Abstract. The use of geostationary orbits (GEO) for Earth observation has led to advances in weather prediction and more recently, new spectroscopic observations of air quality through a virtual constellation of GEO satellites predominantly observing over the northern hemisphere. In this brief communication, we introduce the concept of Inclined Geosynchronous Orbits (IGOs) for Earth observation and contrast them to GEO and other orbits for expanding the coverage from the atmospheric composition virtual constellation. Many key advantages of IGOs presented here for observing atmospheric composition extend to other types of Earth observation (e.g. surface imaging) in which the area of interest reaches to the high latitudes of both hemispheres presenting challenges for GEO.

We present a novel raster dataset of surface inland water body fraction over Canada and neighbouring regions, including the northern parts of the United States, as well as Greenland, Iceland, and the northeastern sector of Russia, at 250-m spatial resolution. It was derived from the Global Surface Water (GSW) dataset (version 5) using a two-step resampling to ensure an accurate replication of the original data and spatial consistency in terms of extent and resolution with the Long-Term Satellite Data Records derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) sensors. Additional input data and several coastline vector shape databases were utilized to refine the delineation of waterbodies and land-ocean interface. The resulting dataset is an 8-bit signed integer map, where each pixel represents either the water fraction or a land/ocean mask. Positive values indicate water bodies within Canada, while negative values represent areas outside of Canada. This dataset provides a more precise and up-to-date tool for medium-resolution studies of surface inland water in Canada, aligning closely with satellite imagery of similar spatial resolution. The dataset is freely available through the Government of Canada’s Open Government Portal.

The Minimum Snow/Ice (MSI) extent is an important climate and environmental indicator related to surface hydrology and freshwater resources. Variations in the MSI extent over the four first-order regions (1-4) included in the Randolph Glacier Inventory (RGI) for Canada and the Northern USA were analyzed in this study using an improved land-water mask to better discriminate landfast ice in the high Arctic coastal zone. The analysis utilized warm season snow/ice probability maps derived from MODIS clear-sky composite imagery at a 250-m spatial resolution. Results showed statistically significant declining trends in the minimum snow/ice extent with the average value of the slope for the entire area (-1,177.7 +/- 362.8) km2/yr. The variations in MSI extent are well correlated with surface air temperature. The correlation coefficients are statistically significant, ranging from -0.79 to -0.82. The detailed analysis revealed a reduction of the area with snow/ice probability 100% over the RGI glaciated zones, while areas with lower probability values were increasing in size, which may be interpreted as an indication of general glacier shrinkage over the study area. L'& eacute;tendue minimale de neige/glace (MNG) est un indicateur climatique et environnemental important li & eacute; & agrave; l'hydrologie de surface et aux ressources en eau douce. Les variations du MNG dans les quatre r & eacute;gions de premier ordre (1-4) incluses dans l'Inventaire de glaciers Randolph (IGR) pour le Canada et le nord des & Eacute;tats-Unis ont & eacute;t & eacute; analys & eacute;es dans cette & eacute;tude & agrave; l'aide d'un masque terre-eau am & eacute;lior & eacute; pour mieux identifier la glace de mer dans les zone c & ocirc;ti & egrave;re du Haut-Arctique. L'analyze a utilis & eacute; les cartes de probabilit & eacute; de neige/glace de la saison chaude d & eacute;riv & eacute;es de l'imagerie composite de ciel clair MODIS & agrave; une r & eacute;solution spatiale de 250 m. Les r & eacute;sultats ont montr & eacute; des tendances statistiquement significatives & agrave; la baisse de l'& eacute;tendue minimale de neige/glace avec la valeur moyenne de la pente pour l'ensemble de la zone (-1777.7 +/- 362.8) km2/an. Les variations de l'& eacute;tendue du MNG sont bien corr & eacute;l & eacute;es & agrave; la temp & eacute;rature de l'air en surface. Les coefficients de corr & eacute;lation sont statistiquement significatifs, variant de -0,79 & agrave; -0,82. L'analyze d & eacute;taill & eacute;e a montr & eacute; une r & eacute;duction de 100% de la zone avec une probabilit & eacute; de neige/glace sur les zones glaciaires IGR, tandis que les zones avec des valeurs de probabilit & eacute; plus faibles augmentaient leurs surfaces, ce qui peut & ecirc;tre interpr & eacute;t & eacute; comme une indication du retrait g & eacute;n & eacute;ral des glaciers sur la zone d'& eacute;tude.

A novel satellite image processing technique was utilized to produce an annual time series of the minimum snow/ice (MSI) extent over the entire Greenland landmass for the period 2000-22. The information was derived from the Moderate Resolution Imaging Spectroradiometer 10-day clear-sky composites over the April-September period. The data products were generated from 250-m swath imagery. The annual aggregates were downscaled to a 150-m grid for consistency with data on margins of Greenland available from the Geological Survey of Denmark and Greenland (GEUS) and the Greenland Ice Mapping Project. Interannual variations in the MSI extent were derived and analyzed for each of the seven major glacier basins in Greenland split into the main ice sheet, represented by a static map, and the peripheral areas from which all variations originated. Four of the seven regions demonstrated statistically significant negative trends in the MSI extent. The entire Greenland area also showed a declining snow/ice extent although this was not statistically significant. The region-wide and peripheral snow/ice extent varied from a minimum of 1.807 x 106 6 km2 2 (1.449 x 105 5 km2 2 for peripheral areas) observed in 2012 to a maximum of 1.860 x 106 6 km2 2 (1.977 x 105 5 km2) 2 ) observed in 2006 with an average value of 1.829 x 106 6 km2 2 (1.664 x 105 5 km2). 2 ). The derived MSI variations showed a statistically significant correlation with the near-surface 2-m air temperature from the ERA5-Land reanalysis and Greenland ice mass balance from GEUS for all catchments, with correlation coefficients for the entire area equal to -0.74 and 0.53, respectively. The mapping of many peripheral glaciers and ice shelves included in the glaciology databases and utilized for the IPCC reporting is not always consistent with our results and requires improvement, especially in coastal areas.

The Minimum Snow/Ice (MSI) extent is an important climate and environmental indicator related to surface hydrology and freshwater resources. Variations in the MSI extent over the four first-order regions (1-4) included in the Randolph Glacier Inventory (RGI) for Canada and the Northern USA were analyzed in this study using an improved land-water mask to better discriminate landfast ice in the high Arctic coastal zone. The analysis utilized warm season snow/ice probability maps derived from MODIS clear-sky composite imagery at a 250-m spatial resolution. Results showed statistically significant declining trends in the minimum snow/ice extent with the average value of the slope for the entire area (-1,177.7 ± 362.8) km2/yr. The variations in MSI extent are well correlated with surface air temperature. The correlation coefficients are statistically significant, ranging from −0.79 to −0.82. The detailed analysis revealed a reduction of the area with snow/ice probability 100% over the RGI glaciated zones, while areas with lower probability values were increasing in size, which may be interpreted as an indication of general glacier shrinkage over the study area.

Telluric currents, often known as geomagnetically induced currents (GIC), are produced by the natural variations of the Earth's magnetic field.The corrosion protection system of a buried pipeline generally comprises the coating and cathodic protection system. Cathodic protection is an electrochemical protection system that maintains the pipe-to-soil potential (PSP) sufficiently negative in order to reduce corrosion to negligible levels. Varying telluric currents alter the PSP, thus interfering with the pipeline corrosion protection system and can create conditions when corrosion might increase above acceptable levels.This paper presents an evaluation of telluric-associated corrosion derived from measured and modelled PSP variations. The corrosion rates (metal loss per year) due to varying telluric currents with continuous frequency spectra (1 Hz-10-5 Hz) are approximated with the use of published experimental results derived for the specific sets of fixed frequencies.Results are presented for PSP observed on Australian and European pipelines during two periods of strong geomagnetic activity (in 2003 and 2004) and for identical hypothetical pipelines located at different latitudes for the entire year 2004.From the analysis of recorded PSP, it was found that the corrosion rates for a near-equatorial pipeline (Australia) could be higher than for mid-latitudes (Europe). This is possible because telluric-associated corrosion rates depend not only on geomagnetic activity, but on the properties of the pipeline coating, the performance of the cathodic protection system and environmental conditions.The study demonstrated that without cathodic protection the estimated corrosion rates exceeded the bench-mark values recommended by national and international standards, and in exceptional case can exceed the acceptable values even with cathodic protection.Telluric-associated corrosion estimated for the identical hypothetical pipelines located in zones with different geomagnetic activity, clearly demonstrated the latitudinal dependence. The substantial increase of corrosion rates (about 5 times) has been found with increase of latitude from subauroral to auroral locations.

Two decades (2000–2019) of the landfast ice properties in the Beaufort Sea region in the Canadian Arctic were analyzed at 250 m spatial resolution from two sources: (1) monthly maps derived at the Canada Centre for Remote Sensing from the Moderate Resolution Imaging Spectroradiometer clear-sky satellite image composites; and (2) Canadian Ice Service charts. Detailed comparisons have been conducted for the landfast ice spatial extent, the water depth at, and the distance to the outer seaward edge from the coast in four sub-regions: (1) Alaska coast; (2) Barter Island to Herschel Island; (3) Mackenzie Bay; and (4) Richards Island to Cape Bathurst. The results from both sources demonstrate good agreement. The average spatial extent for the entire region over the April–June period is 48.5 (±5.0) × 103 km2 from Canadian Ice Service data versus 45.1 (±6.1) × 103 km2 from satellite data used in this study (7.0% difference). The correlation coefficient for April–June is 0.73 (p = 2.91 × 10−4). The long-term linear trends of the April–June spatial extent since 2000 demonstrated statistically significant decline: −4.45 (±1.69) × 103 km2/decade and −4.73 (±2.17) × 103 km2/decade from Canadian Ice Service and satellite data, respectively. The landfast ice in the Beaufort Sea region showed the general tendency for an earlier break-up, later onset, and longer ice-free period. The break-up date has decreased by 7.6 days/decade in the Mackenzie Bay region. The western part of the study area did not demonstrate statistically significant changes since 2000.

A novel satellite image processing technique developed at the Canada Centre for Remote Sensing has been utilized to produce annual time series of the minimum snow/ice (MSI) extent over the northern circumpolar landmass area (9,000 km × 9,000 km) for 2000–19. The information has been derived from the Moderate Resolution Imaging Spectroradiometer 10-day clear-sky composites generated at 250-m spatial resolution over the April–September period. Derived interannual variations agree very well with the warm-season average surface air temperatures from the European reanalysis (ERA5). The region-average correlation coefficient is −0.78. The total MSI extent demonstrated a statistically significant declining trend equal to −1,477 km2 yr−1. Results have been compared with data from the Randolph Glacier Inventory (RGI 6.0). The comparison points to a significant contribution of minimum seasonal snow cover relative to RGI glacierized areas. Quantitative estimates obtained for the first time showed that the region-average snow extent that survives the summer melt and resides outside of RGI area can be as high as 15% (or 53 × 103 km2) while in the northern Canadian Arctic it can reach 41% (or 43 × 103 km2). The derived MSI time series data can be recommended to the glacier and land-cover scientific community as a source of validation data and annual updates of snow and ice maps over the northern circumpolar landmass.

Landfast ice (LFI) is a prominent climatological feature in the Canadian Arctic. LFI is generally defined as immobile near-shore ice that remains fast along the coast and forms seaward from the land. It affects the coastline dynamics, is important for the near-shore ecosystems, wildlife, and human socio-economic activities. A method is proposed for mapping the LFI using time series of 10-day clear-sky composites derived at the Canada Center for Remote Sensing (CCRS) from the Moderate Resolution Imaging Spectroradiometer (MODIS) 250-m imagery. The delineation of coastal zone ice utilizes simultaneous analysis of the mean and standard deviation of MODIS monthly reflectance maps. The application of this method is demonstrated for a 20-year period (2000–2019) over the coastal zone of Banks Island in the Beaufort Sea. Detailed analyses have been conducted for three LFI parameters: (1) the total area (spatial extent) occupied by LFI; (2) the distance from the coast to the outer seaward LFI edge, and (3) the water depth at the outer seaward LFI edge. Comparison with the Canadian Ice Service (CIS) data demonstrates good agreement. The average correlation coefficients between CIS and CCRS time series in April-June, when the area reaches a maximum, are equal to 0.87–0.88. The mean differences (CIS-CCRS) are 344 km2 (5,464 km2 vs 5,120 km2) or 6.3% for the spatial extent; 1.3 km (17.6 km vs 16.3 km) or 7.4% for the distance; −2.7 m (−27.4 m vs −24.7 m) or 10% for the water depth. Because the CCRS method uses monthly statistics, it tends to exclude potentially more mobile continuous landfast ice zones than the CIS analysis which is based on data collected on a specific date. The long-term trends of the LFI seasonal cycle in our region of interest since 2000 have shown a tendency for an earlier break-up, later onset, and longer ice-free period; however, these trends are not statistically significant.

Continuous observation of polar regions from space remains an important unsolved technical challenge of great interest for the international meteorological community. This capacity would allow achieving global continuous coverage once combined with the geostationary (GEO) satellite network. From a practical point of view, continuous coverage of polar regions with a small number of spacecraft can be obtained from a constellation of satellites either in highly elliptical orbits (HEO) or in medium Earth orbits (MEO). The study compares HEO and MEO satellite constellations for their capacity to provide continuous imaging of polar regions as function of the viewing zenith angle (VZA) and evaluates the corresponding latitude limits that ensure sufficient overlap with GEO imagery. Earlier studies assumed the latitude boundary of 60 degrees and the VZA range 70 degrees-85 degrees depending on the space mission focus: meteorological purposes or communications. From the detailed analysis of meteorological retrieval requirements, this study suggests that the overlap of the GEO and polar observing systems (HEO or MEO) should occur down to the latitude band 45 degrees-50 degrees with a maximum VZA ranging between 60 degrees and 64 degrees. This coverage requirement can be met with two sets of three-satellite HEO constellations (one for each polar area) or a six-satellite MEO constellation. The 12-h Molniya and 14-, 15-, and 16-h HEO systems have been analyzed and determined to meet these revised requirements. The study demonstrates that the six-satellite 24-h MEO system can provide a suitable solution, which is also beneficial from the point of view of ionizing radiation and image acquisition geometry. Among the HEO systems, the 16-h HEO has some advantages relative to other HEO systems from the point of view of spatial coverage and space radiation.

The Visible Infrared Imaging Radiometer Suite (VIIRS) represents a new generation of satellite imagers for global operational observations. In many aspects, it is comparable to the Moderate Resolution Imaging Spectroradiometer (MODIS) operated since 2000, i.e. almost for two decades. The Canada Centre for Remote Sensing has developed a unique MODIS processing chain to produce a long-term time series of clear-sky composites and some terrestrial products at 250 m spatial resolution over a 5700 km × 4800 km region centered on Canada. The paper describes an extension of the MODIS time series at the top of the atmosphere level using VIIRS data. The VIIRS clear-sky composites are produced on a 250-m spatial grid for I-bands and a 500-m grid for M-bands. Nominal products are generated as 10-day composites, while snow mask and normalized difference vegetation index are generated as daily products. Preliminary assessment of VIIRS versus MODIS composites has been conducted through comparison of value-added warm season snow/ice probability maps and minimum snow/ice extent. The results demonstrate a high level of consistency (with the average different difference around 0.12%), which indicates that the developed VIIRS processing technology produces results that can potentially be used to extend MODIS time series into the future.

AIM-North is a proposed satellite mission that would provide observations of unprecedented frequency and density for monitoring northern greenhouse gases (GHGs), air quality (AQ) and vegetation. AIM-North would consist of two satellites in a highly elliptical orbit formation, observing over land from ∼40°N to 80°N multiple times per day. Each satellite would carry a near-infrared to shortwave infrared imaging spectrometer for CO2, CH4, and CO, and an ultraviolet-visible imaging spectrometer for air quality. Both instruments would measure solar-induced fluorescence from vegetation. A cloud imager would make near-real-time observations, which could inform the pointing of the other instruments to focus only on the clearest regions. Multiple geostationary (GEO) AQ and GHG satellites are planned for the 2020s, but they will lack coverage of northern regions like the Arctic. AIM-North would address this gap with quasi-geostationary observations of the North and overlap with GEO coverage to facilitate intercomparison and fusion of these datasets. The resulting data would improve our ability to forecast northern air quality and quantify fluxes of GHG and AQ species from forests, permafrost, biomass burning and anthropogenic activity, furthering our scientific understanding of these processes and supporting environmental policy.

The study reports results of analysis related to minimization of the total ionizing dose (TID) for the Multiple Apogee Highly Elliptical Orbit with periods 14 h, 15 h and 16 h introduced earlier for continuous observation of the Earth's polar regions. The modeling of space environment has been conducted with use of the European Space Agency's SPENVIS tool based on the AE8/AP8 radiation models. Originally, the set of orbital parameters has been derived through the optimization process that included among other factors criteria for the apogee height limit and minimization of the radiation dose caused by trapped protons. By relaxing the apogee altitude limit, this study found the total ionizing dose TID can be significantly reduced for 15-h and 16-h orbits, while the originally proposed 14-h orbit is already at the minimum of radiation dose. For 15-h and 16-h orbits this converts into reduction of the thickness of aluminum shielding by factor 1.24-1.28 or an equivalent increase in the mission lifetime by up to 8.1 years. For example, an increase in apogee altitude to 49,620 km for 16-h orbit (eccentricity e = 0.74) in comparison to the originally proposed 16-h orbit (altitude equal to 43,500 km, e = 0.55) reduces the TID so that the shielding thickness decreases to 3.53 mm, instead of 4.35 mm of aluminum slab for the same 15-year duration of mission. Decrease of the TID is achieved due to significant reduction of ionizing radiation from the trapped electrons through the better placing of the orbit trajectory in the slot area, but at the expense of slight increase of ionizing radiation from the trapped protons and increase in apogee altitude to 46,640 km and 49,620 km for 15-h and 16-h orbit, correspondingly. Crown Copyright (C) 2019 Published by Elsevier Ltd on behalf of COSPAR.

The application of the gradient search method for reprojection of Visible Infrared Imaging Radiometer Suite (VIIRS) satellite data record (SDR) imagery is described. The method is an extension of the scheme developed earlier for reprojection of Moderate Resolution Imaging Spectroradiometer (MODIS) L1B imagery. The new scheme has three important improvements: 1) the interscan and intrascan search steps are combined into a single step to save computational time; 2) onesided (left-right, up-down) gradients are utilized to improve convergence; and 3) the use of the map projection instead of the latitude-longitude coordinate system to improve performance and robustness. The scheme is computationally very fast, employing only basic arithmetic operations and precalculated matrices of spatial gradients. An average number of iteration steps for the reprojection of mid-latitude quadruple VIIRS SDR granule is less than 1.5, i.e., the scheme usually converges in less than 2 iterations. The ambiguity in the overlapping areas due to the bow-tie effect is resolved by forcing a solution located closer to the scan line center. In addition, the accuracy of VIIRS imagery geo-location was evaluated by comparison against MODIS 250 m images. Absolute geolocation biases of the VIIRS imagery over the 1-year period from June 01, 2016 to May 01, 2017 were found on average to be within 0.004 and -0.003 of the sample size (Delta line) in the along-track direction and 0.055 and 0.035 of the sample size (Delta pixel) in the along-scan direction for bands I2 and M7, respectively. These results demonstrate the excellent geometric performance of the VIIRS Suomi National Polar-orbiting Partnership sensor and are consistent with those reported by the VIIRS geolocation teams.

The approach, sensitivity analysis and evaluation results are presented in this study for application of MODIS 250-m imagery to assess the VIIRS/S-NPP image geolocation accuracy at subpixel level. The method employed is based on 4th degree polynomial fitting of the correlation matrix between VIIRS and MODIS reference images in the swath (pixel-line) projection. Sensitivity analysis has shown that the uncertainty from this method is better that +/- 0.04 of the VIIRS I-band pixel size. Analysis of geolocation accuracy conducted over the 2017 period at semi-monthly intervals has shown that the average geolocation bias for VIIRS/S-NPP band I2 was 0.055 (0.003) along (across) the scan directions. Corresponding numbers are 0.028 (-0.003) for band M7.

The development of snow and ice probability maps at the Canada Centre for Remote Sensing (CCRS) from the MODIS and VIIRS sensors is described. Time series are generated for each warm season (April-September) since 2000 at 250m spatial resolution over the Northern latitudes that cover Canada and neighboring regions. These data are valuable for characterization of fresh water resources, such as snow and land ice, which are very sensitive to climate variations. Comparison of CCRS data against several land cover schemes revealed large discrepancies in the permanent snow/ice extent that can reach nearly 200% over the Canadian Arctic region. CCRS results are very consistent with the Randolph Glacier Inventory (RGI) and can be used for the RGI validation and updates. Data are publicly available from the Canadian Federal Geospatial Platform (FGP) data archive.

Snow and ice over land are important hydrological resources and sensitive indicators of climate change. The Moderate Resolution Imaging Spectroradiometer (MODIS) dataset at 250-m spatial resolution generated at the Canada Centre for Remote Sensing (CCRS) is used to derive the annual minimum snow and ice (MSI) extent over the Canadian Arctic landmass over a 17-yr time span (2000-16). The smallest MSI extent (1.53 x 10(5) km(2)) was observed in 2012, the largest (2.09 x 10(5) km(2)) was observed in 2013; the average value was 1.70 x 10(5) km(2). Several reanalyses and observational datasets are assessed to explain the derived MSI variations: the ERA-Interim reanalysis, North American Regional Reanalysis (NARR), Clouds and the Earth's Radiant Energy System (CERES) radiative fluxes, and European Space Agency's GlobSnow dataset. Comparison with the Randolph Glacier Inventory (RGI) showed two important facts: 1) the semipermanent snowpack in the Canadian Arctic that persists through the entire melting season is a significant component relative to the ice caps and glacier-covered areas (up to 36% or 5.58x10(4) km(2)), and 2) the MSI variations are related to variations in the local climate dynamics such as warm season average temperature, energy fluxes, and snow cover. The correlation coefficients (absolute values) can be as high as 0.77. The reanalysis-based MSI estimates agree with satellite MSI results (average bias of 2.2 x 10(3) km(2) or 1.3% of the mean value).

Snow and ice are important hydrological resources. Their minimum spatial extent over land, here referred to as annual minimum snow/ice (MSI) cover, plays a very important role as an indicator of long-term changes and baseline capacity for surface water storage. Data from Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra satellite for the period of 2000-2014 were utilized in this study. The level-2 MODIS swath imagery for bands B1 to B7 was employed and the 500-m bands B3-B7 were spatially downscaled to a 250-m swath grid. The imagery is available daily with multiple overpasses. This allows for more accurate identification of annual minimum in comparison to high-resolution imagery (e.g., Landsat, ASTER, etc.) available at much coarser temporal rates. Atmospherically corrected 10-day clear-sky composites converted into normalized surface reflectance over the warm season (April 1 to September 20) were employed to identify persistent snow and ice presence. Results were compared with our previous results derived from the MODIS Circumpolar Arctic clear-sky composites, generated for the end of melting season, and showed smaller MSI extent by 24%, on average. Produced MSI distributions were also compared with the permanent snow and ice maps available from 6 global land cover datasets: (i) Global Land Cover GLC-2000, (ii & iii) European Space Agency's (ESA) Globcover circa 2005 and 2009, (iv-vi) land cover maps derived under the ESA Climate Change Initiative (CCI) for 2000, 2005, and 2010. Significant biases were discovered between various land cover datasets and our results. For example, GLC-2000 overestimated snow/ice extent by 194% (325,400km(2)) for the Canadian Arctic. The biases over the entire landmass (excluding Greenland) are 135% (3.7 x 10(5) km(2)), 113% (3.0 x 10(5) km(2)), 89% (2.2 x 10(5) km(2)), and 28% (0.8 x 10(5) km(2)) between our results and GLC-2000, ESA Globcover 2005, ESA Globcover 2009, and ESA CCI datasets, correspondingly. The derived MSI extent was compared with Randolph Glacier Inventory (RGI) 4.0 and showed much better consistency (ranging from 1% to 15%).

This report describes the background, methodology and results of using annual Minimum Snow and Ice (MSI) extent derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m data to validate glacier outline data from the Randolph Glacier Inventory: Version 5.0 (RGI 5.0). This work was a four part collaborative effort conducted by 1) a team from the Canada Centre for Remote Sensing (CCRS) who produced the MODIS MSI raster data and worked with the Atlas of Canada Data (Atlas Data) team to facilitate the use of the raster imagery, 2) the CCRS GeoAnalytics team who evaluated sources of glacier data, 3) the Atlas Data team who carried out the classification and vectorization of the MODIS raster imagery and the validation of the RGI 5.0 glaciers and 4) the Geological Survey of Canada (GSC) who advised on the interpretation of Google Earth and LANDSAT 8 OLI_TIRS image products that were used as references. In particular, it was observed that seventeen glaciers with an area greater than 2.0 km2 are suspected of having either fully or significantly melted. They are distributed across northern Canada, with four located in the Yukon, seven located in Arctic Canada South region and six located in Arctic Canada North region. The validated glacier data will be generalized to the 1:1,000,000 scale and used as a national scale dataset for Canadian glaciers.