cmgds.marine.usgs.gov/catalog/whcmsc/SB_data_release/DR_P9V7F6UX/ParI14_SupClas_GeoSet_SubType_VegDen_VegType_meta.html>
Generated by mp version 2.9.51 on Wed Jun 26 15:25:10 2024