Exploring Siachen glacier thickness change over eastern Himalayas by integrating multispectral and SAR time-series dataset

The change in ice thickness plays a primary role in measuring the glacier mass balance. Remote sensing techniques, such as optical and SAR instruments are regarded as powerful tools to monitor glacier thickness with different resolutions at a multi-scale. Despite great interesting, the temporal resolution becomes a main limitation to provide the continuous monitoring. In this paper, we for the first time integrate Sentinel-1/2 and GF-3 time-series dataset to enhance the temporal resolution. Also, the increased degrees of freedom from multi-source integration allow the full evaluation of three-dimensional glacier motion. Using data set ranging from January 2018 to December 2020, we use this methodology to explore the change in Siachen glacier thickness over the eastern Himalayas. More concretely, after estimating pixel offsets from individual sensors, the full three-dimensional flow velocity of glacier is first estimated by L1-norm minimization, followed by least-squares. The vertical velocity is then decomposed into Surface-Parallel Flow (SPF) of the glacier's movement along the glacier surface slope and non-Surface-Parallel Flow (nSPF) of the internal ice deformation and glacier thickness change. The seasonal and interannual variation of the flow velocity is also observed. We found a maximum thickness thinning velocity up to 23 cm/day in the lower middle portion of the glacier. The extracted time series demonstrate a remarkable temporal variability in flow velocities. Compared with the results estimated from the individual sensors, the integration improves the three-dimensional flow velocity by 26%, 19% and 4% in the east-west, north-south and vertical direction respectively. This study is of great significance for obtaining high temporal resolution and high accuracy glacier thickness changes using multi-source remote sensing data, and mitigating the disasters caused by glaciers.