PK TwWH CMECS Benthic Cover/de_db10.gdb/PK Z_KHulv lv / CMECS Benthic Cover/de_db10-biotic_Metadata.xml
Delaware Bay Benthic Habitats
Bartholomew Wilson, Delaware Bay Benthic Mapping Project
Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management (OCM)
2015
Delaware Bay, Delaware Benthic Habitats 2010 Biotic
vector digital data
Charleston, SC
NOAA's Ocean Service, Office for Coastal Management (OCM)
ftp://ftp.coast.noaa.gov/pub/benthic/Benthic_Cover_Data/DE_DelawareBay.zip
https://coast.noaa.gov/digitalcoast/publications/cmecs
http://www.cmecscatalog.org/
https://coast.noaa.gov/digitalcoast/
https://coast.noaa.gov/
The Coastal Program of Delaware's Division of Soil and Water conservation (DNREC), the University of Delaware, Partnership for the Delaware Estuary, and the New Jersey Department of Environmental Protection have partnered and are carrying out a bottom and sub-bottom imaging project to identify and map the benthic habitat and sub-bottom sediments of Delaware Bay and River. This project was initiated to better understand the distribution of bottom sediment types, habitat biodiversity, and most importantly, human's impact on the bay bottom and its living resources. The project integrates the use of three types of acoustical systems: Roxann Seabed classification system, chirp sub-bottom profiling, and multi-beam bathymetric mapping. Verification of the acoustic data with bottom and sub-bottom sediments is performed through the collection of bra banc core samples and underwater video images.
The Delaware Bay project has four principle goals. The first is to determine the location and extent of oyster reef habitats in upper Delaware Bay which will greatly improve the ability of Delaware and New Jersey to manage these commercial resources. The second goal is to evaluate short-nose, and atlantic sturgeon habitat. Sturgeon in the bay have shown an affinity for certain regions within the system. A better understanding of the conditions in these areas would improve the ability to assess the impact of dredging or other activities. A third goal was to identify potential borrow sites for beach re-nourishment materials. Finally, the high-resolution bathymetry collected in the bay will improve the understanding of sediment movement and other human impacts on the bay
2004
2010
ground condition
As needed
-75.6056
-75.16708
39.83218
38.80217
ISO 19115 Topic Category
environment
None
Benthic Habitat
Bottom Sediments
Shellfish Beds
SAV
Environmental Monitoring
None
CMECS
Coastal and Marine Ecological Classification Standard
Biotic Component
None
Delaware
Delaware River
State of Delaware
State of New Jersey
Delaware Bay
USA
None
Surface Sediment Mapping
Sediment Water Interface
Public Information
None
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
https://coast.noaa.gov/data/Images/Collections/BenthicCover_thumbnail.jpg
Sample of benthic cover data
JPEG
Ground truth information was collected at the time of the original surveys to calibrate the mapping and ensure the accuracy of the habitat designations.
Very shallow areas within the Delaware River/Bay system were not surveyed due to access limitations.
Coastal Program of Delaware's Division of Soil and Water Conservation (DNREC)
2010
Delaware Bay Benthic Mapping Project
CD-ROM
2004
2010
ground condition
Delaware Coastal Program
This is a compilation of several habitat data sets collected through a variety of methods.
Bivalve Reef (Oyster, Identified Oyster, and Corbicula) polygons were derived from the bottom sediment map that were constructed by the utilization of a Roxann Seabed Classification System and extensive sediment grab samples bottom sediment map that were constructed by the utilization of a Roxann Seabed Classification System and extensive sediment grab samples. Corbicula fluminea beds were identified on the Roxann output by the occurrence of data point which had moderate to high hardness return (E2) and an anomalously high roughness return (E1), as compared to the adjacent sediments. The sediments surrounding these beds are usually of a finer (silt to clay) grain size, with low roughness and hardness values. The regions where these types of returns were encountered were then sampled with a grab sampler. Several samples (2 to 3 samples) were collected at each station to increase the likely hood that Corbicula would be encountered, if it was indeed located in that region. Corbicula beds can have varying densities, distributions, and bed configurations; hence this sampling scheme was enacted to account for this spatial variability.
Submersed Rooted Vascular Plants (Vallisneria Americana) beds outlines were identified through the same bottom sediment map used for delineating bivalve reef. SRV beds were identified on the Roxann output by the occurrence of data point which had very low hardness returns (E2) and an anomalously high roughness return (E1), as compared to the adjacent sediments. The regions where these types of returns were encountered, where then sampled with a grab sampler. Several samples (2 to 3 samples) were collected at each station to increase the likely hood that SAV would be encountered, if it was indeed located in that region. SAV beds can have varying densities, distributions, and bed configurations; hence the sampling scheme was enacted to account for this spatial variability.
Outcrop areas consist of Cretaceous sediment that is at the river bottom surface (or near the surface ~1 to 2 cm). These areas are scour or erosional zones within the river. The outcropping material consists of highly compacted/de-watered silty fine sand to fine sandy silts, which contain relict burrow casts and glauconite. Outcrop boundaries were derived from the bottom sediment map raster grid.
2008
Bartholomew Wilson
DNREC
mailing and physical
89 Kings Highway
Dover
DE
19901
USA
302-739-9283
The bottom sediment map was constructed by the utilization of a Roxann Seabed Classification System and extensive
sediment grab samples. Data was collected in a gridded trackline configuration, with tracklines spacing of 100 meters parallel to
the shoreline and 200 meters perpendicular to the shoreline. This project is an extension of the work currently being performed in
Delaware waters by DNREC's Delaware Coastal Program's Delaware Bay Benthic Mapping Project. The bottom sediment point data, which
has been classified according to the existing benthic mapping Roxann box plot, are converted from a number that categorizes the
point according to its corresponding box (in the Roxann) into a number which reflects the sediment properties of each box in
relation to one another. A ranking scale is used to allow a statistical gridding scheme to interpolate between sediment data
points, while minimizing erroneous sediment classifications and allowing gradational sediment deposits to be gridded. A ranking
scale from 0 to 28 was used for this project, with 0 representing the finest grained classifications (fluidized clay) and 28
representing the coarsest grained classifications (dense shell material). Table 1 illustrates the distribution of sediment
classifications along the ranking scale, which takes into account the relation of sediment types and grain sizes to one another
using both the Wentworth Scale and Shepard's classification system. Finer grains are more similar in their deposition
environments, such as clay and silts, because they reflect similar current regimes, sorting, and reworking patterns (Poppe et al.,
2003). While coarse sediments are much more dissimilar to finer grains, with respect to current velocities, sorting, and winnowing,
the finer grains are much more closely related in their sediment diameters that the coarser grains as you increase in Phi size
and/or diameter. These account for the close clustering of coarse grained deposit descriptions at the upper end of the ranking
scale, while the finer grained sediments show a gradation as you increase in the rating scale.The bottom sediment data is gridded in Surfer degrees 8, a surface and terrain modeling program, using block kriging and a nugget effect. This statistical griding technique estimates the average value of a variable within a prescribed local area (Isaaks and Srivastava, 1989). Block kriging utilizes the existing point data values, weights the values of the data depending upon the proximity to the point being estimated, to discretize the local area into an array of estimated data value points and then averaging those individual point estimates together to get an average estimated value over the area of interest (Isaaks and Srivastava, 1989). A variogram is constructed for the data, and the resultant spatial model that is developed from the variogram is used in the block kriging surface model to more accurately interpolate the sediment data . The fitted model was a nugget effect (with an error variance of 21.8%) and a linear model (with a slope of 0.00286 and an anisotropy of 1, which represents a complete lack of spatial correlation).The accuracy of the estimation is dependent upon the grid size of the area of interpolation, the size of each cell within the grid, and the number of discretized data points that are necessary to estimate the cells within that grid spacing. The grid size that was used to interpolate the bottom sediment maps was 442 lines x 454 lines, with a cell size of 44.93 m2. The nugget effect is added to allow the griding to assume there is very little, if any, lateral correlation or trends within the bottom sediment (Isaaks and Srivastava, 1989). The nugget effect model entails a complete lack of spatial correlation; the point data values at any particular location bear no similarity even to adjacent data values (Isaaks and Srivastava, 1989). Without the nugget effect the gridding would assume that you could only have a linear progression of sediment types and would insert all the sediment types along the scale between two sediment types (i.e. silty fine to medium sands and fine to medium sand with varying amounts of pebbles would be inserted between fine sand and coarse sand even though that is not what is occurring along the bottom. The sediment data is gridded with no drift for the data interpolation, also helping to minimize erroneous classifications. Sediment Classification Ranking Sediment Description 0-11-2 Clay, 2-33-44-55-66-7 Silt,7-88-9 Sandy Silts, 9-1010-11 Fine Sand, 11-1212-13 Silty Fine to Medium Sands, 13-14 Silty Medium Sand, 14-1515-16 Fine to Medium Sand, 16-1717-18 Fine to Medium Sand with abundant shell material and/or pebbles, 18-1919-20 Coarse Sand with varying amounts of pebbles, 20-2121-2222-23 Moderate Shell Material/Sandy Pebbles, 23-2424-2525-26 Abundant Shell Material/Gravel, 26-2727-28 Dense Oyster Shell.
2008
Bartholomew Wilson
DNREC
mailing and physical
89 Kings Highway
Dover
Delaware
19901
USA
302-739-9283
Separate shapefiles for oyster beds, identified oyster beds, SAV, corbicula, outcroppings, and depositional zones were integrated into a single feature layer to produce a comprehensive benthic cover polygon data set using the ArcMap 10 Merge tool. A review of the bottom sediment raster data sets (Delaware River/Bay, Upper Shelf, and Roxann 2004 which lies along the Delaware near-shore area) indicated that they consisted entirely of various types of unconsolidated sediments ranging from fluidized clay to oyster shells. Each of these rasters were converted into a single Unconsolidated Sediments polygon layer, merged together and then joined with the other features (oyster, SAV, etc.) to form a continuous benthic cover layer for the entire project area. As a final step habitat classes from the Florida System for Classifying Habitats in Estuarine and Marine Environments (SCHEME) were added to the attribute table for this single polygon file to ensure consistency with other Digital Coast benthic cover data sets.
2012
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
The bottom sediment maps (source for the unconsolidated sediments polygons in the vector data set) were constructed by
the utilization of a Roxann Seabed Classification System and extensive sediment grab samples. Data was collected in a gridded
trackline configuration, with tracklines spacing of 100 meters parallel to the shoreline and 200 meters perpendicular to the
shoreline.This project is an extension of the work currently being performed in Delaware waters by DNREC's Delaware Coastal
Program's Delaware Bay Benthic Mapping Project.The bottom sediment point data, which has been classified according to the existing
benthic mapping Roxann box plot, are converted from a number that categorizes the point according to its corresponding box (in the
Roxann) into a number which reflects the sediment properties of each box in relation to one another. A ranking scale is used to
allow a statistical griding scheme to interpolate between sediment data points, while minimizing erroneous sediment classifications
and allowing gradational sediment deposits to be gridded. A ranking scale from 0 to 28 was used for this project, with 0
representing the finest grained classifications (fluidized clay) and 28 representing the coarsest grained classifications (dense
shell material). This ranking scale takes into account the relation of sediment types and grain sizes to one another using both the
Wentworth Scale and Shepard's classification system. Finer grains are more similar in their deposition environments, such as
clay and silts, because they reflect similar current regimes, sorting, and reworking patterns (Poppe et al., 2003). While coarse
sediments are much more dissimilar to finer grains, with respect to current velocities, sorting, and winnowing, the finer grains
are much more closely related in their sediment diameters that the coarser grains as you increase in Phi size and/or diameter.
These account for the close clustering of coarse grained deposit descriptions at the upper end of the ranking scale, while the
finer grained sediments show a gradation as you increase in the rating scale.The bottom sediment data is gridded in Surfer degrees 8, a
surface and terrain modeling program, using block kriging and a nugget effect. This statistical griding technique estimates the
average value of a variable within a prescribed local area (Isaaks and Srivastava, 1989). Block kriging utilizes the existing point
data values, weights the values of the data depending upon the proximity to the point being estimated, to discretize the local area
into an array of estimated data value points and then averaging those individual point estimates together to get an average
estimated value over the area of interest (Isaaks and Srivastava, 1989). A variogram is constructed for the data, and the resultant
spatial model that is developed from the variogram is used in the block kriging surface model to more accurately interpolate the
sediment data . The fitted model was a nugget effect (with an error variance of 21.8%) and a linear model (with a slope of 0.00286
and an anisotropy of 1, which represents a complete lack of spatial correlation).The accuracy of the estimation is dependent upon
the grid size of the area of interpolation, the size of each cell within the grid, and the number of discretized data points that
are necessary to estimate the cells within that grid spacing. The grid size that was used to interpolate the bottom sediment maps
was 442 lines x 454 lines, with a cell size of 44.93 m2. The nugget effect is added to allow the griding to assume there is very
little, if any, lateral correlation or trends within the bottom sediment (Isaaks and Srivastava, 1989). The nugget effect model
entails a complete lack of spatial correlation; the point data values at any particular location bear no similarity even to
adjacent data values (Isaaks and Srivastava, 1989). Without the nugget effect the griding would assume that you could only have a
linear progression of sediment types and would insert all the sediment types along the scale between two sediment types (i.e. silty
fine to medium sands and fine to medium sand with varying amounts of pebbles would be inserted between fine sand and coarse sand
even though that is not what is occurring along the bottom. The sediment data is gridded with no drift for the data interpolation,
also helping to minimize erroneous classifications. Sediment Classification Ranking Sediment Description: 0-11-2 Clay, 2-33-44-55-66-7
Silt, 7-88-9 Sandy Silts, 9-1010-11 Fine Sand, 11-1212-13 Silty Fine to Medium Sands, 13-14 Silty Medium Sand, 14-1515-16 Fine to
Medium Sand, 16-1717-18 Fine to Medium Sand, with abundant shell material and/or pebbles, 18-1919-20 Coarse Sand, with varying
amounts of pebbles 20-2121-2222-23 Moderate Shell Material / Sandy Pebbles, 23-2424-2525-26 Abundant Shell Material / Gravel 26-2727-28 Dense Oyster Shell
2012
The data were converted from a single ESRI polygon shapefile classified according to the System for Classifying Habitats in Estuarine and Marine Environments (SCHEME) to the Coastal and Marine Ecological Classification Standard (CMECS) 2012 format (which can be found at https://coast.noaa.gov/digitalcoast/tools/cmecs-crosswalk) which produces separate geoform, biotic, and biotic feature layers from the original input benthic habitat dataset. This biotic feature layer contains CMECS biotic component attributes where an "Equal" or "Nearly Equal" SCHEME value was present in the original data. Polygons for which no biotic information was present have been removed. No other changes to the original polygon boundaries or any other alterations of the original SCHEME data were made during this process.
2015
Vector
G-polygon
Universal Transverse Mercator
18
0.99960000
-75.00000000
0.0
500000.00000000
0.0
coordinate pair
0.0000001
0.0000001
meters
D North American 1983
GRS 1980
6378137.0
298.257222101
Biotic
Shallow benthic habitats CMECS 2012 biotic component polygons
NOAA Office for Coastal Management
OBJECTID
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
SHAPE
Feature geometry.
Esri
Coordinates defining the features.
Shape_Length
Length of line features in meters
Esri
Distance
Shape_Area
Polygon area in square meters
Esri
Area
CMECS_CODE
CMECS biotic unit code.
Coastal and Marine Ecological Classification Standard, FGDC 2012
Alphanumeric code for CMECS units
B_SETTING
Biotic Setting - Indication of whether the biota are attached or closely associated with the benthos or are suspended or floating in the water column.
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of biotic setting units; CMECS FGDC 2012
See definitions of biotic setting units; CMECS FGDC 2012
CMECS FGDC 2012
B_CLASS
Biotic Class - Dominant (percent cover) taxonomy and life forms of the living components of the sampled area at a fairly coarse level.
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of biotic class units; CMECS FGDC 2012
See definitions of biotic class units; CMECS FGDC 2012
CMECS FGDC 2012
B_SUBCLASS
Biotic Subclass - Dominant (percent cover) taxonomy and life forms of the living components of the sampled area at a fairly coarse level
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of biotic subclass units; CMECS FGDC 2012
See definitions of biotic subclass units; CMECS FGDC 2012
CMECS FGDC 2012
B_GROUP
Biotic Group - Functional groupings of characteristic biological types based on finer distinctions of taxonomy, structure, position, environment, and salinity levels
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of biotic group units; CMECS FGDC 2012
See definitions of biotic group units; CMECS FGDC 2012
CMECS FGDC 2012
B_COMMUNITY
Biotic Community - repeatable, characteristic assemblages of organisms that are relatively uniform in structure, species composition, and habitat conditions
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of biotic community units; CMECS FGDC 2012
See definitions of biotic community units; CMECS FGDC 2012
CMECS FGDC 2012
Description
Descriptive information on biotic units
Dewberry, Inc./NOAA Office for Coastal Management
Free text further describing biotic units
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
Downloadable Data
NOAA provides no warranty, nor accepts any liability occurring from any incomplete, incorrect, or misleading data, or from any incorrect, incomplete, or misleading use of the data. It is the responsibility of the user to determine whether or not the data is suitable for the intended purpose.
20160211
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
FGDC Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998
local time
PK `KH9E4 4 4 CMECS Benthic Cover/de_db10-geodatabase_Metadata.xml
Delaware Bay Benthic Habitats
Bartholomew Wilson, Delaware Bay Benthic Mapping Project
Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management (OCM)
2015
Delaware Bay, Delaware Benthic Habitats 2010 Geodatabase
vector digital data
Charleston, SC
NOAA's Ocean Service, Office for Coastal Management (OCM)
ftp://ftp.coast.noaa.gov/pub/benthic/Benthic_Cover_Data/DE_DelawareBay.zip
https://coast.noaa.gov/digitalcoast/publications/cmecs
http://www.cmecscatalog.org/
https://coast.noaa.gov/digitalcoast/
https://coast.noaa.gov/
The Coastal Program of Delaware's Division of Soil and Water conservation (DNREC), the University of Delaware, Partnership for the Delaware Estuary, and the New Jersey Department of Environmental Protection have partnered and are carrying out a bottom and sub-bottom imaging project to identify and map the benthic habitat and sub-bottom sediments of Delaware Bay and River. This project was initiated to better understand the distribution of bottom sediment types, habitat biodiversity, and most importantly, human's impact on the bay bottom and its living resources. The project integrates the use of three types of acoustical systems: Roxann Seabed classification system, chirp sub-bottom profiling, and multi-beam bathymetric mapping. Verification of the acoustic data with bottom and sub-bottom sediments is performed through the collection of bra banc core samples and underwater video images.
The Delaware Bay project has four principle goals. The first is to determine the location and extent of oyster reef habitats in upper Delaware Bay which will greatly improve the ability of Delaware and New Jersey to manage these commercial resources. The second goal is to evaluate short-nose, and atlantic sturgeon habitat. Sturgeon in the bay have shown an affinity for certain regions within the system. A better understanding of the conditions in these areas would improve the ability to assess the impact of dredging or other activities. A third goal was to identify potential borrow sites for beach re-nourishment materials. Finally, the high-resolution bathymetry collected in the bay will improve the understanding of sediment movement and other human impacts on the bay
This file geodatabase contains three feature layers corresponding to the CMECS 2012 Geoform, Substrate, and Biotic components. These layers were converted from an earlier version classified according to the System for Classifying Habitats in Estuarine and Marine Environments (SCHEME) using the CMECS Crosswalk Tool. Each feature layer has its own metadata record describing the attributes, and data development methods associated with it.
2004
2010
ground condition
As needed
-75.6056
-75.16708
39.83218
38.80217
ISO 19115 Topic Category
environment
None
Benthic Habitat
Bottom Sediments
Shellfish Beds
SAV
Environmental Monitoring
None
CMECS
Coastal and Marine Ecological Classification Standard
Geoform Component
Biotic Component
Substrate Component
None
Delaware
Delaware River
State of Delaware
State of New Jersey
Delaware Bay
USA
None
Surface Sediment Mapping
Sediment Water Interface
Public Information
None
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
https://coast.noaa.gov/data/Images/Collections/BenthicCover_thumbnail.jpg
Sample of benthic cover data
JPEG
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
Downloadable Data
NOAA provides no warranty, nor accepts any liability occurring from any incomplete, incorrect, or misleading data, or from any incorrect, incomplete, or misleading use of the data. It is the responsibility of the user to determine whether or not the data is suitable for the intended purpose.
20160211
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
FGDC Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998
local time
PK Z`KHut t 0 CMECS Benthic Cover/de_db10-geoform_Metadata.xml
Delaware Bay Benthic Habitats
Bartholomew Wilson, Delaware Bay Benthic Mapping Project
Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management (OCM)
2015
Delaware Bay, Delaware Benthic Habitats 2010 Geoform
vector digital data
Charleston, SC
NOAA's Ocean Service, Office for Coastal Management (OCM)
ftp://ftp.coast.noaa.gov/pub/benthic/Benthic_Cover_Data/DE_DelawareBay.zip
https://coast.noaa.gov/digitalcoast/publications/cmecs
http://www.cmecscatalog.org/
https://coast.noaa.gov/digitalcoast/
https://coast.noaa.gov/
The Coastal Program of Delaware's Division of Soil and Water conservation (DNREC), the University of Delaware, Partnership for the Delaware Estuary, and the New Jersey Department of Environmental Protection have partnered and are carrying out a bottom and sub-bottom imaging project to identify and map the benthic habitat and sub-bottom sediments of Delaware Bay and River. This project was initiated to better understand the distribution of bottom sediment types, habitat biodiversity, and most importantly, human's impact on the bay bottom and its living resources. The project integrates the use of three types of acoustical systems: Roxann Seabed classification system, chirp sub-bottom profiling, and multi-beam bathymetric mapping. Verification of the acoustic data with bottom and sub-bottom sediments is performed through the collection of bra banc core samples and underwater video images.
The Delaware Bay project has four principle goals. The first is to determine the location and extent of oyster reef habitats in upper Delaware Bay which will greatly improve the ability of Delaware and New Jersey to manage these commercial resources. The second goal is to evaluate short-nose, and atlantic sturgeon habitat. Sturgeon in the bay have shown an affinity for certain regions within the system. A better understanding of the conditions in these areas would improve the ability to assess the impact of dredging or other activities. A third goal was to identify potential borrow sites for beach re-nourishment materials. Finally, the high-resolution bathymetry collected in the bay will improve the understanding of sediment movement and other human impacts on the bay
2004
2010
ground condition
As needed
-75.6056
-75.16708
39.83218
38.80217
ISO 19115 Topic Category
environment
None
Benthic Habitat
Bottom Sediments
Shellfish Beds
SAV
Environmental Monitoring
None
CMECS
Coastal and Marine Ecological Classification Standard
Geoform Component
None
Delaware
Delaware River
State of Delaware
State of New Jersey
Delaware Bay
USA
None
Surface Sediment Mapping
Sediment Water Interface
Public Information
None
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
https://coast.noaa.gov/data/Images/Collections/BenthicCover_thumbnail.jpg
Sample of benthic cover data
JPEG
Ground truth information was collected at the time of the original surveys to calibrate the mapping and ensure the accuracy of the habitat designations.
Very shallow areas within the Delaware River/Bay system were not surveyed due to access limitations.
Coastal Program of Delaware's Division of Soil and Water Conservation (DNREC)
2010
Delaware Bay Benthic Mapping Project
CD-ROM
2004
2010
ground condition
Delaware Coastal Program
This is a compilation of several habitat data sets collected through a variety of methods.
Bivalve Reef (Oyster, Identified Oyster, and Corbicula) polygons were derived from the bottom sediment map that were constructed by the utilization of a Roxann Seabed Classification System and extensive sediment grab samples bottom sediment map that were constructed by the utilization of a Roxann Seabed Classification System and extensive sediment grab samples. Corbicula fluminea beds were identified on the Roxann output by the occurrence of data point which had moderate to high hardness return (E2) and an anomalously high roughness return (E1), as compared to the adjacent sediments. The sediments surrounding these beds are usually of a finer (silt to clay) grain size, with low roughness and hardness values. The regions where these types of returns were encountered were then sampled with a grab sampler. Several samples (2 to 3 samples) were collected at each station to increase the likely hood that Corbicula would be encountered, if it was indeed located in that region. Corbicula beds can have varying densities, distributions, and bed configurations; hence this sampling scheme was enacted to account for this spatial variability.
Submersed Rooted Vascular Plants (Vallisneria Americana) beds outlines were identified through the same bottom sediment map used for delineating bivalve reef. SRV beds were identified on the Roxann output by the occurrence of data point which had very low hardness returns (E2) and an anomalously high roughness return (E1), as compared to the adjacent sediments. The regions where these types of returns were encountered, where then sampled with a grab sampler. Several samples (2 to 3 samples) were collected at each station to increase the likely hood that SAV would be encountered, if it was indeed located in that region. SAV beds can have varying densities, distributions, and bed configurations; hence the sampling scheme was enacted to account for this spatial variability.
Outcrop areas consist of Cretaceous sediment that is at the river bottom surface (or near the surface ~1 to 2 cm). These areas are scour or erosional zones within the river. The outcropping material consists of highly compacted/de-watered silty fine sand to fine sandy silts, which contain relict burrow casts and glauconite. Outcrop boundaries were derived from the bottom sediment map raster grid.
2008
Bartholomew Wilson
DNREC
mailing and physical
89 Kings Highway
Dover
DE
19901
USA
302-739-9283
The bottom sediment map was constructed by the utilization of a Roxann Seabed Classification System and extensive
sediment grab samples. Data was collected in a gridded trackline configuration, with tracklines spacing of 100 meters parallel to
the shoreline and 200 meters perpendicular to the shoreline. This project is an extension of the work currently being performed in
Delaware waters by DNREC's Delaware Coastal Program's Delaware Bay Benthic Mapping Project. The bottom sediment point data, which
has been classified according to the existing benthic mapping Roxann box plot, are converted from a number that categorizes the
point according to its corresponding box (in the Roxann) into a number which reflects the sediment properties of each box in
relation to one another. A ranking scale is used to allow a statistical gridding scheme to interpolate between sediment data
points, while minimizing erroneous sediment classifications and allowing gradational sediment deposits to be gridded. A ranking
scale from 0 to 28 was used for this project, with 0 representing the finest grained classifications (fluidized clay) and 28
representing the coarsest grained classifications (dense shell material). Table 1 illustrates the distribution of sediment
classifications along the ranking scale, which takes into account the relation of sediment types and grain sizes to one another
using both the Wentworth Scale and Shepard's classification system. Finer grains are more similar in their deposition
environments, such as clay and silts, because they reflect similar current regimes, sorting, and reworking patterns (Poppe et al.,
2003). While coarse sediments are much more dissimilar to finer grains, with respect to current velocities, sorting, and winnowing,
the finer grains are much more closely related in their sediment diameters that the coarser grains as you increase in Phi size
and/or diameter. These account for the close clustering of coarse grained deposit descriptions at the upper end of the ranking
scale, while the finer grained sediments show a gradation as you increase in the rating scale.The bottom sediment data is gridded in Surfer degrees 8, a surface and terrain modeling program, using block kriging and a nugget effect. This statistical griding technique estimates the average value of a variable within a prescribed local area (Isaaks and Srivastava, 1989). Block kriging utilizes the existing point data values, weights the values of the data depending upon the proximity to the point being estimated, to discretize the local area into an array of estimated data value points and then averaging those individual point estimates together to get an average estimated value over the area of interest (Isaaks and Srivastava, 1989). A variogram is constructed for the data, and the resultant spatial model that is developed from the variogram is used in the block kriging surface model to more accurately interpolate the sediment data . The fitted model was a nugget effect (with an error variance of 21.8%) and a linear model (with a slope of 0.00286 and an anisotropy of 1, which represents a complete lack of spatial correlation).The accuracy of the estimation is dependent upon the grid size of the area of interpolation, the size of each cell within the grid, and the number of discretized data points that are necessary to estimate the cells within that grid spacing. The grid size that was used to interpolate the bottom sediment maps was 442 lines x 454 lines, with a cell size of 44.93 m2. The nugget effect is added to allow the griding to assume there is very little, if any, lateral correlation or trends within the bottom sediment (Isaaks and Srivastava, 1989). The nugget effect model entails a complete lack of spatial correlation; the point data values at any particular location bear no similarity even to adjacent data values (Isaaks and Srivastava, 1989). Without the nugget effect the gridding would assume that you could only have a linear progression of sediment types and would insert all the sediment types along the scale between two sediment types (i.e. silty fine to medium sands and fine to medium sand with varying amounts of pebbles would be inserted between fine sand and coarse sand even though that is not what is occurring along the bottom. The sediment data is gridded with no drift for the data interpolation, also helping to minimize erroneous classifications. Sediment Classification Ranking Sediment Description 0-11-2 Clay, 2-33-44-55-66-7 Silt,7-88-9 Sandy Silts, 9-1010-11 Fine Sand, 11-1212-13 Silty Fine to Medium Sands, 13-14 Silty Medium Sand, 14-1515-16 Fine to Medium Sand, 16-1717-18 Fine to Medium Sand with abundant shell material and/or pebbles, 18-1919-20 Coarse Sand with varying amounts of pebbles, 20-2121-2222-23 Moderate Shell Material/Sandy Pebbles, 23-2424-2525-26 Abundant Shell Material/Gravel, 26-2727-28 Dense Oyster Shell.
2008
Bartholomew Wilson
DNREC
mailing and physical
89 Kings Highway
Dover
Delaware
19901
USA
302-739-9283
Separate shapefiles for oyster beds, identified oyster beds, SAV, corbicula, outcroppings, and depositional zones were integrated into a single feature layer to produce a comprehensive benthic cover polygon data set using the ArcMap 10 Merge tool. A review of the bottom sediment raster data sets (Delaware River/Bay, Upper Shelf, and Roxann 2004 which lies along the Delaware near-shore area) indicated that they consisted entirely of various types of unconsolidated sediments ranging from fluidized clay to oyster shells. Each of these rasters were converted into a single Unconsolidated Sediments polygon layer, merged together and then joined with the other features (oyster, SAV, etc.) to form a continuous benthic cover layer for the entire project area. As a final step habitat classes from the Florida System for Classifying Habitats in Estuarine and Marine Environments (SCHEME) were added to the attribute table for this single polygon file to ensure consistency with other Digital Coast benthic cover data sets.
2012
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
The bottom sediment maps (source for the unconsolidated sediments polygons in the vector data set) were constructed by
the utilization of a Roxann Seabed Classification System and extensive sediment grab samples. Data was collected in a gridded
trackline configuration, with tracklines spacing of 100 meters parallel to the shoreline and 200 meters perpendicular to the
shoreline.This project is an extension of the work currently being performed in Delaware waters by DNREC's Delaware Coastal
Program's Delaware Bay Benthic Mapping Project.The bottom sediment point data, which has been classified according to the existing
benthic mapping Roxann box plot, are converted from a number that categorizes the point according to its corresponding box (in the
Roxann) into a number which reflects the sediment properties of each box in relation to one another. A ranking scale is used to
allow a statistical griding scheme to interpolate between sediment data points, while minimizing erroneous sediment classifications
and allowing gradational sediment deposits to be gridded. A ranking scale from 0 to 28 was used for this project, with 0
representing the finest grained classifications (fluidized clay) and 28 representing the coarsest grained classifications (dense
shell material). This ranking scale takes into account the relation of sediment types and grain sizes to one another using both the
Wentworth Scale and Shepard's classification system. Finer grains are more similar in their deposition environments, such as
clay and silts, because they reflect similar current regimes, sorting, and reworking patterns (Poppe et al., 2003). While coarse
sediments are much more dissimilar to finer grains, with respect to current velocities, sorting, and winnowing, the finer grains
are much more closely related in their sediment diameters that the coarser grains as you increase in Phi size and/or diameter.
These account for the close clustering of coarse grained deposit descriptions at the upper end of the ranking scale, while the
finer grained sediments show a gradation as you increase in the rating scale.The bottom sediment data is gridded in Surfer degrees 8, a
surface and terrain modeling program, using block kriging and a nugget effect. This statistical griding technique estimates the
average value of a variable within a prescribed local area (Isaaks and Srivastava, 1989). Block kriging utilizes the existing point
data values, weights the values of the data depending upon the proximity to the point being estimated, to discretize the local area
into an array of estimated data value points and then averaging those individual point estimates together to get an average
estimated value over the area of interest (Isaaks and Srivastava, 1989). A variogram is constructed for the data, and the resultant
spatial model that is developed from the variogram is used in the block kriging surface model to more accurately interpolate the
sediment data . The fitted model was a nugget effect (with an error variance of 21.8%) and a linear model (with a slope of 0.00286
and an anisotropy of 1, which represents a complete lack of spatial correlation).The accuracy of the estimation is dependent upon
the grid size of the area of interpolation, the size of each cell within the grid, and the number of discretized data points that
are necessary to estimate the cells within that grid spacing. The grid size that was used to interpolate the bottom sediment maps
was 442 lines x 454 lines, with a cell size of 44.93 m2. The nugget effect is added to allow the griding to assume there is very
little, if any, lateral correlation or trends within the bottom sediment (Isaaks and Srivastava, 1989). The nugget effect model
entails a complete lack of spatial correlation; the point data values at any particular location bear no similarity even to
adjacent data values (Isaaks and Srivastava, 1989). Without the nugget effect the griding would assume that you could only have a
linear progression of sediment types and would insert all the sediment types along the scale between two sediment types (i.e. silty
fine to medium sands and fine to medium sand with varying amounts of pebbles would be inserted between fine sand and coarse sand
even though that is not what is occurring along the bottom. The sediment data is gridded with no drift for the data interpolation,
also helping to minimize erroneous classifications. Sediment Classification Ranking Sediment Description: 0-11-2 Clay, 2-33-44-55-66-7
Silt, 7-88-9 Sandy Silts, 9-1010-11 Fine Sand, 11-1212-13 Silty Fine to Medium Sands, 13-14 Silty Medium Sand, 14-1515-16 Fine to
Medium Sand, 16-1717-18 Fine to Medium Sand, with abundant shell material and/or pebbles, 18-1919-20 Coarse Sand, with varying
amounts of pebbles 20-2121-2222-23 Moderate Shell Material / Sandy Pebbles, 23-2424-2525-26 Abundant Shell Material / Gravel 26-2727-28 Dense Oyster Shell
2012
The data were converted from a single ESRI polygon shapefile classified according to the System for Classifying Habitats in Estuarine and Marine Environments (SCHEME) to the Coastal and Marine Ecological Classification Standard (CMECS) 2012 format (which can be found at https://coast.noaa.gov/digitalcoast/tools/cmecs-crosswalk) which produces separate geoform, geoform, and geoform feature layers from the original input benthic habitat dataset. This geoform feature layer contains CMECS geoform component attributes where an "Equal" or "Nearly Equal" SCHEME value was present in the original data. Polygons for which no geoform information was present have been removed. No other changes to the original polygon boundaries or any other alterations of the original SCHEME data were made during this process.
2015
Vector
G-polygon
Universal Transverse Mercator
18
0.99960000
-75.00000000
0.0
500000.00000000
0.0
coordinate pair
0.0000001
0.0000001
meters
D North American 1983
GRS 1980
6378137.0
298.257222101
Geoform
Shallow benthic habitats CMECS 2012 geoform component polygons
NOAA Office for Coastal Management
OBJECTID
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
SHAPE
Feature geometry.
Esri
Coordinates defining the features.
CMECS_CODE
CMECS biotic unit code.
Coastal and Marine Ecological Classification Standard, FGDC 2012
Alphanumeric code for CMECS units
TECTPROV
Tectonic Setting - Continental scale geomorphological setting of the study area.
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of geoform tectonic province units; CMECS FGDC 2012
See definitions of geoform setting units; CMECS FGDC 2012
CMECS FGDC 2012
PHYSIOPROV
Physiographic Province as per the CMECS Geoform component.
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of geoform class units; CMECS FGDC 2012
See definitions of Geoform class units; CMECS FGDC 2012
CMECS FGDC 2012
G_ORIGIN
Primary process by which the geoform was formed as per the Coastal and Marine Ecological Classification Standard, FGDC 2012
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of geoform origin units; CMECS FGDC 2012
See definitions of geoform origin units; CMECS FGDC 2012
CMECS FGDC 2012
GEOFORM
Geoform - Individual geomorphological and physical features which provide a context for CMECS biotic an substrate information at a variety of spatial scales.
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of Geoform units; CMECS FGDC 2012
See definitions of Geoform units; CMECS FGDC 2012
CMECS FGDC 2012
GEOFORM_TYPE
More specific variant of geoform.
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of geoform type units; CMECS FGDC 2012
See definitions of geoform type units; CMECS FGDC 2012
CMECS FGDC 2012
Shape_Length
Length of line features in meters
Esri
Distance
Shape_Area
Polygon area in square meters
Esri
Area
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
Downloadable Data
NOAA provides no warranty, nor accepts any liability occurring from any incomplete, incorrect, or misleading data, or from any incorrect, incomplete, or misleading use of the data. It is the responsibility of the user to determine whether or not the data is suitable for the intended purpose.
20160211
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
FGDC Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998
local time
PK `KHH(v (v 2 CMECS Benthic Cover/de_db10-substrate_Metadata.xml
Delaware Bay Benthic Habitats
Bartholomew Wilson, Delaware Bay Benthic Mapping Project
Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management (OCM)
2015
Delaware Bay, Delaware Benthic Habitats 2010 Substrate
vector digital data
Charleston, SC
NOAA's Ocean Service, Office for Coastal Management (OCM)
ftp://ftp.coast.noaa.gov/pub/benthic/Benthic_Cover_Data/DE_DelawareBay.zip
https://coast.noaa.gov/digitalcoast/publications/cmecs
http://www.cmecscatalog.org/
https://coast.noaa.gov/digitalcoast/
https://coast.noaa.gov/
The Coastal Program of Delaware's Division of Soil and Water conservation (DNREC), the University of Delaware, Partnership for the Delaware Estuary, and the New Jersey Department of Environmental Protection have partnered and are carrying out a bottom and sub-bottom imaging project to identify and map the benthic habitat and sub-bottom sediments of Delaware Bay and River. This project was initiated to better understand the distribution of bottom sediment types, habitat biodiversity, and most importantly, human's impact on the bay bottom and its living resources. The project integrates the use of three types of acoustical systems: Roxann Seabed classification system, chirp sub-bottom profiling, and multi-beam bathymetric mapping. Verification of the acoustic data with bottom and sub-bottom sediments is performed through the collection of bra banc core samples and underwater video images.
The Delaware Bay project has four principle goals. The first is to determine the location and extent of oyster reef habitats in upper Delaware Bay which will greatly improve the ability of Delaware and New Jersey to manage these commercial resources. The second goal is to evaluate short-nose, and atlantic sturgeon habitat. Sturgeon in the bay have shown an affinity for certain regions within the system. A better understanding of the conditions in these areas would improve the ability to assess the impact of dredging or other activities. A third goal was to identify potential borrow sites for beach re-nourishment materials. Finally, the high-resolution bathymetry collected in the bay will improve the understanding of sediment movement and other human impacts on the bay
2004
2010
ground condition
As needed
-75.6056
-75.16708
39.83218
38.80217
ISO 19115 Topic Category
environment
None
Benthic Habitat
Bottom Sediments
Shellfish Beds
SAV
Environmental Monitoring
None
CMECS
Coastal and Marine Ecological Classification Standard
Substrate Component
None
Delaware
Delaware River
State of Delaware
State of New Jersey
Delaware Bay
USA
None
Surface Sediment Mapping
Sediment Water Interface
Public Information
None
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
https://coast.noaa.gov/data/Images/Collections/BenthicCover_thumbnail.jpg
Sample of benthic cover data
JPEG
Ground truth information was collected at the time of the original surveys to calibrate the mapping and ensure the accuracy of the habitat designations.
Very shallow areas within the Delaware River/Bay system were not surveyed due to access limitations.
Coastal Program of Delaware's Division of Soil and Water Conservation (DNREC)
2010
Delaware Bay Benthic Mapping Project
CD-ROM
2004
2010
ground condition
Delaware Coastal Program
This is a compilation of several habitat data sets collected through a variety of methods.
Bivalve Reef (Oyster, Identified Oyster, and Corbicula) polygons were derived from the bottom sediment map that were constructed by the utilization of a Roxann Seabed Classification System and extensive sediment grab samples bottom sediment map that were constructed by the utilization of a Roxann Seabed Classification System and extensive sediment grab samples. Corbicula fluminea beds were identified on the Roxann output by the occurrence of data point which had moderate to high hardness return (E2) and an anomalously high roughness return (E1), as compared to the adjacent sediments. The sediments surrounding these beds are usually of a finer (silt to clay) grain size, with low roughness and hardness values. The regions where these types of returns were encountered were then sampled with a grab sampler. Several samples (2 to 3 samples) were collected at each station to increase the likely hood that Corbicula would be encountered, if it was indeed located in that region. Corbicula beds can have varying densities, distributions, and bed configurations; hence this sampling scheme was enacted to account for this spatial variability.
Submersed Rooted Vascular Plants (Vallisneria Americana) beds outlines were identified through the same bottom sediment map used for delineating bivalve reef. SRV beds were identified on the Roxann output by the occurrence of data point which had very low hardness returns (E2) and an anomalously high roughness return (E1), as compared to the adjacent sediments. The regions where these types of returns were encountered, where then sampled with a grab sampler. Several samples (2 to 3 samples) were collected at each station to increase the likely hood that SAV would be encountered, if it was indeed located in that region. SAV beds can have varying densities, distributions, and bed configurations; hence the sampling scheme was enacted to account for this spatial variability.
Outcrop areas consist of Cretaceous sediment that is at the river bottom surface (or near the surface ~1 to 2 cm). These areas are scour or erosional zones within the river. The outcropping material consists of highly compacted/de-watered silty fine sand to fine sandy silts, which contain relict burrow casts and glauconite. Outcrop boundaries were derived from the bottom sediment map raster grid.
2008
Bartholomew Wilson
DNREC
mailing and physical
89 Kings Highway
Dover
DE
19901
USA
302-739-9283
The bottom sediment map was constructed by the utilization of a Roxann Seabed Classification System and extensive
sediment grab samples. Data was collected in a gridded trackline configuration, with tracklines spacing of 100 meters parallel to
the shoreline and 200 meters perpendicular to the shoreline. This project is an extension of the work currently being performed in
Delaware waters by DNREC's Delaware Coastal Program's Delaware Bay Benthic Mapping Project. The bottom sediment point data, which
has been classified according to the existing benthic mapping Roxann box plot, are converted from a number that categorizes the
point according to its corresponding box (in the Roxann) into a number which reflects the sediment properties of each box in
relation to one another. A ranking scale is used to allow a statistical gridding scheme to interpolate between sediment data
points, while minimizing erroneous sediment classifications and allowing gradational sediment deposits to be gridded. A ranking
scale from 0 to 28 was used for this project, with 0 representing the finest grained classifications (fluidized clay) and 28
representing the coarsest grained classifications (dense shell material). Table 1 illustrates the distribution of sediment
classifications along the ranking scale, which takes into account the relation of sediment types and grain sizes to one another
using both the Wentworth Scale and Shepard's classification system. Finer grains are more similar in their deposition
environments, such as clay and silts, because they reflect similar current regimes, sorting, and reworking patterns (Poppe et al.,
2003). While coarse sediments are much more dissimilar to finer grains, with respect to current velocities, sorting, and winnowing,
the finer grains are much more closely related in their sediment diameters that the coarser grains as you increase in Phi size
and/or diameter. These account for the close clustering of coarse grained deposit descriptions at the upper end of the ranking
scale, while the finer grained sediments show a gradation as you increase in the rating scale.The bottom sediment data is gridded in Surfer degrees 8, a surface and terrain modeling program, using block kriging and a nugget effect. This statistical griding technique estimates the average value of a variable within a prescribed local area (Isaaks and Srivastava, 1989). Block kriging utilizes the existing point data values, weights the values of the data depending upon the proximity to the point being estimated, to discretize the local area into an array of estimated data value points and then averaging those individual point estimates together to get an average estimated value over the area of interest (Isaaks and Srivastava, 1989). A variogram is constructed for the data, and the resultant spatial model that is developed from the variogram is used in the block kriging surface model to more accurately interpolate the sediment data . The fitted model was a nugget effect (with an error variance of 21.8%) and a linear model (with a slope of 0.00286 and an anisotropy of 1, which represents a complete lack of spatial correlation).The accuracy of the estimation is dependent upon the grid size of the area of interpolation, the size of each cell within the grid, and the number of discretized data points that are necessary to estimate the cells within that grid spacing. The grid size that was used to interpolate the bottom sediment maps was 442 lines x 454 lines, with a cell size of 44.93 m2. The nugget effect is added to allow the griding to assume there is very little, if any, lateral correlation or trends within the bottom sediment (Isaaks and Srivastava, 1989). The nugget effect model entails a complete lack of spatial correlation; the point data values at any particular location bear no similarity even to adjacent data values (Isaaks and Srivastava, 1989). Without the nugget effect the gridding would assume that you could only have a linear progression of sediment types and would insert all the sediment types along the scale between two sediment types (i.e. silty fine to medium sands and fine to medium sand with varying amounts of pebbles would be inserted between fine sand and coarse sand even though that is not what is occurring along the bottom. The sediment data is gridded with no drift for the data interpolation, also helping to minimize erroneous classifications. Sediment Classification Ranking Sediment Description 0-11-2 Clay, 2-33-44-55-66-7 Silt,7-88-9 Sandy Silts, 9-1010-11 Fine Sand, 11-1212-13 Silty Fine to Medium Sands, 13-14 Silty Medium Sand, 14-1515-16 Fine to Medium Sand, 16-1717-18 Fine to Medium Sand with abundant shell material and/or pebbles, 18-1919-20 Coarse Sand with varying amounts of pebbles, 20-2121-2222-23 Moderate Shell Material/Sandy Pebbles, 23-2424-2525-26 Abundant Shell Material/Gravel, 26-2727-28 Dense Oyster Shell.
2008
Bartholomew Wilson
DNREC
mailing and physical
89 Kings Highway
Dover
Delaware
19901
USA
302-739-9283
Separate shapefiles for oyster beds, identified oyster beds, SAV, corbicula, outcroppings, and depositional zones were integrated into a single feature layer to produce a comprehensive benthic cover polygon data set using the ArcMap 10 Merge tool. A review of the bottom sediment raster data sets (Delaware River/Bay, Upper Shelf, and Roxann 2004 which lies along the Delaware near-shore area) indicated that they consisted entirely of various types of unconsolidated sediments ranging from fluidized clay to oyster shells. Each of these rasters were converted into a single Unconsolidated Sediments polygon layer, merged together and then joined with the other features (oyster, SAV, etc.) to form a continuous benthic cover layer for the entire project area. As a final step habitat classes from the Florida System for Classifying Habitats in Estuarine and Marine Environments (SCHEME) were added to the attribute table for this single polygon file to ensure consistency with other Digital Coast benthic cover data sets.
2012
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
The bottom sediment maps (source for the unconsolidated sediments polygons in the vector data set) were constructed by
the utilization of a Roxann Seabed Classification System and extensive sediment grab samples. Data was collected in a gridded
trackline configuration, with tracklines spacing of 100 meters parallel to the shoreline and 200 meters perpendicular to the
shoreline.This project is an extension of the work currently being performed in Delaware waters by DNREC's Delaware Coastal
Program's Delaware Bay Benthic Mapping Project.The bottom sediment point data, which has been classified according to the existing
benthic mapping Roxann box plot, are converted from a number that categorizes the point according to its corresponding box (in the
Roxann) into a number which reflects the sediment properties of each box in relation to one another. A ranking scale is used to
allow a statistical griding scheme to interpolate between sediment data points, while minimizing erroneous sediment classifications
and allowing gradational sediment deposits to be gridded. A ranking scale from 0 to 28 was used for this project, with 0
representing the finest grained classifications (fluidized clay) and 28 representing the coarsest grained classifications (dense
shell material). This ranking scale takes into account the relation of sediment types and grain sizes to one another using both the
Wentworth Scale and Shepard's classification system. Finer grains are more similar in their deposition environments, such as
clay and silts, because they reflect similar current regimes, sorting, and reworking patterns (Poppe et al., 2003). While coarse
sediments are much more dissimilar to finer grains, with respect to current velocities, sorting, and winnowing, the finer grains
are much more closely related in their sediment diameters that the coarser grains as you increase in Phi size and/or diameter.
These account for the close clustering of coarse grained deposit descriptions at the upper end of the ranking scale, while the
finer grained sediments show a gradation as you increase in the rating scale.The bottom sediment data is gridded in Surfer degrees 8, a
surface and terrain modeling program, using block kriging and a nugget effect. This statistical griding technique estimates the
average value of a variable within a prescribed local area (Isaaks and Srivastava, 1989). Block kriging utilizes the existing point
data values, weights the values of the data depending upon the proximity to the point being estimated, to discretize the local area
into an array of estimated data value points and then averaging those individual point estimates together to get an average
estimated value over the area of interest (Isaaks and Srivastava, 1989). A variogram is constructed for the data, and the resultant
spatial model that is developed from the variogram is used in the block kriging surface model to more accurately interpolate the
sediment data . The fitted model was a nugget effect (with an error variance of 21.8%) and a linear model (with a slope of 0.00286
and an anisotropy of 1, which represents a complete lack of spatial correlation).The accuracy of the estimation is dependent upon
the grid size of the area of interpolation, the size of each cell within the grid, and the number of discretized data points that
are necessary to estimate the cells within that grid spacing. The grid size that was used to interpolate the bottom sediment maps
was 442 lines x 454 lines, with a cell size of 44.93 m2. The nugget effect is added to allow the griding to assume there is very
little, if any, lateral correlation or trends within the bottom sediment (Isaaks and Srivastava, 1989). The nugget effect model
entails a complete lack of spatial correlation; the point data values at any particular location bear no similarity even to
adjacent data values (Isaaks and Srivastava, 1989). Without the nugget effect the griding would assume that you could only have a
linear progression of sediment types and would insert all the sediment types along the scale between two sediment types (i.e. silty
fine to medium sands and fine to medium sand with varying amounts of pebbles would be inserted between fine sand and coarse sand
even though that is not what is occurring along the bottom. The sediment data is gridded with no drift for the data interpolation,
also helping to minimize erroneous classifications. Sediment Classification Ranking Sediment Description: 0-11-2 Clay, 2-33-44-55-66-7
Silt, 7-88-9 Sandy Silts, 9-1010-11 Fine Sand, 11-1212-13 Silty Fine to Medium Sands, 13-14 Silty Medium Sand, 14-1515-16 Fine to
Medium Sand, 16-1717-18 Fine to Medium Sand, with abundant shell material and/or pebbles, 18-1919-20 Coarse Sand, with varying
amounts of pebbles 20-2121-2222-23 Moderate Shell Material / Sandy Pebbles, 23-2424-2525-26 Abundant Shell Material / Gravel 26-2727-28 Dense Oyster Shell
2012
The data were converted from a single ESRI polygon shapefile classified according to the System for Classifying Habitats in Estuarine and Marine Environments (SCHEME) to the Coastal and Marine Ecological Classification Standard (CMECS) 2012 format (which can be found at https://coast.noaa.gov/digitalcoast/tools/cmecs-crosswalk) which produces separate geoform, substrate, and substrate feature layers from the original input benthic habitat dataset. This substrate feature layer contains CMECS substrate component attributes where an "Equal" or "Nearly Equal" SCHEME value was present in the original data. Polygons for which no substrate information was present have been removed. No other changes to the original polygon boundaries or any other alterations of the original SCHEME data were made during this process.
2015
Vector
G-polygon
Universal Transverse Mercator
18
0.99960000
-75.00000000
0.0
500000.00000000
0.0
coordinate pair
0.0000001
0.0000001
meters
D North American 1983
GRS 1980
6378137.0
298.257222101
Substrate
Shallow benthic habitats CMECS 2012 substrate component polygons
NOAA Office for Coastal Management
OBJECTID
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
SHAPE
Feature geometry.
Esri
Coordinates defining the features.
CMECS_CODE
CMECS substrate unit code.
Coastal and Marine Ecological Classification Standard, FGDC 2012
Alphanumeric code for CMECS units
S_ORIGIN
Substrate Origin - Dominance (percent cover) of either the geologic, biogenic (but no longer living), or anthropogenic origin of the upper layer of substrate
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of substrate origin units; CMECS FGDC 2012
See definitions of substrate origin units; CMECS FGDC 2012
CMECS FGDC 2012
S_CLASS
Substrate Class - Composition and particle size of the dominant substrate material in the surface sediments.
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of substrate class units; CMECS FGDC 2012
See definitions of substrate class units; CMECS FGDC 2012
CMECS FGDC 2012
S_SUBCLASS
Substrate Subclass - Composition and particle size of the dominant substrate material in the surface sediments.
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of substrate subclass units; CMECS FGDC 2012
See definitions of substrate subclass units; CMECS FGDC 2012
CMECS FGDC 2012
S_GROUP
Substrate Group - Determined by Folk (1954) mixes for Geologic Sediments and by taxa for the Biogenic Substrates
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of substrate group units; CMECS FGDC 2012
See definitions of substrate group units; CMECS FGDC 2012
CMECS FGDC 2012
S_SUBGROUP
Substrate Subgroup - Determined by Folk (1954) mixes for Geologic Sediments and by taxa for the Biogenic Substrates
Coastal and Marine Ecological Classification Standard, FGDC 2012
See list of substrate subgroup units; CMECS FGDC 2012
See definitions of substrate subgroup units; CMECS FGDC 2012
CMECS FGDC 2012
Shape_Length
Length of line features in meters
Esri
Distance
Shape_Area
Polygon area in square meters
Esri
Area
Description
Descriptive information on substrate units
Delaware Coastal Program/NOAA Office for Coastal Management
Free text further describing substrate units
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
Downloadable Data
NOAA provides no warranty, nor accepts any liability occurring from any incomplete, incorrect, or misleading data, or from any incorrect, incomplete, or misleading use of the data. It is the responsibility of the user to determine whether or not the data is suitable for the intended purpose.
20160211
NOAA Office for Coastal Management
mailing and physical
2234 South Hobson Avenue
Charleston
SC
29405-2413
843-740-1202
coastal.info@noaa.gov
FGDC Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998
local time
PK IGs K &