The Arctic-boreal zone (ABZ) is warming due to climate change. Current spaceborne remote sensing techniques and retrieval methodologies need to be complemented to improve systematic monitoring of the cryosphere. To that end, this article presents a new investigation of the use of the global navigation satellite system reflectometry (GNSS-R) remote sensing technique by a SmallSat constellation. A new freeze/thaw (F/T) seasonal multithresholding algorithm (STA) is developed using high-inclination orbit near-Nadir Spire Global GNSS-R data acquired through the National Aeronautics and Space Administration (NASA) Commercial Smallsat Data Acquisition (CSDA) Program. Five different soil surface reflectivity Gamma models are proposed to account for the impact of vegetation cover and small-scale surface roughness on Earth-reflected GNSS signals. The sensitivity of the Gamma models to F/T surface state transitions is evaluated, and the optimum model is selected to construct a seasonal scale factor. Then, a multithresholding matrix is obtained for F/T classification using a specific threshold for every surface grid cell. Results for the annual frozen soil duration (days yr(-1)) are compared with those by the Soil Moisture Active Passive (SMAP) mission. Additionally, freezing and thawing periods are analyzed to determine when the moisture exchange with the atmosphere is locked, which is an important climatic factor. A novel metric is introduced to characterize the freeze intensity moving beyond classical F/T binary classifications. Results are evaluated using air and soil temperature, snow depth and temperature, and soil moisture content (SMC) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5-Land reanalysis product.

来源平台：IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING