Sediment Texture of the Sea Floor offshore of western and southern Martha's Vineyard and north of Nantucket, Massachusetts

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• How was the data set created?
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What does this data set describe?

1. How might this data set be cited?
   U.S. Geological Survey, 2018, Sediment Texture of the Sea Floor offshore of western and southern Martha's Vineyard and north of Nantucket, Massachusetts: data release DOI:10.5066/P9E9EFNE, U.S. Geological Survey, Reston, VA.

   Online Links:

   • https://doi.org/10.5066/P9E9EFNE
   • https://www.sciencebase.gov/catalog/item/5bfd6064e4b0815414ca39e1

   This is part of the following larger work.
   Pendleton, Elizabeth A., Baldwin, Wayne E., Foster, David S., Ackerman, Seth D., Andrews, Brian D., Brothers, Laura L., and Schwab, William C., 2018, Geospatial Data Layers of Shallow Geology, Sea-Floor Texture, and Physiographic Zones from the Inner Continental Shelf of Martha’s Vineyard from Aquinnah to Wasque Point, and Nantucket from Eel Point to Great Point: data release DOI:10.5066/P9E9EFNE, U.S. Geological Survey, Reston, VA.

   Online Links:

   • https://doi.org/10.5066/P9E9EFNE
   • https://www.sciencebase.gov/catalog/item/5afee3bfe4b0da30c1bfbd28

   Other_Citation_Details:

   Suggested citation: Pendleton, E.A., Baldwin, W.E., Foster, D.F., Ackerman, S.D., Andrews, B.D, Brothers, L.L., and Schwab, W.C., 2018, Geospatial data layers of shallow geology, sea-floor texture, and physiographic zones from the inner continental shelf of Martha's Vineyard from Aquinnah to Wasque Point, and Nantucket from Eel Point to Great Point: U.S. Geological Survey data release, https://doi.org/10.5066/P9E9EFNE.

2. What geographic area does the data set cover?

   West_Bounding_Coordinate: -70.8627
   East_Bounding_Coordinate: -70.0341
   North_Bounding_Coordinate: 41.3894
   South_Bounding_Coordinate: 41.1958
   

3. What does it look like?

   https://www.sciencebase.gov/catalog/file/get/5bfd6064e4b0815414ca39e1/?name=MV_ACK_sedtexture_browse.png (PNG)

   Image of the sediment texture shapefile for offshore of western and southern Martha's Vineyard and north of Nantucket. The browse graphic is derived from the companion OFR (Pendleton and others, 2018).

4. Does the data set describe conditions during a particular time period?

   Beginning_Date: 09-Aug-2007

   Ending_Date: 11-Jun-2013

   Currentness_Reference:

   ground condition of the source data used for the interpretation

5. What is the general form of this data set?

   Geospatial_Data_Presentation_Form: vector digital data
   

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 (438)
   2. What coordinate system is used to represent geographic features?
      Horizontal positions are specified in geographic coordinates, that is, latitude and longitude. Latitudes are given to the nearest 0.0197427722. Longitudes are given to the nearest 0.0261514554. Latitude and longitude values are specified in Decimal seconds. The horizontal datum used is WGS_1984.
      The ellipsoid used is WGS_84.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257223563.
      
7. How does the data set describe geographic features?

   MV_ACK_sedtexture.shp

   Sediment texture shapefile (Source: U.S. Geological Survey)

   FID

   Internal feature number. (Source: Esri) Sequential unique whole numbers that are automatically generated.

   Shape

   Feature geometry. (Source: Esri) Coordinates defining the features.

   Barnhardt

   Bottom-type classification on the basis of twelve composite units that represent combinations of four end-member units (R= rock; G= gravel; S= sand; M= mud). (Source: Barnhardt and others (1998))

   Value	Definition
   G	The end-member texture (= or greater than 90%) Gravel (G) is the primary texture.
   Gs	The dominant texture (greater than 50%) Gravel (G) is given the upper case letter and the subordinate texture (less than 50%) sand (s) is given a lower case letter.
   S	The end-member texture (= or greater than 90%) Sand (S) is the primary texture.
   Sg	The dominant texture (greater than 50%) Sand (S) is given the upper case letter and the subordinate texture (less than 50%) gravel (g) is given a lower case letter.
   Sm	The dominant texture (greater than 50%) Sand (S) is given the upper case letter and the subordinate texture (less than 50%) mud (m) is given a lower case letter.
   Ms	The dominant texture (greater than 50%) Mud (M) is given the upper case letter and the subordinate texture (less than 50%) sand (s) is given a lower case letter.
   Rs	The dominant texture (greater than 50%) Rock (R) is given the upper case letter and the subordinate texture (less than 50%) sand (s) is given a lower case letter.
   Sr	The dominant texture (greater than 50%) Sand (S) is given the upper case letter and the subordinate texture (less than 50%) rock (r) is given a lower case letter.

   Confidence

   Each interpreted polygon was assigned a data interpretation confidence value from 1-4 (more to less confident) on the basis of the quality and number of input data sources. (Source: U.S. Geological Survey)

   Value	Definition
   1	Sediment texture regions that were defined on the basis of the highest resolution bathymetry (10m) and backscatter (1m), bottom photos, sediment samples with laboratory analysis, and seismic interpretations were given the highest data interpretation confidence value of 1.
   2	Sediment texture regions that were defined on the basis of the highest resolution bathymetry (10m), backscatter (1m), and seismic interpretations, and possibly bottom photos and/or qualitative descriptions of sediment samples, but no sediment samples with laboratory analysis were given the data interpretation confidence value of 2
   3	Sediment texture regions that were defined on the basis of the highest resolution bathymetry (10m) and/or lidar bathymetry, and sediment samples with laboratory analysis and/or qualitative descriptions, but no acoustic backscatter or seismic interpretations were given the data interpretation confidence value of 3.
   4	Sediment texture regions that were defined on the basis of the highest resolution bathymetry (10m) and/or lidar bathymetry, but no sediment samples with laboratory analysis and/or qualitative descriptions, and no acoustic backscatter or seismic interpretations were given the data interpretation confidence value of 3.

   Count_

   The number of sediment samples (with laboratory analyzed grain size statistics) that occur within each qualitatively derived polygon. This field was automatically generated by Esri when point data (sample database) is joined to a polygon (sediment texture interpretation). A value of -999 indicates there are no samples within that polygon. (Source: Esri)

   Range of values
   Minimum:	1
   Maximum:	33
   Units:	count
   Resolution:	1

   Avg_GRAVEL

   Average percent weight (%) gravel (as determined from samples with laboratory analyzed grain size statistics) within each qualitatively derived polygon. This field was automatically generated by Esri as a summary of the numeric attributes of the points that fall inside a polygon when point data (sample database) is joined to a polygon (sediment texture interpretation). A value of -999 indicates that no sample was available within a particular feature. (Source: U.S. Geological Survey)

   Range of values
   Minimum:	0
   Maximum:	30.73
   Units:	percent

   Avg_SAND

   Average percent weight (%) sand within each qualitatively derived polygon. This field was automatically generated by Esri as a summary of the numeric attributes of the points that fall inside a polygon when point data (sample database) is joined to a polygon (sediment texture interpretation). A value of -999 indicates that no sample was available within a particular feature. (Source: U.S. Geological Survey)

   Range of values
   Minimum:	25.27
   Maximum:	100
   Units:	percent

   Avg_MUD

   Average percent weight (%) silt and clay within each qualitatively derived polygon. This field was automatically generated by Esri as a summary of the numeric attributes of the points that fall inside a polygon when point data (sample database) is joined to a polygon (sediment texture interpretation). A value of -999 indicates that no sample was available within a particular feature. (Source: U.S. Geological Survey)

   Range of values
   Minimum:	0
   Maximum:	73.2
   Units:	percent

   Carbonate

   Average percent weight (%) of carbonate within each qualitatively derived polygon. A few samples from Nantucket sound had received carbonate analysis and these data were incorporated into the CZM sample database. A value of -999 indicates that no sample was available within a particular feature. (Source: U.S. Geological Survey)

   Range of values
   Minimum:	0.02
   Maximum:	23.25
   Units:	percent

   Biogenic_c

   Description of carbonate sediment based on percent weight of carbonate. (Source: U.S. Geological Survey)

   Value	Definition
   trace	The weight percent of the coarse fraction (sand + gravel) that is carbonate is less than 2 percent
   present	The weight percent of the coarse fraction (sand + gravel) that is carbonate is more than 2 percent but less than 10 percent
   abundant	The weight percent of the coarse fraction (sand + gravel) that is carbonate is more than 10 percent but less than 50 percent
   unknown	The weight percent of the coarse fraction (sand + gravel) that is carbonate is unknown because no carbonate analysis was performed.

   Avg_GRAVEL_1

   Average percent weight (%) gravel (as determined from samples WITH and WITHOUT laboratory analyzed grain size statistics) within each qualitatively derived polygon. This field was automatically generated by Esri as a summary of the numeric attributes of the points that fall inside a polygon when point data (sample database) is joined to a polygon (sediment texture interpretation). A value of -999 indicates that no sample was available within a particular feature. (Source: U.S. Geological Survey)

   Range of values
   Minimum:	0
   Maximum:	100
   Units:	percent

   Avg_SAND_1

   Average percent weight (%) sand (as determined from samples WITH and WITHOUT laboratory analyzed grain size statistics) within each qualitatively derived polygon. This field was automatically generated by Esri as a summary of the numeric attributes of the points that fall inside a polygon when point data (sample database) is joined to a polygon (sediment texture interpretation). A value of -999 indicates that no sample was available within a particular feature. (Source: U.S. Geological Survey)

   Range of values
   Minimum:	0
   Maximum:	100
   Units:	percent

   Avg_MUD_1

   Average percent weight (%) mud (as determined from samples WITH and WITHOUT laboratory analyzed grain size statistics) within each qualitatively derived polygon. This field was automatically generated by Esri as a summary of the numeric attributes of the points that fall inside a polygon when point data (sample database) is joined to a polygon (sediment texture interpretation). A value of -999 indicates that no sample was available within a particular feature. (Source: U.S. Geological Survey)

   Range of values
   Minimum:	0
   Maximum:	100
   Units:	percent

   simple

   sediment nomenclature on the basis of 3 simple classes: sand, mud, hardbottom as defined in the CZM sample database (Source: U.S. Geological Survey)

   Value	Definition
   sand	Sediment whose primary component (greater than 50%) is sand
   hardbottom	Sediment whose primary component is rock, boulder, cobble, or coarse gravel
   mud	Sediment whose primary component (greater than 50%) is silt and clay

   water_dept

   Average seafloor elevation in meters below NAVD 88 within each qualitatively derived polygon. (Source: U.S. Geological Survey)

   Range of values
   Minimum:	-31.45
   Maximum:	-3.49
   Units:	meters
   Resolution:	0.01

Who produced the data set?

1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
   • U.S. Geological Survey
2. Who also contributed to the data set?
3. To whom should users address questions about the data?
   Elizabeth A. Pendleton

   U.S. Geological Survey

   Geologist

   384 Woods Hole Rd.

   Woods Hole, MA
   

   USA

   508-548-8700 x2226 (voice)

   508-457-2310 (FAX)

   ependleton@usgs.gov

Why was the data set created?

These sea floor sediment texture distributions were created from geophysical and sample data collected from south of Martha's Vineyard and north of Nantucket, and are used to characterize the sea floor in the area. Sediment texture maps are important data layers for marine resource managers charged with protecting fish habitat, delineating marine boundaries, and assessing environmental change due to natural or human impacts.

How was the data set created?

1. From what previous works were the data drawn?

   Denny and others, 2009 (source 1 of 6)

   Denny, J.F., Danforth, W.W., Foster, D.S., and Sherwood, C.R., 2009, Geophysical data collected off the south shore of Martha's Vineyard, Massachusetts: Open-File Report 2008-1288, U.S. Geological Survey, Reston, VA.

   Online Links:

   • http://pubs.usgs.gov/of/2008/1288/

   Type_of_Source_Media: online
   Source_Contribution:

   This report provided source geophysical data (sidescan-sonar, bathymetry, and seismic-reflection profiles) for the area south of Martha's Vineyard surrounding the Martha's Vineyard Coastal Observatory. The 2007 mapping was conducted aboard the M/V Megan T. Miller. High-resolution chirp seismic-reflection profiles were collected during U.S. Geological Survey field activity 2007-011-FA using an EdgeTech Geo-Star full spectrum sub-bottom (FSSB) system and SB-0512i towfish. Thorough descriptions of acquisition and processing parameters for the survey are provided by Denny and others (2009) in the report and seismic-reflection metadata. Shallow geologic framework and surficial geology were interpreted from post-processed chirp seismic-reflection profiles.

   Andrews and others, 2014 (source 2 of 6)

   Andrews, B.D., Ackerman, S.D., Baldwin, W.E., Foster, D.S., and Schwab, W.C., 2014, High-Resolution Geophysical Data from the Inner Continental Shelf: Vineyard Sound, Massachusetts: Open-File Report 2012-1006, U.S. Geological Survey, Reston, VA.

   Online Links:

   • https://pubs.usgs.gov/of/2012/1006/

   Type_of_Source_Media: online
   Source_Contribution:

   This report provided source geophysical data (sidescan-sonar, bathymetry, and seismic-reflection profiles) for the study area on the western side of Martha's Vineyard. The 2011 mapping was conducted on the R/V Scarlett Isabella during U.S. Geological Survey field activity 2011-004-FA. Chirp seismic-reflection data were collected using an EdgeTech Geo-Star FSSB subbottom profiling system and an SB-0512i towfish. Thorough descriptions of acquisition and processing parameters for each survey are provided by Andrews and others (2014) in the methods section and seismic-reflection metadata. Shallow geologic framework was interpreted from post-processed chirp seismic-reflection profiles. Only the data collected along the western shore of Martha’s Vineyard was used for this dataset.

   Ackerman and others, 2016 (source 3 of 6)

   Ackerman, S.D., L.L., Brothers, Foster, D.S., B.D., Andrews, W.E., Baldwin, and W.C., Schwab, 2016, High-Resolution Geophysical Data From the Inner Continental Shelf: South of Martha's Vineyard and North of Nantucket, Massachusetts: Open-File Report 2016-1168, U.S. Geological Survey, Reston, VA.

   Online Links:

   • https://pubs.usgs.gov/of/2016/1168/
   • https://doi.org/10.3133/ofr20161168

   Type_of_Source_Media: online
   Source_Contribution:

   This report provided source geophysical data (sidescan-sonar, bathymetry, and seismic-reflection profiles) for the majority of this study including offshore of southern Martha's Vineyard and north of Nantucket. These areas were surveyed with the R/V Scarlett Isabella 2013 during U.S. Geological Survey field activity 2013-003-FA. Seismic-reflection data were collected using an EdgeTech Geo-Star FSSB subbottom profiling system and an SB-0512i towfish. Thorough descriptions of acquisition and processing parameters for each survey are provided by Ackerman and others (2016) in the methods section and seismic-reflection metadata. Shallow geologic framework and surficial geology were interpreted from post-processed chirp seismic-reflection profiles.

   Andrews and others, 2018 (source 4 of 6)

   Andrews, Brian, Baldwin, Wayne, Sampson, Daniel, and Schwab, William, 2018, Continuous Bathymetry and Elevation Models of the Massachusetts Coastal Zone and Continental Shelf: data release DOI:10.5066/F72806T7, U.S. Geological Survey, Reston, VA.

   Online Links:

   • https://doi.org/10.5066/f72806t7

   Type_of_Source_Media: online
   Source_Contribution:

   This report provided source bathymetry for the study area including offshore of southern Martha's Vineyard and north of Nantucket. Thorough descriptions of the merging and processing parameters are provided by Andrews and others (2018) in the metadata.

   CZM sample database (source 5 of 6)

   Ford, K.H., Huntley, E.C., Sampson, D.W., and Voss, S., Unpublished Material, Massachusetts Sediment Database.

   Other_Citation_Details:

   This sample database has been compiled and vetted from existing samples and datasets by the Massachusetts Office of Coastal Zone Management. The data are currently unpublished, but may be acquired by contacting the CZM office: 251 Causeway St Boston, MA 02114 (617) 626-1000 czm@state.ma.us

   Type_of_Source_Media: digital vector
   Source_Contribution:

   Sediment sample databases of Ford and Voss (2010) and McMullen and others (2011) were combined then edited and supplemented with NOAA chart sampling data and bottom photos and descriptions by a group of GIS specialists at the Massachusetts Office of Coastal Zone Management (Emily Huntley, personal communication). These data contained sediment laboratory statistics when available, visual descriptions if sediment analysis was not performed or if the site was a bottom photograph, and classification fields of Barnhardt and others (1998), Shepard (1954), and Wentworth (1922) as well as average sediment statistics and phi size, when laboratory analysis was conducted.

   USACE-JALBTCX, 2009 (source 6 of 6)

   U.S. Army Corps of Engineers - Joint Airborne Lidar Bathymetry Center of Expertise, 2009, 2005 - 2007 US Army Corps of Engineers (USACE) Topo/Bathy Lidar: Maine, Massachusetts, and Rhode Island: NOAA National Ocean Service (NOS), Coastal Services Center (CSC), Charleston, SC.

   Online Links:

   • http://coast.noaa.gov/dataviewer/index.html?action=advsearch&qType=in&qFld=ID&qVal=116
   • ftp://coast.noaa.gov/pub/DigitalCoast/lidar1_z/geoid12a/data/116

   Type_of_Source_Media: online
   Source_Contribution:

   The source lidar data for the very nearshore (less than -5 m) region along the western and southern shoreline of Martha's Vineyard. Lidar (Light Detection and Ranging) data were acquired with a SHOALS-1000T (for hydrographic and topographic data) using the Joint Airborne Joint Airborne LiDAR Bathymetry Center of Expertise (JALBTCX) lidar plane. These data are now publically available in LAS lidar format via NOAA's Digital Coast website.

2. How were the data generated, processed, and modified?

   Date: 2017 (process 1 of 3)

   The texture and spatial distribution of sea-floor sediment were qualitatively analyzed in ArcGIS using several input data sources (listed in the source contribution), including acoustic backscatter, bathymetry, seismic-reflection profile interpretations, bottom photographs, and sediment samples. The interpretation was initiated by creating a new polygon feature class in an ArcMap 10.5 file geodatabase based on the extent of the regional bathymetric DEM (Andrews and others, 2018, and clipped to the extent of this study area). The polygon was then partitioned into multiple sediment texture polygons using 'cut polygon' and 'auto-complete polygon' in an edit session. In general, polygon editing was done at scales between 1:8,000 and 1:25,000, depending on the size of the traced feature and the resolution of the source data. Some areas interpreted as a single sediment textural unit may contain multiple polygons that indicate different interpretation confidence levels. The following numbered steps outline the workflow of the data interpretation. 1. Backscatter intensity data was the first input. Changes in backscatter were digitized to outline possible changes in sea-floor texture on the basis of acoustic return. Areas of high backscatter (light colors) have strong acoustic reflections and suggest boulders, gravels, and generally coarse sea-floor sediments. Low-backscatter areas (dark colors) have weak acoustic reflections and are generally characterized by finer grained material such as muds and fine sands. 2. The polygons were then refined and edited using gradient, rugosity, and hillshaded relief images derived from interferometric and multibeam swath bathymetry. Areas of rough topography and high rugosity are typically associated with rocky areas, while smooth, lower-relief regions tend to be blanketed by fine-grained sediment. These bathymetric derivatives helped to refine polygon boundaries where changes from primarily rock to primarily gravel may not have been apparent in backscatter data, but could easily be identified in hillshaded relief and slope changes. 3. The third data input (where available) was the stratigraphic interpretation of seismic-reflection profiles, which further constrained the extent and general shape of sea-floor sediment distributions and rocky outcrops, and also provided insight concerning the likely sediment texture of the feature on the basis of glacial or post-glacial origin. Seismic lines and the surficial geologic maps derived from them are used here as input data and were collected at typically 100-meter spacing, with tie-lines generally spaced 1-km apart. 4. After all the sea-floor features were traced from the geophysical data, a spatial join was conducted to provide grain size statistics based on sediment samples. The fields that contain sediment texture statistics or mean water depth information were created and populated using data joins or zonal statistics functions within ArcMap (version 10.5). The fields beginning with "Avg_" and the 'Count_' field were automatically generated by computing a data join where the CZM sample database (vector points) was edited to include only the samples with laboratory sediment analysis and joined to the qualitatively derived polygon file. The fields beginning with "Avg_" and ending in "_1" were automatically generated by computing a data join where the CZM sample database (vector points) included samples with laboratory and visual sediment analysis. Each polygon was given an average of the numeric attributes of the points (with laboratory grain size analysis or with and without laboratory analysis) that fall inside it, and the count field shows how many laboratory analyzed points fall inside each polygon. 153 samples were analyzed in the laboratory. Several fields that were not needed were deleted after the join. A mean water depth (NAVD 88) field was created using ArcMap (version 10.5): ArcToolbox - Spatial Analyst Tools > Zonal > Zonal Statistics as Table, where the mean water depth for each polygon (input zone data using the zone field sed_type) was derived from the regional bathymetric DEM (see Andrews and others, 2018). No data raster values were ignored in determining the output value for each polygon zone. The output was saved to a table, which was joined with the sediment type polygon shapefile. All of the joined fields except MEAN were turned off. 5. A new field was created in the shapefile called 'Barnhardt'. Seafloor composition observations from sediment samples and bottom photographs/video were used to define sediment texture for the polygons using Barnhardt and others (1998) classification. Samples with laboratory grain size analysis were preferred over visual descriptions when defining sediment texture throughout the study area; however within large polygons with a small number of samples (1 or 2), visual samples were considered and used to provide additional insight on the mean sediment texture. Bottom photo stations are typically around 2-km apart, but do not always provide a clear view of the sea floor, and the density of sediment samples varies throughout the study area. Some polygons contained more than one sample with grain-size statistics, while others contained none. For multiple samples within a polygon, the dominant sediment texture was used to classify sediment type (often aided by the 'data join' sediment statistics described in an earlier processing step). In rocky areas, bottom photos were used in the absence of sediment samples to qualitatively define sediment texture. Polygons that lacked sample information were texturally defined through extrapolation from adjacent or proximal polygons of similar acoustic character that did contain sediment samples. Person who carried out this activity:
   

   Elizabeth Pendleton

   U.S. Geological Survey

   Geologist

   384 Woods Hole Rd.

   Woods Hole, MA
   

   USA

   508-548-8700 x2259 (voice)

   508-457-2310 (FAX)

   ependleton@usgs.gov

   Date: 2017 (process 2 of 3)

   After some additional qualitative polygon editing and reshaping was done in order to create a sediment map that was in the best agreement with all input data: lidar, bathymetry, backscatter, seismic interpretations, bottom photographs, and sediment samples, 4 more fields were added (ArcMap version 9.3.1). The first field, 'simple' is just 3 classes: sand, mud, or hardbottom. A field 'Confidence' was added as a data interpretation confidence, which describes how confident we are in the interpretation on the basis of the number and quality of the input data sources (see the entity and attribute sections for more information on these fields). The last 2 ('Carbonate' and 'Biogenic_C') fields were added and populated manually to incorporate percent carbonate information that accompanied sample analyses in Nantucket Sound. Finally, a second join was conducted similar to the previous processing steps, but allowing all samples with analysis (visual and laboratory) to be incorporated into the statistics.
   The polygon feature class containing the sediment texture units was assigned topology rules, (i.e. no gaps and no overlaps). Topology errors were identified and remedied using the topology toolbar in ArcMap (10.5). Finally, the sediment texture was exported from the geodatabase as a shapefile. Person who carried out this activity:
   

   Elizabeth Pendleton

   U.S. Geological Survey

   Geologist

   384 Woods Hole Rd.

   Woods Hole, MA
   

   USA

   508-548-8700 x2259 (voice)

   508-457-2310 (FAX)

   ependleton@usgs.gov

   Data sources used in this process:

   • polygons containing sediment texture units

   Date: 07-Aug-2020 (process 3 of 3)

   Added keywords section with USGS persistent identifier as theme keyword. Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: VeeAnn A. Cross

   Marine Geologist

   384 Woods Hole Road

   Woods Hole, MA
   

   508-548-8700 x2251 (voice)

   508-457-2310 (FAX)

   vatnipp@usgs.gov

3. What similar or related data should the user be aware of?
   Kelley, J.T., Barnhardt, W.A., Belknap, D.F., Dickson, S.M., and Kelley, A.R., 1998, The Seafloor Revealed: The Geology of the Northwestern Gulf of Maine Inner Continental Shelf: Maine Geological Survey Open-File Report 96-6, Maine Geological Survey, Natural Resources Information and Mapping Center, Augusta, Maine.

   Online Links:

   • https://digitalmaine.com/mgs_publications/119/

   Barnhardt, W.A., Kelley, J.T., Dickson, S.M., and Belknap, D.F., 1998, Mapping the Gulf of Maine with Side-scan Sonar: a New Bottom-type Classification for Complex Seafloors: Journal of Coastal Research 14(2), Coastal Education and Research Foundation, Inc., Royal Palm Beach, FL.

   McMullen, K.Y., Paskevich, V.F., and Poppe, L.J., 2014, USGS East-coast Sediment Analysis: Procedures, Database, and GIS Data: Open-File Report 2005-1001, U.S. Geological Survey, Reston, VA.

   Online Links:

   • https://pubs.usgs.gov/of/2005/1001/

   Ford, K.H., and Voss, S.E, 2010, Seafloor Sediment Composition in Massachusetts Determined Using Point Data: Massachusetts Division of Marine Fisheries Technical Report TR-45, Massachusetts Division of Marine Fisheries, New Bedford, MA.

   U.S. Geological Survey, 2013, Geologic Mapping of the Seafloor Offshore of Massachusetts: U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

   Online Links:

   • https://woodshole.er.usgs.gov/project-pages/coastal_mass/

   Other_Citation_Details:

   Geologic mapping of the Massachusetts inner continental shelf is a cooperative effort that was initiated in 2003 by the U.S. Geological Survey (USGS) and the Massachusetts Office of Coastal Zone Management (CZM). The National Oceanic and Atmospheric Administration (NOAA-NOS) is also an important partner and contributes hydrographic data that are integrated into the maps. The overall goal of this cooperative is to determine the geologic framework of the sea floor inside the 3-mile limit of State waters, using high-resolution geophysical techniques, sediment sampling, and sea-floor photography. Any source data used to generate interpretative maps and data products are cited in detail in the source citation section of this metadata file.

   Baldwin, Wayne E., Foster, David S., Pendleton, Elizabeth A., Barnhardt, Walter A., Schwab, William C., Andrews, Brian D., and Ackerman, Seth, 2016, Shallow geology, sea-floor texture, and physiographic zones of Vineyard and western Nantucket Sounds, Massachusetts: Open-File Report 2016-1119, US Geological Survey, Reston, VA.

   Online Links:

   • https://doi.org/10.3133/ofr20161119

   Foster, David S., Baldwin, Wayne E., Barnhardt, Walter A., Schwab, William C., Ackerman, Seth D., Andrews, Brian D., and Pendleton, Elizabeth A., 2015, Shallow geology, sea-floor texture, and physiographic zones of Buzzards Bay, Massachusetts: Open-File Report 2014-1220, U.S. Geological Survey, Reston, VA.

   Online Links:

   • https://doi.org/10.3133/ofr20141220

   Pendleton, Elizabeth E., Barnhardt, Walter A., Baldwin, Wayne E., Foster, David S., Schwab, William C., Andrews, Brian D., and Ackerman, Seth D, 2015, Sea-floor texture and physiographic zones of the inner continental shelf from Salisbury to Nahant, Massachusetts, including the Merrimack Embayment and Western Massachusetts Bay: Open-File Report 2015-1153, U.S. Geological Survey, Reston, VA.

   Online Links:

   • https://doi.org/10.3133/ofr20151153

   Pendleton, Elizabeth A., Baldwin, Wayne E., Barnhardt, Walter A., Ackerman, Seth D., Foster, David S., Andrews, Brian D., and Schwab, William C., 2013, Shallow Geology, Seafloor Texture, and Physiographic Zones of the Inner Continental Shelf from Nahant to Northern Cape Cod Bay, Massachusetts: Open-File Report 2012-1157, U.S. Geological Survey, Reston, VA.

   Online Links:

   • https://pubs.usgs.gov/of/2012/1157/

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

1. How well have the observations been checked?
   
2. How accurate are the geographic locations?
   These data were produced qualitatively from acoustic and sample data with varying resolutions. Horizontal uncertainty associated with sample collection especially, can be quite high (100's of meters), much higher than positional uncertainty associated with acoustic data (usually less than 10's of meters). The date of sample collection and ship station positioning all contribute to sample position uncertainty. These qualitatively derived polygons outlining sea floor features are estimated to be within 50 meters, horizontally, but locally may be higher when delineation is based on sample information alone.
3. How accurate are the heights or depths?
   
4. Where are the gaps in the data? What is missing?
   These sediment cover data are defined for areas where source data exists. In general, gaps in the coverage coincide with gaps in the source data. However, some small data gaps were interpreted through extrapolation. Areas of lower data quality and incomplete coverage are noted in a data confidence attribute field. All of the interpretive layer bounds in this report are a little short of the data bounds in western Vineyard Sound, this is because this dataset abuts the interpretive layers of Baldwin and others (2016), and are not redundant with that interpretation.
5. How consistent are the relationships among the observations, including topology?
   These data were drawn and vetted for accuracy using the source input raster files and point sample data described in the processing steps and source contributions. Overlapping features and unintentional gaps within the survey area were identified using the topology checker in ArcMap (version 10.5) and corrected or removed. Not all digitized sea-floor features contained sample information, so often the sea-floor texture is characterized by the nearest similar feature that contains a sample. Conversely, sometimes a digitized feature contained multiple samples and not all of the samples within the feature were in agreement (of the same texture). In these cases all data (raster and sample) were considered, and the dominant sediment texture from sample analyses did not necessarily determine the primary texture assigned to a polygon. Samples from rocky areas often only consist of bottom photographs, because large particle size often prevents the recovery of a sediment sample. Bottom photo classification can be subjective, such that determining the sediment type that is greater than 50% of the view frame is estimated by the interpreter and may differ among interpreters. Bottom photo transects often reveal changes in the sea floor over distances of less than 100 m and these changes are often not resolved in acoustic data. Heterogeneous sea floor texture can change very quickly, and many small-scale changes will not be detectable or mappable at a scale of 1:25,000. The boundaries of polygons are often inferred on the basis of sediment samples, and even boundaries that are traced on the basis of amplitude changes in geophysical data are subject to migration. Polygon boundaries should be considered an approximation of the location of a change in texture.

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:

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. Additionally, there are limitations associated with qualitative sediment mapping interpretations. Because of the scale of the source geophysical data and the spacing of samples, not all changes in sea floor texture are captured. The data were mapped between 1:8,000 and 1:25,000, but the recommended scale for application of these data is 1:25,000.

1. Who distributes the data set? (Distributor 1 of 1)
   
   U.S. Geological Survey

   Attn: GS ScienceBase

   Denver Federal Center, Building 810, Mail Stop 302

   Denver, CO
   

   United States

   1-888-275-8747 (voice)

   sciencebase@usgs.gov
2. What's the catalog number I need to order this data set? MV_ACK_sedtexture (and the related shapefile componensts) contains qualitatively derived polygons that define sea floor sediment texture offshore of western and southern Martha's Vineyard and north of Nantucket, MA. The dataset also contains a browse graphic (MV_ACK_sedtexture_browse.png), and the associated CSDGM metadata in XML format.
3. What legal disclaimers am I supposed to read?

   Neither the U.S. Government, the Department of the Interior, nor the USGS, nor any of their employees, contractors, or subcontractors, make any warranty, express or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, nor represent that its use would not infringe on privately owned rights. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the U.S. Geological Survey in the use of these data or related materials. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government

4. How can I download or order the data?
   • Availability in digital form:

     Data format:	shapefile (version ArcGIS v. 10.5.1 shapefile) Size: 0.39
     Network links:	https://www.sciencebase.gov/catalog/item/5bfd6064e4b0815414ca39e1 https://www.sciencebase.gov/catalog/file/get/5bfd6064e4b0815414ca39e1 https://doi.org/10.5066/P9E9EFNE

     Data format:	ArcGIS v. 10.5.1 shapefile provided through a WMS (web mapping service). in format WMS
     Network links:	https://www.sciencebase.gov/catalogMaps/mapping/ows/5aff06afe4b0da30c1bfcdf1?service=wms&request=getcapabilities&version=1.3.0 https://www.sciencebase.gov/catalog/item/5aff06afe4b0da30c1bfcdf1 https://doi.org/10.5066/P9E9EFNE

     Data format:	ArcGIS v. 10.5.1 shapefile provided through a WFS (web feature service). in format WFS
     Network links:	https://www.sciencebase.gov/catalogMaps/mapping/ows/5aff06afe4b0da30c1bfcdf1?service=wfs&request=getcapabilities&version=1.0.0 https://www.sciencebase.gov/catalog/item/5aff06afe4b0da30c1bfcdf1 https://doi.org/10.5066/P9E9EFNE

   • Cost to order the data: None

5. What hardware or software do I need in order to use the data set?

   These data are available in Environmental Systems Research Institute (Esri) shapefile format. The user must have software capable of importing and processing this data type.

Who wrote the metadata?

Dates:

Last modified: 07-Aug-2020
Last Reviewed: 2017

Metadata author:

Elizabeth A Pendleton

U.S. Geological Survey

Geologist

384 Woods Hole Rd.

Woods Hole, MA

USA

508-548-8700 x2259 (voice)

508-457-2310 (FAX)

ependleton@usgs.gov

Metadata standard:

FGDC Content Standards for Digital Geospatial Metadata (FGDC-STD-001-1998)