Emplacement des grandes infrastructures, de ressources, projets pétroliers et gaziers au Nunavut, Territoires du Nord-Ouest et du Yukon. Les données et les cartes sont pour des fins d'illustration seulement.

Location of Major Infrastructure, Resource, Oil and Gas Projects in Nunavut, Northwest Territories and Yukon. Data and maps for illustrative purposes only. Users understand that, although all efforts have been made to accurately and exhaustively compile, locate and classify projects, the authors do not guarantee the accuracy and/or the comprehensiveness of the data and assume no responsibility for errors or omissions. CanNor does not assume responsibility for errors or omissions. In support of this initiative, proponents and partners are encouraged to contact CanNor should they identify any errors or omissions.

This dataset corresponds to daily snow cover percentage at 1km resolution grid over land areas of Canada from 2006-2010. The data are subsampled by 4km to reduce data volumes and considering the geolocation uncertainty of the input satellite imagery. The daily maps are generated by assimilation of daily cloud screened NOAA AVHRR satellite imagery and Canadian Meteorological Centre (CMC) snow depth analysis snow depth and density fields within an off-line version of the CMC daily snow depth model. The snow depth model is modified to include snowpack reflectance model and a surface radiative transfer scheme that relates vegetation and snowpack reflectance to top-of-canopy bi-directional reflectance. A logistic vegetation phenology model is used to parameterize temporal dynamics of canopy leaf area index. A per-pixel particle filter with a 30 day moving window is applied to assimilation observations corresponding to 1km resolution visible band directional reflectance and normalized difference vegetation index and 24km CMC daily snow depth and monthly snow density fields. The assimilation is forced using daily air temperature and precipitation fields. Validation of the datasets has been performed by comparison to MODIS snow cover maps and in-situ snow depth stations across Canada. Validation suggests similar accuracy to MODIS snow cover products over relatively flat terrain. Validation over mountainous regions is ongoing.

The Government of Canada acquired a national image coverage from the Systeme Pour l'Observation de la Terre (SPOT 4 - 5) satellites that includes four multispectral bands in the visible to shortwave infrared region at 20m spatial resolution. Five years from 2005 - 2010 were necessary to image all of Canada under clear-sky conditions, while acquisition anniversary dates were less important provided the data were imaged during the snow-free period. These data were downloaded from the GeoBase Orthoimage 2005 - 2010 dataset (http://www.geobase.ca/geobase/en/data/imagery/imr/description.html) and used to map 2005 - 2010 land cover south of treeline. Northern Canada has not currently been remapped since circa 2000 due to technical challenges associated with land cover variability and image acquisition dates relative to short summers. This land cover product includes 16 generic classes based on plant functional and a minimum mapping unit of 20m. Radiometric normalization was applied to balance images acquired near mid-summer during the 'peak-of-season' temporal window. The combined Enhancement and Classification by Progressive Generalization methods were used to classify large-area balanced mosaics over twenty mapping zones. Image interpretation was guided using high resolution imagery and other content in Google Earth. Knowledge of land cover spectral signatures, field experience and published reports were also used to assist interpretation in many regions. Remaining images acquired outside the peak-of-season window in early spring or late fall were subsequently classified using decision trees trained on data from overlapping classified peak-of-season images. Accuracy was assessed using ground truth data acquired during several field campaigns conducted with other government departments such as Parks Canada and the Geological Survey. This sample was enhanced using points interpreted in Google Earth as described above to provide a more even spatial coverage of Canada. Overall accuracy assessed at 71% using 1566 reference points, more than half of which were acquired in the field. When assessed using only land cover that was homogeneous within 3 by 3 pixels to account for potential geolocation errors, accuracy increased to 85% for 349 points that were biased towards easily classified classes such as water.

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.

This collection is a legacy product that is no longer maintained. It may not meet current government standards. Users of Atlas of Canada National Scale Data 1:1,000,000 (release of May 2017) should plan to make the transition towards the new CanVec product. The Atlas of Canada National Scale Data 1:1,000,000 Series consists of boundary, coast, island, place name, railway, river, road, road ferry and waterbody data sets that were compiled to be used for atlas large scale (1:1,000,000 to 1:4,000,000) mapping. These data sets have been integrated so that their relative positions are cartographically correct. Any data outside of Canada included in the data sets is strictly to complete the context of the data.

This collection is a legacy product that is no longer maintained. It may not meet current government standards. Users of Atlas of Canada National Scale Data 1:15,000,000 (release of May 2017) should plan to make the transition towards the new CanVec product. The Atlas of Canada National Scale Data 1:15,000,000 Series consists of boundary, coast and coastal islands, place name, railway, river, road, road ferry and waterbody data sets that were compiled to be used for atlas small scale (1:15,000,000 to 1:30,000,000) mapping. These data sets have been integrated so that their relative positions are cartographically correct. Any data outside of Canada included in the data sets is strictly to complete the context of the data.

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.

This collection is a legacy product that is no longer maintained. It may not meet current government standards. Users of Atlas of Canada National Scale Data 1:5,000,000 (release of May 2017) should plan to make the transition towards the new CanVec product. The Atlas of Canada National Scale Data 1:5,000,000 Series consists of boundary, coast, island, place name, railway, river, road, road ferry and waterbody data sets that were compiled to be used for atlas medium scale (1:5,000,000 to 1:15,000,000) mapping. These data sets have been integrated so that their relative positions are cartographically correct. Any data outside of Canada included in the data sets is strictly to complete the context of the data.

The Moderate Resolution Imaging Spectroradiometer (MODIS ) is one of the most sophisticated sensors that is used in a wide range of applications related to land, ocean and atmosphere. It has 36 spectral channels with spatial resolution varying between 250 m and 1 km at nadir. MODIS channels 1 (B1, visible) and 2 (B2, near infrared) are available at 250 m spatial resolution, an additional five channels for terrestrial applications (bands B3 to B7) are available at 500 m spatial resolution, the other twenty-nine channels not included in this data set capture images with a spatial resolution of 1 km. The MODIS record begins in March 2000 and extends to present with daily measurements over the globe. This level 3 product for Canada was created from the following original Level 1 (1B) MODIS data (collection 5): a) MOD02QKM - Level 1B 250 m swath data, 5 min granules; b ) MOD02HKM - level 1B , 500 m swath data, 5 min granules; c) MOD03 - level 1 geolocation information, 1 km swath data, 5 min granules. All these data are available from the DAAC Earth Observing System Data Gateway (NASA http://ladsweb.nascom.nasa.gov/data/search.html). The terrestrial channels MODIS (B3 to B7) at 500 m spatial resolution were reduced to 250 m with an adaptive regression system and normalization described in Trishchenko et al. (2006, 2009), and the data were mapped using a Lambert Conformal Conic (LCC ) projection (Khlopenkov et al., 2008). These data were combined to form pan-Canadian images using a technique for detection of clear sky, clouds and cloud shadows with a maximum interval of 10 days (Luo et al., 2008). Atmospheric and sun-sensor geometry corrections have not been applied. For each date, data include forward and backward scattering observations as separate files. This allows data to be optimized for a given application. For general use, data from either forward or backward scattering or both should be used. Future release of the MODIS time series will correct the forward and backward scattering geometry to provide a single best observation for each pixel.