We present technical advances and methods to measure effective broadband physical albedo in snowy mountain headwaters using a prototype dual-sensor pyranometer mounted on an Autonomous Aerial Vehicle (an AAV). Our test flights over snowy meadows and forested areas performed well during both clear sky and snowy/windy conditions at an elevation of ~2650 m above mean sea level (MSL). Our AAV-pyranometer platform provided high spatial (m) and temporal resolution (sec) measurements of effective broadband (310–2700 nm) surface albedo. The AAV-based measurements reveal spatially explicit changes in landscape albedo that are not present in concurrent satellite measurements from Landsat and MODIS due to a higher spatial resolution. This AAV capability is needed for validation of satellite snow albedo products, especially over variable montane landscapes at spatial scales of critical importance to hydrological applications. Effectively measuring albedo is important, as annually the seasonal accumulation and melt of mountain snowpack represent a dramatic transformation of Earth’s albedo, which directly affects headwaters’ water and energy cycles.

High latitude lakes and ponds are heavily impacted by climate change (Webb et al., 2022;Xu et al., 2022), and many studies report severe changes in open water extent following shifts in precipitation patterns, loss of sub-surface permafrost, land collapse, and other climate-caused ecosystem disturbances (Arp

Snow albedo is highly variable over multiple temporal and spatial scales. This variability is more pronounced in areas that experience seasonal snowpack. Satellite retrievals, physically based models and parameterizations for snow albedo all require ground-based measurements for calibration, initialization, and validation. Ground measurements are generally made using upward and downward-facing pyranometers at opportunistically located weather stations that are sparsely distributed, particularly in mountainous regions. These station-based measurements cannot capture the spatial variability of albedo across the land surface. Uncrewed Aerial Vehicles (UAVs) equipped with upward and downward-facing pyranometers provide near-surface measurements of broadband albedo that are spatially distributed across landscapes, offering improvements over in-situ sensors. At the hillslope to watershed scale albedo measurements from UAVs taken over heterogeneous terrain are a function of the spatial variability in albedo and topography within the downward-facing sensor’s field-of-view (FOV). In this research we propose methods for topographic correction of UAV snow albedo measurements and comparison to gridded satellite albedo products. These methods account for the variability of surface topography and albedo within the sensor FOV, sensor tilt, and the angular response of pyranometers. We applied the proposed methodologies to UAV snow albedo measurements collected over an alpine meadow in southwest Montana, United States (45.23°, −111.28°). Sensitivity analyses were conducted to determine the effect of altering the processing FOV (PFOV) for both topographic corrections and comparison to coincident Landsat 8-derived albedo measurements. Validation from ground-based albedo measurements showed the topographic correction to reduce albedo measurement error considerably over mildly sloping terrain. Our sensitivity analyses demonstrated that outcomes from the topographic correction and satellite comparison are highly dependent on the specified PFOV. Based on field observations and analyses of UAV albedo measurements made at different altitudes, we provide guidelines for strategizing future UAV albedo surveys. This research presents considerable advances in the standardization of UAV-based albedo measurement. We establish the foundation for future research to utilize this platform to collect near-surface validation measurements over heterogeneous terrain with high accuracy and consistency.