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Glaciers in the Alps are receding at unprecedented rates. Firn area is declining even at high elevations and many glaciers have experienced completely snow free summers in recent years. Glacier albedo is an important control for the amount of energy available for melt and, hence, mass balance and future glacier evolution. Glacier-scale studies have shown considerable variability of glacier-wide and bare-ice albedo in both space and time. At regional and Alps-wide scales, analyses of MODIS data have found decreasing albedo trends over time. However, the relatively coarse resolution of MODIS (500 m) does not resolve small-scale variability and limits applicability especially for very small glaciers, which are numerous in the Alps. Deriving glacier-wide albedo products and addressing albedo variability over bare-ice areas using Landsat and Sentinel-2 multispectral surface reflectance (10 to 30 m resolution) has the potential to improve understanding of albedo driving factors and, for example, resolve regional impacts of heatwaves and other meteorological forcings. Landsat and Sentinel-2 surface reflectance products are available via Google Earth Engine (GEE) and the computational accessibility enabled by server-side operations within GEE allows flexible analyses at scale. For example, a glacier-wise analysis of the Sentinel-2 record indicates that the median snow cover fraction for glaciers in Austria dropped to around 10 % during the record-breaking summer of 2022, compared to values between 20 and over 30 % in the previous years. Applying a broadband albedo conversion to the multispectral reflectance data, we find the median glacier area fraction with very low albedo values below 0.2 increased to over 35 % in 2022. At elevations above 3000 m, median glacier albedo ranged from 0.4 to 0.5 in years prior to 2022 and dropped to below 0.3 in 2022, with persistently low values through 2025.In principle, these GEE workflows can be scaled to much larger regions and thousands of individual glaciers without great difficulties. However, “traditional” challenges related to cloud cover, local topographic shading, data availability, and validation approaches remain. It has become relatively simple to produce values like the preliminary results given above and, for example, greatly extend the dataset by including the entire Landsat record. However, given the large amount of readily available data across different collections and generations of satellites, care should be taken in accounting for issues such as sensor comparability and level-2 product consistency, and developing meaningful validation metrics seems particularly important. We will present our ongoing work related to ice albedo and firn loss in the European Alps and aim to foster discussions of challenges and limitations that arise when scaling analyses from individual glaciers to larger regions.