These data represent benthic habitats in a coastal area near Green Bay, Wisconsin. The area extends approximately 91 kilometers between Suamico, Wisconsin, and Menominee, Michigan, and covers approximately 64 square kilometers. Benthic biota and substrates were classified using the Coastal and Marine Ecological Classification Standard (CMECS). The classification process involved object-based image segmentation of lidar bathymetry, cross-referencing geospatial data with the CMECS hierarchy, and expert interpretation. Biotic and substrate components were classified to the CMECS group or community level, with additional detail provided by co-occurring elements and modifiers. Mapping confidence was higher in areas with Digital Elevation Models (DEMs), as geomorphometric details from digital elevation models could often be directly linked to substrate types through professional geologic judgment. In areas lacking DEM coverage, object-based segmentation was not possible, leading to lower confidence and requiring manual interpretation of substrate and biotic data from available source and ancillary data. In some instances, with support from geologic judgment or imagery, CMECS Substrate Component classifications at DEM boundaries were linearly extrapolated across gaps in DEM coverage. The layers available within the data download include biotic, confidence, and substrate. Partners: Coastal States Organization

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. Original contact information: Contact Org: NOAA Office for Coastal Management Phone: 843-740-1202 Email: coastal.info@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. Original contact information: Contact Org: NOAA Office for Coastal Management Phone: 843-740-1202 Email: coastal.info@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. Original contact information: Contact Org: NOAA Office for Coastal Management Phone: 843-740-1202 Email: coastal.info@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. Original contact information: Contact Org: NOAA Office for Coastal Management Phone: 843-740-1202 Email: coastal.info@noaa.gov

These data provide benthic habitat maps for a 42-square-kilometer area at South Manitou Island in Lake Michigan. This joint pilot project between NOAA's Office for Coastal Management and the National Park Service applies the Coastal and Marine Ecological Classification Standard (CMECS) in the Great Lakes region and, specifically, the Sleeping Bear Dunes National Lakeshore. The project primarily focuses on mapping lakeshore substrates to assess their value as fisheries habitat. Additionally, the mapping effort aims to determine the distribution and extent of the widespread nuisance filamentous algae, Cladophora sp., found in the area. The workflow combined photo interpretation, object-based image analysis, field verification, and expert manual interpretation. These data include CMECS substrate and biotic components, classified to at least the subclass level. Co-occurring elements and modifiers (e.g., percent cover, induration, surface pattern) were also included for both components. Example images and corresponding CMECS classifications are available in the project report. These data also include GPS navigation tracks for each field site, video clips for many sites, and field validation points conducted over two days in August 2017 to ensure the accuracy of the map products. Source data for the mapping included underwater photography, aerial imagery, acoustic backscatter (side-scan and multibeam sonar), and high-resolution lidar data collected around the island in 2016. The layers available within the data download include: biotic, field_point, substrate, and transect. Partners: National Park Service

These data provide several geoform data products for the Gulf of Maine derived from NOAA's BlueTopo bathymetric grid products. The spatial domain of these data extends from the landward limit of BlueTopo tiles seaward to the 24-nautical-mile Contiguous Zone boundary. These data support coordinated ocean planning among three state partnership agencies, between state and federal organizations, and for the public at large. The Gulf of Maine is an area rich in history, natural resources, and ocean uses. Effective planning for new infrastructure and changes in ocean use requires accurate data and collaboration among multiple stakeholders and resource management organizations. To address long-expressed regional needs, NOAA's Office for Coastal Management collaborated with the states of Maine, New Hampshire, and Massachusetts to develop a regional geomorphology dataset. This dataset serves as a framework for collaborative planning and assessment. Coastal and Marine Ecological Classification Standard (CMECS) geoforms for the area were generated using NOAA's BlueTopo bathymetric products. Semiautomated methods were employed to ensure consistent mapping of features across the region. Following the semiautomated process, additional interpretation, guided by regional marine geology and mapping experts, was conducted to add and refine features of interest not detected automatically. Efforts to expand and update this product are planned. The layers available within the data download include: confidence_update, geoform, geoform_interpreted, and isobath. Partners: Maine Coastal Program, Massachusetts Office of Coastal Zone Management, New Hampshire Coastal Program, and NOAA Office of Coast Survey

These data provide a baseline inventory of submerged aquatic vegetation within Long Island's South Shore bays. The data were derived from conventional-color metric film diapositives obtained in June 2002 from the New York Department of State's Division of Coastal Resources. Benthic classifications follow the System for Classification of Habitats in Estuarine and Marine Environments (SCHEME). The study area spans approximately 443 square kilometers, extending from the west end of Long Beach Island in Nassau County eastward to Heady Creek at the east end of Shinnecock Bay in Suffolk County. The creation of this baseline inventory was a critical need identified in the Comprehensive Management Plan for the Long Island South Shore Estuary Reserve. Established following the state legislature's passage of the Long Island South Shore Estuary Reserve Act in 1993, the management plan aimed to protect and improve the estuary's ecosystem, enhance public access, and support sustainable economic activities. Ultimately, the goal was to sustain existing high-quality habitats and restore degraded areas to support the productivity of commercially and ecologically important estuarine species. The management plan also mandated a long-term monitoring program to evaluate progress toward estuarine resource improvement goals, building upon this foundational benthic habitat data. The layers available within the data download include biotic, geoform, and substrate. Partners: New York Department of State's Division of Coastal Resources

In June 2002, 200 1:20,000 scale conventional-color metric film diapositives for Long Island, New York were collected as part of an effort to map submerged aquatic vegetation (SAV) in Long Islands South Shore bays. They were provided by New York State Department of State's Division of Coastal Resources. Photographs were taken at low tide and during times that the growth stage of the SAV allowed for clear identification. Care was taken to minimize the effects of turbidity, sun glint, wind, and haze on the photos. The photos were scanned at a resolution of 15 microns. Ground control points were collected primarily from NYSDS 2 ft orthophotos. Additional control points were collected from USGS DOQQs where coverage from the primary source was lacking. All elevations were derived from USGS digital elevation models. A bundle block adjustment was performed using Albany and exterior orientation parameters were calculated. Boeing/Autometric's Softplotter was used to orthorectify the photos. The images were then dodged and mosaicked using Z/I's Orthopro. No additional color-balancing was performed as the mosaic's intended purpose was the delineation of benthic habitats. The mosaic was then output into 1000m by 1000m tiles with a 0.5m pixel resolution. The naming convention uses the first 3 numbers of the UTM x coordinate followed by the first 4 numbers in the UTM y coordinate of the southwest corner. Stereo digital images were created and the habitat features were interpreted and digitized on screen using softplotter microstation resulting in accurate and efficient 3D extraction of the data. Habitats were delineated with a high level of detail with the minimum mapping unit (MMU) being 0.01 hectares(approx.10m x 10m).The digitized polygons have the following specifications: Vertex Distance less than 1.0 m Node Snap Distance less than 4.0 m Arc Snap Distance less than 4.0 m During August 2002, NOAA staff collected 95 field observations throughout the study area and this information was incorporated into the map. In June 2003, after reviewing the photography, questionable areas were visited by Greenhorne and O'Mara staff and the findings were subsequently applied to the map. The map layers show delineated polygons and lines representing benthic habitat data. Each polygon feature is given a 1,2,3 or 4 digit number representing 11 habitats. The item numbers are stored in the attribute table under Text. The benthic data is classified according to the System for Classification of Habitats in Estuarine and Marine Environments (SCHEME). This system is fully described in "Development of a System for Classification of Habitats in Estuarine and Marine Environments (SCHEME) for Florida, Report to U.S. EPA - Gulf of Mexico Program, Florida Fish and Wildlife Conservation Commission, Florida Marine Research Institute. Review Draft 12/04/02."The collected data was converted to an ARCGIS format for quality control and delivery. The data was assessed for horizontal spatial accuracy and thematic agreement during 2003. Original contact information: Contact Org: NOAA Office for Coastal Management Phone: 843-740-1202 Email: coastal.info@noaa.gov

The area of coverage consists of 192 square miles of benthic habitat mapped from 2005 to 2007 in the Delaware River and Upper Delaware Bay. 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 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). 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 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