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The paper presents the potential of combining satellite radar data and neural networks for quasi-automatic detection of glacier grounding lines. The conducted research covered five years and was carried out in the area of the Amery Ice Shelf. It has a very complex shoreline, so its grounding-line location is uncertain. Thus, it has always been the subject of much research. The main objective of our work was to find out if Synthetic Aperture Radar data combined with a deep learning implementation would enable rapid detection of ice shelf grounding lines over large areas. For this purpose, 290 radar images from the Sentinel-1 satellite covering 46 000 km² were used. Processed by the Differential Interferometry of Synthetic Aperture Radar four-pass method, the images formed a timeconsistent series between 2017 and 2021. As a result of performed calculations, a total length of 1280 km of grounding line was determined. They were validated by comparing with other independent data sources based on manual measurements. It has been demonstrated that the combination of satellite radar data and automated data processing allows for obtaining high-precision results continuously in a very short time. Such an approach allows monitoring of grounding line position in the long term with intervals of less than one week. It enables analysis of the dynamics changes with unprecedented frequency and the identification of patterns. [ABSTRACT FROM AUTHOR]

The article presents a proposal to make simultaneous allowance for both ionospheric and tropospheric corrections in differential synthetic aperture radar interferometry (DInSAR) measurements. Atmospheric delay in the interferometric phase may cause the detection of terrain-surface changes to be impossible or significantly distorted. This fact remains of special importance in the case of surface changes that show limited amplitude and spatial range. Two areas were chosen to verify the validity of the proposed solution. The first area includes terrains affected by underground copper-ore mining activity (Poland), which shows high induced seismic activity. Mining tremors recorded in this area cause the terrain surface to locally subside. The authors analyzed three tremors that were recorded in 2016, 2017, and 2019. Each of the tremors exceeded a magnitude of Mw 4.0. The second area is located in the coastal region of Chile, in the Cardenal Caro province. In this case, the authors focused on a series of three earthquakes recorded on 11 March 2010. The strongest of the earthquakes was of Mw 7.0 magnitude. In the first case, calculations were based on obtained data from the Sentinel 1 satellites, and in the second case from the ALOS-1 satellite. It is demonstrated that simultaneous allowance for both the tropospheric and ionospheric corrections significantly improves the final results. The authors were also able to use the analyzed cases to demonstrate that implementation of the corrections does not have negative influence on the range and magnitude of local ground-surface deformations. At the same time, such implementation minimizes local displacement fluctuations and reduces displacement values in areas affected by deformations. The examples used in the article served to show that tropospheric correction is mainly responsible for global corrections (i.e., within the whole analyzed spatial range), while ionospheric correction reduces local fluctuations. [ABSTRACT FROM AUTHOR]