Glacial lakes are a sensitive indicator of regional climate change and one of the initiators of glacier disasters. It is of great significance to understand the spatial distribution and change characteristics of glacial lakes for exploring their response patterns to climate change and assessing the glacial lake outburst flood (GLOF) susceptibility. Based on Gaofen-1/6 PMS, Sentinel-2A/2B MSI and Landsat TM/ETM+/OLI images from 2000 to 2020, we integrated geographic information technology and mathematical and statistical methods to analyze the spatial and temporal distribution of glacial lakes in Nepal and their dynamic changes, and further discriminated and evaluated the GLOF susceptibility of glacial lakes. The results show that there were 2420 glacial lakes in Nepal in 2020, mainly distributed within the 4500~5500 m, with an area of 87.21 km² and a water storage of 1921.72 × 10⁶ m³. The number and area of glacial lakes with each area above 0.01 km² in Nepal showed an increasing trend from 2000 to 2020, while 499 new glacial lakes were born, 139 lakes disappeared, the area and water storage increased by 19.46 km², 403.07 × 10⁶ m³, respectively. Glacial lakes at altitudes <3000 m were relatively stable, while the number and area of glacial lakes at altitudes within 4500~5500 m increased rapidly. We assessed the GLOF susceptibility of 40 moraine-dammed glacial lakes with an area above 0.2 km² in Nepal, and found that there were 8, 12, 14 and 6 glacial lakes with low, medium, high and very high susceptibility, respectively. Among glacial lakes with very high GLOF susceptibility, potential GLOF events of Tsho Rolpa glacial lake, Lower Barun glacial lake and glacial lake with code of GL87091E27797N will cause great harm to downstream regions. GLOFs in Nepal will be in an active status in the future, therefore, the dynamics of glacial lakes and their surroundings should be continuously monitored.

The advancing of glaciers is a manifestation of dynamic glacial instability. Glaciers in the Tien Shan region, especially in the Central Tien Shan, show instability, and advancing glaciers have been recently detected. In this study, we used Landsat TM/ETM+/OLI remote sensing images to identify glaciers in the Tien Shan region from 1990 to 2019 and found that 48 glaciers advanced. Among them, thirty-four glaciers exhibited terminal advances, and 14 glaciers experienced advances on the tributary or trunk. Ten of the glaciers experiencing terminal advances have been identified as surging glaciers. These 48 glaciers are distributed in the western part of the Halik and Kungey Mountain Ranges in the Central Tien Shan, and Fergana Mountains in the Western Tien Shan, indicating that the Tien Shan is also one of the regions where advancing and surging glaciers are active. From 1990 to 2019, a total of 169 times advances occurred on 34 terminal advancing glaciers in the Tien Shan region; the highest number of advancing and surging of glaciers occurred in July (26 and 14 times, respectively). With reference to the existing literature and the present study, the surge cycle in the Tien Shan is longer than that in other regions at high latitudes in Asia, lasting about 35–60 years. Surging glaciers in the Tien Shan region may be affected by a combination of thermal and hydrological control. An increase in temperature and precipitation drives surging glaciers, but the change mechanism is still difficult to explain based on changes in a single climate variable, such as temperature or precipitation.

High Mountain Asia (HMA) is one of the concentrated areas of surging glaciers in the world. The dynamic movement of surging glaciers not only reshapes the periglacial landscape but also has the potential to directly or indirectly trigger catastrophic events. Therefore, it is crucial to understand the distribution patterns, periodicities, and occurrence mechanisms of surging glaciers. Based on Landsat TM/ETM+/OLI remote sensing images from 1986 to 2021, a total of 244 surging glaciers were identified in HMA in this study, covering an area of 11,724 km² and accounting for 12.01% of the total area of glaciers in this region. There are 185 surging glaciers identified within the Karakoram Range and Pamirs, which constitute the primary mountainous regions in HMA. From 1986 to 2021, these surging glaciers advanced at least 2802 times and exhibited different temporal and spatial patterns. A total of 36 glaciers in HMA experienced 2 or more surges during this period, with the highest number observed in the Pamirs (19), followed by the Karakorum (13), with the other regions having fewer occurrences. Obvious differences exist in the surge phase and the quiescent phase of glaciers in different regions of HMA. The surge phase of surging glaciers in the Karakoram Range and Pamirs is generally short, mostly in the range of 2~6 years. The quiescent phase lasts for 5~19 years and the overall surge cycle ranges from 9 to 24 years. The complex nature of glacier surges in HMA suggests that multiple mechanisms may be at play, necessitating further research.

The glacial lakes in the Southeastern Qinghai–Tibet Plateau (SEQTP) have undergone dramatic expansion in the context of global warming, leading to several glacial lake outburst floods (GLOFs) disasters. However, there is a gap and incompleteness in glacial lake inventories across this area due to the heavy cloud cover. In this study, an updated and comprehensive glacial lake inventory was produced by object-based image analysis (OBIA) and manual vectorization based on the Sentinel-1 SAR and Sentinel-2 MSI images acquired in 2022. Detailed steps regarding the OBIA were provided, and the feature set of Sentinel-1 SAR images suitable for extracting glacial lakes was also determined in this paper. We found that the mean combination of ascending-orbit and descending-orbit images is appropriate for mapping glacial lakes. VV-polarized backscattering coefficients from ascending-orbit achieved a better performance for delineating glacial lakes within the study area. Moreover, the distribution of glacial lakes was characterized in terms of four aspects: size, type, elevation, and space. There were 3731 glacial lakes with a total area of 1664.22 ± 0.06 km² in the study area; most of them were less than 0.07 km². Ice-contacted lakes were primarily located in the Palongzangbo basin (13.24 ± 0.08 km²). Nyang Qu basin had the most abundant glacial lake resources (2456 and 93.32 ± 0.18 km²). A comparison with previously published glacial lake datasets demonstrated that our dataset is more complete. This inventory is useful for evaluating water resources, studying glacier–glacial lake interactions, and assessing GLOFs’ susceptibility in the SEQTP.

Glaciers are sensitive indicators of climate change, and investigation of their dynamics is crucial for ensuring regional ecological security as well as disaster prevention and mitigation measures. Based on Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+)/Operational Land Imager (OLI) imagery, the outlines and length of glaciers in the West Kunlun Main Peak Area (WKMPA) during 2000–2020 were obtained by combining a band ratio method with manual interpretation and an automatic extraction method for the glacier centerline, respectively. There were 440 glaciers in the WKMPA in 2020, covering an area of 2964.59 ± 54.87 km², with an average length of 2916 ± 60 m. The glacier count increased due to division, while the area and length all exhibited a declining trend from 2000 to 2020, at rates of −0.04%·a⁻¹ (24.83 km²) and −0.11%·a⁻¹ (66 m), respectively. Glacier retreat was primarily observed during the early period (2000–2005). Except for glaciers located above an elevation of 6250 m, the glacier area decreased with each altitude interval from 2000 to 2020, and the rate of relative change in glacier area generally decreased with increasing altitude. Moreover, except for a slight increase in north-facing glaciers, the area of glaciers facing other orientations decreased during 2000–2020. The accuracy of the empirical formula fit for glacier length was highly dependent on glacier class, with greater precision observed for smaller glaciers and lower precision for larger valley-basin glaciers due to their complex morphological structures being neglected and only a single quantitative relationship being considered. There was a time lag of 12 years between temperature changes and glacier area response in this region. The mechanism by which glacier division affects glacier change is complex, requiring dissection of multiple factors such as area, length, and terminal elevation before and after division.

As an important part of the cryosphere, lake ice is a sensitive indicator of climate change. Remote sensing technology can quickly and accurately monitor the process of its formation and decay, among which Moderate Resolution Imaging Spectroradiometer (MODIS) images are the most widely used data in the remote sensing monitoring of lake ice. The reasonable selection of monitoring methods is of great significance to grasp the dynamic process and response to climate change of lake ice. In this study, five commonly used remote sensing monitoring methods of lake ice based on MODIS MOD09GA data, including the single band threshold method (SBT), reflectance difference threshold method (RDT), normalized difference snow index method (NDSI), modified normalized difference snow index method (MNDSI) and lake ice index method (LII), were selected to compare their accuracies in extracting lake ice extent by combining them with four evaluation metrics of accuracy, precision, recall and mean intersection over union (MIoU). In addition, the ability of the high-precision LII method for extracting long time series lake ice phenology and its applicability to multiple types of lakes were verified. The results showed that compared with the NDSI method, the other four methods more easily distinguished between lake ice and lake water by setting thresholds. The SBT method and the RDT method had better extraction effects in the freezing process and the melting process, respectively. Compared with the NDSI and MNDSI methods, the LII method showed a significant improvement in lake ice extraction over the entire freeze–thaw cycle, with the smallest mean monitoring error of 1.53% for the percentage of lake ice area in different periods. Meanwhile, the LII method can be used to determine long term lake ice phenology dates and had good performance in extracting lake ice for different types of lakes on the Qinghai–Tibet Plateau with the optimal threshold interval of 0.05~0.07, which can be used for lake ice monitoring and long-term phenological studies in this region.