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Article

Spatial Distribution and Characteristics of Debris-Covered Glaciers in Xinjiang Based on CGI-XJ2020

by
Zexin Zhan
1,
Zhongqin Li
1,2,3,4,*,
Jianxin Mu
1,2,
Feiteng Wang
1,2,3,
Qibin Liang
4,
Qian Wang
4,
Wei Chen
3,
Yefei Yang
1,2 and
Weibo Zhao
1,2
1
Xinjiang Tianshan Glacier National Field Observation and Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
College of Science, Shihezi University, Shihezi 832000, China
4
College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2026, 18(1), 106; https://doi.org/10.3390/rs18010106
Submission received: 29 October 2025 / Revised: 21 November 2025 / Accepted: 26 December 2025 / Published: 27 December 2025
(This article belongs to the Special Issue Advances in Remote Sensing for Glacier Preservation)
Browse Figures
Versions Notes

Highlights

What are the main findings?
  • We employed high-resolution satellite imagery together with field measurements from 18 debris-covered glaciers to systematically identify and map debris-covered glaciers across Xinjiang.
  • Using this high-resolution dataset, we identified 1612 debris-covered glaciers (10,922.06 km2), with 10.65% of their total area mantled by debris.
What are the implications of the main findings?
  • Compared with previous glacier inventories and studies, this high-resolution dataset significantly improves the accuracy of debris-cover delineation and quantification, providing a more reliable basis for debris-covered glacier monitoring.
  • The results provide a high-resolution dataset for subsequent investigations of glacier mass balance, surface energy processes, and debris-cover dynamics in arid mountain regions.

Abstract

Debris cover is widespread on glaciers and strongly alters their surface albedo, energy balance, and ablation. Using the Chinese Glacier Inventory of Xinjiang 2020 (CGI-XJ2020), this study investigates the spatial distribution of debris-covered glaciers in Xinjiang. A total of 1612 debris-covered glaciers were identified, covering 10,922.06 km2, with 1163.32 km2 (~10.65%) mantled by debris. The estimated uncertainties are 266.27 km2 (2.44%) for debris-covered glaciers and 106.04 km2 (9.12%) for debris-covered portions. These glaciers are mainly distributed across the Tianshan Mountains, Pamir Plateau, Karakoram Mountains, and Kunlun Mountains, with debris concentrated near their largest glacierized centers in the first three ranges. Debris cover is primarily distributed below the median elevation of debris-covered glaciers in each mountain range and is predominantly concentrated on gentle slopes (0–15°), with a preference for north-facing aspects. Among drainage basins, the Tarim Interior Basin hosts the largest debris-covered area (1083.47 km2). Correlation analyses indicate that debris distribution is primarily controlled by glacier topography and debris-supply zone characteristics, with steep supply zones (slope > 45°) playing a key role in debris formation.

1. Introduction

Debris-covered glaciers are defined as those possessing a continuous debris mantle extending across the entire width of the glacier surface within the ablation zone [1]. Supraglacial debris is mainly derived from rockfall and weathering of surrounding slopes, as well as from glacial erosion of underlying bedrock [2]. The latter material is transported to the ablation zone and accumulates on the glacier surface, forming a relatively stable debris layer [3,4]. This debris cover modifies glacier surface albedo and modulates energy exchange processes, thereby exerting a substantial influence on the glacier’s surface energy balance [5,6,7]. Depending on its thickness, the debris layer can either enhance or inhibit glacier melting with implications for glacial hydrology [8,9,10,11,12]. Furthermore, thick debris layers can reduce ablation near glacier termini, enabling glaciers to retain elongated tongues and extend to lower elevations [13,14,15,16]. Consequently, a comprehensive understanding of the spatial distribution of supraglacial debris is critical for accurately evaluating glacier energy balance, modeling melt processes, and predicting glacier responses to climate change.
Globally, approximately 4.8–7.3% of the total mountain glacier area is covered by supraglacial debris [17,18]. The High Mountain Asia (HMA) region—which encompasses the Himalaya, Karakoram, Pamir, Tianshan, Kunlun, and Hengduan Mountains—is the most extensively glacierized region on Earth outside the polar areas [19] and is often referred to as the “Roof of the World.” In this region, roughly 11–13% of the glacierized area is debris-covered [20,21]. Abundant debris supply is generated by intense tectonic uplift, steep mountainous terrain, and frequent rockfalls and weathering processes [3,22,23]. In recent years, numerous international studies have focused on debris-covered glaciers across the HMA. These investigations have explored not only the spatial distribution of debris cover [24,25,26,27] but also its impacts on glacier energy balance and mechanisms of climatic response [28,29]. Several glacier inventories within the HMA now incorporate detailed information on debris distribution and characteristics. These include the debris-cover dataset based on the Randolph Glacier Inventory 6.0 [17,18], the Second Chinese Glacier Inventory (CGI-2) [30], the Pamir–Karakoram Glacier Inventory (GI_KP) [31], and the multi-temporal Karakoram Glacier Inventory (KGI) [32].
However, discrepancies persist among these studies and glacier inventories, particularly with respect to glacier counts and the regional distribution of debris cover. These differences are mainly attributable to the use of relatively coarse-resolution satellite imagery (30 m), which limits the accurate delineation of debris portions [25,33,34]. They also arise from the widespread reliance on semi-automatic extraction methods. Such approaches tend to yield higher classification errors for small glaciers (area < 1 km2) and numerous small debris patches (<5 pixels) [17,35], often leading to an overestimation of debris-covered glacier numbers. Furthermore, the limited availability of field-validation data hampers the evaluation and cross-comparison of different mapping techniques. Most existing glacier inventories were derived from datasets acquired prior to 2010, making them outdated and insufficient to capture the current extent of debris-covered glaciers.
Xinjiang, located along the northern margin of the HMA, is characterized by complex mountain systems, pronounced topographic relief, and extensive glacier development with widespread debris cover. However, compared with other regions of the HMA, studies focusing on debris-covered glaciers in Xinjiang remain relatively scarce. Recently, Li et al. [36] published the Chinese Glacier Inventory of Xinjiang 2020 (CGI-XJ2020), which employs high-resolution Chinese satellite imagery (2 m) combined with field validation data from 18 debris-covered glaciers. This dataset markedly enhances the accuracy of debris delineation and feature identification, effectively overcoming the limitations of previous inventories and studies. Building upon this high-resolution dataset, the present study systematically analyzes the spatial distribution of debris-covered glaciers and debris cover in Xinjiang and further investigates the topographic factors that control debris coverage.

2. Study Region

The Xinjiang Uygur Autonomous Region (XUAR) lies in the arid zone of northwestern China (73°40′E~96°23′E, 34°25′N~49°10′N; Figure 1). Dominated by westerly circulation and distant from oceanic influence, the region exhibits a typical continental climate [37]. Its mountain systems extend mainly east–west, forming a composite orogenic belt uplifted through multiple Cenozoic events [38]. From north to south, these include the Altay, Tianshan, Pamir, Karakoram, Kunlun, and Altun Mountains (Figure 1). Intense tectonic activity has sculpted the rugged mountains and intricate terrain of Xinjiang. Frequent faulting and rock fracturing supply abundant debris to glaciers, and together, these geological and geomorphological processes have facilitated the widespread development of supraglacial debris [22]. The Altay Mountains are a stable ancient fold system of sedimentary, metamorphic, and igneous rocks [39]. Rising 2000–4000 m, they host glaciers around Friendship Peak (4373 m), showing limited debris cover. The Tianshan Mountains, a major Central Asian fold-and-thrust belt, have undergone intense uplift from the collision of the Indian and Eurasian plates [40]. Large valley glaciers near Tomur (7439 m) and Khan Tengri (6995 m) peaks exhibit extensive debris cover [41]. Several major glaciers in this area, including Tomur, Tugebieliqi, Ukur, and Qiongtelian, exceed 100 km2 and have debris-covered tongues extending more than 10 km. In contrast, glaciers in eastern Tianshan—such as around Bogda Peak (5445 m)—are only partly mantled [42]. The Kunlun and Karakoram Mountains form the tectonic boundary between the Tarim Basin and the Tibetan Plateau, featuring dense fault zones and strong activity [43]. The Kunlun range stretches ~2500 km, with many peaks > 6000 m and debris concentrated in the middle and lower glacier tongues. The Karakoram, averaging ~6500 m, hosts giant glaciers around K2 (8611 m) with extensive debris. The Pamir Plateau in western Xinjiang, a junction of several orogenic systems, has active tectonics, rugged terrain, and complex lithology [44]. With elevations above 4000 m and a cold, humid climate, it supports vast glaciers with large debris-covered areas. The Altun Mountains, the eastern extension of the Kunlun, remain tectonically active under the Altun fault zone [43], featuring an arid climate, high peaks, and small glaciers with limited debris accumulation.

3. Data and Methodology

3.1. Data

This study employs the CGI-XJ2020 dataset, derived from the third glacier inventory of XAUR using high-resolution Chinese remote-sensing imagery (2 m) [36]. Glacier outlines in CGI-XJ2020 were delineated through a “manual visual interpretation and revision” approach [45,46]. GPS measurements from the termini of 38 glaciers were used to evaluate boundary accuracy. The dataset includes 37 attribute fields, such as glacier ID, name, area, elevation, and topographic parameters (e.g., slope and aspect). The detailed compilation procedures and full methodological workflow of CGI-XJ2020 can be found in Li et al. [36].
A total of 114 high-resolution satellite images were analyzed to extract debris-covered glacier outlines across XAUR. These include GF-1 (69 scenes), GF-6 (19), ZY-1 (4), and ZY-3 (22) images acquired between 2019 and 2021, all with cloud cover below 10%. To minimize seasonal biases and ensure consistency in debris-cover detection, all images were selected from the glacier ablation period (August–September). Among them, 76 scenes were from 2020 and there were 19 each from 2019 and 2021. Standard preprocessing steps were applied, including ortho-correction, radiometric calibration, atmospheric correction, and image fusion [47,48]. The fusion was performed using the nearest-neighbor diffusion-based pan-sharpening (NNDiffuse) method [49], resulting in synthesized images with a spatial resolution of 2 m. Debris-covered portions were delineated using the same visual interpretation and manual revision method, refined through field observations [36] and the distinct characteristics of debris surfaces—such as texture, color, supraglacial lakes, lateral moraines, ice cliffs and shadows, proglacial lakes, and outwash plains [50,51,52]. Expert glaciological judgment was further applied to refine ambiguous areas.
Additionally, Copernicus DEM (COP-DEM, 30 m) was used to derive elevation, slope, and debris-supply zones. Compared with other open-access DEMs, COP-DEM provides finer topographic detail, with an effective resolution superior to its nominal 30 m [53].

3.2. Methodology

3.2.1. Extraction and Spatial Distribution Analysis of Debris-Covered Glaciers

In this study, attributes from the CGI-XJ2020 inventory—including glacier area, count, volume, mountain range, basin code, and topographic parameters—were used to systematically analyze the spatial distribution of debris-covered glaciers in Xinjiang. Several of these attributes originate from earlier datasets: for example, the basin codes are derived from the Glacier Inventory of China [54], and the glacier volumes were obtained through volume–area scaling, as documented by Li et al. [36]. Notably, CGI-XJ2020 does not contain fields related to debris-covered portions. Therefore, based on this dataset, outlines of debris-covered areas were derived, and corresponding attribute fields were added. Using the spatial join tool in ArcGIS (version 10.8), attributes such as mountain range and basin code were spatially linked to each debris-covered polygon.
Topographic parameters of the debris-covered portions—including minimum, maximum, mean, and median elevation, as well as mean slope and aspect—were calculated using COP-DEM values clipped by each glacier mask. The resulting parameters were then appended to the attribute table. Mean slope was derived by averaging DEM-based slope raster values within the glacier mask. The mean aspect was computed using trigonometric conversion (sine–cosine transformation followed by arctangent calculation) from the aspect raster [45]. The resulting continuous aspect values were subsequently classified into directional ranges.
Additionally, the DEM was used to extract individual glacier catchments, defining the extent, elevation, and slope of each debris-supply zone. These zones were delineated using hydrological analysis tools in ArcGIS, excluding glacier-covered areas [22,55]. Elevation statistics for debris-supply zones were obtained through mask analysis. By integrating glacier and debris-supply zone parameters, we performed a multivariate correlation analysis to identify the key topographic controls on debris-cover extent.

3.2.2. Uncertainty Assessment

According to existing glacier inventories, boundary uncertainties can be categorized into three components: technical, interpretation, and methodological errors [56,57]. For CGI-XJ2020, Li et al. [36] reported that uncertainties are primarily attributed to methodological limitations in glacier delineation. Their assessment employed GPS-measured glacier termini and high-resolution satellite imagery, using the glacier-area buffer method [58,59,60] to estimate boundary errors. The overall glacier boundary uncertainty in Xinjiang was approximately 3%, based on field measurements collected between 2019 and 2024 with GPS, RTK-GPS, and UAV surveys. These included 496 positioning points from 38 glaciers, of which 18 were debris-covered.
In this study, glacier boundary uncertainties were assessed using the GPS-based glacier boundary validation method. Specifically, a total of 232 GPS points from 18 debris-covered glaciers (see Appendix Table A1) were used. For each point, the shortest distance to the mapped glacier outline was calculated using the Near Analysis tool in ArcGIS. Points were classified into bare-ice and debris-covered groups according to their spatial relationship with glacier outlines, and the mean distance of each group was taken as the boundary error. To minimize temporal discrepancies caused by glacier retreat, only GPS measurements near glacier margins were used. The GPS-based validation produced mapping errors of 2.8 m for bare-ice portions and 8.9 m for debris-covered portions.
Additionally, buffer analyses were conducted separately for both glacier types. During CGI-XJ2020 compilation, ten analysts independently digitized glacier outlines to evaluate inter-operator variability [61]. Comparison of the same 18 glaciers showed discrepancies of 0.5–1 pixel for bare-ice portions and 2–4 pixels for debris-covered portions, corresponding to spatial errors of 1 m and 4.5 m, respectively. Considering additional technical uncertainty from image resolution, one pixel (2 m) was adopted as the overall technical error. Combining all error components through the error propagation equation [62] (Equation (1)), the final glacier outline uncertainties were estimated as ±4 m for bare-ice and ±10 m for debris-covered portions (rounded to integers).
σ g = σ t 2 + σ m 2 + σ s 2
Here, σ g presents the glacier outline uncertainty, σ t denotes the image resolution error (2 m), σ m refers to the manual visual interpretation error, and σ s corresponds to the digitization error among compilers. Based on the calculated σ g values for bare-ice and debris-covered portions, the total area of the resulting buffer portions was used to estimate glacier area uncertainty. The area uncertainty for debris-covered glaciers in Xinjiang was calculated as 266.27 km2, accounting for 2.44% of the total debris-covered glacier area, while the uncertainty in debris-covered portions was 106.04 km2, representing 9.12% of the total debris-covered area.

4. Main Results

4.1. Overall Distribution of Debris-Covered Glaciers in Xinjiang

According to the CGI-XJ2020, a total of 24,202 glaciers were identified across Xinjiang in 2020, with a combined area of 23,629.28 km2. Among them, 1612 were classified as debris-covered glaciers (Figure 2), encompassing a total area of 10,922.06 km2 and an estimated ice volume of 984.77 km3. Debris cover accounted for 1163.32 km2, representing 10.65% of the total glacierized area. The mean glacier area was 6.77 km2, and the mean debris-covered area was approximately 0.72 km2.
Glacier statistics by area class (Figure 3a) show that debris-covered glaciers between 2 and 5 km2 are the most numerous (507 glaciers, 1643.89 km2 in total). However, debris cover is predominantly concentrated in large glaciers (>10 km2), of which 188 glaciers collectively cover 7065.89 km2—representing 63.5% of the total number and 71.5% of the total area of glaciers larger than 10 km2. The debris-covered area within these large glaciers reaches 690.32 km2, accounting for 59.3% of the total debris-covered area in Xinjiang. Based on elevation statistics at 100 m intervals (Figure 3b), glaciers occur between 2376 m and 8565 m, with the greatest concentration between 4000 m and 6000 m, which contains 78.9% of the total glacierized area. Debris-covered zones are mainly located below 5500 m, with 70% concentrated between 3500 m and 5000 m. This vertical pattern reflects the geomorphological characteristics of the surrounding mountain ranges. The mean slope of debris-covered glaciers ranges from 10.7° to 48.5°, with an average of 25.4° (Figure 3c), and the slope generally decreases with increasing glacier size. Aspect statistics (Figure 3d) indicate a predominant north-facing orientation: 854 glaciers (4820.39 km2) face north, accounting for 53% of the total number and 44.1% of the total area. Southeast-facing debris-covered glaciers are the least common, with only 50 glaciers totaling 408.84 km2.

4.2. Spatial Distribution of Debris Cover Across Mountain Ranges

Debris-covered glaciers in Xinjiang are mainly distributed across the Altay Mountains, Tianshan Mountains, eastern Pamir Plateau, Kunlun Mountains, Karakoram Mountains, and Altun Mountains (Figure 4). The characteristics of debris cover vary markedly among these mountain ranges. According to statistical results (Table 1), the Tianshan Mountains host the largest number of debris-covered glaciers (556) and the greatest total debris-covered area (489.63 km2), with a debris-cover ratio of 12.28%. The Kunlun Mountains rank second, containing 507 debris-covered glaciers with a debris-covered area of 245.87 km2 and a ratio of 8.25%. The eastern Pamir Plateau comprises 247 debris-covered glaciers with a total debris-covered area of 260.42 km2, exhibiting the highest ratio (18.86%). In the Karakoram Mountains, the debris-covered area reaches 159.18 km2, corresponding to a ratio of 6.41%. The Altay and Altun Mountains contain relatively few debris-covered glaciers—10 and 9, respectively—but their debris-covered areas are 2.96 km2 and 5.26 km2, with debris-cover ratios of 6.72% and 11.28%, respectively.
Glaciers larger than 100 km2 are mainly concentrated in the glacierized centers [54] of major mountain ranges (Figure 5a–d), exhibiting distinct regional characteristics. In the Tianshan Mountains, the Tomur–Khan Tengri peak region hosts 167 debris-covered glaciers, accounting for 65% of the range’s total debris-covered area. Farther east, around the Harkness Mountains and the Muzart Glacier, 102 debris-covered glaciers constitute another major cluster, representing 20% of the Tianshan region. Together, these two regions form the principal glacierized centers of the Tianshan Mountains. On the eastern Pamir Plateau, the Kongur Tagh and Muztagh Mountains contain 111 debris-covered glaciers, whose combined debris-covered area represents 63% of the regional total, indicating strong spatial concentration. In the Karakoram Mountains, K2 (Chogori Peak) is surrounded by 181 debris-covered glaciers that collectively contain 82% of the total debris-covered portions. In the western Kunlun Mountains, the Kunlun Peak region along the main ridge constitutes the largest glacierized center, with 40 large glaciers (>10 km2), including 8 classified as giant glaciers (>100 km2). However, debris cover is sparse, totaling only 4.30 km2 (<2%). Unlike other glacierized centers, the western Kunlun is characterized by extensive ice fields, gentle topography, limited exposed rock walls, and restricted sediment supply. Glaciers in this region exhibit relatively rapid ice flow, promoting sediment evacuation and resulting in minimal debris accumulation on glacier surfaces [22]. In contrast, centers with steeper and more rugged terrain provide abundant rockfall material, favoring more extensive and concentrated debris-cover development.
Figure 6 shows the relationship between glacier area and debris coverage for the entire Xinjiang region and its individual mountain ranges. Approximately 76.4% of debris-covered glaciers have debris coverage below 20%, and overall, debris coverage decreases with increasing glacier size. Among all mountain ranges, only the Pamir and Altun Mountains do not pass the significance test for the relationship between glacier area and debris coverage (Figure 6b), indicating a much larger variability in debris-cover distribution in these regions. In contrast, all other mountain ranges show significant correlations, consistent with overall trends for the Xinjiang region. Moreover, for glaciers larger than 10 km2, debris coverage in the Kunlun and Karakoram Mountains is notably lower than in the Tianshan Mountains and the Pamir Plateau.
Figure 7 illustrates the elevation distribution of debris-covered glaciers in Xinjiang and shows broadly consistent, yet regionally distinctive, patterns. Debris cover is generally concentrated at elevations below the median glacier elevation across all mountain ranges, although the characteristic elevation bands differ markedly among regions due to strong climatic and topographic contrasts. The median glacier elevation—commonly used as a proxy for the balanced-budget equilibrium-line altitude (ELA) [64,65,66]—closely corresponds to the transition from debris-free to debris-covered ice in most ranges. Mountain systems with lower median elevations, such as the Altay, display similarly low debris-cover elevations, whereas high-relief ranges, including the Kunlun, Karakoram, and Altun, exhibit debris cover at substantially higher elevations. Although debris cover is mainly confined below the inferred ELA, Figure 7 also shows that glaciers in the Tianshan, Pamir, and Kunlun Mountains host debris-covered ice extending into the lower accumulation zone. This upward extension is likely driven by the presence of steep cirque headwalls and valley-side rock walls, which supply abundant rockfall and weathered material directly onto glacier surfaces [22]. By contrast, the Altay Mountains show debris cover almost exclusively within ablation areas, consistent with their lower relief and limited debris supply.
Figure 8 shows that debris cover in Xinjiang is concentrated on relatively gentle glacier surfaces, primarily within a narrow band of low-to-moderate slopes. Across most mountain ranges, more than 70% of debris-covered ice occurs within the 0–15° slope interval, which corresponds to the gently inclined glacier tongues where ablation is most active. Consistently, debris-covered portions exhibit substantially lower slopes than bare-ice areas, with a mean difference of approximately 11.1°. This pattern indicates that debris cover develops mainly on low-angle ablation zones rather than on the steeper upper slopes associated with snow and ice avalanching. Mountain ranges with higher relief, such as the Tianshan, Pamir, and Karakoram, show a broader slope distribution of debris cover. This reflects strong topographic variability and abundant debris supply from steep headwalls. In addition, Pamir Plateau displays the strongest concentration of debris cover within a specific slope band, with 43.2% of its debris-covered area occurring on slopes between 5° and 10°, highlighting the combined influence of high relief and substantial debris input.
The upper-right panel of Figure 8 illustrates the normalized areal distribution of debris-covered glaciers by aspect across Xinjiang. Debris cover predominantly occurs on north-facing slopes. In the Altay, Kunlun, and Altun Mountains, debris cover is highly concentrated on north-facing aspects, with minor occurrences on northeast-, northwest- and southwest-facing slopes in the Kunlun and Altun Mountains. In the Karakoram Mountains, debris cover is mainly oriented toward the north and northeast, with only limited areas facing east or northwest. In contrast, the Tianshan Mountains and Pamir Plateau exhibit more dispersed aspect patterns. In the Tianshan mountains, debris cover occurs mainly on north-, northwest-, and east-facing slopes, with minimal presence on southwest-facing slopes. In the Pamir Plateau, north-facing slopes dominate overall, but the largest debris cover ratio (32.9%) is observed on east-facing slopes.
Overall, debris cover is mainly concentrated in low-elevation and gentle-slope regions, indicating that debris tends to accumulate and be preserved near glacier termini and in areas with smaller gradients during glacier flow [2,4]. In contrast, with increasing elevation and slope, stronger ice flow and higher transport capacity promote the removal or downslope sliding of surface debris, inhibiting the formation of continuous debris layers. Consequently, debris cover becomes less extensive at higher elevations and on steep slopes. The predominance of north-facing debris cover primarily reflects the general northward orientation of glaciers in Xinjiang (Figure 3d). Glaciers with other aspects are fewer in number, leading to a higher proportion of debris cover occurring on north-facing slopes.

4.3. Spatial Distribution of Debris Cover Among Drainage Basins

Debris-covered glaciers are unevenly distributed across the five drainage basins, and the Tarim Interior Basin (5Y6) shows the highest number and largest total debris-covered area (Table 2; Figure 9). The Tarim Interior Basin (5Y6) contains the largest number and total area of debris-covered glaciers, with 1313 glaciers covering 9756.51 km2. The total debris-covered area is 1083.47 km2, corresponding to a debris-cover ratio of 11.11% and a maximum of 74.08%. The Ili River Basin (5X0) ranks second, with 213 debris-covered glaciers totaling 57.42 km2 and a debris-cover ratio of 7.24%, ranging from 0.44% to 62.45%. The Turpan–Hami Interior Basin (5Y8) has only two debris-covered glaciers, totaling 0.74 km2, with a debris-cover ratio of 8.19%.
Based on the drainage code attributes in CGI-XJ2020, the Tarim Interior Basin (5Y6) is further subdivided into nine third-class sub-basins (Figure 9). Among these, the Kaxgar River Basin (5Y66) has the largest debris-covered area (251.93 km2) and the highest debris-cover ratio (19.20%). These glaciers are mainly distributed around the Kungay, Kongur Tagh, and Muztagh Mountains on the eastern Pamir Plateau, where glacier tongues are extensively mantled by debris. The Aksu River Basin (5Y67) ranks second, with a total debris-covered area of 230.10 km2, a debris-cover ratio of 13.97%, and a maximum of 71.87%. Debris cover in this basin is concentrated near the Tomur Peak region of the Tianshan Mountains, where numerous debris-covered glaciers occur. The Yarkant River Basin (5Y65) contains the most debris-covered glaciers (392), totaling 206.30 km2, with a debris-cover ratio of 7.04% and a maximum of 68.96%. Approximately 60% of these glaciers are clustered around K2 (Chogori Peak) in the Karakoram Mountains, where debris cover is particularly well developed. No debris cover is recorded in the Kaidu River Basin (5Y69).

5. Discussion

5.1. Analysis of Factors Influencing Glacier Debris Coverage

This study examined the relationships between debris coverage and debris-source regions using glacier topographic parameters (elevation and slope) and debris-supply zone characteristics, including steeper debris-supply zones (slope > 45°). Based on data from all debris-covered glaciers in Xinjiang, a correlation matrix was constructed (Figure 10). The results show that both glacier topography and debris-supply zone attributes are significantly correlated with debris coverage. Glacier area, mean elevation, maximum elevation, and mean slope exhibit negative correlations, whereas the areas of debris-supply zones and steeper debris-supply zones show positive correlations. Regions with higher mean or maximum elevations and larger glacier areas tend to have lower debris coverage. In contrast, glaciers with larger and steeper debris-supply zones, and greater elevation differences within them, tend to have higher debris coverage. Maximum glacier elevation is closely linked to debris-cover development: glaciers located around the highest peaks coincide with extensive steep-slope zones (>45°), which act as major debris-source regions. Higher peaks therefore support both larger steep-slope areas and stronger debris supply. At the same time, these peak-centered glaciers generally have much larger areas (Figure 5), which reduces the areal proportion of supraglacial debris—consistent with the observed negative correlation between glacier area and debris coverage (Figure 10). This pattern characterizes the main glacier accumulation centers in the Tianshan, Pamir, and Karakoram ranges (Figure 5a–c), where high relief promotes efficient debris delivery. Notably, the western Kunlun center (Figure 5d) forms a clear exception: although the peaks are extremely high, they are mantled by extensive icefields and perennial snow, leaving little exposed rock walls. The limited debris-supply terrain results in a very small debris-covered area despite the high maximum elevations.
The correlation analysis further indicates that steeper debris-supply zones have the strongest relationship with debris coverage (Figure 10), suggesting that topographic conditions within glacier catchments—particularly the presence of steep rock walls—are key controls on the formation and evolution of supraglacial debris. In glacier catchment basins, steep rock walls are prone to frost weathering, rockfall, and avalanching, continuously supplying debris to glacier surfaces [67,68]. These materials accumulate along the upper and lateral parts of glaciers and are gradually transported downglacier, forming thick debris mantles in the middle and lower reaches [69,70]. In areas with greater elevation differences across steep slopes, rock walls are more extensively exposed, enhancing sediment supply and leading to higher debris coverage. Variations in rock-wall aspect and geothermal conditions within debris-supply zones may further influence weathering rates [71,72,73], while the lithology and structural properties of surrounding rock walls determine debris size, joint density, and resistance to erosion, thereby affecting the rate of material delivery to glacier surfaces [74].

5.2. Comparison with Previous Studies

In this study, we compared the debris-covered areas obtained from different glacier inventories and related studies (Table 3). During the compilation of CGI-XJ2020, cross-border glacier boundaries were retained to preserve glacier integrity; therefore, the debris-covered area of the South Inylchek Glacier (61.22 km2) was excluded from comparison. Compared with CGI-2, which identified 1339 debris-covered glaciers with a total debris-covered area of 1042.86 km2, the CGI-XJ2020 result differs by 59.24 km2 (~5.68%). As both inventories employed the same debris-mapping method, this discrepancy is mainly attributed to improvements in image resolution [25,33,34]. Given that the two inventories were compiled roughly a decade apart, the difference is considered primarily methodological. Scherler et al. [17], using the RGI 6.0 dataset and automated extraction methods (band-ratio thresholds, normalized difference snow index, and linear spectral unmixing), reported a total debris-covered area of 1338.23 km2 in Xinjiang—about 17.64% higher than our result. This difference likely arises from unremoved debris in accumulation zones and uncertainties in detecting small glaciers. Their reported number of debris-covered glaciers was also much higher, largely due to numerous small (<5-pixel) debris patches (Figure 11b) included in automated results. Similarly, the GI_KP dataset by Mölg et al. [31], which also adopted automated extraction methods, reported a debris-covered area of 541.87 km2 in the Pamir and Karakoram regions of Xinjiang—22.5% greater than our result. This discrepancy mainly reflects temporal differences, as GI_KP represents glacier conditions around the year 2000. Although 2007–2009 imagery was used for validation, glacier boundaries were primarily based on data from 2000, likely leading to overestimation relative to CGI-XJ2020. The inclusion of numerous small (<5-pixel) debris patches in GI_KP also contributed to an inflated count of debris-covered glaciers.
To complement the regional comparison, we further examined the debris-cover distribution at the glacier scale. Specifically, the glacier tongues of two large representative glaciers—Qimugan Glacier and Kekesayi Glacier—were compared across different inventories (Figure 11). The comparison shows that automated datasets (e.g., Sch_FDC and GI_KP) often map numerous small (<5-pixel) debris patches and tend to overestimate debris-covered areas, particularly in spectrally complex tongue regions. In contrast, the manually derived CGI-XJ2020 and CGI-2 outlines present more spatially coherent and topographically constrained debris-cover patterns. For Qimugan Glacier (Figure 11a), the CGI-XJ2020 inventory adopts a more conservative delineation of debris cover at the glacier terminus. Our inspection of the imagery indicates that the elevated moraine southwest of the outlet contains visible vegetation, suggesting uncertainty regarding whether ice exists beneath the exposed moraine surface. This ambiguity may contribute to differences between inventories in this specific area.
Considering the temporal differences between CGI-XJ2020 and other glacier inventories, we further compared our results with several recent studies. For the glaciers across the eastern Pamir Plateau, Feroz et al. [76] used SDGSAT-1 imagery from 2022 and Sentinel-2 imagery from 2015, combined with a machine-learning approach, to delineate glacier boundaries in the Kongur Tagh region. Their estimated debris-covered area was 89.83 km2, only 8.01 km2 (≈9%) larger than the CGI-XJ2020 result. The discrepancy mainly stems from boundary delineation differences at the terminus of the Qimugan Glacier and in the accumulation zone of the Karayaylak Glacier, but overall, the two datasets are highly consistent. Lu et al. [77] applied Random Forest (RF) and Graph Neural Network (GNN) algorithms to Landsat-8 OLI imagery from 2017 to map glaciers in the Kongur region, obtaining a debris-covered area of 85.4 km2—only 4.2% smaller than our estimate. Similarly, Liu et al. [75] used the RF algorithm with 2024 Landsat imagery to extract debris-covered areas on the eastern Pamir Plateau, reporting 258.08 km2, differing by just 1% from our value in Table 1.
These comparisons demonstrate that the debris-covered area estimates derived in this study are highly consistent with recent research. The use of high-resolution GF and ZY satellite imagery, combined with field validation data [36] and careful manual corrections to remove misclassifications, substantially improved spatial accuracy. Consequently, our results reliably represent the spatial distribution of debris-covered glaciers in Xinjiang and are in strong agreement with other recent findings.

6. Conclusions

This study systematically analyzed the distribution characteristics of debris-covered glaciers in Xinjiang for 2020 using CGI-XJ2020 and its attribute dataset. Glacier basin boundaries were delineated from DEM data, and multivariate correlation analysis was conducted to examine the relationships between debris coverage and the topographic parameters of glaciers, debris-supply zones, and steeper debris-supply zones.
In 2020, Xinjiang contained 1612 debris-covered glaciers spanning 10,922.06 km2, including 1163.32 km2 of debris cover—accounting for 10.65% of the total glacierized area. These glaciers are mainly distributed across the Altay, Tianshan, Pamir, Kunlun, Karakoram, and Altun Mountains. The Tianshan Mountains host the largest number (556) and total area (489.63 km2) of debris-covered glaciers, while the eastern Pamir Plateau shows the highest mean debris coverage (18.86%). Most debris cover is concentrated within the glacierized centers of the Tianshan, Pamir, and Karakoram ranges, accounting for over 60% of the total. Debris cover is concentrated below the median elevation of debris-covered glaciers in each mountain range and is predominantly distributed on gentle slopes (0–15°). It is predominantly north-facing, though the Pamir Plateau exhibits the highest coverage (32.9%) on east-facing slopes. Across drainage basins, debris-covered glaciers are concentrated in the Tarim Interior Basin (1083.47 km2), with the Kaxgar River sub-basin having the largest debris-covered area (251.93 km2) and the Yarkant sub-basin the highest glacier count. Correlation analysis indicates that glacier topography and debris-supply zone terrain strongly influence debris distribution, with steep debris-supply zones (slope > 45°) being the dominant control. This high-resolution inventory enhances understanding of debris–glacier interactions and supports improved modeling of glacier melt, water resources, and regional climate impacts.

Author Contributions

Conceptualization, Z.Z. and Z.L.; methodology, Z.Z.; software, Z.Z.; validation, J.M., Q.L., Q.W., W.C., Y.Y. and W.Z.; formal analysis, Z.Z. and J.M.; investigation, Q.L., Q.W. and W.C.; resources, Z.L.; data curation, Z.Z., J.M., Q.L., Q.W., W.C., Y.Y. and W.Z.; writing—original draft preparation, Z.Z.; writing—review and editing, Z.L., J.M. and F.W.; visualization, Z.Z.; supervision, Z.L. and F.W.; project administration, Z.L. and F.W.; funding acquisition, Z.L. and F.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Third Xinjiang Scientific Expedition Program (Grant No. 2022xjkk0101; Grant No. 2022xjkk0802), the Second Qinghai–Tibet Scientific Expedition Program (Grant No. 2019 QZKK0201), the National Natural Science Foundation of China (Grant No. 42301166), the National Science Foundation of Gansu Province (Grant No. 23JRRA658) and China Railway Group Limited Science and Technology Research and Development Plan (Academy of Scientific Research 2023-Major-01).

Data Availability Statement

The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author. COP-DEM data in this research are available for free through the following website: https://dataspace.copernicus.eu (accessed on 11 April 2023).

Acknowledgments

We would like to express our sincere gratitude to the field observation team of the Tianshan Glaciological Station, including Lin Maowei, Wang Fanglong, Chen Jian’an, and Ma Yinghui, for their dedicated efforts in glacier field measurements and data collection. We also thank the contributors to the CGI-XJ2020 glacier inventory, namely, Xi Juanwei, Ma Hao, Xu Mengwei, and Jin Xiang, for their valuable work and data support.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

Glacier_Mean_Elevmean glacier elevation (m)
Glacier_Min_Elevminimum glacier elevation (m)
Glacier_Max_Elevmaximum glacier elevation (m)
Glacier_Mean_Slpmean glacier slope (°)
DS_Areaarea of debris-supply zone (km2)
DS_Mean_Elevmean elevation of debris-supply zone (m)
DS_Elev_Rangeelevation range of debris-supply zone (m)
UAVunmanned aerial vehicle
DS_Mean_Slpmean slope of debris-supply zone (°)
Stp_Areaarea of steeper debris-supply zone (km2)
Stp_Relrelative proportion of the steeper debris-supply zone (areas with slope > 45°) (%)
Stp_Min_Elevminimum elevation of the steeper debris-supply zone (m)
Stp_Max_Elevmaximum elevation of the steeper debris-supply zone (m)
Stp_Elev_Rangeelevation range of the steeper debris-supply zone (m)

Appendix A

Field observations were obtained by the team of the Tianshan Glaciological Station from 18 debris-covered glaciers across Xinjiang, focusing on GPS measurement points within the ablation zones. The dataset spans the period from 2019 to 2024 and was acquired using advanced techniques, including unmanned aerial vehicles (UAVs) and RTK-GPS surveys. All field measurements were supported by extensive ground-truth data collected during the Third Xinjiang Scientific Expedition and the Second Tibetan Plateau Scientific Expedition. Due to temporal discrepancies between GPS acquisition and glacier digitization, this difference was not considered in the uncertainty assessment.
Table A1. Measured debris-covered glacier information in the Xinjiang region.
Table A1. Measured debris-covered glacier information in the Xinjiang region.
No.Glacier NameGLIMS_ID *MountainAreaNo. of GPS PointsDebris Cover (m)Bare Ice (m)
(km2)MeanStd.MeanStd.
1Kanas GlacierG087802E49107NAltay24.31109.20 1.51 ——
2Heigou Glacier No. 8G088356E43783NTianshan6.8215——2.85 0.78
3Urumqi Glacier No. 2G086823E43100NTianshan0.69225.46 1.79 ——
4Lujiaowan GlacierG085162E43876NTianshan1.16167.80 1.47 ——
5Alchalter GlacierG080950E42402NTianshan43.47912.30 2.03 3.21 0.53
6Muzart GlacierG080921E42304NTianshan163.181210.80 2.57 ——
7Keqikekuzibayi GlacierG080548E41955NTianshan27.951410.25 2.00 ——
8Koxkar Baxi GlacierG080106E41803NTianshan85.95118.60 1.28 ——
9Qiongkuermu GlacierG079957E41784NTianshan8.3310——2.30 0.81
10Qingbingtan Glacier No. 74G079920E41785NTianshan8.34128.40 1.19 ——
11Qingbingtan Glacier No. 72G079894E41780NTianshan6.55179.50 1.53 ——
12East branch of Kumalak River Glacier No. 79G079944E41725NTianshan0.58147.20 1.23 ——
13West branch of Kumalak River Glacier No. 79G079936E41723NTianshan0.76117.80 1.68 ——
14Kumalak River Glacier No. 80G079926E41723NTianshan0.59118.94 1.80 ——
15Tomor GlacierG079999E41932NTianshan330.641210.69 2.80 ——
16Oitabe GlacierG075148E38872NPamir19.48128.70 1.94 ——
17Karayaylak GlacierG075252E38643NPamir103.89109.74 2.10 ——
18Karachon GlacierG075081E38251NPamir18.71149.40 1.50 ——
GLIMS_ID * is the GLIMS code generated from coordinates of a glacier’s center.

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Figure 1. Overview of the study region.
Figure 1. Overview of the study region.
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Figure 2. Spatial distribution of debris-covered glaciers in Xinjiang.
Figure 2. Spatial distribution of debris-covered glaciers in Xinjiang.
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Figure 3. Distribution of debris-covered glaciers in Xinjiang by glacier area class (a), elevation (b), mean slope (c), and aspect (d). In panel (b), the upper and lower black dashed lines represent the maximum and minimum elevations of debris-covered glaciers, while the blue dashed line indicates the median elevation. In panel (c), the blue dashed line indicates the mean slope of all debris-covered glaciers, while the red dashed line represents the linear regression trend (r = 0.39, p < 0.05).
Figure 3. Distribution of debris-covered glaciers in Xinjiang by glacier area class (a), elevation (b), mean slope (c), and aspect (d). In panel (b), the upper and lower black dashed lines represent the maximum and minimum elevations of debris-covered glaciers, while the blue dashed line indicates the median elevation. In panel (c), the blue dashed line indicates the mean slope of all debris-covered glaciers, while the red dashed line represents the linear regression trend (r = 0.39, p < 0.05).
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Figure 4. Distribution of debris-covered glaciers across major mountain ranges in Xinjiang. Mountain range divisions follow the Level 2 regions of RGI 7.0 [63].
Figure 4. Distribution of debris-covered glaciers across major mountain ranges in Xinjiang. Mountain range divisions follow the Level 2 regions of RGI 7.0 [63].
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Figure 5. Distribution of debris cover in the glacierized centers of the Tianshan Mountains (a), the Pamir Plateau (b), the Karakoram Mountains (c), and the Kunlun Mountains (d) in Xinjiang.
Figure 5. Distribution of debris cover in the glacierized centers of the Tianshan Mountains (a), the Pamir Plateau (b), the Karakoram Mountains (c), and the Kunlun Mountains (d) in Xinjiang.
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Figure 6. Scatter plots showing the relationship between debris cover (%) and glacier area for (a) the entire Xinjiang region and (b) individual mountain ranges.
Figure 6. Scatter plots showing the relationship between debris cover (%) and glacier area for (a) the entire Xinjiang region and (b) individual mountain ranges.
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Figure 7. Elevation range distribution of glaciers in different mountain ranges of Xinjiang at 100 m intervals. The red and blue dashed lines indicate the median elevations of debris-covered and bare-ice portions, respectively, while the black dashed line represents the median glacier elevation.
Figure 7. Elevation range distribution of glaciers in different mountain ranges of Xinjiang at 100 m intervals. The red and blue dashed lines indicate the median elevations of debris-covered and bare-ice portions, respectively, while the black dashed line represents the median glacier elevation.
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Figure 8. Distribution of debris-covered glacier area in six mountain ranges of Xinjiang by slope (5° intervals) and aspect (area-normalized). In the polar plots, black, red, and blue lines represent the mean slopes of the entire glacier, the debris-covered portion, and the bare-ice portion, respectively.
Figure 8. Distribution of debris-covered glacier area in six mountain ranges of Xinjiang by slope (5° intervals) and aspect (area-normalized). In the polar plots, black, red, and blue lines represent the mean slopes of the entire glacier, the debris-covered portion, and the bare-ice portion, respectively.
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Figure 9. Distribution of debris-covered glaciers in different drainage basins of Xinjiang. The Tarim interior basin is divided into nine sub-basins (drainage codes 5Y61–5Y69).
Figure 9. Distribution of debris-covered glaciers in different drainage basins of Xinjiang. The Tarim interior basin is divided into nine sub-basins (drainage codes 5Y61–5Y69).
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Figure 10. Correlations between glacier and debris-supply zone parameters and debris coverage. Colors represent Pearson correlation coefficients ranging from –1 (red) to 1 (blue), with circle size indicating the strength of correlation. Asterisks (*) denote statistically significant correlations. The parameters included in the analysis comprise debris coverage; glacier parameters (area, mean elevation, minimum elevation, maximum elevation, and mean slope); debris-supply (DS) zone parameters (DS area, DS mean elevation, DS elevation range, and DS mean slope); and steeper debris-supply zone parameters (areas with slope > 45°, including their area, elevation range, and relative proportion).
Figure 10. Correlations between glacier and debris-supply zone parameters and debris coverage. Colors represent Pearson correlation coefficients ranging from –1 (red) to 1 (blue), with circle size indicating the strength of correlation. Asterisks (*) denote statistically significant correlations. The parameters included in the analysis comprise debris coverage; glacier parameters (area, mean elevation, minimum elevation, maximum elevation, and mean slope); debris-supply (DS) zone parameters (DS area, DS mean elevation, DS elevation range, and DS mean slope); and steeper debris-supply zone parameters (areas with slope > 45°, including their area, elevation range, and relative proportion).
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Figure 11. Comparison of debris-covered glacier delineations from different glacier inventories for Qimgan Glacier (a) across Kongur Tagh and Koksay Glacier (b) across the Muztagh Mountains. The datasets include CGI-XJ2020 (red), CGI-2 (purple), GI-KP (blue), and Sch_FDC (yellow, Scherler et al. [17] derived from RGI 6.0 using linear spectral unmixing-based fractional debris cover).
Figure 11. Comparison of debris-covered glacier delineations from different glacier inventories for Qimgan Glacier (a) across Kongur Tagh and Koksay Glacier (b) across the Muztagh Mountains. The datasets include CGI-XJ2020 (red), CGI-2 (purple), GI-KP (blue), and Sch_FDC (yellow, Scherler et al. [17] derived from RGI 6.0 using linear spectral unmixing-based fractional debris cover).
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Table 1. Distribution of debris-covered glaciers across mountain ranges in Xinjiang.
Table 1. Distribution of debris-covered glaciers across mountain ranges in Xinjiang.
Mountain RangeCountArea (km2)Uncertainty (km2)Average Size (km2)Volume (km3)Debris Cover (km2)Uncertainty (km2)Debris Cover Area Ratio (%)Min_DC * (%)Max_DC (%)Mean_DC (%)
Altay1044.061.434.412.942.960.596.721.3351.2017.03
Tianshan5563987.3190.547.17410.00489.6337.9312.280.1371.8712.35
Pamir2471381.1343.905.5996.12260.4221.1918.860.9058.2918.00
Kunlun5072981.2674.515.88229.00245.8727.558.250.1674.0814.50
Karakoram2832481.6654.108.77244.08159.1817.976.410.1466.8610.37
Altun946.641.795.182.645.260.8111.284.1217.6111.74
Total161210,922.06266.276.78984.771163.32106.0410.650.1374.0813.57
* Min_DC, Max_DC, and Mean_DC denote the minimum, maximum, and mean debris coverage, respectively, where debris coverage is defined as the proportion of debris-covered area relative to the total glacier area for each individual debris-covered glacier.
Table 2. Distribution of debris-covered glaciers in the second-class drainage basins of Xinjiang.
Table 2. Distribution of debris-covered glaciers in the second-class drainage basins of Xinjiang.
Drainage BasinDrainage Code *CountArea (km2)Uncertainty (km2)Volume (km3)Debris Cover (km2)Uncertainty (km2)Debris Cover Area Ratio (%)Min_DC (%)Max_DC (%)Mean_DC (%)
Ertix river5A21044.061.432.942.960.596.721.3351.2017.03
Ili river5X0213793.0322.4850.8757.428.687.240.4462.459.8
Tarim5Y613139756.51231.91910.511083.4793.0211.110.1374.0814.26
Junggar5Y774319.4510.0019.9718.733.585.860.4855.6811.52
Turpan-Hami5Y829.020.440.480.740.188.195.9915.0110.5
Total161210,922.06266.27984.771163.32106.0410.650.1374.0813.57
* The drainage codes are derived from the glacier attribute fields of the CGI-XJ2020 inventory, and their source can be referenced in Li et al. [36].
Table 3. Comparison with other glacier inventories and previous studies.
Table 3. Comparison with other glacier inventories and previous studies.
RegionGlacier
Inventory		Data SourcePeriodResolutionResearch
Methods		Debris-Covered Glacier CountsDebris Cover (km2)Source
XinjiangCGI-XJ2020GF/ZY scenes20202 mManual + revise16111102.097This study
XinjiangCGI-2Landsat TM/ETM + scenes2004~201030 mManual + revise13391042.86[30]
XinjiangRGI 6.0Landsat-8 OLI scenes2004~201030 mAutomatic methods10,5321338.23[17]
Karakoram + PamirCGI-XJ2020GF/ZY scenes20202 mManual + revise530419.6This study
Karakoram + PamirGI_KPLandsat TM/ETM+, ALOS-1 and PALSAR-1 scenes1998~202230/10 mAutomatic methods4426541.87[31]
Pamir—Landsa-8 OLI scenes202430 mAutomatic methods—258.08[75]
Kongur TaghCGI-XJ2020GF/ZY scenes20202 mManual + revise3181.82This study
Kongur Tagh—SDGSAT-1 scenes202230/10 mAutomatic methods—89.83[76]
Kongur Tagh—Landsa-8 OLI scenes201730 mAutomatic methods—85.4[77]
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MDPI and ACS Style

Zhan, Z.; Li, Z.; Mu, J.; Wang, F.; Liang, Q.; Wang, Q.; Chen, W.; Yang, Y.; Zhao, W. Spatial Distribution and Characteristics of Debris-Covered Glaciers in Xinjiang Based on CGI-XJ2020. Remote Sens. 2026, 18, 106. https://doi.org/10.3390/rs18010106

AMA Style

Zhan Z, Li Z, Mu J, Wang F, Liang Q, Wang Q, Chen W, Yang Y, Zhao W. Spatial Distribution and Characteristics of Debris-Covered Glaciers in Xinjiang Based on CGI-XJ2020. Remote Sensing. 2026; 18(1):106. https://doi.org/10.3390/rs18010106

Chicago/Turabian Style

Zhan, Zexin, Zhongqin Li, Jianxin Mu, Feiteng Wang, Qibin Liang, Qian Wang, Wei Chen, Yefei Yang, and Weibo Zhao. 2026. "Spatial Distribution and Characteristics of Debris-Covered Glaciers in Xinjiang Based on CGI-XJ2020" Remote Sensing 18, no. 1: 106. https://doi.org/10.3390/rs18010106

APA Style

Zhan, Z., Li, Z., Mu, J., Wang, F., Liang, Q., Wang, Q., Chen, W., Yang, Y., & Zhao, W. (2026). Spatial Distribution and Characteristics of Debris-Covered Glaciers in Xinjiang Based on CGI-XJ2020. Remote Sensing, 18(1), 106. https://doi.org/10.3390/rs18010106

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