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Change of supraglacial lakes (SGLs) is an important hydrological activity on the Greenland ice sheet (GrIS), and storage and drainage of SGLs occur throughout the year. However, current studies tend to split SGL changes into melt/non-melt seasons, ignoring the effect of buried lakes in the exploration of drainage, and the existing threshold-based approach to SGL extraction in a synthetic aperture radar (SAR) is influenced by the choice of the study area mask. In this study, a new method (Otsu–Canny–Otsu (OCO)), which accesses the features of SGLs on optical and SAR images objectively, is proposed for full-year SGL extraction with Google Earth Engine (GEE). The SGLs on the Petermann Glacier were monitored well by OCO throughout 2021, including buried lakes and more detailed rapid drainage events. Some SGLs’ extent varied minimally in a year (area varying by 10–25%) while some had very rapid drainage (a rapid drainage event from July 26 to 30). The SGL extraction results were influenced by factors such as the mode of polarization, the surface environment, and the depth of the lake. The OCO method can provide a more comprehensive analysis for SGL changes throughout the year.

Study region: This study investigates the Supraglacial lakes (SGLs) of Sermeq Avannarleq glacier. This glacier is in southwest Greenland, which has active glacial meltwater. Study focus: Supraglacial lakes (SGLs) are an essential part of the hydrological systems of ice sheets, and their development is vital for determining the stability of ice sheets. This paper use 188 scenes of Landsat images during the melting season from 2000 to 2020 with Google Earth Engine to analyze the seasonal changes of the SGLs. New hydrological insights: 1) The area, volume, and depth of the SGLs, increased, indicating the increasing melt in this area from 2000 to 2020. 2) the SGLs development peaked at 190–200 days of the year. The melting area significantly expanded at the initial stage, while the melting depth change was more significant than the area at the later stage. 3) The elevation reached by the SGLs advanced approximately 300 m inland from 1400 m to 1700 m elevation. The convergence of small lakes (

Monitoring surface deformation for highways built on soft clay subgrades is fundamental for understanding the dynamics of the settlement process and preventing the occurrence of safety accidents. Most of the traditional interferometric synthetic aperture radar (InSAR) deformation models for highway monitoring are based on a combination of one or several empirical functions, which ignores the underground mechanism of highway deformation. To overcome this limitation, we proposed an advanced InSAR approach that improved the InSAR deformation model and parameter estimation algorithm for soft clay road deformation monitoring. The improved InSAR deformation model is based on the Poisson curve, which considers the characteristics of the temporal physical deformation evolution of the soft clay. The improved algorithm for the unknown parameter estimation is based on a GARN algorithm, which can solve the parameters with better accuracy by combining the genetic algorithm and the regularized Newton iterative algorithm. To evaluate the better performance for the proposed approach and its feasibility for soft clay highway monitoring, both the simulation and the real data experiments on a soft clay highway in Foshan, China, are performed. The time-series deformation from January 1, 2015 to January 18, 2017, is retrieved, and the temporal deformational characteristics over this area are analyzed, which facilitates a greater understanding of the deformational evolution process of the soft clay highway. The results are verified in terms of the residual high-pass deformation and the final obtained vertical deformation compared with the external leveling measurements, which indicate the greater reliability of our method.

As a kind of sustainable energy source, ocean wave energy has always attracted attention. Because of the characteristics of multi-directions and low-bandwidth, the harvesting of wave energy has always been difficult. To harvest broadband wave energy in multiple directions and improve power generation efficiency, we present a multi-modal energy harvesting device by using a cross beam structure. In this device, the efficient harvesting of multi-frequency vibration energy in multiple directions has been achieved by using the multi-modal characteristics of the structure and the high power generation efficiency of the electric device based on liquid metal. Contrast experiments in multiple directions show that the device not only has the capability of multi-directional energy harvesting but also can work in the sweep range of the full band. Under horizontal excitation, compared with traditional single cantilever structure, the peak power density increased to 2227% and the working frequency band increased to 6.25 times. The experimental results show that the device significantly improves the efficiency of low-bandwidth multi-directional energy harvesting, providing a new method for vibration energy harvesting.

Landfast ice has undergone a dramatic decline in recent decades, imposing potential effects on ice travel for coastal populations, habitats for marine biota, and ice use for industries. The mapping of landfast ice deformation and the investigation of corresponding causes of changes are urgent tasks that can provide substantial data to support the maintenance of the stability of the Arctic ecosystem and the development of human activities on ice. This work aims to investigate the time-series deformation characteristics of landfast ice at multi-year scales and the corresponding influence factors. For the landfast ice deformation monitoring technique, we first combined the small baseline subset approach with ascending and descending Sentinel-1 images to obtain the line-of-sight deformations for two flight directions, and then we derived the 2D deformation fields comprising the vertical and horizontal directions for the corresponding periods by introducing a transform model. The vertical deformation results were mostly within the interval [−65, 23] cm, while the horizontal displacement was largely within the range of [−26, 78] cm. Moreover, the magnitude of deformation observed in 2019 was evidently greater than those in 2020 and 2021. In accordance with the available data, we speculate that the westerly wind and eastward-flowing ocean currents are the dominant reasons for the variation in the horizontal direction in Cambridge Bay, while the factors causing spatial differences in the vertical direction are the sea-level tilt and ice growth. For the interannual variation, the leading cause is the difference in sea-level tilt. These results can assist in predicting the future deformation of landfast ice and provide a reference for on-ice activities.

The infrastructures built on soft clay in the Dongting Lake area are more prone to settlement and instability due to its significant rheological properties. It is of great importance to conduct a long-term surface deformation monitoring over this area. The most commonly used Synthetic Aperture Radar Interferometry (InSAR) deformation models are based on combinations of one or several pure empirical mathematical functions without considering the physical and mechanical characteristics of the observed objects. In this work, we propose an improved deformation model based on the functional relationship between strain and time in the Maxwell rheological model. The rheological parameters of elastic modulus and viscosity are introduced into a traditional empirical seasonal model. The improved model is applied for the investigation of the spatial-temporal surface evolution over the Dongting Lake area with the Small Baseline Subset InSAR (SBAS-InSAR) technology and TerraSAR-X satellite imagery. With the proposed model, the rheological parameters and the time series deformation are estimated, with the maximum accumulated subsidence estimated as 38 mm. Through the analysis of the generated results, we find that the lower the viscosity and elastic modulus are, the higher the deformation is. Temporally, the overall deformation follows a generally subsiding trend with a seasonal recovery of 5 mm from October 2012 to November 2012 and 12 mm from January 2013 to February 2013. To compensate for the deficiency of the unavailability of external geodetic measurements over this area, three different accuracy indexes (residual phase, temporal coherence, and high-pass deformation) are utilized to evaluate the modeling accuracy. The results of the improved model are also compared to three traditional models (seasonal model, cubic polynomial model, and linear model). The comparison shows that the improved model is highly recommended in this area because of its better accuracy.

Highways built on soft clay subgrade are more prone to subsidence due to the geotechnical characteristics of soft clay. Monitoring ground movements in this area is significant for understanding the deformation dynamics and reducing maintenance cost as well. In this paper, small baseline subset synthetic aperture radar interferometry (SBAS-InSAR) technique is exploited to obtain and investigate the time series ground surface deformation after the construction of a road embankment over soft clay settlement. Considering the important effect of temporal deformation models on the final accuracy of estimated deformation, both the linear velocity model and seasonal deformation model are utilized to conduct the comparative investigation of deformation time series. Two highways in Fuoshan, China—G1501 Guangzhou Belt Highway and Lungui Highway—were selected as the test area. Thirteen TerraSAR-X images acquired from October 2014 to November 2015 were analyzed. Comparative study based on two groups of analyses generated from the two models for both highways were conducted. Consequently, several feature points distributed near the two highways were analyzed in detail to understand the temporal evolution of the settlement. In order to evaluate the reliability of our measurements, the residual phase was analyzed to assess the modelling accuracy of the two models. In addition, leveling data were also used to validate the experimental results. Our measurements suggest that the seasonal model is more suitable for the test highways, with an accuracy of ±3 mm with respect to the leveling results.

The grounding line position of glaciers and ice shelves is an essential observation for the study of the Earth's ice sheets. However, in some locations, such as the Antarctic Peninsula, where many grounding lines have not been mapped since the 1990s, remote sensing of grounding line position remains challenging. Here we present a tidal motion offset correlation (TMOC) method for measuring the grounding line position of tidewater glaciers and ice shelves, based on the correlation between tide amplitude and synthetic aperture radar offset tracking measurements. We apply this method to the Antarctic Peninsula Ice Sheet to automatically delineate a new grounding line position for 2019-2020, with near complete coverage along 9,300 km of coastline, updating the 20-year-old record. A comparison of the TMOC grounding line to contemporaneous interferometrically-measured grounding line position shows the method has a mean seaward offset compared to interferometry of 185 m and a standard deviation of 295 m. Our results show that over the last 24 years there has been grounding line retreat at a number of fast flowing ice streams on the Antarctic Peninsula, with the most retreat concentrated in the north-eastern sector, where grounding lines have retreated following the collapse of ice shelves. We observe a maximum grounding line retreat since 1996 of 16.3 km on Hektoria Glacier, with other notable glaciers retreating by 9.3 km, 9.1 km, and 3.6 km respectively. Our results document dynamic change on Antarctic Peninsula glaciers and show the importance of using an updated grounding line location to delineate the boundary between floating and grounded ice. [ABSTRACT FROM AUTHOR]