Debris-covered glaciers are common features on the eastern Pamir and serve as important indicators of climate change promptly. However, mapping of debris-covered glaciers in alpine regions is still challenging due to many factors including the spectral similarity between debris and the adjacent bedrock, shadows cast from mountains and clouds, and seasonal snow cover. Considering that few studies have added movement velocity features when extracting glacier boundaries, we innovatively developed an automatic algorithm consisting of rule-based image segmentation and Random Forest to extract information about debris-covered glaciers with Landsat-8 OLI/TIRS data for spectral, texture and temperature features, multi-digital elevation models (DEMs) for elevation and topographic features, and the Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) for movement velocity features, and accuracy evaluation was performed to determine the optimal feature combination extraction of debris-covered glaciers. The study found that the overall accuracy of extracting debris-covered glaciers using combined movement velocity features is 97.60%, and the Kappa coefficient is 0.9624, which is better than the extraction results using other schemes. The high classification accuracy obtained using our method overcomes most of the above-mentioned challenges and can detect debris-covered glaciers, illustrating that this method can be executed efficiently, which will further help water resources management.

The inner Tibetan Plateau is a glacierized region where glaciers show heterogeneous change. The Xinqingfeng and Malan ice caps are located in this region, and a transition zone exists with shifting influences between the westerlies and Indian summer monsoon. However, there is a lack of detailed information regarding glacier area and mass changes in this region before 2000. In the present study, we describe an integrated view of the glacier area and its mass changes for Mt. Xinqingfeng and Mt. Malan as derived from topographic maps, Landsat, ASTER, SRTM DEM, and TerraSAR-X/TanDEM-X from 1970 to 2012 and from 1970 to 2018, respectively. Our results show that the glaciers experienced a slight shrinkage in area by 0.09 ± 0.03% a−1 from 1970 to 2018 with a median mass loss rate of 0.22 ± 0.17 m w.e. a−1 and 0.29 ± 0.17 m w.e. a−1 between 1999 and 2012 at Mt. Xinqingfeng and Mt. Malan, respectively. The glaciers of Mt. Malan had a total mass loss of 0.19 ± 0.14 m w.e. a−1 during the period 1970–1999. A minimum of seven glaciers at Mt. Xinqingfeng and Mt. Malan showed heterogeneous variations with either surging or advancing during the observation period. Among them, the West Monuomaha Glacier, Monuomaha Glacier, and Zu Glacier were identified as surging glaciers, and the others may also be surging glaciers, although more evidence is required. These glaciers showed a long active period and low velocities. Therefore, we suggested that thermal controls are important for surge initiation and recession.

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Glacier velocity is the key to understanding the nature of glaciers. Its variation plays an important role in glacier dynamics, mass balance, and climate change. The Muztag-Kongur Mountains are an important glacier region in the Eastern Pamir Plateau. Under the background of global warming, the glacier velocity variation has been widely considered, but details of the inter-annual and intra-annual changes have not been clear. In this study, we explored the inter-annual and intra-annual variations in the glacier velocity from 1990 to 2021, and the influencing factors, based on Landsat images, Inter-Mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE), and Karakoram Highway (KKH) data product analysis. The results showed the following: (1) the glacier velocity has increased since 1990, and significant growth occurred in 1995–1996. (2) A transverse profile of two typical glaciers was used to analyze the monthly variation in glacier velocity during the year. The peaks of monthly velocity occurred in May and August. (3) Since 1990, the inter-annual precipitation has increased, and the temperature increase slowed down from 2000 to 2013. The trend of inter-annual glacier velocity variation was consistent with that of the precipitation. The glacier velocity peaked in 1996/1997 due to increased precipitation in 1995. The glacier velocity over the year was consistent with the monthly precipitation trends, which indicates that precipitation has a significant influence on the change in glacier velocity. (4) In addition to temperature and precipitation, the glacier velocity variation was moderately correlated with the glacier size (length and area) and weakly correlated with the slope. The spatial distribution of glaciers shows that the spatial heterogeneity of glaciers in the Muztag-Kongur Mountains is affected by the westerly circulation. The long-term glacier velocity variation research of the Muztag-Kongur Mountains will contribute to a better understanding of glacier dynamics within the context of climatic warming, and the different influencing factors were analyzed to further explain the glacier velocity variation.

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