Spiny dogfish (Squlaus acanthias), is a species found in Atlantic Canadian waters which is encountered mostly in commercial fisheries. Pop-up Satellite Archival Tags (PSAT) from Wildlife Computers were applied to spiny dogfish from 2008 to 2009 to collect data on depth (pressure), temperature and ambient light level (for position estimation). Deployments were conducted in Canada on commercial fishing vessels from August to October. Wildlife Computers PSAT Mk10 (N=6) were used and 3 of 6 tags reported. One tag was found washed up on shore and was returned. The spiny dogfish tagged ranged in size from 80 cm to 96 cm Fork Length (curved); all 6 were female. Time at liberty ranged from 75 – 234 days and the 43 tags that reported remained on the sharks for the programmed duration. 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 deployments can be obtained upon request from: warren.joyce@dfo-mpo.gc.ca or heather.bowlby@dfo-mpo.gc.ca.

Natural areas abutting Lake Simcoe are areas of a continuous vegetation community class that have a minimum size of 1 ha and are wholly or partially within the 30 m buffer zone of the Lake Simcoe shoreline. These areas may be a narrow band of vegetation along the shoreline or larger areas, which extend a greater distance from the shoreline. As described in policy 6.31-SA, the MNR and the MOE will map the location of natural areas abutting Lake Simcoe.

The National Ecological Framework for Canada's "Surficial Geology by Ecozone” dataset contains tables that provide surficial geology information with the ecozone framework polygons. It provides codes that characterize surficial geology (unconsolidated geologic materials) and their English and French-language descriptions as well as information about the area and percentage of the polygon that the material occupies.

Railway network on the territory of the city. **Collection context** Historical data from the Government of Quebec. Additional data by photointerpretation. **Collection method** Computer-aided mapping. **Attributes** * `ID_VFR` (`integer`): Identifier * `SOURCE` (`varchar`): Source * `DATE_CREATION` (`smalldatetime`): Created on * `DATE_MODIFICATION` (`smalldatetime`): Modified on * `USER_MODIFICATION` (`varchar`): Modified by For more information, consult the metadata on the Isogeo catalog (OpenCatalog link).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Electoral division of the 2017 election. **Collection context** Creation of districts in collaboration with the legal services and the electoral data of the Director General of Elections (DGE). Balancing of districts according to anthropogenic constraints and number of voters. **Collection method** Computer-aided mapping. **Attributes** * `ID_SEC_DIS` (`long`): Identifier * `NAME_DISTRI` (`varchar`): District name * `NO` (`long`): District number * `AREA` (`varchar`): Area * `ADVISORY_NAME` (`varchar`): Name of the advisor * `SOURCE` (`varchar`): Source * `DATE_CREAT` (`date`): Creation date * `DATE_MODIF` (`date`): Date of modification * `USER_MODIF` (`varchar`): Modified by For more information, consult the metadata on the Isogeo catalog (OpenCatalog link).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Major assignment layer. **Collection context** Taken from the zoning by-law. **Collection method** Computer-aided mapping. **Attributes** * `ID_ASSIGNATION` (`integer`): Identifier * `ASSIGNMENT` (`varchar`): Assignment * `CODE_ASSIGNATION` (`varchar`): Assignment code * `ZON_AREA` (`numeric`): Area * `SECTOR` (`varchar`): Sector * `NOTE` (`varchar`): Note * `DATE_CREATION` (`smalldatetime`): Created on * `DATE_MODIFICATION` (`smalldatetime`): Modified on * `USER_MODIFICATION` (`varchar`): Modified by * `SOURCE` (`varchar`): Source For more information, consult the metadata on the Isogeo catalog (OpenCatalog link).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Polygonal layer of electoral districts for the 2025 election. New balancing of voters increases the number of districts from 11 to 10 for the 2025 election. **Collection context** Review committee to balance the districts according to the data of the Chief Electoral Officer. **Collection method** Analysis of voters by address using cartographic analysis software. Update by computer-aided mapping. **Attributes** * `ID_SEC_DISTRICT_ELEC` (`integer`): Identifier * `DISTRICT_NAME` (`varchar`): District name * `NO` (`integer`): Number * `AREA` (`varchar`): Area * `ADVISOR_NAME` (`varchar`): Recommended * `SOURCE` (`varchar`): Source * `DATE_CREATION` (`smalldatetime`): Created on * `DATE_MODIFICATION` (`smalldatetime`): Modified on * `USER_MODIFICATION` (`varchar`): Modified by For more information, consult the metadata on the Isogeo catalog (OpenCatalog link).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Buffer zone of 300 meters around the railways present on the territory of the city. Used in public safety analyses. **Collection context** Derived from the layer of railways in the territory of the city of Saint-Hyacinthe. **Collection method** Buffer zone of 300 meters. Spatial analysis. **Attributes** * `Id` (`long`): Identifier For more information, consult the metadata on the Isogeo catalog (OpenCatalog link).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The data layer (.shp) presented is the result of an unsupervised classification method for classifying seafloor habitat on German Bank (off South West Nova Scotia, Canada). This method involves separating environmental variables derived from multibeam bathymetry (Slope, Curvature) and backscatter (principal components: Q1, Q2, and Q3) into spatial units (i.e. pixels) and classifying the acoustically separated units into 5 habitat classes (Reef, Glacial Till, Silt, Silt with Bedforms, and Sand with Bedforms) using in situ data (imagery). Benthoscape classes (synonymous to landscape classifications in terrestrial ecology) describe the geomorphology and biology of the seafloor and are derived from elements of the seafloor that were acoustically distinguishable. Unsupervised classifications (acoustic classifications) optimized at 15 classes using Idrisi CLUSTER method (pixel based) Number representing the benthoscape classes (CLASS) derived from in situ imagery and video (See Brown et al., 2012, Figure 3, Table 1). Benthoscape classes (See Brown et al., 2012, Figure 3). Reference: Brown, C. J., Sameoto, J. A., & Smith, S. J. (2012). Multiple methods, maps, and management applications: Purpose made seafloor maps in support of ocean management. Journal of Sea Research, 72, 1–13. https://doi.org/10.1016/j.seares.2012.04.009 Cite this data as: Brown, C. J., Sameoto, J. A., & Smith, S. J. Data of: Benthoscape Map of German Bank. Published: February 2021. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/b7f81d4a-2cb6-4393-b35b-e536ec63e834

In 2019, 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 (RADARSAT-2) 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 Alberta, Saskatchewan, Manitoba, & Quebec; point observations from the PEI Department of Environment, Water and Climate Change and data collection supported by our regional AAFC Research and Development Centres in St. John’s, Kentville, Charlottetown, Fredericton, and Guelph.