Data has been collected primarily using a depth measurement device, such as an echo-sounder, in combination with a Global Positioning System (GPS) for horizontal positioning. Other survey methods, such as bathymetric LiDAR may also have been used. The survey method used in each body of water is shown in the [Bathymetry Index](https://geohub.lio.gov.on.ca/datasets/mnrf::bathymetry-index ).

Towfish (sidescan and video) and echo sounder surveys were utilized to examine bottom type and macrophyte cover within the area of two coastal marine finfish aquaculture sites, one in New Brunswick (Welch Cove) and one in Nova Scotia (Jordan Bay). Both towfish and echo sounder data could be used independently of one another. However, the towfish data were very useful for ground truthing echo sounder based classifications. All survey data were placed into a GIS which could be used to answer management questions such as the placement of cages at sites, benthic impacts and baseline conditions to determine long term changes.Cite this data as: Vandermeulen H. Data of: Exploratory Video-Sidescan and Echosounder Survey of Jordan Bay. Published: March 2019. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/752d277f-8b3e-40c7-b99d-cfa67e69d975

Towfish (sidescan and video) and echo sounder surveys were utilized to examine bottom type and macrophyte cover within the area of two coastal marine finfish aquaculture sites, one in New Brunswick (Welch Cove) and one in Nova Scotia (Jordan Bay). Both towfish and echo sounder data could be used independently of one another. However, the towfish data were very useful for ground truthing echo sounder based classifications. All survey data were placed into a GIS which could be used to answer management questions such as the placement of cages at sites, benthic impacts and baseline conditions to determine long term changes.Cite this data as: Vandermeulen H. Data of: Exploratory Video-Sidescan and Echosounder Survey of Welch Cove. Published: June 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/0083e317-8bb5-492a-8348-c021e183f307

This dataset corresponds to daily snow cover percentage at 1km resolution grid over land areas of Canada from 2006-2010. The data are subsampled by 4km to reduce data volumes and considering the geolocation uncertainty of the input satellite imagery. The daily maps are generated by assimilation of daily cloud screened NOAA AVHRR satellite imagery and Canadian Meteorological Centre (CMC) snow depth analysis snow depth and density fields within an off-line version of the CMC daily snow depth model. The snow depth model is modified to include snowpack reflectance model and a surface radiative transfer scheme that relates vegetation and snowpack reflectance to top-of-canopy bi-directional reflectance. A logistic vegetation phenology model is used to parameterize temporal dynamics of canopy leaf area index. A per-pixel particle filter with a 30 day moving window is applied to assimilation observations corresponding to 1km resolution visible band directional reflectance and normalized difference vegetation index and 24km CMC daily snow depth and monthly snow density fields. The assimilation is forced using daily air temperature and precipitation fields. Validation of the datasets has been performed by comparison to MODIS snow cover maps and in-situ snow depth stations across Canada. Validation suggests similar accuracy to MODIS snow cover products over relatively flat terrain. Validation over mountainous regions is ongoing.

Geographic bathymetric grid data at 100 m x 100 m pixel resolution.Datum: WGS84Collaboration of Canada, the United States of America and the European Union as part of the Atlantic Ocean Research Alliance's second project under the Galway Statement. Project mapped the North Atlantic seafloor along a transect from Halifax, Canada to Tromsø, Norway to further the understanding of marine habitats, conservation and navigation. Chief Scientist / Primary Investigator name: Paola Travaglini Platform: CCGS Louis S. St- Laurent (Canadian heavy icebreaker)Device 1 type: Multibeam echo-sounder (sonar)Device 1 manufacturer: Kongsberg Device 1 model: EM122, hull installed behind ice protection window Data and Data format:100 m resolution grid of bathymetryBAG format: Bathymetric Attributed Grid ObjectNavigation and positioning: Trimble GNSS receiver + antennas Applanix POS/MV v5 inertial measuring system Horizontal Datum: WGS84 (G1762) Tidal correction:Zero tide applied: tides are not well known for the major part of the data and tides over very deep water are generally negligible. Sound Velocity Profile measurements:In-situ sound velocity profiles were applied.Note on accuracy/S-44 survey standards:Considering the intended output from this survey (IHO Order 1a - Areas shallower than 100 metres where under-keel clearance is less critical but features of concern to surface shipping may exist.) and using an average depth of 2000m as ‘d’ in the IHO Standard Equation - the allowable Total Vertical Uncertainty (TVU) must be < 26m which indeed the data has achieved (by comparison with overlapping datasets from other surveys/agency data).IHO Order 1aHorizontal positioning accuracy: 5.0 m + 5% of depth (95% Confidence level)(~105 m at a mean depth of 2000 m)Vertical positioning accuracy: 2.5 m < 26 m = Sqrt((0.5 m)^2+(0.013 x 2000 m)^2)

Predicted sand percentage (%) at a defined depth range.

Between 2017 and 2024, underwater imaging sampling campaigns were conducted by Fisheries and Oceans Canada across a broad area of the shallow coastal zone of the St. Lawrence Estuary and Gulf. The sampling targeted the lower intertidal and subtidal zones, to a maximum depth of approximately 10 m, with an emphasis on eelgrass beds and macroalgae. These targeted surveys were primarily intended to produce ground-truth data for the mapping of estuarine and marine macrophytes of the Québec maritime region (Provencher-Nolet et al., 2025), supporting oil spill preparedness and response activities.This dataset summarizes information generated from the analysis of underwater video footage collected at 3,179 sampling stations using small boats equipped with a pole-mounted camera system, as described in Grégoire et al. (2025). The dataset documents multiple characteristics of coastal ecosystems, including the cover of erect vegetation, vegetation assemblages, dominant and minor vegetation, substrates, fauna, as well as the presence of encrusting algae, for each sampling station. The different attributes recorded during video analysis, along with certain identification criteria, are presented in the visual dictionary of Grégoire et al. (2022).

Bathymetry line data was collected to assess fish habitat in Ontario. Spot depths (bathymetry points) were used to measure the depth contours, which function like isobars to show lines of constant depth. Their density and positional accuracies vary depending on the survey style and parameters. This data should never be used for navigation.

A tidal resource assessment dataset for the Quatsino Sound region, British Columbia, was developed, including temporal maximum, mean, and minimum velocity magnitudes, standard deviations, and power density. The dataset was generated using a high-resolution 2D depth-averaged hydrodynamic model based on the Telemac-Mascaret solver, with Natural Neighbor interpolation applied for raster creation. This newly published dataset is the first in a series of regional tidal energy maps for Canada. Developed by CanmetENERGY Ottawa in collaboration with partners, these maps aim to support effective project planning and development by providing comprehensive tidal resource data across the country.Disclaimer:Potential errors in the model results may arise from inherent limitations in the topo-bathymetric data accuracy, assumptions in boundary conditions, approximations within the numerical methods, and the input data used in the numerical modeling. These factors introduce uncertainties that can affect the overall model outcomes. The model is subject to the following conditions:• Topo-bathymetric data: Obtained from electronic navigational charts and the Canadian Hydrographic Service’s (CHS) NONNA-10 Bathymetric Data packages, consolidating CHS-managed digital bathymetric sources with a maximum resolution of 10 m.• Tidal and current harmonic components: Used as boundary conditions from the TPXO9 global tidal model.• Model calibration and validation: Performed using data from Acoustic Doppler Current Profilers (ADCP), surface elevations recorded at CHS tidal stations, and Lagrangian drifter measurements.• Interpolation method: Dataset outputs were generated with Natural Neighbor interpolation, which assumes smoothly varying data and may not capture sharp local gradients or features.• Modeled estimates: All values for velocity magnitudes, velocity standard deviations, and power density are modeled estimates and not direct field measurements.This dataset is intended for preliminary assessment of tidal projects only. It should not be the sole basis for making critical decisions or investments. We strongly recommend further validation and in-depth analysis. Users are responsible for conducting their own due diligence and additional research to verify the data's accuracy and relevance for specific applications.By accessing and using this dataset, users acknowledge and accept these disclaimers. The providers of this dataset explicitly absolve themselves of any responsibility or liability for any consequences arising from the use, reliance upon, or interpretation of this dataset. Users are advised that their use of the dataset is at their own risk, and they assume full responsibility for any actions or decisions made based on the information contained therein. This disclaimer is in accordance with applicable laws and regulations, and by accessing or utilizing the dataset, users agree to release the providers of this dataset from any legal claims, damages, or liabilities that may arise from such use.

This dataset includes five depth-attenuated relative wave exposure index layers in raster format. Relative Exposure Index (REI) values are calculated based on effective fetch (derived from fetch values) combined with modelled wind data. The output REI layers are attenuated by depth, resulting in greater values in shallow, nearshore areas (Bekkby et al. 2008). The cell values represent an estimate of wave exposure at bottom depth normalized between regions from 0 (protected) to 1 (exposed).The objective of this dataset is to provide an estimate of wave exposure at bottom depth, primarily for use in species distribution modelling. Each single-band raster corresponds to a marine region, which generally coincide with the following layers from the Species Distribution Modelling Boundaries (https://www.gis-hub.ca/dataset/sdm-boundaries) dataset: Nearshore_HG, Nearshore_NCC, Nearshore_QCS, Nearshore_QCS, and Shelf_SalishSea. These layers extend to 50 m depth and up to 5 km from shore.Tabular data (csv files) are also included as part of the data package. These data are the calculated Relative Exposure Index (REI) values with fields for position information. The fetch values from gridded nearshore fetch (https://gis-hub.ca/dataset/gridded-nearshore-fetch) are used as a source dataset and the locations in the REI are the same as the gridded fetch.