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.

The AAFC Infrastructure Flood Mapping in Saskatchewan 20 centimeter colour orthophotos is a collection of georeferenced color digital orthophotos with 20 cm pixel size. The imagery was delivered in GeoTIF and ECW formats. The TIF and ECW mosaics were delivered in the same 1 km x 1 km tiles as the LiDAR data, and complete mosaics for each area in MrSID format were also provided. The digital photos were orthorectified using the ground model created from the DTM Key Points. With orthorectification, only features on the surface of the ground are correctly positioned in the orthophotos. Objects above the surface of the ground, such as building rooftops and trees, may contain horizontal displacement due to image parallax experienced when the photos were captured. This is sometimes apparent along the cut lines between photos. For positioning of above-ground structures it is recommended to use the LiDAR point clouds for accurate horizontal placement.

The MODIS surface albedo dataset was produced by the Canada Center for Remote Sensing (CCRS), Natural Resources Canada. The dataset represents the solar shortwave broadband surface albedo and it is at a 10-day interval covering the entire Canadian landmass as well as northern USA, Alaska, and the Greenland. The dataset was derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the TERRA satellite which provides a global coverage every 1-2 days in 36 spectral bands ranging from visible to infrared and to thermal wavelengths between 405 and 14,385 nm, and was available since 2000. For the estimation of surface albedo, the first seven spectral bands of B1 to B7 ranging from 459 nm to 2155 nm were used. B1 and B2 have a 250 meter resolution and B3 to B7 have a 500 meter resolution. A downscaling method using a regression and normalization scheme was employed to downscale the bands B3 to B7 to 250 meter resolution while preserving radiometric properties of the original data. To obtain clear-sky observations from MODIS, composite images for a 10 day period were generated by using a series of advanced algorithms (Luo et al., 2008). The 10-day composites of B1-B7 reflectance were then used to retrieve spatially continuous spectral albedo by using a combined land/snow BRDF (Bi-directional Reflectance Distribution Function) model. In that method, the modified RossThick-LiSparse BRDF model (Maignan et al., 2004) for land and Kokhanovsky and Zege’s model (2004) for snow are linearly combined for mixed surface conditions. They are weighted by snow fraction (0.0 ~ 1.0). The seven spectral albedo were then converted into the shortwave broadband surface albedo using the empirical MODIS polynomial conversion equation of Liang et al. (1999). The data product is in LCC (Lambert Conformal Conic) projection with a 250m pixel resolution. There are 36 albedo images per year. A dataset representing the pixel state (e.g. cloud/shadow, snow/ice, water, land, et al.) was also generated for each 10-day corresponding to the surface albedo product. References: Kokhanovsky, A. A. and Zege, E. P., 2004, Scattering Optics of Snow, Applied Optics, 43, 1589-1602, doi:10.1364/AO.43.001589, 20. Liang, S., Strahler, A.H., Walthall, C., 1999. Retrieval of land surface albedo from satellite observations: a simulation study. J. Appl. Meteorol. 38, 712–725. Luo, Y., Trishchenko, A.P., Khlopenkov, K.V., 2008. Developing clear-sky, cloud and cloud shadow mask for producing clear-sky composites at 250-meter spatial resolution for the seven MODIS land bands over Canada and North America. Remote Sens. Environ. 112, 4167–4185. Maignan, F., F.M. Bréon and R. Lacaze, 2004, Bidirectional reflectance of Earth targets : evaluation of analytical models using a large set of spaceborne measurements with emphasis with the hot spot, Remote Sens. Environ., 90, 210-220.

Note: To visualize the data in the viewer, zoom into the area of interest. The National Air Photo Library (NAPL) of Natural Resources Canada archives over 6 million aerial photographs covering all of Canada, some of which date back to the 1920s. This collection includes Time Series of aerial orthophoto mosaics over a selection of major cities or targeted areas that allow the observation of various changes that occur over time in those selected regions. These mosaics are disseminated through the Data Cube Platform implemented by NRCan using geospatial big data management technologies. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The data is available as Cloud Optimized GeoTIFF (COG) files for direct access and as Web Map Services (WMS) or Web Coverage Services (WCS) with a temporal dimension for consumption in Web or GIS applications. The NAPL mosaics are made from the best spatial resolution available for each time period, which means that the orthophotos composing a NAPL Time Series are not necessarily coregistered. For this dataset, the spatial resolutions are: 100 cm for the year 1947 and 50 cm for the year 1977. The NAPL indexes and stores federal aerial photography for Canada, and maintains a comprehensive historical archive and public reference centre. The Earth Observation Data Management System (EODMS) online application allows clients to search and retrieve metadata for over 3 million out of 6 million air photos. The EODMS online application enables public and government users to search and order raw Government of Canada Earth Observation images and archived products managed by NRCan such as aerial photos and satellite imagery. To access air photos, you can visit the EODMS web site: https://eodms-sgdot.nrcan-rncan.gc.ca/index-en.html

The 2005 AAFC Land Use is a culmination and curated metaanalysis of several high-quality spatial datasets produced between 1990 and 2021 using a variety of methods by teams of researchers as techniques and capabilities have evolved. The information from the input datasets was consolidated and embedded within each 30m x 30m pixel to create consolidated pixel histories, resulting in thousands of unique combinations of evidence ready for careful consideration. Informed by many sources of high-quality evidence and visual observation of imagery in Google Earth, we apply an incremental strategy to develop a coherent best current understanding of what has happened in each pixel through the time series.

The ‘Circa 1995 Landcover of the Prairies’dataset is a geospatial raster data layer portraying the rudimentaryland cover types of all grain-growing areas of Manitoba, Saskatchewan, Alberta and northeastern British Columbia at a 30-metre resolution for the 1995 timeframe. It is the collection of all the classified imagery (1993 to 1995) of the Western Grain Transition Payment Program (WGTPP) assembled into a single seamless raster data layer.

This dataset includes the extent of the boreal forest as well as the extent of managed boreal forest worldwide. The extent of boreal forest was produced from Brandt et al. (2013) and a modified version of Goudilin (1987). Managed forest was defined as suggested by IPCC (2003) using data from FAFS (2009), Gauthier et al. (2014), See et al. (2015) and AICC maps. The extent of managed forest mostly includes areas managed for wood production, areas protected from large-scale disturbances as well as formal protected areas. Both boreal forest extent and managed boreal forest extent are available in raster and vector data. Please cite this data product as: Boucher, D., D.G. Schepaschenko, S. Gauthier, P. Bernier, T. Kuuluvainen, A. Z. Shvidenko. 2024. World boreal forest and managed boreal forest extent. DOI: 10.23687/88d70716-2600-4995-8d5f-86f96e383abf These data were presented in the following article: Gauthier, S., P. Bernier, T. Kuuluvainen, A. Z. Shvidenko, D. G. Schepaschenko. 2015. Boreal forest health and global change. Science 349:819-822. DOI: 10.1126/science.aaa9092 References: J. P. Brandt, M. D. Flannigan, D. G. Maynard, I. D. Thompson, W. J. A. Volney, Environ. Rev. 21, 207–226 (2013) I. S. Goudilin, Landscape map of the USSR. Legend to the landscape map of the USSR. Scale 1:2 500 000. Moscow, Ministry of Geology of the USSR (1987) [in Russian]. Inter-governmental panel on climate change (IPCC). J. Penman, M. Gytarsky, T. Hiraishi, T. Krug, D. Kruger, et al., Eds., Good practice guidance for land use, land-use change and forestry (IPCC/NGGIP/IGES, Kanawaga, 2003) Federal Agency of Forest Service (FAFS), Forest Fund of the Russian Federation (state by 1 January 2009) (Federal Agency of Forest Service, Moscow, 2009) [in Russian] S. Gauthier et al., Environ. Rev. 22, 256–285 (2014). See et al., Harnessing the power of volunteers, the internet and Google Earth to collect and validate global spatial information using Geo-Wiki. Technological Forecasting and Social Change. (2015). doi:10.1016/j.techfore.2015.03.002 Alaska Interagency Coordination Center (AICC). Fire Information. https://fire.ak.blm.gov/content/maps/aicc/Large%20Maps/Alaska_Fire_Management_Options.pdf (the version of 2014 was used)

The Saskatchewan Digital Land Cover was created to be used in the interim. The National Land Cover Project plans to integrate land cover information compiled by Natural Resources Canada, Canadian Forest Service, and Agriculture and Agri-Food Canada. The Saskatchewan Digital Land Cover raster provides a seamless provincial coverage of the province and was created by combining the Saskatchewan Research Council's Northern Digital Land Cover (NDLC) with the Southern Digital Land Cover (SDLC).  With exception to the SDLC's value 2 (i.e. Hay Crops) and value 3 (i.e. Native Dominant Grass Lands), the NDLC takes precedence over the SDLC in areas that the two rasters overlap because the NDLC is more current than the dated SDLC. The SDLC's values 2 and 3 were preserved because these land covers are not specifically represented in the NDLC. For the purpose of this dataset, some of the SDLC and NDLC values were reclassified to new values to reconcile varying definitions.  It should also be noted that because the NDLC's 30 x 30 metre pixels do not align with the SDLC's 30 x 30 metre pixels, this raster was snapped to the NDLC. Last, as is with the SDLC and the NDLC, the extent of this raster does not extend all of the way to the Saskatchewan boundary, specifically, the Information Services Corporation's SaskGIS Provincial Boundary dataset, in numerous areas along the west, south and southeast borders: There are gaps of up to 500 m wide of "no data" between the provincial boundary and the raster along these areas of the Saskatchewan boundary. Classification Value AGRICULTURE 1 HAY CROPS 2 NATIVE DOMINANT GRASSLANDS 3 TALL SHRUBS 4 PASTURE 5 HARDWOODS (OPEN CANOPY) 6 HARDWOODS (CLOSED CANOPY) 7 JACKPINE (CLOSED CANOPY) 8 JACKPINE (OPEN CANOPY) 9 SPRUCE (CLOSED CANOPY) 10 SPRUCE (OPEN CANOPY) 11 MIXED WOODS 12 TREED ROCK 13 RECENT BURNS 14 REVEGETATING/REGENERATION BURN 15 CUTOVERS 16 WATER 17 MARSH 18 HERBACEOUS FEN 19 MUD/SAND/SALINE 20 SHRUB FEN (TREED SWAMP) 21 TREED BOG 22 OPEN BOG 23 FARMSTEAD 24 UNCLASSIFIED 25 BARREN LAND 26 MIXED SOFTWOODS (OPEN & CLOSED) 27 PASTURE UPLAND HERBACEOUS GRAMINOID 30 1. AGRICULTURE - Cropland, including all lands dedicated to the production of annual cereal, oil seed, and other specialty crops, and typically cultivated on an annual basis; and agricultural clearing areas.  2. HAY CROPS (Forage) - Alfalfa and alfalfa/tame grass mixtures.  3. NATIVE DOMINANT GRASSLANDS - Native dominant grasslands. (May contain tame grasses and herbs.)  4. TALL SHRUBS - Communities containing both low and tall shrub, snowberry, saskatoon, chokecherry, buffaloberry, and willow.  5. PASTURE (Seeded Grass Lands) - Grassland dominated by tame grass species.  6. HARDWOODS (I.E. OPEN CANOPY) - Greater than 75% hardwoods by area, including trembling aspen, white birch, balsam poplar; 10 - 55% crown closure.  7. HARDWOODS (I.E. CLOSED CANOPY) - Greater than 75% hardwoods by area, including trembling aspen, white birch, balsam poplar; Greater than 55% crown closure.  8. JACKPINE (I.E. CLOSED CANOPY) - Greater than 75% of Jack Pine by area; Greater than 55% crown closure.  9. JACKPINE (I.E. OPEN CANOPY) - Greater than 75% of Jack Pine by area; 10 - 55% crown closure.  10. SPRUCE (I.E. CLOSED CANOPY) - Greater than 75% or greater Black and White Spruce; Greater than 55% crown closure.  11. SPRUCE (I.E. OPEN CANOPY) - Greater than 75% Black and White Spruce; 10-55% crown closure.  12. MIXED WOODS - All softwood/hardwood mixtures; open and closed canopy (i.e. An area of hardwood and softwood combinations in which neither hardwood nor softwood account for greater than 75% of species by area, and where the crown closure is greater than 10%).  13. TREED ROCK - Areas of exposed bedrock with generally less then 10% tree cover.  14. RECENT BURNS - An area showing evidence of recent burning natural or prescribed and there is little to no regeneration or revegetation visible.  15. REVEGETATING/REGENERATION BURN - An area showing evidence of natural or prescribed burning and where regeneration or revegetation is visible.  16. CUTOVERS - An area of deforestation, vegetated and non-vegetated.  17. WATER - These areas include lakes, rivers, streams and reservoirs  18. MARSH - A periodically wet or continually flooded but non peat-forming area supporting grasses, sedges, and reeds.  19. HERBACEOUS FEN - A wetland area consisting of decomposing peat supporting vascular and nonvascular plants (i.e. grasses, sedges, reeds).  20. MUD/SAND/SALINE - Water saturated soil, sand containing no vegetation, and salt water.  21. SHRUB FEN (I.E. TREED SWAMP) - A wetland area consisting of decomposing peat supporting low shrubs, forbs, grass, moss, and a sparse tree cover.  22. TREED BOG - A wetland area consisting of decomposing peat moss, lichen, and shrubs, with 10% or more canopy by trees (i.e. primarily black spruce and tamarack).  23. OPEN BOG - A wetland area consisting of decomposing peat moss, lichen, and sparse tree cover.  24. FARMSTEAD - Farmsteads, towns, cities, exposed areas with little or no vegetation.  25. UNCLASSIFIED  26. BARREN LAND - Any area of exposed rock, soil, or non-vegetated land.  27. MIXED SOFTWOODS (OPEN & CLOSED) - Jack Pine/Spruce, Spruce/Jack Pine Open and Closed, an area of softwood combinations in which neither Jack Pine or Spruce account for greater than 75% of species by area, and where crown closure is greater than 10%.  30. PASTURE UPLAND HERBACEOUS GRAMINOID - Lands containing known pastures, tame or native grasses, and herbaceous vegetation. These lands may contain low-lying shrubs with less then 10% tree cover.

Topographic maps produced by Natural Resources Canada conform to the National Topographic System (NTS) of Canada. Indexes are available in three standard scales: 1:1,000,000, 1:250,000 and 1:50,000. The area covered by a given mapsheet is determined by its latitude and longitude. 1:1,000,000 mapsheets are identified by a combination of three numbers (e.g. 098). 1:250,000 mapsheets are identified by a combination of numbers, and letters ranging from A through P (e.g. 098C). Sixteen smaller segments (1 to 16) form blocks used for 1:50,000 mapping (e.g. 098C03).

The 1 cm resolution digital surface model (DSM) was created from unmanned aerial vehicle (UAV) imagery acquired from a single day survey, July 28th 2016, in Cambridge Bay, Nunavut. Five control points taken from a Global Differential Positioning System were positioned in the corners and the center of the vegetation survey. The DSM covering 525m2 was produced by Canada Centre for Remote Sensing /Canada Centre for Mapping and Earth Observation. The UAV survey was completed in collaboration with the Canadian High Arctic Research Station (CHARS) for northern vegetation monitoring research. For more information, refer to our current Arctic vegetation research: Fraser et al; "UAV photogrammetry for mapping vegetation in the low-Arctic" Arctic Science, 2016, 2(3): 79-102. http://www.nrcresearchpress.com/doi/abs/10.1139/AS-2016-0008