An Operational Methodology for Validating Satellite-Based Snow Albedo Measurements Using a UAV

Abstract

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.

UAV hyperspectral imaging for multiscale assessment of Landsat 9 snow grain size and albedo

“…There have been case studies, though, that have demonstrated mapping of broadband albedo in snow-covered environments. These studies have used paired pyranometers mounted in upward-and downward-looking configurations (Webster and Jonas, 2018;Sproles et al, 2020;Mullen et al, 2022) or a single downward-looking pyranometer on the UAV and a stationary upward-looking pyranometer within the flight area (Levy et al, 2018). These measurements return a single spectrally integrated value for incident and reflected radiation, from which broadband albedo can be calculated.…”

“…These measurements return a single spectrally integrated value for incident and reflected radiation, from which broadband albedo can be calculated. If care is taken to fly only over snow, this would be an effective snow albedo (Mullen et al, 2022), otherwise, snow cannot be separated from other land surface types with a spectrally integrated measurement. Rather, the goal is to measure mixed land surfaces to understand heterogeneity when snow is present with other land surface types (Webster and Jonas, 2018).…”