The Annual Minimum Snow and Ice (MSI) Extent of the Atlas of Canada National Scale Data, are data sets compiled containing annual data from 2000 to present. The data sets were derived from research published by the Canada Centre for Remote Sensing which classified satellite imagery over Canada and neighbouring regions for the continued presence or absence of snow and ice from April 1 to September 20 each year. The Atlas of Canada MSI products consist of a vector dataset and a raster time-series animation application.VECTOR DATASETThe vector dataset has been generalized to display at the scale of 1:1,000,000.TIME-SERIES ANIMATION APPLICATIONThe time-series animation application has not been generalized from its original scale (250 m pixels).The application is disseminated through the Data Cube Platform, implemented by the Canada Centre for Mapping and Earth Observation, Natural Resources Canada using geospatial big data management techniques. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The time-series is also available as a Web Map Service (WMS) and Web Coverage Service (WCS).CREDITSource data provided by Alexander P. Trishchenko, Canada Centre for Remote Sensing, Natural Resources Canada Metadata record: https://open.canada.ca/data/en/dataset/808b84a1-6356-4103-a8e9-db46d5c20fcf

Surveyed Borders are an Administrative Land Object that represents the spatial limits of a jurisdiction that is created and managed as a separate entity within the ICM database. In the original ICM dataset from NRCAN, this feature class is called Administrative Boundaries. Administrative Boundaries are available for the Yukon Territory, Northwest Territories and Nunavut and may include International, Provincial and Territorial boundaries. This cadastral framework provides a parcel base of properly structured vector data designed and suited for Geographical Information System (GIS) application and can be used for land management purposes. This data set is not be used for defining boundaries. Administrative decisions should be based on legal documents and legal survey plans.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)

Data provided shows grants and contributions provided to Canadian firms by National Research Council (NRC) and its Industrial Research Assistance Program (IRAP) between April 1, 2023 and March 31, 2024.

Data provided shows grants and contributions provided to Canadian firms by National Research Council (NRC) and its Industrial Research Assistance Program (IRAP) between April 1, 2018 and March 31, 2019.

This is a legacy product that is no longer supported. It may not meet current government standards.The Canadian Digital Surface Model (CDSM) is part of Natural Resources Canada's altimetry system designed to better meet the users' needs for elevation data and products. The 0.75-second (~20 m) CDSM consists of a derived product from the original 1-second (30 m) Shuttle Radar Topographic Mission (SRTM) digital surface model (DSM). In these data, the elevations are captured at the top of buildings, trees, structures, and other objects rather than at ground level.A CDSM mosaic can be obtained for a pre-defined or user-defined extent. The coverage and resolution of a mosaic varies according to the extent of the requested area.Derived products such as slope, shaded relief and colour shaded relief maps can also be generated on demand by using the Geospatial-Data Extraction tool. Data can then be saved in many formats.The pre-packaged GeoTiff datasets are based on the National Topographic System of Canada (NTS) at the 1:50 000 scale; the NTS index file is available in the Resources section in many formats.

Data provided shows grants and contributions provided to Canadian firms by National Research Council (NRC) and its Industrial Research Assistance Program (IRAP) between April 1, 2024 and March 31, 2025.

Data provided shows grants and contributions provided to Canadian firms by National Research Council (NRC) and its Industrial Research Assistance Program (IRAP) between April 1, 2020 and March 31, 2021.

Data include a collection of annual land cover maps derived from MODIS 250 m spatial resolution remotely sensed imagery for the period 2000 to 2011. Processing of the time series was designed to reduce the occurrence of false change between maps. The method was based on change updating as described in Pouliot et al. (2011, 2013). Change detection accounted for both abrupt changes such as forest harvesting and more gradual changes such as recurrent insect defoliation. To determine the new label for a pixel identified as change, an evidential reasoning approach was used to combine spectral and contextual information. The 2005 MODIS land cover of Canada at 250 m spatial resolution described in Latifovic et al. (2012) was used as the base map. It contains 39 land cover classes, which for time series development was considered too detailed and was reduced to 25 and 19 class versions. The 19 class version corresponds to the North America Land Change Monitoring System (NALCMS) Level 2 legend as described in Latifovic et al. (2012). Accuracy assessment of time series is difficult due to the need to assess many maps. For areas of change in the time series accuracy was found to be 70% based on the 19 class thematic legend.This time series captures the spatial distribution of dominant land cover transitions. It is intended for use in modeling, development of remote sensing products such as leaf area index or land cover based albedo retrievals, and other exploratory analysis. It is not appropriate for use in any rigorous reporting or inventory assessments due to the accuracy of the land cover classification and uncertainty as to the capture of all relevant changes for an application.

Data provided shows grants and contributions provided to Canadian firms by National Research Council (NRC) and its Industrial Research Assistance Program (IRAP) between April 1, 2019 and March 31, 2020.

Regional Deterministic Air Quality Analysis (RDAQA) is an objective analysis of surface pollutants that combines numerical forecasts from the Regional Air Quality Deterministic Prediction System (RAQDPS) with hourly observations from various monitoring networks in North America, including the Canadian measurement networks operated by the provinces, territories and certain cities, as well as the various American networks in the context of the AIRNow program administered by US/EPA (US Environmental Protection Agency). RDAQA analysis provides the best description of current air quality conditions, and is used to inform the public, meteorologists in the various Environment and Climate Change Canada forecasting offices, Health Canada and other users about the distribution of air pollutants near the ground, and the performance of forecasting models. Each hour, a preliminary product is available approximately one hour after the observation measurement time, while final and Firework products are available approximately two hours after the measurement time. The preliminary and final products contain analysis of the chemical constituents O3, SO2, NO, NO2, PM2.5 (fine particles with diameters of 2.5 micrometers or less) and PM10 (coarse particles with diameters of 10 micrometers or less), while the Firework product contains analysis of PM2.5 and PM10.