As global warming becoming a more critical issue, how to perform a long-term and accurate enough method to sense and monitor arctic area glacier movement becomes more important. With the benefits of remote sensing techniques, we can continuously achieve wide coverage ground information in all-weather conditions. Russell glacier, one of the biggest and quick-moving glaciers located in western Greenland which is near Island’s main airport, was selected as our case study area.

Because the pre-knowledge supra/under glacial hydrological channel is known to be a crucial key to investigate glacier, it is needed to be modeled firstly. With conventional D-InSAR (Differential Interferometric SAR) technique, we can only detect LOS (Line-Of-Sight) direction displacement which would be insufficient to monitor overall movement pattern over rapid changing glacier area.

In this paper, we use both optical and Synthetic Aperture Radar (SAR) images to construct comprehensive glacier landscape model and deformation monitoring. The practical approaches are summarized as following:

1) Channel bathymetry is built up with both calibrated Landsat images and SAR along-track stereo DTM, which is used in 2D numerical hydrodynamic simulation; 2) decomposed 3D migration vectors by combining D-InSAR analysis together with the in-house pixel tracking method employing optical flow and sub-pixel refinement with C band Sentinel-1 and L band ALOS PALSAR-2 images, 3) eventually an ice sheet model was used to extract the bedrock and basal characteristics of the glaciers.

The results revealed the importance of hydrological channel morphology as a dominant factor over migration speeds of glaciers. Moreover, the subglacial movement and underlying bedrock height estimated by remote sensing observations and the numerical model were highly correlated with the observed local migration speeds in terminus of the Russell glacier.

These experiences indicate the feasibility to achieve a complete understanding of the processes of arctic glaciers. Therefore, based on the results of this study, the proposed method can be used to solve the ice sheet change monitoring which occurs in the Greenland coastal area.