To support a wide range of efforts to understand the geographic context and historical conditions of the Indian residential schools sites for a wide range of stakeholders, Indigenous Services Canada has created a Web service to access and visualize historical aerial photography for those sites. The Historical aerial photography of Indian residential schools dataset contains digital scans of aerial photographs that were acquired from 1924 to 1998 over Indian Residential school sites and surrounding areas across Canada, as well as basic information about each photography and depicted site. The digital images were georeferenced, to match ground coordinates, saved in a resampled uncompressed raster format and compiled in a single mosaic layer. The dataset does not include the complete range of aerial photographs of each site. Instead, an attempt has been made to select a single optimal photograph for each site based on good photographic quality and the site's years of operation. In some cases no photograph is available, and in others a photograph was only available after the years of operation. The source scanned prints was obtained from the archives of the National Air Photo Library (NAPL) of Natural Resources Canada (NRCAN). This dataset should be considered evergreen as new information and photography sources are identified.It should be noted that this dataset can only be downloaded using ArcGIS and ArcPro software as well as other GIS software.

**ATTENTION! The files in this dataset are designed for streaming, not downloading. For the best experience, please follow the instructions available in the resources.**In replacement of the former Canadian Digital Elevation Model (CDEM) that is no longer supported, the Medium Resolution Digital Elevation Model (MRDEM) product is a multi-source product that integrates elevation data from the Copernicus DEM** acquired during the TanDEM-X Mission (AIRBUS, 2022), and the High Resolution Digital Elevation Model data derived from airborne lidar. This product provides a complete, 30 meters resolution, nationwide coverage for Canada. It includes a Digital Terrain Model (DTM), a Digital Surface Model (DSM) and other derived products. The spatial coverage extends into the USA, where needed, to provide coverage for cross-border watersheds in support of hydrological studies and applications. The MRDEM-30-DSM is partially based on the GLO-30 version of the Copernicus DEM** (hereafter named GLO-30). Since elevation values from the GLO-30 are referenced to the EGM2008 geoid model, they were transformed to the Canadian Height Reference System of 2013 (CGVD2013), using the CGG2013 geoid model. Where available, the MRDEM-30-DSM integrates surface data from the lidar-derived HRDEM mosaic, resampled from 1 m to 30 m. The process to generate the MRDEM-30-DTM is more complex. Where available, the HRDEM Mosaic derived from lidar was used since it already provides reliable terrain elevation values. The HRDEM Mosaic data used was resampled from 1m to 30m. Elsewhere, the processing workflow combines a forest removal model and a settlement removal model that is applied to the GLO-30 values in order to estimate the terrain elevation values. Both datasets are projected to Canada Atlas Lambert NAD83 (CSRS) (EPSG:3979).The MRDEM is referenced to the CGVD2013 which is the reference standard for orthometric heights across Canada.The product Medium Resolution Digital Elevation Model (MRDEM) is part of the CanElevation Series created in support to the National Elevation Data Strategy implemented by NRCan.** This product was in part produced using Copernicus WorldDEM-30 © DLR e.V. 2010-2014 and © Airbus Defence and Space GmbH 2014- 2018 provided under COPERNICUS by the European Union and ESA; all rights reserved.The organisations in charge of the Copernicus program by law or by delegation do not incur any liability for any use of the Copernicus WorldDEM-30.

A feature is a representation of a real world object, such as a lake, stream, dam or rapid. There are three hydrographic feature classes:  points, lines and polys. All may impede or be hazardous to waterflow and/or navigation on a watercourse or waterbody. This data shows natural and manmade point features. Examples include: * waterfalls * rapids * rocks * Sea Lamprey barriers * shipwrecks This product requires the use of geographic information system (GIS) software. [Technical Bulletin: Data migrated to new Ontario Hydro Network (OHN) - Hydrographic Feature Data Classes (PDF)](https://geohub.lio.gov.on.ca/datasets/mnrf::ontario-hydro-network-ohn-hydrographic-point/)

Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) sensors were used to generate the circa 2010 Mosaic of Canada at 30 m spatial resolution. All scenes were processed to Standard Terrain Correction Level 1T by the United States Geological Survey (USGS). Further processing performed by the Canada Centre for Remote Sensing included conversion of sensor measurements to top of atmosphere reflectance, cloud and cloud shadow detection, re-projection, selection of best measurements, mosaic generation ,noise removal and quality control. To provide a clear sky measurement for each location in Canada, data from the years 2009, 2010, and 2011 were used, but 2010 was preferentially selected. Bands 3 (0.63-0.69 µm), 4 (0.76-0.90 µm), 5 (1.55-1.75 µm), and 7 (2.08-2.35 µm) are provided in this version as significant atmosphere effects strongly limit the quality of the blue (0.45-0.52 µm) and green (0.52-0.60 µm) bands. Multi-criteria compositing was used for the selection of the most representative pixel. For ETM+ onboard Landsat 7 a scan line malfunction caused missing lines of data in all scenes collected after May 2003. Atmosphere and target variability between scenes cause these lines to have significant radiometric differences in some cases. A Fourier transformation approach was applied to correct this occurrence. This mosaic was developed for land cover and biophysical mapping applications across Canada. Other applications of these data are also possible, but should consider the temporal and spectral limitations of the product. Research to enhance the spatial, spectral and temporal aspects are in development for future versions of moderate resolution products from historical Landsat sensors, Landsat 8, and Sentinel 2 data.

1:250,000 NTDB Cultural Point Features. Man made featuresDistributed 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)

This interactive map commemorates Canada’s participation in armed conflicts at home and abroad by highlighting a sample of the many geographical features and places named for those that served our country. These commemorative geographical names help us remember war casualties, soldiers, sailors, airmen and airwomen, military leaders, and civilians recognized or decorated for outstanding acts of bravery and sacrifice in battle. These names also commemorate notable battles in which Canada participated, and Canadian military units, regiments, squadrons, and ships in which Canadians served. Federal, provincial and territorial members of the Geographical Names Board of Canada provided these commemorative names for the development of the map. Many more commemorative place names exist in Canada, and will be added in future releases of this evergreen interactive map. If you would like to contribute names to this project, please contact the Geographical Names Board of Canada Secretariat at Natural Resources Canada.

High-resolution false-color Landsat image composite of Canada's forested ecosystems (2022). This national image product represents the Composite to Change (C2C) proxy composite image derived from thousands of Landsat images acquired between July 1 and August 30, 2022. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The overall process followed is described in (Hermosilla et al. 2016 ) with details on the generation of gap-free surface reflectance composites in ( Hermosilla et al. 2015). Following the motivation and rationale presented in White et al. (White et al. 2014), Landsat imagery is subjected to a series of processing steps to remove clouds and shadows as well as haze and other unwanted atmospheric effects. Year-on-year time series of Landsat imagery are interrogated to avoid missing values, and to ensure exhaustive spatial coverage of the national surface reflectance composites. False-colour 3-channel image (bands: shortwave infrared, SWIR1; near infrared; red)When using these data, please cite as: Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G.W. Hobart, L.B. Campbell, 2016. Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. International Journal of Digital Earth 9(11), 1035-1054 (Hermosilla et al. 2016 ).

A building is a structure that has a roof and walls and stands more or less permanently in one place. Symbols are used when buildings and structures are permanent landmarks. Symbolized buildings have no side larger than 50 metres for 1:20,000 data or no side larger than 30 metres for 1:10,000 data. Small structures (including buildings less than 50 square metres) are not shown unless they constitute a point of orientation. This product requires the use of geographic information system (GIS) software. [Land Information Ontario: Data Class Fact Sheet - Building to Scale (PDF)](https://www.sdc.gov.on.ca/sites/MNRF-PublicDocs/EN/CMID/Building%20to%20Scale%20-%20Data%20Description.pdf)

This model is derived from geological, geophysical and other forms of geodata. Feature extraction used deep learning. Predictive modelling made use of the deep ensemble method. Displayed is a Pan-Canadian probability map of mineral potential of graphite. This map was generated using known graphite deposits and occurrences and their associated features. Higher probability values highlight areas with an increased probability of graphite mineral systems.

This dataset contains the surface temperature and salinity data of the enlarged coastal thermograph network of the St. Lawrence river, estuary and gulf system. It includes data from the Canadian Hydrographic Service water level network (SINECO), the Department of Fisheries and Oceans (DFO)-Quebec long-termed thermograph monitoring program network and the oceanographic buoy network.Each station is linked with a .png file showing the temperature and salinity time series and with a .csv file containing the surface temperature and salinity data themselves (columns : Station,Latitude,Longitude,Date(UTC),Depth/Profondeur(m),Temperature/Température(ºC),Salinity/Salinité(psu)).Supplemental InformationA detailed description of the networks (SINECO, oceanographic buoys and the DFO-Quebec thermograph monitoring program) is available at the St. Lawrence Global Observatory (SLGO) portal :SINECO : https://ogsl.ca/en/tide-gauges-dfo-chs/Oceanographic buoys : https://ogsl.ca/en/marine-conditions-buoys-dfo/Thermographs: https://ogsl.ca/en/marine-conditions-thermographs-dfo/Technical Reports related to the Thermograph Network (the last one is also available at the same hypertext link mentionned above) :Pettigrew, B., Gilbert, D. and Desmarais R. 2016. Thermograph network in the Gulf of St. Lawrence. Can. Tech. Rep. Hydrogr. Ocean Sci. 311: vi + 77 p.Pettigrew, B., Gilbert, D. and Desmarais R. 2017. Thermograph network in the Gulf of St. Lawrence: 2014-2016 update. Can. Tech. Rep. Hydrogr. Ocean Sci. 317: vii + 54 p.