The basking shark (Cetorhinus maximus), is a species found in Atlantic Canadian waters which is mostly encountered “basking” on the surface waters and sometimes caught accidentally in commercial fisheries. One Pop-up Satellite Archival Tag (PSAT Mk10) from Wildlife Computers was applied to a single female basking shark in September 2008 on a commercial vessel to collect data on depth (pressure), temperature and ambient light level (for position estimation). The basking shark was 610 cm Total Length (curved). The tag released on the pre-programmed date 125 days after deployment. Raw data transmitted from the PSAT’s after release was processed through Wildlife Computers software (GPE3) to get summary files, assuming a maximum swimming speed of 2m/s, NOAA OI SST V2 High Resolution data set for SST reference and ETOPO1-Bedrock dataset for bathymetry reference. The maximum likelihood position estimates are available in .csv and .kmz format and depth and temperature profiles are also in .csv format. Other tag outputs as well as metadata from the deployment can be obtained upon request from: warren.joyce@dfo-mpo.gc.ca or heather.bowlby@dfo-mpo.gc.ca.

This layer details Important Areas (IAs) relevant to important geographic features in the Pacific North Coast Integrated Management Area (PNCIMA). This data was mapped to inform the selection of marine Ecologically and Biologically Significant Areas (EBSA). Experts have indicated that these areas are relevant based upon their high ranking in one or more of three criteria (Uniqueness, Aggregation, and Fitness Consequences). The distribution of IAs within ecoregions is used in the designation of EBSAs. Canada’s Oceans Act provides the legislative framework for an integrated ecosystem approach to management in Canadian oceans, particularly in areas considered ecologically or biologically significant. DFO has developed general guidance for the identification of ecologically or biologically significant areas. The criteria for defining such areas include uniqueness, aggregation, fitness consequences, resilience, and naturalness. This science advisory process identifies proposed EBSAs in Canadian Pacific marine waters, specifically in the Strait of Georgia (SOG), along the west coast of Vancouver Island (WCVI, southern shelf ecoregion), and in the Pacific North Coast Integrated Management Area (PNCIMA, northern shelf ecoregion). Initial assessment of IA's in PNCIMA was carried out in September 2004 to March 2005 with spatial data collection coordinated by Cathryn Clarke. Subsequent efforts in WCVI and SOG were conducted in 2009, and may have used different scientific advisors, temporal extents, data, and assessment methods. WCVI and SOG IA assessment in some cases revisits data collected for PNCIMA, but should be treated as a separate effort. Other datasets in this series detail IAs for birds, cetaceans, coral and sponges, fish, invertebrates, and other vertebrates. Though data collection is considered complete, the emergence of significant new data may merit revisiting of IA's on a case by case basis.

The National Ecological Framework for Canada's "Total Land and Water Area by Ecozone” dataset provides land and water area values for ecozone framework polygons, in hectares. It includes attributes for a polygon’s total area, land-only area and large water body area.

The National Ecological Framework for Canada's "Soil Development by Ecoregion” dataset contains tables that provide soil development information for components within the ecoregion framework polygon. It provides soil development codes and their English and French-language descriptions as well as the percentage of the polygon that the component occupies. The soil development descriptions are based on the second edition of the Canadian System of Soil Classification (Agriculture Canada Expert Committee on Soil Survey, 1987).

The National Ecological Framework for Canada's "Soil Texture by Ecozone” dataset contains tables that provide soil texture information within the ecozone framework polygon. It provides soil texture codes and their English and French language descriptions as well as the percentage of the polygon that the component occupies. Soil texture indicates the relative proportions of the various soil separates (sand, silt, clay) as described by classes of texture. Soil separates are mineral particles, 2.0 mm in diameter and include: gravel 0.2 -7.5 cm and cobbles 7.5-25.0 cm. There are 12 texture group classes definitions and one class definition for Not Applicable (which indicates, for example, water, ice or urban areas).

This data contains an Index identifying Ontario Base Map map tiles. Eastern and Southern Ontario is covered at a scale of 1:10,000. Northern Ontario is covered at a scale of 1:20,000. We are no longer updating this data. It is best suited for historical research and analysis. This product requires the use of geographic information system (GIS) software.

A novel towfish incorporating sidescan and video hardware was used to ground truth echosounder data for the nearshore of Halifax Harbour. The resulting sampling grid extended from the shoreline to a depth of 10 m, including Bedford Basin through the Inner Harbour to the Outer Harbour. Each of these three zones could be distinguished from the others based upon combinations of substrate type, benthic invertebrates, and macrophyte canopy. Bedford Basin had a relative lack of macrophytes and evidence of intense herbivory. The Inner Harbour was characterized by shoreline hardening due to anthropogenic activities. The Outer Harbour was the most “natural” nearshore area with a mix of bottom types and a relatively abundant and diverse macrophyte canopy. All survey data were placed into a GIS, which could be used to answer management questions such as the placement and character of habitat compensation projects in the harbour. Future surveys utilizing similar techniques could be used to determine long term changes in the nearshore of the harbour. Cite this data as: Vandermeulen H. Data of: A Video, Sidescan and Echosounder Survey of Nearshore Halifax Harbour. Published: September 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/9122c3e2-3cfc-45d0-ac36-aecb306130f6

In 2021, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) repeated the process of generating annual crop inventory digital maps using satellite imagery to for all of Canada, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-8, Sentinel-2), and radar (RCM) based satellite images, and having a final spatial resolution of 30m. In conjunction with satellite acquisitions, ground-truth information was provided by: provincial crop insurance companies in Manitoba, & Quebec; point observations from the PEI Department of Environment, Water and Climate Change; Ontario Ministry of Agriculture, Food and Rural Affairs; University of Guelph - Ridgetown campus; British Columbia Ministry of Agriculture; and data collection supported by our regional AAFC Research and Development Centres in St. John's, Charlottetown, Kentville, Fredericton, Guelph and Summerland. Due to COVID-19 travel restrictions and forest fires, complete sampling coverages in BC was not possible, as a result the general agriculture class (120) is found in this province in areas where there was no ground data collected.

This dataset was collected in support of a Competitive Science and Research Fund project (21-CC-05-06 Impacts of coastal acidification and climate change stressors on the Atlantic sea scallop: larval supply, recruitment and adaptive capacity to multiple global change drivers) lead by Fisheries and Oceans Canada (DFO). The objective of this research is to characterize coastal environmental conditions associated with scallop spawning and larval drift in Passamaquoddy Bay, New Brunswick. This dataset includes temperature, conductivity, salinity, sigma-theta, sea pressure, and depth information taken at weekly intervals at the sampling stations. In total, this dataset represents a total of 62 CTD profiles collected across 3 sampling stations over 22 sampling days from June to October 2022. Sampling stations were selected to compare scallop recruitment signals from Chamcook Harbour, a decommissioned scallop aquaculture site in Big Bay (MS-1077) and in the middle of Passamaquoddy Bay. Data were processed in accordance with instrumentation manufacturer guidelines and DFO Ocean Data and Information Section QAQC procedures. Cite this data as: Miller, E., Quinn, B., Azetsu-Scott, K., Childs, D., Gabriel, C-E., Newhook, M. 2025. Impacts of coastal acidification and climate change stressors on the Atlantic sea scallop. Published October 2025. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B

OneSoil employs a proprietary machine learning (ML) model based on state-of-the-art instance segmentation to detect field boundaries. Utilizing raw Sentinel-2 data aggregated according to local vegetation season maps and an additional upscaling module to enhance boundary accuracy, we ensure precise results. OneSoil’s data preprocessing involves the utilization of their cloud detector module and local season mapping.