Preliminary hard and soft seafloor substrate map derived from an unsupervised classification of multibeam backscatter and bathymety derivatives at French Frigate Shoals, Northwestern Hawaiian Islands, USA. The dataset was derived using a combination of Simrad em3002d and Reson 8101 backscatter, bathymetric variance and bathymetric rugosity. The sonar frequencies are 300 kHz and 240 kHz for the em3002d and the 8101 data respectively and all data were resampled to 5 m grid cell size prior to the classification. Initial supervised classifications of the backscatter data into hard and soft seafloor substrates, using seafloor photographs for groundtruthing and to define regions of interest, were used to define unsupervised class types and to visually evaluate the accuracy of the unsupervised classification seafloor substrate map.

Preliminary hard and soft seafloor substrate map classified from sidescan data and bathymetric derivatives at Apra Harbor, Guam U.S. Territory. The dataset was created using Bathymetric Position Index (bpi) zones derived from Reson SeaBat 8125 multibeam data at a 1 m grid cell size, and Klein 3000 sidescan sonar data. The sonar frequency is 455 kHz for the Reson Seabat 8125 multibeam echosounder. Additional information on multibeam and sidescan datasets can be found in the Data Acquisition and Processing Report (DAPR) that can be accessed at: www.soest.hawaii.edu/pibhmc. Classification of the bathymetry and sidescan data into hard and soft seafloor substrates were validated using groundtruth data collected for the US Navy in Appendix J of the Final EIS Statement: Guam and CNMI Military Relocation accessed at: http://www.guambuildupeis.us/final_documents. Survey site images can be found at http://guamreeflife.com/htm/reeftour/cvn_survey_sites.htm. Although hard and soft classes from the substrate map are highly correlated with those from the optical validation data, the substrate map should be used with caution as groundtruth data were mostly collected at areas of known hard bottom in less than 60 ft of water depth.

This dataset contains multibeam bathymetry, backscatter, and LiDAR bathymetry and reflectance. These GeoTIFFs represent water depth and acoustic intensity of the seafloor from Phase II of the Long Island Sound (LIS) Benthic Habitat Priority Areas of Interest (AOI) project. The original Phase II datasets were surveyed by NOAA Ship Nancy Foster (R-352), NOAA Ship Thomas Jefferson, and the Navigation Response Team (NRT-5) using 400 khz Reson 7125 multibeam sonars from 2003 to 2014. In 2018, the LIS Cable Fund contracted the State University of New York (SUNY) at Stony Brook School of Marine and Atmospheric Sciences (SoMAS) to fill gaps and resurvey areas where multibeam data was not acceptable with R/V Pritchard using 400 khz Kongsberg dual-swath EM2040c multibeam sonars in coordination with the NOAA National Centers for Coastal Ocean Science (NCCOS) Biogeography Branch and the NOAA Integrated Ocean and Coastal Mapping (IOCM) Program. The multibeam and LiDAR were corrected, calibrated, and integrated into a seamless 32-bit raster using CARIS and ArcGIS. Backscatter data was collected and mosaicked into a raster using Fledermaus Geocoder Toolbox, ArcGIS 10.4, and PCI Geomatica 2018 software.

Multibeam backscatter imagery extracted from gridded bathymetry of Rose Island, American Samoa, South Pacific. These data provide coverage between 20 and 5000 meters. The backscatter dataset includes data collected using Simrad EM300 and Reson 8101 multibeam sonars. The sonars frequencies are 30 kHz and 240 kHz respectively and the backscatter data from each sonar are processed and gridded separately. These metadata are for the 5 m grid cell size Simrad em300 multibeam backscatter data only.

These metadata describe the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) merged acoustic-backscatter imagery that was collected in 2005, 2007, and 2010 in Skagit Bay Washington that is provided as a 5-m resolution TIFF image. In 2004, 2005, 2007, and 2010 the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) collected bathymetry and acoustic backscatter data in Skagit Bay, Washington using an interferometric bathymetric sidescan sonar system mounded to the USGS R/V Parke Snavely and the USGS R/V Karluk. The research was conducted in coordination with the Swinomish Indian Tribal Community, Skagit River System Cooperative, Skagit Watershed Council, Puget Sound Nearshore Ecosystem Restoration Project, and U.S. Army Corps of Engineers to characterize estuarine habitats and processes, including the sediment budget of the Skagit River and the influence of river-delta channelization on sediment transport. Information quantifying the distribution of habitats and extent that sediment transport influences habitats and the morphology of the delta is useful for planning for salmon recovery, agricultural resilience, flood risk protection, and coastal change associated with sea-level rise.

These metadata describe the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) merged acoustic-backscatter imagery that was collected in 2005, 2007, and 2010 in Skagit Bay Washington that is provided as a 5-m resolution TIFF image. In 2004, 2005, 2007, and 2010 the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) collected bathymetry and acoustic backscatter data in Skagit Bay, Washington using an interferometric bathymetric sidescan sonar system mounded to the USGS R/V Parke Snavely and the USGS R/V Karluk. The research was conducted in coordination with the Swinomish Indian Tribal Community, Skagit River System Cooperative, Skagit Watershed Council, Puget Sound Nearshore Ecosystem Restoration Project, and U.S. Army Corps of Engineers to characterize estuarine habitats and processes, including the sediment budget of the Skagit River and the influence of river-delta channelization on sediment transport. Information quantifying the distribution of habitats and extent that sediment transport influences habitats and the morphology of the delta is useful for planning for salmon recovery, agricultural resilience, flood risk protection, and coastal change associated with sea-level rise.