A new method is presented using a TerraSAR-X quad-pol synthetic aperture radar (SAR) observation for detection and velocity measurement of sea ice drift, which can be useful information to improve sea ice models in the Arctic and Antarctic Oceans. It is very difficult to detect and measure slow moving natural objects using only a space-borne SAR observation without any terrestrial measurement. The core idea is to exploit a slight time difference between different polarizations (i.e., H- and V-pol transmitted signals). The ground motion can be estimated by measuring the slope of residual Doppler frequency versus azimuth time difference without the knowledge of different scattering centers. The results demonstrate effective detection of the flow of brash ice. The SAR-measured velocities were approximately 0.2-0.3 m/s for ice floes and 1.4-3.5 m/s for brash ice flowing through ice fractures. The method was validated by using a pursuit monostatic TanDEM-X mode observation, by which two satellites observed the same sea ice with about a ten-second time interval. The sea ice velocities measured by the proposed approach using only one dataset well correlated with the results from offset tracking method applied to the two datasets with a correlation determination R2 of 0.93. The cross-pol (HV- and VH-pol) pair is more effective to measure the velocity because the scattering center distance decreases significantly in the cross-pol pair, and data with high coherence are required for velocity estimation.
Bibliographical noteFunding Information:
Authors thank the German Aerospace Center (DLR) and S. Wdowinski for the TerraSAR-X and TanDEM-X quad-pol SAR data (PID: HYD0930, OTHER6732). This work was partially supported by the National Space Lab program (2013M1A3A3 A02042314) through the Korea Science and Engineering Foundation funded by the Ministry of Science and ICT. This research was funded by the Korea government (MSIT) and supported by the National Research Foundation of Korea (NRF) under the Space Core Technology Development Program (project id: 2017M1A3A3A02016234).
All Science Journal Classification (ASJC) codes
- Water Science and Technology
- Earth-Surface Processes