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Wilkes Land and Totten Glacier (TG) in East Antarctica (EA) have been losing ice mass significantly since 1989. There is a lack of knowledge of long-term mass balance in the region which hinders the estimation of its contribution to global sea level rise. Here we show that this acceleration trend in TG has occurred since the 1960s. We reconstruct ice flow velocity fields of 1963–1989 in TG from the first-generation satellite images of ARGON and Landsat-1&4, and build a five decade-long record of ice dynamics. We find a persistent long-term ice discharge rate of 68 ± 1 Gt/y and an acceleration of 0.17 ± 0.02 Gt/y 2 from 1963 to 2018, making TG the greatest contributor to global sea level rise in EA. We attribute the long-term acceleration near grounding line from 1963 to 2018 to basal melting likely induced by warm modified Circumpolar Deep Water. The speed up in shelf front during 1973–1989 was caused by a large calving front retreat. As the current trend continues, intensified monitoring in the TG region is recommended in the next decades. Historical velocity maps reveal over five decade-long acceleration and high-level discharge in Totten Glacier, East Antarctica, from 1963-2018, induced by warm modified Circumpolar Deep Water.

Accurate ice flow velocity data are essential for studying the mass balance of the Antarctic ice sheet. However, there is a lack of ice velocity maps of 1960s–80s in basin-wide regions or the entire ice sheet. In this study, an enhanced hierarchical network densification approach is developed for basin-wide Antarctic velocity mapping using historical ARGON and Landsat images. The produced multiple historical velocity maps from 1963 to 1989 in the region of the Fimbul and Jelbart ice shelves, East Antarctica, achieved an accuracy better than 29 m a−1. They revealed that the ice flow velocity had no significant changes over the period. Combining the surface mass balance estimate with the ice discharge estimated from our historical velocity maps and recently published velocity maps, we estimated a positive mass balance of 8.6 ± 3.9 Gt a−1 in the study area from 1963 and 2015. Our results indicate that the region's positive mass balance, as estimated in recently published studies, has been maintained since the 1960s. It is also in concordance with the low level of mass balance from 1992 to 2017 in East Antarctica. This suggests that the study area has been stable since the 1960s.

Melting and calving of glaciers and ice caps in Antarctica and Greenland could potentially contribute significantly to global sea level rise. Updates to existing outlines that provide critical glacier baseline information in both regions could help in the analysis of particular changes in glacier parameters such as area and volume from time-series inventories. Here we synthesize previously established techniques and apply new multi-source datasets to update glacier outlines in selected test areas of Antarctica and Greenland, as well as to reduce uncertainties and errors during the mapping process. The workflow includes mapping glacier boundaries, subdividing glaciers by watersheds and assigning glacier attributes. Complicated glacier scenarios and updating challenges in polar regions are discussed and demonstrated by representative case studies. For the first time in Antarctica, we analyze the effect of terminus types on mapped glacier areas, and in Greenland we compare the differences with glacier mapping results using Landsat OLI and ETM+. With new data sources, the methods described in this study might help to create glacier outlines on a larger scale in Antarctica and Greenland. Although data sources can be substituted, the enormous amount of manual labor required to update glacier inventories remains a significant challenge.

Subglacial water bodies are critical components in analyzing the instability of the Antarctic ice sheet. Their detection and identification normally rely on geophysical and remote sensing methods such as airborne radar echo sounding (RES), ground seismic, and satellite/airborne altimetry and gravity surveys. In particular, RES surveys are able to detect basal terrain with a relatively high accuracy that can assist with the mapping of subglacial hydrology systems. Traditional RES processing methods for the identification of subglacial water bodies mostly rely on their brightness in radargrams and hydraulic flatness. In this study, we propose an automatic method with the main objective to differentiate the basal materials by quantitatively evaluating the shape of the A-scope waveform near the basal interface in RES radargrams, which has been seldom investigated. We develop an automatic algorithm mainly based on the traditional short-time Fourier transform (STFT) to quantify the shape of the A-scope waveform in radargrams. Specifically, with an appropriate window width applied on the main peak of each A-scope waveform in the RES radargram, STFT shows distinct and contrasting frequency responses at the ice-water interface and ice-rock interface, which is largely dependent upon their different reflection characteristics at the basal interface. We apply this method on 882 RES radargrams collected in the Antarctic’s Gamburtsev Province (AGAP) in East Antarctica. There are 8822 identified A-scopes with the calculated detection value larger than the set threshold, out of the overall 1,515,065 valid A-scopes in these 882 RES radargrams. Although these identified A-scopes only takes 0.58% of the overall A-scope population, they show exceptionally continuous distribution to represent the subglacial water bodies. Through a comprehensive comparison with existing inventories of subglacial lakes, we successfully verify the validity and advantages of our method in identifying subglacial water bodies using the detection probability for other basal materials of theoretically the highest along-track resolution. The frequency signature obtained by the proposed joint time–frequency analysis provides a new corridor of investigation that can be further expanded to multivariable deep learning approaches for subglacial and englacial material characterization, as well as subglacial hydrology mapping.

Accurate estimate of active layer thickness (ALT) is crucial for understanding permafrost and ecosystem responses to climate change. Interferometric Synthetic Aperture SAR (InSAR) technology can detect active layer freeze-thaw induced surface deformation with high accuracy, facilitating more accurate ALT estimation at the regional scale. Previous studies revealed a positive relationship between ALT and seasonal deformation in poorly drained Arctic soils. However, whether such relationship still holds in arid permafrost regions such as the Qinghai-Tibet Plateau (QTP) remains uncertain. Through synthesizing extensive field observations and remote sensing data, we find an overall negative correlation ( r  = -0.53, p  < 0.01) between ALT and seasonal deformation in QTP, which tends to become more negative with sparser vegetation and drier soils, in contrast to the Arctic. After normalizing the climatic effect on ALT, we observe a decreasing sensitivity of seasonal deformation to active-layer changes with drier soils. Our study reveals a non-linear relationship between ALT and seasonal deformation across different permafrost regions, which helps to inform future development of InSAR-based permafrost applications.

Pine Island Glacier (PIG) is one of the largest contributors to sea level rise in Antarctica. Continuous thinning and frequent calving imply significant destabilization of Pine Island Glacier Ice Shelf (PIGIS). To understand the mechanism of its accelerated disintegration and its future development, we conducted a long-term monitoring and comprehensive analysis of PIGIS, including ice flow velocity, ice shelf fronts, ocean water temperature, rifts, and surface strain rates, based on multi-source satellite observations during 1973–2020. The results reveal that: (1) ice flow velocities of PIGIS increased from 2.3 km/yr in 1973 to 4.5 km/yr in 2020, with two rapid acceleration periods of 1995–2009 and 2017–2020, and its change was highly correlated to the ocean water temperature variation. (2) At least 13 calving events occurred during 1973–2020, with four unprecedented successive retreats in 2015, 2017, 2018, and 2020. (3) The acceleration of ice shelf rifting and calving may correlate to the destruction of shear margins, while this damage was likely a response to the warming of bottom seawater. The weakening southern shear margin may continue to recede, indicating that the instability of PIGIS will continue.

This paper reviewed the developments of the last ten years in the field of international high-resolution earth observation, and introduced the developmental status and plans for China＇s high-resolution earth observation program. In addition, this paper expounded the transformation mechanism and procedure from earth observation data to geospatial information and geographical knowledge, and examined the key scientific and technological issues, including earth observation networks, high-precision image positioning, image understanding, automatic spatial information extraction, and focus services. These analyses provide a new impetus for pushing the application of China＇s high-resolution earth observation system from a ＂quantity＂ to ＂quality＂ change, from China to the world, from providing products to providing online service.

Landslides are occurring more frequently in China under the conditions of extreme rainfall and changing climate, according to News reports. Landslide hazard assessment remains an international focus on disaster prevention and mitigation, and it is an important step for compiling and quantitatively characterizing landslide damages. This paper collected and analyzed the historical landslide events data of the past 60 years in China. Validated by the frequencies and distributions of landslides, nine key factors (lithology, convexity, slope gradient, slope aspect, elevation, soil property, vegetation coverage, flow, and fracture) are selected to construct landslide susceptibility (LS) empirical models by back-propagation artificial neural network method. By integrating landslide empirical models with surface multi-source geospatial and remote sensing data, this paper further performs a large-scale LS assessment throughout China. The resulting landslide hazard assessment map of China clearly illustrates the hot spots of the high landslide potential areas, mostly concentrated in the southwest. The study implements a complete framework of multi-source data collecting, processing, modeling, and synthesizing that fulfills the assessment of LS and provides a theoretical basis and practical guide for predicting and mitigating landslide disasters potentially throughout China.

Early detection and early warning are of great importance in giant landslide monitoring because of the unexpectedness and concealed nature of large-scale landslides. In China, the western mountainous areas are prone to landslides and feature many giant complex landslides, especially following the Wenchuan Earthquake in 2008. This work concentrates on a new technique, known as the “hybrid-SAR technique”, that combines both phase-based and amplitude-based methods to detect and monitor large-scale landslides in Li County, Sichuan Province, southwestern China. This work aims to develop a robust methodological approach to promptly identify diverse landslides with different deformation magnitudes, sliding modes and slope geometries, even when the available satellite data are limited. The phase-based and amplitude-based techniques are used to obtain the landslide displacements from six TerraSAR-X Stripmap descending scenes acquired from November 2014 to March 2015. Furthermore, the application circumstances and influence factors of hybrid-SAR are evaluated according to four aspects: (1) quality of terrain visibility to the radar sensor; (2) landslide deformation magnitude and different sliding mode; (3) impact of dense vegetation cover; and (4) sliding direction sensitivity. The results achieved from hybrid-SAR are consistent with in situ measurements. This new hybrid-SAR technique for complex giant landslide research successfully identified representative movement areas, e.g., an extremely slow earthflow and a creeping region with a displacement rate of 1 cm per month and a typical rotational slide with a displacement rate of 2–3 cm per month downwards and towards the riverbank. Hybrid-SAR allows for a comprehensive and preliminary identification of areas with significant movement and provides reliable data support for the forecasting and monitoring of landslides.

Landslides represent a major type of natural hazards worldwide. For development of risk mitigation capabilities, an effective system for monitoring dynamic process of slope failure, capable of gathering spatially distributed information before, during and after a landslide occurrence at real-time manner is essential. A spatial sensor network (SSN), which integrates the real-time communication infrastructure and observations from in situ sensors and remote sensing platforms, offers an efficient and effective approach for such purpose. In this paper, a SSN-based landslide monitoring system was designed and evaluated through a model test study conducted at Tongji University, China. This system, MUNOLD (MUlti-Sensor Network for Observing Landslide Disaster), has been designed as a comprehensive monitoring framework, including sensor observations, multi-channel wireless communication, remote data storage, visualization, data processing and data analysis. In this model test study, initial experimentation demonstrated the capabilities of the MUNOLD system for collecting real-time information about the dynamic process and propagation of slope failure. Innovatively, generated from the high-speed stereo images, the sequential surface deformation vector field can be created and may exhibit the dynamic process during the extremely critical and short period of the slope failure. After this model test study, the MUNOLD system is going to be further improved and extended in a landslide prone region in Sichuan Province, China.