This dataset provides wall-to-wall maps of forest structure across Canada's 650 million hectare forested ecosystems for the year 2022, generated at a spatial resolution of 30 m. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Structure estimates include key attributes such as canopy height, canopy cover, and aboveground biomass, derived using a combination of airborne lidar and Landsat-based spectral composites. Structure models were trained using the - lidar-plot framework - (Wulder et al. 2012), which integrates co-located airborne lidar data and ground plot measurements with Landsat time-series composites (Hermosilla et al. 2016). A Nearest Neighbour imputation approach was applied to estimate structural attributes across the full extent of Canada's forested area. These nationally consistent products are intended to support strategic-level forest monitoring and assessment and are not designed for operational forest management.For further details on the methods, accuracy assessment, and source data, see Matasci et al. (2018).Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment, 216, 697-714. https://doi.org/10.1016/j.rse.2018.07.024 (Matasci et al. 2018)

Feature point layer showing COVID-19 rapid antigen test kit distribution sites in Manitoba.Feature point layer showing locations of distribution sites that currently have COVID-19 rapid antigen test kits available in Manitoba. The main purpose of this data is to provide the public with the hours of operation for these sites. Distributors include pharmacies, retail stores, and community libraries. This data is populated by Manitoba Shared Health and is updated as needed. This feature layer is used in the Manitoba COVID-19 Rapid Antigen Test Kit Availability Map and Manitoba COVID-19 Rapid Antigen Test Kit Availability application. For more information on Manitoba’s response to COVID-19, please visit the following site: https://www.gov.mb.ca/covid19/index.html Fields included [Alias (Field Name): Field description] Site Category (Site_Category): Indicates whether the site is a retail business, pharmacy, or community library Site Name (Site_Name): Official business name of the site  Address (Address): Street address of the site  City or Town (City_or_Town): City or town in which the site is located Postal Code (Postal_Code): Postal code that corresponds with the street address of the site  Phone (Phone): Telephone number for the site French Service (French_Service): Indicates whether a site self-identified as having services available in French; if unknown, value is null   Health Authority (Health_Authority): Name of the regional health authority where the site is located Hours of Operation (Hours_of_Operation): Listing of days and times that the site is open to the public Alt Hours Start (Alt_Hours_Start): Start date of when alternate hours are in effect Alt Hours End (Alt_Hours_End): End date of when alternate hours are in effect Alternate Hours of Operation (Alternate_Hours_of_Operation): Listing of alternate days and times that the site is open to the public Latitude (Latitude): Latitudinal coordinate of the site Longitude (Longitude): Longitudinal coordinate of the site

This dataset provides results obtained by Health Canada’s Canadian Radiological Monitoring Network (CRMN) for 90Sr activity in milk samples originating from various locations across Canada. More information about the CRMN network can be found on the Health Canada website (see link below). From 1984 to 1993, data was collected from 20 locations. After 1993, routine milk analysis for radio-strontium activity was discontinued for all monitoring stations, except the Ottawa location. The results provided here are 90Sr activity concentrations in units of becquerels per litre (Bq/L). Milk is an important matrix for environmental radioactivity assessment since many radionuclides of health concern exhibit efficient soil to milk uptake pathways. As such, the surveillance of milk provides a very good indication as to the severity of environmental impact following a nuclear event. Strontium-90 (90Sr) is a radionuclide of particular concern because it has a long radiological and biological half-life coupled with a high affinity for incorporation into human bone and teeth. Nuclear weapons testing and nuclear accidents have released such long-lived radionuclides into the atmosphere, which in turn have entered the biological life cycle. Nevertheless, a steady decline in the activity concentration of 90Sr in milk can be seen since most of the nuclear weapon testing was halted in the 1960s. The map shows the approximate sampling location for each monitoring station. Stations are found within the associated location range.

Statistics Canada, in collaboration with the Public Health Agency of Canada and Natural Resources Canada, is presenting selected Census data to help inform Canadians on the public health risk of the COVID-19 pandemic and to be used for modelling analysis. The data provided here show the counts of the population in nursing homes and/or residences for senior citizens by broad age groups (0 to 79 years and 80 years and over) and sex, from the 2016 Census.Nursing homes and/or residences for senior citizens are facilities for elderly residents that provide accommodations with health care services or personal support or assisted living care.Health care services include professional health monitoring and skilled nursing care and supervision 24 hours a day, 7 days a week, for people who are not independent in most activities of daily living.Support or assisted living care services include meals, housekeeping, laundry, medication supervision, assistance in bathing or dressing, etc., for people who are independent in most activities of daily living.Included are nursing homes, residences for senior citizens, and facilities that are a mix of both a nursing home and a residence for senior citizens.Excluded are facilities licensed as hospitals, and facilities that do not provide any services (which are considered private dwellings).

Yukon Bioclimate Zones and Subzones Version 1.0 is derived from a 30 m Digital Elevation Model (DEM) and a set of "rule-polygons". Each rule-polygon contains attributes that define upper and lower elevation limits of the bioclimate zone/subzone(s) that occur within the rule-polygon. Rule-polygon attributes and extent is defined by field data, expert observation and/or available imagery. Where available, rule-polygons were derived from plot data representative of climate (i.e. reference site). Yukon Bioclimate Zones and Subzones Version 1.0 may be used at scales larger than 1:250,000 with caution. This mapping is deliberately extended across the ocean, lakes, glaciers, etc to facilitate intersection with a terrestrial landcover layer of the user's choice. A map legend and map for this version is published in Southern Lakes Boreal Low Subzone (BOLsl): A Field Guide to Ecosite (Environment Yukon 2017). The Yukon Bioclimate Classification and Mapping project is ongoing, and subject to periodic updates or revisions. Because of this, the onus is on the end-user to ensure that they are using the most current version of the data. Although every effort has been made to ensure the correctness of the report and spatial products, there still may be errors. Please report errors in the data to the Custodian.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

MetNotes are a geo- and time-referenced, free form polygon product issued by MSC that complement today's location-based dissemination systems. The concise text of a MetNote (similar to a Tweet) is consistent with communication today where people are seeking information at a glance. Meteorologists will issue a MetNote to add contextual and/or impact information to complement the public forecast that is valid over a specific area, for a specific time range.

High-resolution map of leading tree species distribution for Canada’s forested ecosystems (2019). Leading tree species map produced from a 2019 Landsat image composite, geographic and climate data, elevation derivatives, and remote sensing derived phenology following the framework described in Hermosilla et al. (2022). Regional classification models were generated based on Canada’s National Forest Inventory using a 150x150 km tiling system. The leading tree species are defined by representing the most voted tree species from the Random Forests classification models (i.e. the class with the highest class membership probability).The data represents leading tree species of Canada's forested ecosystems in 2019. An image compositing window of August 1 ± 30 days was used to generate the best-available-pixel (BAP) image composites utilized as source data for the classification.The science and methods developed to generate the information outcomes shown here, that track and characterize the history of Canada’s forests, were led by Canadian Forest Service of Natural Resources Canada, developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS), partnered with the University of British Columbia, augmented by processing capacity from Digital Research Alliance of Canada.For an overview on the data, image processing, and methods applied, as well as information on independent accuracy assessment of the data, see Hermosilla et al. (2022) https://doi.org/10.1016/j.rse.2022.113276When using this data, please cite as: Hermosilla, T., Bastyr, A., Coops, N.C., White, J.C., Wulder, M.A., 2022. Mapping the presence and distribution of tree species in Canada’s forested ecosystems. Remote Sensing of Environment 282, 113276.

Statistics Canada, in collaboration with the Public Health Agency of Canada and Natural Resources Canada, is presenting selected Census data to help inform Canadians on the public health risk of the COVID-19 pandemic and to be used for modelling analysis.The data provided here show the population counts and percentage distribution for various geographic levels by broad age groups, males, females and both sexes, from the 2016 Census.

In this dataset, we share maps of annual dominant tree species (also known as leading tree species) from 1984-2022 covering the entirety of Canada's 650 Mha forested ecosystems using Landsat time-series imagery at a 30-m spatial resolution. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Classifications are based on regionally representative Random Forests model using local training samples from Canada's National Forest Inventory (Hermosilla et al., 2024). Descriptive metrics provide information on spectral, geographic, climatic, and topographic characteristics. Initial annual tree species classifications were subjected to a time series post-classification process using the forward-backward Hidden Markov Model to improve the temporal consistency of tree species transitions within the time series. Assessment of the annual species maps using independent validation data resulted in an overall accuracy of 86.1% ± 0.14% (95%-confidence interval). These data allow consistent comparison of trends and rates of change in tree species composition nationally and across regions using a common time frame, spatial resolution, and analytical approach.Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Bater, C.W., Hobart, G.W., 2024. Characterizing long-term tree species dynamics in Canada's forested ecosystems using annual time series remote sensing data. Forest Ecology and Management, 122313. https://doi.org/10.1016/j.foreco.2024.122313 (Hermosilla et al. 2024)

The Wildlife Management Unit Biologist Contact Boundaries dataset is comprised of all the polygons that represent the Wildlife Management Unit Biologist Contact Boundaries within the Province of Alberta. The dataset is to help determine which Biologist is responsible for each Wildlife Management Unit. Please refer to the metadata included with the data for full entity attribute information.