The Innu Audio Index is an extract from the Canadian Geographical Names Data Base (CGNDB) of geographical names with associated audio. The shared audio with the Geographical Names Board of Canada (GNBC) is the intellectual property of the Innu Nation. The points represent official geographical names in Innu-aimun, the language of the Innu Nation. The CGNDB is the authoritative national database of Canada's geographical names. It contains geographical names and their attributes that have been approved by the GNBC, the national coordinating body responsible for standards and policies on place names.The GNBC is working to increase awareness of existing Indigenous place names and help promote the revitalization of Indigenous cultures and languages. The GNBC does not warrant or guarantee that the information is accurate, complete or current at all times. For more information, to report data errors, or to suggest improvements, please contact the GNBC Secretariat at Natural Resources Canada with questions or for more information.

The Indigenous Geographical Names dataset presents an extract from the Canadian Geographical Names Data Base (CGNDB) of geographical names with roots in Indigenous cultures. These geographical names reflect heritage, language, personal names, and cultural practices. Terrain and water features, populated places and culturally relevant places are geographical feature types present in the dataset. The Geographical Names Board of Canada (GNBC) is working to increase awareness of existing Indigenous place names and help promote the revitalization of Indigenous cultures and languages. Many more Indigenous place names exist in Canada, and this dataset will be constantly evolving as additional Indigenous place names are officially recognized and identified. The Geographical Names Board of Canada does not warrant or guarantee that the information is accurate, complete or current at all times. For more information, to report data errors, or to suggest improvements, please contact the GNBC Secretariat at Natural Resources Canada with questions or for more information. The CGNDB is the authoritative national database of Canada's geographical names. The purpose of the CGNDB is to store geographical names and their attributes that have been approved by the GNBC, the national coordinating body responsible for standards and policies on place names. This dataset is extracted from the CGNDB on a weekly basis, and consists of current officially approved names, feature type, coordinates of the feature, decision date, source, Indigenous language of origin where known, and other attributes.

The Canadian Geographical Names Data Base (CGNDB) is the authoritative national database of Canada's geographical names. The purpose of the CGNDB is to store place names and their attributes that have been approved by the Geographical Names Board of Canada (GNBC), the national coordinating body responsible for standards and policies on place names. The CGNDB is maintained by Natural Resources Canada, through the Canada Centre for Mapping and Earth Observation. The geographic extent of the CGNDB is the Canadian landmass and water bodies; the temporal extent is from 1897 to present. This dataset is extracted from the CGNDB on a weekly basis, and consists of current officially approved names, feature type, coordinates of the feature, decision date, source, and other attributes. The output file formats for this product are: text (CSV), Shape (SHP), and Keyhole Markup Language (KML).Content advisory: The Canadian Geographical Names Database contains historical terminology that is considered racist, offensive and derogatory. Geographical naming authorities are in the process of addressing many offensive place names, but the work is still ongoing. For more information, please contact the GNBC Secretariat.

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

Notice - Replacement of the English and French Web services (WMS and ESRI REST) with a bilingual one.The NRN product is distributed in the form of thirteen provincial or territorial datasets and consists of two linear entities (Road Segment and Ferry Connection Segment) and three punctual entities (Junction, Blocked Passage, Toll Point) with which is associated a series of descriptive attributes such as, among others: First House Number, Last House Number, Street Name Body, Place Name, Functional Road Class, Pavement Status, Number Of Lanes, Structure Type, Route Number, Route Name, Exit Number. The development of the NRN was realized by means of individual meetings and national workshops with interested data providers from the federal, provincial, territorial and municipal governments. In 2005, the NRN edition 2.0 was alternately adopted by members from the Inter-Agency Committee on Geomatics (IACG) and the Canadian Council on Geomatics (CCOG). The NRN content largely conforms to the ISO 14825 from ISO/TC 204.

The daily climate records database, also known as Long Term Climate Extremes (LTCE), was developed to address the fragmentation of climate information due to station changes (opening, closing, relocation, etc.) over time. For approximately 750 locations in Canada, "virtual" climate stations have been developed by joining (threading) climate data for an urban location, from nearby stations to make long-term records. Each long-term record consists of the extremes (record values) of daily maximum/minimum temperatures, total precipitation and snowfall for each day of the year. Many of the longest data sets of extremes date as far back as the 1800s. This data provides the daily extremes of record for Precipitation for each day of the year. Daily elements include: Greatest Precipitation.

This catalog contains annual 30 m spatial resolution snow dynamics metrics for each snow-year from 2018-2019 to 2023-2024 for all of Canada. We gather all Landsat and Sentinel-2 images collected over Canada and identify the status of each pixel observation on the image collection date: snow (and ice), non-snow (i.e., land, water), unclear (i.e., clouds, shadows). We built an algorithm to calculate snow cover metrics for each pixel during each winter: start date of the first (and biggest) snow period [startF, startB], end date of the last (and biggest) snow period [endL, endB], number of days with snow cover in total (or in the biggest snow period) [lengthT, lengthB], number of snow periods (i.e., separated times with multiple confirmed snow observations) [periods], and a status classification (e.g., continuous snow, snow free) [status]. We do not obtain a clear observation every day because of satellite orbit frequencies and clouds. This means that timing-based metrics are identified by the middle date between two clear observations, with uncertainty quantified as half the length of the gap (i.e., ± days) [startF_u, startB_u, endL_u, endB_u, lengthT_u, lengthB_u].

This polygon layer represents accumulated precipitation forecasts from the Global Forecast System (GFS), a global numerical weather prediction model operated by NOAA/NCEP. It provides global medium‑range precipitation forecasts, as a 168‑hour (7‑day) accumulation, to support a wide range of weather and hydrological applications.This polygon layer is generated by extracting the accumulated precipitation field from Global Forecast System (GFS) GRIB2 files. The raw data are converted into a TIF raster, then resampled, smoothed, and classified into discrete precipitation ranges. The resulting polygon features depict forecasted precipitation accumulations over a 7‑day (168‑hour) period, allowing users to monitor expected rainfall and snowfall patterns on a global scale.

Climate

Daily climate observations are derived from two sources of data. The first are Daily Climate Stations producing one or two observations per day of temperature, precipitation. The second are hourly stations that typically produce more weather elements e.g. wind or snow on ground. Only a subset of the total stations is shown due to size limitations. The criteria for station selection are listed as below. The priorities for inclusion are as follows: (1) Station is currently operational, (2) Stations with long periods of record, (3) Stations that are co-located with the categories above and supplement the period of record.