Dynamic Lake Ice Movement on Lake Khovsgol, Mongolia, Revealed by Time Series Displacements from Pixel Offset with Sentinel-2 Optical Images

Abstract

As one of the most sensitive indicators of global climate change, seasonal ice-covered lakes are attracting gaining attention worldwide. As a large seasonal ice-covered lake located in Northern Mongolia, Lake Khovsgol not only provides important freshwater resources for the local population but also serves as a means of water transportation in summer and an important land-based activity for residents in winter. In this study, we used the sub-pixel offset technique with multi-temporal Sentinel-2 optical images to estimate the time-series displacement of lake ice in Lake Khovsgol from 7 December 2020 to 17 June 2021. With the processing of 112 Sentinel-2 images, we obtained 27 pairs of displacement results at intervals of 5, 10, and 15 days. These lake ice movement results covered three stages from ice-on to ice-off. The first stage was the lake ice growth period, which lasted 26 days from 7 December 2020 to 3 January 2021. Ice formation started from the south and extended northward, with a displacement of up to 10 m in 5 days. The second stage was the active phase of the ice cover, which took place from 3 January 2021 to 18 April 2021. Maximum displacement values reached 12 m in the east and 11 m in the north among all observations. The value of the lake ice movement in the north–south direction (NS) was found to be larger than in the east–west direction (EW). The third stage was the melting period, which closed on 17 June 2021. In comparison to the freezing date of November in past years, our results demonstrate the ice-on date of Lake Khovsgol has been delayed to December, suggesting a possible reason that the seasonal ice-covered lake located at the middle latitude has been affected by global warming. In addition, the lake ice movement of our results can reveal the regional climate characteristic. This study is one of the few cases to reveal the distribution characteristics and changing trends of lake ice on the Mongolia Plateau, providing a rare reference for lake ice research in this region.

Lake ice deformation on Khovsgol Lake from Sentinel data before, during and after the 2021 Mw 6.7 earthquake in Turt, Mongolia

“…However, other locations of large displacement gradients, such as R2, R3 and R4, do not show similar changes in the surface texture. In comparison to Zhang and others (2021), our results indicate that the POT observations from Sentinel-1 SAR images is also sensitive to detect ice movement as well as Sentinel-2 optical images, and both of which can complement the mapping of ice motion features in intensity images using traditional remote-sensing classification techniques.…”

“…Among these different features, pressure ridges are the predominant topographical surface structures and generally connect two points on land on either side of a lake or bay mouth. Therefore, the distribution and variability of ridges are important for quantifying ice displacement changes and their stress interactions (Duncan and others, 2018; Zhang and others, 2021). As shown in Figures 2–7, there are a series of large-scale displacement gradients in Phase-1 to Phase-3, and associated surface textural changes can be found in the Sentinel-2 optical intensity images (as shown in Figs S9–S11).…”

“…Some studies have used remote-sensing data to monitor local vegetation (Chu and Guo, 2012) and water-level fluctuations (Zhou and others, 2019). However, few researchers have leveraged remote-sensing data to monitor lake ice patterns in the winter, excepting a recent investigation estimated the time-series displacement of lake ice from ice-on to ice-off on Khovsgol Lake with multi-temporal Sentinel-2 optical images (Zhang and others, 2021).

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The Spatio-Temporal Patterns of Glacier Activities in the Eastern Pamir Plateau Investigated by Time Series Sub-Pixel Offsets From Sentinel-2 Optical Images

“…In this study, the glacier movement was estimated by using the pixel offset tracking (POT) method with the Co-registration of Optically Sensed Images and Correlation (COSI-Corr) package. The COSI-Corr package was developed for coseismic ground displacement extraction with optical images [39] and integrated as a module in ENVI software platform (http://www.tectonics.caltech.edu), and it has been widely used to monitor the earth's surface changes [35,[40][41][42][43] and glacier monitoring [15,26,33,[44][45][46][47]. The output files of the COSI-Corr package include the horizontal ground displacement of the east-west (EW) and north-south (NS) components, as well as the relative signal-to-noise ratio (SNR) in each pair of images.…”

“…The filter in the COSI-Corr package implements a Non-Local Means algorithm to reduce the additive Gaussian white noise while retaining local displacement features [41]. We chose a 7 × 7 pixels filter window, and the noise threshold was 1.6 times the standard deviation [42]. The data processing flow is shown in Fig.…”