NCCOS Mapping: Comprehensive Seafloor Substrate Mapping and Model Validation in the New York Bight from 2017-10-20 to 2019-03-27 (NCEI Accession 0204737)
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abstract: This collection of benthic habitat mapping data is an inventory of hydrographic multibeam sonar surveys, georeferenced benthic photographs and video clips, seafloor morphometric analysis, and predictive models all collected in the New York Wind Energy Areas (NYWEA) designated by the Bureau of Ocean Energy Management (BOEM) in the Northeast Atlantic. These areas are located in a region known as the New York Bight, offshore of the New Jersey and Long Island, NY, coastlines. The multibeam data sets contain both bathymetry and backscatter data of the call areas from 2015-2018. Multibeam products were then processed into a series of topographic morphometrics using an R script and the Bathymetry and Reflectivity-based Estimator for Seafloor Segmentation (BRESS) tool. These products were used as predictions for local and regional substrate modeling and habitat characterization. HD underwater video, still photos, and sediment samples were collected in 2018 for ground validation (GV) and accuracy assessment (AA) of the predictive models. All of the seafloor imagery were analyzed and compiled into a comprehensive benthic habitat map of the NYWEA.
purpose: In September 2011, BOEM received an unsolicited request from the NY Power Authority (NYPA) for a commercial lease that proposed an offshore wind power project south of Long Island, New York. Subsequently, BOEM determined that competitive interest in the area proposed by NYPA (hereafter referred to as the New York Wind Energy Area, or NYWEA) exists and initiated the competitive leasing process. On June 21, 2016, BOEM and NOAA established an Interagency Agreement to conduct a three-year National Centers of Coastal Ocean Science (NCCOS) study of NYWEA and mid-Atlantic region titled, “Comprehensive Seafloor Substrate Mapping and Model Validation in the Atlantic”. The NYWEA (321 km2), located south of Long Island, was leased to Statoil Wind US LLC (now Equinox Wind US LLC) on December 16, 2016, for commercial wind energy development. The NYWEA offshore wind energy development also furthers New York State’s objective to provide 50% of its electricity from renewable energy by 2030, and to implement a comprehensive Offshore Wind Master Plan. These datasets are to inform BOEM managers on the distribution of substrate, geoforms, and biotic cover of the seafloor for the planning of large scale offshore wind farms.
credit: Related Funding Agency: US DOI; BOEM; Office of Renewable Energy Programs (OREP)
credit: Related Funding Agency: NOAA National Centers for Coastal Ocean Science
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supplementalInformation: Submission Package ID: 7M2RD2 Multibeam sonar data (seabed elevation) and acoustic imagery data (backscatter) were collected using a 400khz Reson 7125 multibeam echosounders (MBES) on the NOAA Ship Ferdinand Hassler (2013) and the NOAA Ship Nancy Foster (2017-2018). The Foster also collected Em710 data during the 2017 survey simultaneously with the Reson 7125 at 100 khz to analyze sub surface sediment textures, and 400 khz Em2040 multibeam which replaced the 7125 in 2018. The Hassler survey (H12629) was collected, processed, and archived by the NOAA Office of Coast Survey (OCS) and downloaded from NCEI (https://www.ngdc.noaa.gov/nos/H12001-H14000/H12629.html). The multibeam datasets from the Foster were preliminarily processed by NCCOS who conducted initial processing to corrected for motion, sound speed, and other major artifacts using CARIS HIPS and SIPS workflow. The final data from the Foster 2017 survey were processed and reviewed to ensure IHO S-44 specs by SolMar Hydro, using the Smoothed, Best Estimated Trajectory (SBETs) work flow from the Real Time Kinematic Marinestar GPS system. The 2018 data was collected to resurvey areas from the 2017 survey where data quality was poor due to bad weather and seastate, however that survey was affected by bad weather as well and was not used in the habitat mapping analysis or to supersede existing survey data. The backscatter from the multibeam datasets were mosaicked using the Fledermaus Geocoder Toolbox (FMGT) software. Once the bathymetric and backscatter datasets were finalized, a suite of morphometrics were generated using the Bathymetry and Reflectivity-based Estimator for Seafloor Segmentation (BRESS) software, and from an R script created by NCCOS. The morphometrics were used as predictors for the Boosted Regression Tree (BRT) predictions of the benthic substrate, biotic cover, and geoform components using a pixel based classification method. The Foster 2017 mission also collected Simrad EK60 split beam echo sounder (SBES) data to analyze fish and other biota in the water column. These datasets were cleaned and converted into a CSV file using Echoview software then processed into a point density data using an R script. The point density data could then be projected into ArcMap as a shapefile and was then interpolated into a raster for fish distribution analysis. NCCOS returned to the NYWEA on the R/V Tiki XIV in 2018 to collect ground validation and accuracy assessment data using the Seaviewer system and Gopro Hero 4 underwater cameras and sediment grabs using a modified van Veen sampler. The video and contents from the sediment grabs were used to correct the habitat predictions and estimate biogenic cover. Sediment grab samples were sent to TDI-Brooks to be sieved and separated into the Wentworth phi and grainsize classes. The sediment grab data was also projected onto maps of grainsize distribution using Bayesian Kriging. Once the bathymetric models and grab sample data were finalized for the NYWEA priority area, that information were compiled into a regional substrate and hardbottom model using BRT and Max-Ent, respectively. For more details, see Battista et al. (2019).
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description: Parameter or Variable: Acoustic Bathymetry (measured); Units: depth (m); Observation Category: in situ; Sampling Instrument: Reson 7125 Multibeam Echo sounder; Sampling and Analyzing Method: Measurement of depth of the seafloor. Acoustic bathymetry was collected aboard NOAA Ships Hassler (H12629) and Foster (NF1709, W00438) using Reson 7125 multibeam echosounders (MBES) and processed by NCCOS using CARIS HIPS and SIPS software. The raw soundings were cleaned and had sound velocity profiles and GPS navigation applied to create a Combined Uncertainty Bathymetric Estimation (CUBE) surface of the survey area. The Hassler and the Nancy Foster data were merged seamlessly using ArcMap. For more details, see Battista et al. (2019).; Data Quality Method: Bathymetry was vertically and horizontally corrected by the POS MV system to the ellipsoid and then converted to the NOAA Mean-Low Low Water (MLLW) datum for NOAA hydrographic survey specs and deliverables. Acoustic noise and vessel motion artifacts were filtered by setting a threshold of the standard deviations of the nodes form the CUBE surface. For more details, see Battista et al. (2019)..
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description: Parameter or Variable: Acoustic Backscatter (measured); Units: decibels (dB); Observation Category: in situ; Sampling Instrument: Reson 7125 Multibeam Echo sounder; Sampling and Analyzing Method: Measurement of relative intensity of the sea floor. Acoustic imagery data (backscatter) was collected aboard NOAA Ships Hassler (H12629) and Foster (NF1709, W00438) using Reson 7125 multibeam echosounders (MBES) and processed by NCCOS using FMGT software. The raw sounding and beam form were combined to create a mosaic of the survey area. Datasets were manually edited for constantly of intensity over multiple years and sampling systems. The intensity mosaics were merged seamlessly using ArcMap. For more details, see Battista et al. (2019).; Data Quality Method: NCCOS reviewed and processed the acoustic imagery (backscatter) aspect data using Fledermaus geocoder toolbox (FMGT). FMGT combined the raw intensity from the MBES with the edited/cleaned bathymetry data from CARIS HDCS to get a mosaic cleared of noise and data artifacts. For more details, see Battista et al. (2019)..
processStep: (LE_ProcessStep)
description: Parameter or Variable: Grain Size Distribution (calculated); Units: percent composition; Observation Category: in situ; Sampling Instrument: Van Veen Grab Sampler; Sampling and Analyzing Method: The grain size distribution models were derived from the Van Veen Grab samples using Bayesian Kriging for the local NYWEA and 3D Inverse Distance weighting for the regional sediment models. Each sediment grab sample had a ~8 oz sub sample TDI-Brooks Int. Laboratories where they were sorted into different grain sizes using a sediment sieve. The local grain size distribution models of the NYWEA were classified using the Phi scale, whereas the Regional models were classified by grouping Phi’s into a general sediment texture (gravels, sands, and clays). The results were then interpolated using the two different geostatistical methods and produced a percent distribution model for each grain size class. For more details, see Battista et al. (2019).; Data Quality Method: Samples were homogenized in the field and dried before the sieving process. Samples were kept cool but never frozen to prevent concretionary build up. Each sample was sieved for the same amount of time in the laboratory. The models were all produced using the same thresholds for each grain size. For more details, see Battista et al. (2019)..
processStep: (LE_ProcessStep)
description: Parameter or Variable: Fish Density (calculated); Units: Fish per 100m2; Observation Category: in situ; Sampling Instrument: EK60 Split beam Echo sounder; Sampling and Analyzing Method: The fish densities were derived from the cleaned EK60 data using Echoview software. The fish returns were then spatially modeled into data points using an R-script and then classified into size groups (small, medium, large, and all). Then the four point classes were all converted to raster with a 100m cell size to create an almost continuous surface. For more details, see Battista et al. (2019).; Data Quality Method: Data was thoroughly reviewed by a fisheries scientist before it was classified as a fish density target. Data was not resurveyed between night and day for diel patterns nor was it cleaned for vessel motion. For more details, see Battista et al. (2019)..
processStep: (LE_ProcessStep)
description: Parameter or Variable: Composite Habitat Type (measured); Units: none; Observation Category: model output; Sampling Instrument: Models/Analyses > Data Analysis > Environmental Modeling; Sampling and Analyzing Method: The final composite map of the of the predicted spatial distribution of three commonly co-occurring combinations of substrate, geoform, and biotic cover types. For more details, see Battista et al. (2019).; Data Quality Method: For more details, see Battista et al. (2019)..
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metadataMaintenance: (MD_MaintenanceInformation)
maintenanceAndUpdateFrequency: (MD_MaintenanceFrequencyCode) asNeeded
maintenanceNote: Metadata are developed, maintained and distributed by NCEI. Updates are performed as needed to maintain currentness.
contact: (CI_ResponsibleParty)
organisationName: NOAA National Centers for Environmental Information
role: (CI_RoleCode) custodian
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acquisitionInformation: (MI_AcquisitionInformation)
platform: (MI_Platform)
identifier: (MD_Identifier)
code: NOAA Ship Ferdinand R. Hassler
description: Updated information from ICES for the vessel FERDINAND R. HASSLER from UNITED STATES. Name : FERDINAND R. HASSLER Flag : UNITED STATES - US (ISO Country Code) Call Sign : WTEK Title : NOAA Ship Platform Class : 31 Research vessel IMO : 9478599 Pennant : S250 Commissioned Date : 2012-06-08 Current Length : 37.7 Built : 2011-05 Additional Information Sources: - http://www.moc.noaa.gov/fh/ - http://www.marinetraffic.com/ais/shipdetails.aspx?MMSI=369970091 General Comments: Launched 2009-09-19 Build confirmed in Miramar Submitted to ICES on 2013-05-20. Confirmed by NOAA on 2013-06-12.
instrument: (missing)
platform: (MI_Platform)
identifier: (MD_Identifier)
code: NOAA Ship Nancy Foster
description: Title: NOAA Ship Flag: United States of America Vessel Type: Research Vessel (Environmental) DOB: May 1991 IMO: 8993227 Former Name: Agate Pass (YTT-12) (2002)
instrument: (missing)
