Land albedo plays an extremely important role in the surface energy budget, by determining the proportion of incoming solar radiation, which is available to drive photosynthesis and surface heating, and that which is reflected directly back to space. In northern high latitude regions, the albedo of snow covered vegetation, even deciduous forests that are leafless in winter, is quite high (bright), while the albedo of boreal evergreen conifers can either be quite low (dark) (even with extensive snow lying under the canopy) or rather bright depending on the structure and density of the canopy. As a result, surface albedo is an essential variable for weather, climate, hydrologic and biogeochemical modeling, particularly in seasonally snow covered regions. However, surface albedo, an intrinsic quality of the Earth’s surface, varies both temporally and spatially as a function of surface type, surface structure/cover, and ecosystem dynamics, with dramatic and rapid alterations occurring in response to seasonal snow fall and melt, water fluctuations and flooding, and vegetation phenology, as well as natural disturbances such as storm damage, wildfires and insect infestation, and land use such as agriculture, grazing, forestry, and urban expansion. These changes may be quite heterogeneous in extent, yet contribute greatly to the local surface energy budget and ecosystem productivity. Such global variability can only be captured with frequent and detailed remote sensing acquisitions, yet no single current space-based sensor provides both the temporal and spatial resolution required. Cloud-free, near-nadir imagery, such as from the Landsat-8 Operational Land Imager (OLI) and the Sentinel-2A/B Multi-Spectral Imagers (MSI), provides excellent information on the surface heterogeneity and vegetation status over land, and in combination, offer a greatly improved temporal resolution (especially at higher latitudes). However, near-nadir directional surface reflectance measurements are not a satisfactory proxy for albedo, often misrepresenting land albedo values by significant percentages; additional multi-angle reflectance information is required to accurately capture the full effects of surface reflectance anisotropy and to produce realistic bihemispherical albedo quantities. Therefore, daily estimates of surface anisotropy from multi-angle observations acquired by wide-swath sensors, such as the MODerate-resolution Imaging Spectroradiometer (MODIS) or the Visible Infrared Imaging Radiometer Suite (VIIRS), can be coupled with the high quality near-nadir reflectance images of higher resolution, as produced by Landsat 8 and Sentinel-2A/B, to produce improved temporal and spatial resolution estimates of the true land surface albedo, particularly in response to seasonal variation, snow cover, and ecosystem disturbance. The improved combined frequency of acquisition at higher latitudes, and the high radiometric fidelity offered by Landsat-8 and Sentinel-2A/B, (which greatly exceeds the specifications of the earlier Landsat sensors) offer a muchimproved ability to quantify the albedo effects of snow covered land surfaces. Our team has considerable experience in dealing with MODIS, VIIRS, Landsat, and now Sentinel 2 data (among other satellite imagers), as well as familiarity with the Harmonized LandsatSentinel-2 (HLS) dataset currently being prepared by the MuSLI team. Therefore we are uniquely qualified to address the differences in spatial, angular, spectral, and temporal resolution inherent in this multisource effort. The production of higher resolution albedos at increased temporal frequencies in these highly dynamic and heterogeneous high latitude ecosystems will contribute to ongoing climate and energy budget modelling efforts, and will allow greater investigation into the effects of ecosystem disturbance and change and the resultant drivers on the surface energy budget and radiative forcing.