TerraSAR-X in support of the Canadian dual Ku-Band SAR mission

• Main Authors: Wendleder, Anna, Montpetit, Benoit, King, Joshua, Derksen, Chris, Siqueira, Paul, Toose, Peter
• Format: Conference Object
• Language: unknown
• Published: 2023
• Subjects: Internationales Bodensegment; Inuvik
• Online Access: https://elib.dlr.de/199487/

Environment and Climate Change Canada (ECCC) and the Canadian Space Agency (CSA) continue to advance a new satellite Ku-band radar mission focused on providing moderate resolution (500 m) information on seasonal snow mass. Like many regions of the northern hemisphere, estimates of the amount of water stored as seasonal snow are highly uncertain across Canada. To address this gap, a technical concept capable of providing dual-polarization (VV/VH), moderate resolution (500 m), wide swath (~250 km), and high duty cycle (~25% SAR-on time) Ku-band radar measurements at two frequencies (13.5; 17.25 GHz) is under development. An intensive field campaign, Trail Valley Creek experiment (TVCEx), conducted in winter of 2018-19 near Inuvik, NWT, Canada, was conducted. Another field campaign, CryoSAR 2022-23, was conducted in Powassan, Ontario, Canada. Both campaigns acquired airborne Ku-band (13.5 GHz) SAR data to support the science readiness activities of the future Canadian mission. A major challenge of effectively retrieving snow mass information from Ku-Band SAR data is to be able to decouple the contribution of the snow from the underlying background to the backscattered signal. To achieve this, C-Band RADARSAT-2 (TVCEx) and Radarsat Constellation Mission (CryoSAR 2022-23) and X-Band TerraSAR-X data were acquired. Since these radar bands are less sensitive to snow mass of shallow snowpacks, data acquired at both frequencies are used in a forward modeling approach, using the Snow Microwave Radiative Transfer (SMRT) model, to retrieve the effective soil parameters such as soil permittivity and texture. Current results from the TVCEx show that the retrieved soil texture parameters at the lower frequencies are very similar to the measured values using airborne LiDAR. This shows that using a multi-frequency approach is greatly beneficial in retrieving snow mass at higher frequencies. Preliminary results from the CryoSAR2022-23 campaign shows that the Ku-Band data is very sensitive to the snow mass for agricultural ...