Abstract
UWScat, a ground-based Ku- and X-band scatterometer, was used to compare forested and non-forested landscapes in a terrestrial snow accumulation environment as part of the NASA SnowEx17 field campaign. Field observations from Trail Valley Creek, Northwest Territories; Tobermory, Ontario; and the Canadian Snow and Ice Experiment (CASIX) campaign in Churchill, Manitoba, were also included. Limited sensitivity to snow was observed at 9.6 GHz, while the forest canopy attenuated the signal from sub-canopy snow at 17.2 GHz. Forested landscapes were distinguishable using the volume scattering component of the Freeman–Durden three-component decomposition model by applying a threshold in which values ≥50% indicated forested landscape. It is suggested that the volume scattering component of the decomposition can be used in current snow water equivalent (SWE) retrieval algorithms in place of the forest cover fraction (FF), which is an optical surrogate for microwave scattering and relies on ancillary data. The performance of the volume scattering component of the decomposition was similar to that of FF when used in a retrieval scheme. The primary benefit of this method is that it provides a current, real-time estimate of the forest state, it automatically accounts for the incidence angle and canopy structure, and it provides coincident information on the forest canopy without the use of ancillary data or modeling, which is especially important in remote regions. Additionally, it enables the estimation of forest canopy transmissivity without ancillary data. This study also demonstrates the use of these frequencies in a forest canopy application, and the use of the Freeman–Durden three-component decomposition on scatterometer observations in a terrestrial snow accumulation environment.
Highlights
Snow is a critical component in the Earth’s hydrologic cycle and energy balance, as well as a source of fresh water for human consumption [1]
Despite the limited penetration capabilities of these frequencies, this study aims to demonstrate how Ku- and X- band radar scatterometer observations can be used to distinguish forested from non-forested landscapes and can provide biomass-related information for snow water equivalent (SWE) retrievals
Sites with snow in Figure 6a, while a greater difference, up to 4.5 dB and 6 dB for co- and cross-polarized backscatter, was observed between the forested (S21) and non-forested (S9) sites without snow in Figure 6b; the larger cross-polarized difference was a result of enhanced volume scattering in the forest canopy
Summary
Snow is a critical component in the Earth’s hydrologic cycle and energy balance, as well as a source of fresh water for human consumption [1]. More than one-sixth of the global population depends on this water, but its availability is changing with changes to our climate [2]. Given the importance of snow and the predicted changes in its accumulation [3,4,5,6], it is important to monitor; yet, understanding these changes is difficult due to inter-annual variability, inadequate remote sensing products, and poor snow records throughout most of the world [1]. Remote sensing approaches to estimate regional-to-global snow accumulation at a high level of accuracy are not available from satellites or from routine airborne observations. Radar observations have the potential to provide snowpack information, especially the snow water equivalent (SWE), globally and in a timely manner for effective water resource management, this approach has yet to be proven. In situ and limited airborne Ku-band observations of snow have demonstrated sensitivity to the SWE at the local scale with Ku-band backscatter sensitivity to the SWE showing strong signature sensitivity in different environments with applicability for the modeling
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