This substrate, geomorphic, and geologic attributed polygon shapefile in the Offshore of Eureka, California, map area is part of USGS Data Series 781 (Golden and Cochrane, 2019). The map area is one of 83 map areas of the California State Waters Map Series. The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) to be useful for ecosystems management.

This substrate, geomorphic, and geologic attributed polygon shapefile in the Offshore of Eureka, California, map area is part of USGS Data Series 781 (Golden and Cochrane, 2019). The map area is one of 83 map areas of the California State Waters Map Series. The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) to be useful for ecosystems management.

This shapefile has substrate, geomorphic, and geologic attributed polygons in the Offshore of Point Buchon, California, map area, one of 83 map areas of the California State Waters Map Series, USGS Data Series 781 (Golden and Cochrane, 2019). The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) to be useful for ecosystems management.

This shapefile has substrate, geomorphic, and geologic attributed polygons in the Offshore of Point Buchon, California, map area, one of 83 map areas of the California State Waters Map Series, USGS Data Series 781 (Golden and Cochrane, 2019). The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) to be useful for ecosystems management.

This shapefile has substrate, geomorphic, and geologic attributed polygons in the Offshore of Point Buchon, California, map area, one of 83 map areas of the California State Waters Map Series, USGS Data Series 781 (Golden and Cochrane, 2019). The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) to be useful for ecosystems management.

This substrate, geomorphic, and geologic attributed polygon shapefile in the Offshore of Arcata, California, map area is part of USGS Data Series 781 (Golden and Cochrane, 2019). The map area is one of 83 map areas of the California State Waters Map Series. The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) to be useful for ecosystems management.

This substrate, geomorphic, and geologic attributed polygon shapefile in the Offshore of Arcata, California, map area is part of USGS Data Series 781 (Golden and Cochrane, 2019). The map area is one of 83 map areas of the California State Waters Map Series. The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) to be useful for ecosystems management.

This part of USGS Data Series 935 (Cochrane, 2014) presents substrate, geomorphic, and biotope data in the Offshore of Seattle, California, map area, a part of the Southern Salish Sea Habitat Map Series. Given the variable bathymetric resolution, the complex geologic history of the region, and the lack of acoustic backscatter data, automated and semi-automated classification schemes of classifying seafloor substrate and geoform were deemed to have very low accuracy. Instead, classification of these properties was performed manually following the Coastal and Marine Ecological Classification Standard (CMECS; Madden and others, 2009) using observations from underwater video footage. The best overall predictors of biotic assemblage were used to generate the CMECS biotopes. However, the nature of the biological data gathered makes it difficult to define clear biotopes. It was difficult to see or identify many organisms in the underwater video, and with an average of only 3-4 taxa identified per sampling unit, it is hard to characterize biotic assemblages. Some biological clusters of taxa were identified statistically for multiple map areas, and within each area, some of these groupings were found at consistent depths and/or with predictable substrates. The maps are not fine-grained enough to capture the physical variation seen within one-minute video units. Depth zones in the biotope map are based on Dethier (1992).

This part of USGS Data Series 935 (Cochrane, 2014) presents substrate, geomorphic, and biotope data in the Offshore of Seattle, California, map area, a part of the Southern Salish Sea Habitat Map Series. Given the variable bathymetric resolution, the complex geologic history of the region, and the lack of acoustic backscatter data, automated and semi-automated classification schemes of classifying seafloor substrate and geoform were deemed to have very low accuracy. Instead, classification of these properties was performed manually following the Coastal and Marine Ecological Classification Standard (CMECS; Madden and others, 2009) using observations from underwater video footage. The best overall predictors of biotic assemblage were used to generate the CMECS biotopes. However, the nature of the biological data gathered makes it difficult to define clear biotopes. It was difficult to see or identify many organisms in the underwater video, and with an average of only 3-4 taxa identified per sampling unit, it is hard to characterize biotic assemblages. Some biological clusters of taxa were identified statistically for multiple map areas, and within each area, some of these groupings were found at consistent depths and/or with predictable substrates. The maps are not fine-grained enough to capture the physical variation seen within one-minute video units. Depth zones in the biotope map are based on Dethier (1992).

This part of USGS Data Series 935 (Cochrane, 2014) presents substrate, geomorphic, and biotope data in the Offshore of Tacoma, Washington, map area, a part of the Southern Salish Sea Habitat Map Series. Given the variable bathymetric resolution, the complex geologic history of the region, and the lack of acoustic backscatter data, automated and semi-automated classification schemes of classifying seafloor substrate and geoform were deemed to have very low accuracy. Instead, classification of these properties was performed manually following the Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) using observations from underwater video footage. The best overall predictors of biotic assemblage were used to generate the CMECS biotopes. However, the nature of the biological data gathered makes it difficult to define clear biotopes. It was difficult to see or identify many organisms in the underwater video, and with an average of only 3-4 taxa identified per sampling unit, it is hard to characterize biotic assemblages. Some biological clusters of taxa were identified statistically for multiple map areas, and within each area, some of these groupings were found at consistent depths and/or with predictable substrates. The maps are not fine-grained enough to capture the physical variation seen within one-minute video units. Depth zones in the biotope map are based on Dethier (1992).