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Article

Slight Mass Loss in Glaciers over the Ulugh Muztagh Mountains during the Period from 2000 to 2020

by
Lailei Gu
1,
Yanjun Che
2,3,6,*,
Mingjun Zhang
1,3,
Lihua Chen
4,
Yushan Zhou
5 and
Xinggang Ma
6
1
College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
2
Department of Geographical Science, Yichun University, Yichun 336000, China
3
Key Laboratory of Resource Environment and Sustainable Development of Oasis, Lanzhou 730070, China
4
Department of Physical Geography and Resources and Environment, School of Geography and Environment, Jiangxi Normal University, Nanchang 330000, China
5
National Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
6
State Key Laboratory of Cryospheric Science/National Field Science Observation and Research Station of Yulong Snow Mountain Cryosphere and Sustainable Development (or Yulong Snow Mountain Station), Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730070, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2023, 15(9), 2338; https://doi.org/10.3390/rs15092338
Submission received: 3 March 2023 / Revised: 14 April 2023 / Accepted: 26 April 2023 / Published: 28 April 2023
(This article belongs to the Special Issue Unraveling the Hydrology of Himalayan Catchment Based on Remote Sensing Technology)
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Abstract

:
Knowledge about changes in the glacier mass balance and climate fluctuation in the East Kunlun Mountains is still incomplete and heterogeneous. To understand the changes in the glacier mass in the Ulugh Muztagh Mountains in the East Kunlun Mountains due to global warming, a time series of satellite stereo-images from the Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were derived from 2000 to 2020. Digital elevation models (DEMs) of the glaciers were generated and used to assess the changes in these glacier masses from 2000 to 2020. The results show that the surface elevation of glaciers in the Ulugh Muztagh region changed by −0.17 ± 10.74 m from 2000 to 2020, corresponding to a mass change of −0.14 ± 9.13 m w.e. The glacier mass balance increased by 0.64 ± 9.22 m w.e. in 2000–2011 and then decreased by 0.78 ± 9.04 m w.e. in 2011–2020. The annual mass balance of the glaciers was −0.0072 ± 0.46 m w.e./yr from 2000 to 2020, showing glacial stability. The equilibrium line altitude (ELA) of the glacier was 5514 m a.s.l. from 2000 to 2020. In addition, we also found that the glacier mass losses in the west and north slopes were more significant than those in the east and south slopes. There was a phenomenon of glacier surges in the Yulinchuan glacier from 2007 to 2011. Overall, the glaciers were relatively stable with respect to the total glacier thickness in the Ulugh Muztagh Mountains.

1. Introduction

Glaciers are important reserves of freshwater resources on the Earth, accounting for 75% of global freshwater resources. Over recent decades, global glaciers have significantly shrunk due to increasing air temperatures [1]. Additionally, glacier meltwater is an important contributor to sea level rise [2,3], which has had serious impacts in various parts of the world. Furthermore, geological hazards caused by glacier changes have frequently arisen in recent years, threatening the people’s lives and property [4,5,6]. Most importantly, glaciers are vital to rivers in regions with large population densities [7]. Hence, investigating glacier changes is significant. Previous studies have evaluated global glacier changes in terms of their thickness distribution and mass balance, but their thickness is still uncertain in some regions due to a lack of in situ measurements [3,8,9,10].
The overall trend of mass loss in the High-Mountain Asia (HMA) glaciers has been accelerated in recent decades, but the trends are different for different mountains [9]. For example, Gardner et al. [11] indicated a total HMA mass budget of −29 ± 13 Gt/yr from 2003 to 2009 in the East Kunlun Mountains based on the Ice, Cloud, and land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) dataset. Additionally, the interannual variation of glacier elevation had great spatial heterogeneity. Glacier elevation decreases mainly occurred on the edge of the HMA [12]. The southeast Qinghai Tibetan plateau glaciers show the most significant retreat [13,14]. However, an increasing trend of glacier mass can be found in some regions. For instance, Gardelle et al. [15] presented geodetic results from central Karakoram, and their results showed an increasing trend of regional mass balance of 0.11 ± 0.22 m w.e./yr from 1999 to 2008. The abnormal mass balance changes in the Karakoram and West Kunlun Mountains have attracted scholars’ attention, but the East Kunlun Mountains have been less studied. The Ulugh Muztagh Mountains are a glacier accumulation area in the East Kunlun Mountains, located in the Altun Mountains National Nature Reserve, China [16]. The glacier meltwater plays an important role in the lake recharge in the nature reserve, and thus the glaciers are of significance for the ecological and environmental protection of the arid Altun Mountain National Nature Reserve. Based on the scientific investigation of Xinjiang in the 1980s, Chen, Wang, and Wang [16] came to a preliminary understanding of the role, distribution, quantity, and type of Ulugh Muztagh Mountain glaciers. Guo et al. [17] carried out remote sensing monitoring of the glacier surge phenomenon of the Yulinchuan Glacier from 2008 to 2009. Jiang et al. [18] analyzed the changes in glacier area and mass balance in the Ulugh Muztagh Mountains from 1972 to 2011. Liang et al. [19] analyzed the mass balance change over the entire Kunlun Mountains glacier from 2000 to 2013 and its response to climate change.
Numerous remote sensing images and process methods have been used to assess the changes in glacier thickness or surface elevation [20,21,22]. ICESat data are available from 2003 to 2009 and from 2018 to the present. The period is relatively short, and the data are sparse at medium and low latitudes [23]. Therefore, there are not enough data to support glacier research over more than ten years in some regions, given that the Ulugh Muztagh Mountains have been subjected to few ground observations over the last three decades. Satellite pour l’Observation de la Terre (SPOT 5) can generate digital elevation models (DEMs), but few data can be freely obtained. The Shuttle Radar Topography Mission (SRTM) is widely used to assess the glacier surface elevation. However, the monitoring of snow and ice is inaccurate by the radar sensors. One of the reasons for this is that the penetration rate of snow and ice can reach several meters [24]. The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scientific team published the ASTER Global Digital Elevation Model (GDEM) Version 3 in August 2019, meaning that it is now possible for ASTER to generate DEMs to observe the ground. Wang and Kaab [25] evaluated the Fox Glacier and Franz Josef Glacier in New Zealand from 2000 to 2014 using ASTER DEMs and SRTM glacier elevation. Brun et al. [26] also used DEMs derived from ASTER images to assess the mass balance in HMA glaciers from 2000 to 2016. Additionally, they concluded that the average change in the glacier mass balance of the region was −0.18 ± 0.04 m w.e./yr. Moreover, Berthier et al. [27] verified the reliability of the multi-temporal ASTER DEM in the Mont-Blanc area, which provided convincing data resources to explore surface elevation changes. Liang, Wang, Yang, Chen, Hua, Li, and Yang [19] used SRTM and TanDEM-X DEMs to study the mass balance of the Kunlun Mountains from 2000 to 2013 and found that the spatial heterogeneity of the East Kunlun Mountains and West Kunlun Mountains was obvious. Although the Ulugh Muztagh Mountains have been studied, different data sources have been used. Many studies have concluded that the glacier changes were due to the “Karakoram Glacier Anomaly” [15,19,28,29,30]. Although the changes in the glacier surface elevation and mass balance are slight, the glacier’s response to climate change is still not clear in the East Kunlun Mountains.
To understand the changes in the glaciers in the Ulugh Muztagh Mountains of the East Kunlun Mountains in this paper, we calculated the mass balance of glaciers in the Ulugh Muztagh Mountains and its surrounding regions during the period from 2000 to 2020. Our aims were to (I) assess the elevation changes of the glaciers in the study region from 2000 to 2020, (II) calculate the mass balance of the glaciers and understand their spatiotemporal changes during the study period, and (III) discuss the impact of climate change on the mass balance of local glaciers in the past two decades.

2. Study Area

The Ulugh Muztagh Mountains (87.3°E and 36.4°N) are the largest modern glacierized region in the East Kunlun Mountains on the northern edge of the Qinghai–Tibet Plateau (Figure 1a). The Ulugh Muztagh Mountains are perennially affected by continental air masses, leading to a larger difference in the interannual/daily temperature [31]. The westerly jet begins to move northward in March, marking the start of the precipitation season in the Ulugh Muztagh region [32]. Based on the records from the Second Chinese Glacier Inventory (CGI-2), the Ulugh Muztagh Mountains glaciers consist of 214 large and small glaciers [33]. The Ulugh Muztagh Mountains glaciers area covers more than 660 km2 [32,33]. The environment of the Ulugh Muztagh is extremely complex, and the highest elevation is about 6973 m a.s.l. Few people have reached the Ulugh Muztagh Mountains due to the harsh natural environment, high elevation, and dangerous wild animals. Therefore, it is difficult to comprehensively observe the Ulugh Muztagh Mountains glaciers using unmanned aerial vehicles or other measurement methods.

3. Materials and Methods

3.1. Data

3.1.1. ASTER Images

ASTER is a high-resolution satellite imaging device released by the National Aeronautics and Space Administration (NASA) in cooperation with the Ministry of Economy Trade and Industry (METI) of Japan. It was launched on the Terra platform of NASA in December 1999. ASTER provides temperature, radiation, and elevation data in the biosphere, hydrosphere, lithosphere, and atmosphere for researchers. Moreover, it provides the basic data used to analyze land use, natural disasters, and hydrological processes. ASTER provides multispectral remote sensing images with vertical and posterior stereo pairs and mainly monitors wave band information in the visible and near infrared radiometer (VNIR), short wave infrared radiometer (SWIR), and thermal infrared radiometer (TIR) regions [34]. ASTER’s third band has two channels, 3N and 3B, where 3B can be rear-viewed at an angle. DEMs can be generated by 3N and 3B vertical and posterior stereo pairs from ASTER [35]. We selected stereo pairs of the ASTER images without clouds in the Ulugh Muztagh Mountains from 2000 to 2020 (Table 1) to accurately obtain the glacier surface elevation. The ASTER Images can be freely downloaded from the NASA Earthdata Search website (https://search.earthdata.nasa.gov (accessed on 1 January 2022)).

3.1.2. ICESat

The ICESat-1 mission measured the height changes of Greenland and Antarctic ice sheets. GLAS on ICESat-1 has a 1064 nm laser channel for surface altimetry and dense cloud height and a 532 nm lidar channel for the vertical distribution of clouds and aerosols. The accuracy of the surface elevation measurement is 15 cm, the laser footprint diameter is more than 60 m, and the orbital interval is 172 m [36]. ICESat-1 has difficulties capturing the subtle changes inside the ice sheet due to the uncertainty of the measurements. In 2018, NASA launched ICESat-2, which is equipped with the Advanced Topographic Laser Altimeter System (ATLAS) to overcome the problems faced by ICESat-1 [37]. It emits a single laser beam with a wavelength of 532 nm at a high repetition rate of 10 kHz to achieve continuous observation of the ground [38]. Beam spacing along the track is 10 m, and the elevation accuracy is 0.03 m [37,39]. By extracting the elevation at the intersection of the two sets of tracks and eliminating the influence of local terrain between them, a total of 8 sets of data were used as validation sites, which are shown in Figure 1c and Table 2 [37,40]. The ice-free ICESat-1 laser spots in Figure 1d were aimed to calibrate ASTER DEM, and the ICESat-2 laser spots in Figure 1d were designed to verify ASTER DEM (Table 3) [26]. The ICESat-1/2 data can be freely downloaded from the OpenAltimetry website (https://openaltimetry.org (accessed on 1 January 2022)).

3.1.3. Meteorological Dataset

The European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5-Land (ERA5-Land) product is the fifth-generation atmospheric reanalysis data of ECMWF on global climate, covering the entire Earth with a resolution of 0.1° × 0.1° [41]. The ERA5-Land product combines model data with observations from around the world to form a complete and consistent global dataset. The reanalysis product covers various land surface variables, such as air temperature, snow, radiation, heat, evaporation, and precipitation. Previous studies have found that the ERA5-Land dataset can describe climate change well [41]. For example, Zhao and He [42] verified that ERA5-Land described the air temperature trend well based on 17 meteorological stations and ERA5-Land in the Qilian Mountains. Hence, the 2 m air temperature, snowfall, and total precipitation datasets of the Ulugh Muztagh Mountains from ERA5-Land were used to understand climate changes during the period from 2000 to 2020.

3.1.4. Other Data

CGI-2 was used to identify the glacier boundary in the Ulugh Muztagh Mountains [43,44]. SPOT 5 satellite, launched in early May 2002, is an earth observation satellite developed by the Centre National D’Etudes Spatiales (CNES). The SPOT 5 satellite has a significantly higher sensor resolution than other launched satellites, with a 2.5 m panchromatic band and 10 m multispectral band. The DEM can be generated from images obtained by both High-Resolution Stereoscopic (HRS)1 and HRS2 sensors [45,46]. Therefore, we used SPOT 5 DEMs from 2004 and 2008 to validate ASTER results (Table 4) [26,27]. The SPOT 5 Images can be freely downloaded from the CNES website (https://regards.cnes.fr/user/swh/modules/60 (accessed on 1 January 2022)).

3.2. Methods

3.2.1. Principle of DEM Extraction from ASTER Stereopairs

The principle of stereo image pairing is that a specific sensor can concurrently collect data from the same area and then form a stereo image through processing. As is shown in Figure 2 [47], S1 and S2 are two optical sensors, similar to two human eyes. Two ground points (A and B) form a1 and b1, as well as a2 and b2, after being recorded by S1 and S2, respectively. S1 and S2 are distributed at both ends of a line segment, and both of them shoot the area of A to B. When shooting, the connection between S1 and S2 is roughly parallel to the connection between A and B, and two images are formed. Then, the stereo pair can be formed through processing.
ASTER’s third band has two channels, 3N and 3B, of which 3B can be rear-viewed at an angle. S1 and S2 form 3N and 3B (Figure 3), respectively. Two imagers 3N and 3B can perform near-synchronous imaging with a difference of 55 s in the same area with reasonable parallax and heading overlap when the satellite scans along the flight orbit. The resulting image size is 60 km × 60 km obtained by ASTER same-track stereo observation. Note that the accuracy of extracting DEM from remote sensing data is closely related to the base-to-height (BH) ratio, spatial resolution, and influence matching error. The BH of VNIR is 0.6, and the nadir angle is 27.6° [48]. The principle of extracting DEM from the stereo image pair is that S1 and S2 form the angle of S1AS2 when shooting the same point A on the ground, and then the elevation of ground point A can be calculated. DEM will be generated if the elevation of all points on the ground is obtained. The advantage of this method is that DEM entirely depends on satellite optical data. Therefore, it is not affected by signal penetration like the SRTM.

3.2.2. Data Processing Flow

As is shown in Figure 3, the extracted glacier surface elevation mainly included four main steps: (1) generation of DEMs; (2) pretreatment of ASTER DEMs; (3) spatial registration of ASTER DEMs; and (4) calculation of glacier surface elevation variation. In this paper, ASTER images with cloud cover of less than 10% in the Ulugh Muztagh Mountains from 2000 to 2020 were used.
  • Generation of ASTER DEMs;
To accurately extract DEMs from ASTER-L1A images, we used ENVI software to manually process the data instead of using automated methods [26,49,50]. Because the automatic method could not add ground control points (GCPs), complex terrain conditions may cause DEMs to not actually meet the ground [51], so we used the manual method to generate DEMs and added GCPs to make the DEMs more accurate. Although this was inefficient in small areas, the method was advisable. Firstly, the satellite altitude was calculated by the GCPs and the elevation values of the corresponding pixels on the images. We selected the tie points (TPs) of the same name in the two stereo pair images. The images were registered by the TPs of the stereo pairs to calculate the elevation of each pixel. Additionally, a total of 45 GCPs and 144 TPs were then used to generate the ASTER DEMs [52]. It is necessary to provide accurate reference DEMs for GCPs to generate high-quality ASTER DEM and obtain high-precision glacier elevation. In addition, the optical remote sensing image is vulnerable to cloud and parallax when matching in the process of DEM generation [25]. Therefore, we added GCPs to generate DEMs, and the influence of the cloud was removed by eliminating outliers [48,53].
2.
Preprocessing of ASTER DEM;
DEMs of the same year were merged to make one DEM to cover the whole glacier. The precision of DEMs is relatively low on steep terrain derived from the optical stereo image, and the shadow area generated with the increase in slope reduces the DEM extraction accuracy [48]. The glacier area with a slope of >45° was removed to solve the above problem. In addition, the matching of some pixels in the shadow may fail in the process of DEM extraction. Therefore, the generated DEM must be reprocessed from the generated DEM with a spatial resolution of 15 m to output a new DEM with a spatial resolution of 30 m [35,54].
3.
Spatial registration of ASTER DEM;
A three-step method framework proposed by Nuth and Kääb [55] was used to evaluate and correct the generated DEMs. The registration principle is based on the trigonometric function relationship between the DEM elevation deviation dh, slope α, and slope direction φ, which is:
dh/tan α = a cos(b − φ) + c
where a, b, and c are coefficients that can be obtained via a regression analysis of the scatter plot composed of dh/tan α and φ with a slope less than 5° in ice-free areas. The specific steps are described below. First, several calibration regions should be established in the ice-free areas around the Ulugh Muztagh Mountains, where the ice-free areas were regarded as the reference of constant elevation [56]. Secondly, the DEM of 2000 was selected as the reference surface elevation, and the ASTER DEMs in other years were registered one by one to eliminate the spatial offset of ASTER DEMs, which can increase the accuracy of the glacier elevation [27,57]. Herein, we obtained laser points in the southern ice-free area of the mountains for further registration. The coordinate system of ICESat-1 data was unified with the coordinate system of DEM, and the laser points outside the threshold range were eliminated [58]. The elevation difference between the WGS84 ellipsoid of ASTER DEM and the Topex/Poseidon ellipsoid of ICESat-1 is around 70–72 cm. ICESat-1 data are converted to the elevation datum with WGS84 ellipsoid as the reference ellipsoid:
H = h − N − 0.7
where H is the height of the ground point relative to the reference ellipsoid (WGS84), h is the height of the ground point relative to the reference ellipsoid (Topex Poseidon), and N value is the difference between the geoid and the reference ellipsoid.
Then, the elevation of the laser points at the corresponding position was extracted from the DEM. Additionally, the error surface was obtained by subtracting the elevation value of the DEM from the elevation value of ICESat-1 in Figure 1d. The elevation difference was corrected by the error surface [12,59].
hDEM-cor = hDEM − hICESat-1
hDEM-ture = hDEM − hDEM-cor
hDEM-cor represents the DEM elevation correction value, hDEM represents the initial DEM elevation value, hICESat-1 represents the ICESat-1 elevation value in an ice-free area, and hDEM-ture represents the DEM after elevation correction. Finally, the DEM correction values are shown in Table 5.
4.
Glacier surface elevation and mass balance.
The glacier DEMs were extracted by the glacier boundary from CGI-2. Then, the DEMs were limited by excluding the area where the glacier elevation change is greater than three times the standard deviation [60]. The glacier density of 850 ± 60 kg/m3 was used to calculate the mass balance [61]. The formula is as follows:
Δ h = ∑ i = 1 n s i × Δ h i A
Δh is the elevation difference of the grid unit at the same position of the two DEMs, n is the number of grid units, si is the glacier area of a grid cell, Δhi is the elevation difference of the grid unit at the same position as the two DEMs, and A is the glacier area of the study region.
Δ M = ∑ i = 1 n s i × Δ h i × φ A
in which ΔM is the change in mass balance, n is the number of grid units, si is the glacier area of a grid cell, Δhi is the elevation difference of the grid unit at the same position as the two DEMs, φ is the density for glacier volumetric mass conversion, and A is the glacier area of the study region.

3.2.3. Uncertainty Assessment

The estimation of glacier mass balance based on DEMs generated by optical remote sensing is largely decided by the accuracy of the DEMs. The total uncertainty of a mass balance (α) is [55]:
α = β r d n 2 + β s y s 2
where βrdn is a random error and βsys is a systematic error. The system error can be ignored since the results were obtained using the difference between the two images. It is difficult to directly assess the uncertainty of ASTER DEM data using surface data due to insufficient in situ measurements of glacier elevation. βrdn is controlled by the uncertainty of glacier density and elevation change. The error of glacier density is ±60 kg/m3 [61]. As for the uncertainty of elevation change, we used the assessment method of glacier monitoring uncertainty in the papers of Shean, Bhushan, Montesano, Rounce, Arendt, and Osmanoglu [50], and Wang and Kaab [25] in the study:
σ d h = σ s t d 2 + σ h 2
where σdh indicates the error of glacier elevation change and σstd is the standard deviation of the results of the DEM subtraction, which is calculated to be 2.15 m in this paper. σdh includes ICESat-2 errors (0.03 m) [37] and ice-free area elevation errors. The residual error of elevation difference in the ice-free area is less than 1 m after the calibration [62]. In this paper, the error α of glacier mass balance is between 1.69 m w.e. and 2.70 m w.e. The large standard deviation was mainly due to the melting of glaciers at low elevation, high elevation accumulation, and occasional elevation mutation in the Ulugh Muztagh Mountains. ASTER images were obtained in November.

4. Results

4.1. Annual Changes in the Glacier Surface Mass Balance from 2000 to 2020

The elevation changes of glaciers were calculated in the Ulugh Muztagh Mountains from 2000 to 2020 based on the glacier DEM in the specific year. As shown in Figure 4, the glacier surface elevation showed an overall decreasing trend characterized by a cumulative elevation change of −0.17 ± 10.74 m from 2000 to 2020 (Table 6). During the study period, the annual change in the glacier elevation ranged from −0.13 ± 2.94 m to 0.07 ± 1.57 m, with an average elevation change of −0.0085 ± 0.54 m/yr. Moreover, the annual glacier mass balance ranged from −0.11 ± 2.50 m w.e. to 0.06 ±1.33 m w.e., with an average annual mass balance of −0.0072 ± 0.46 m w.e./yr during the period. It was noted that the glacier surface mass balance was accumulated from 2000 to 2011 with an accumulative mass balance of 0.64 ± 9.22 m w.e. The glaciers began to lose mass from 2011 to 2020, during which time the accumulative mass balance was −0.78 ± 9.04 m w.e. The mass balance of the glacier showed a decreasing trend, with an accumulative mass balance of −0.14 ± 9.13 m w.e. from 2000 to 2020.

4.2. Assessment of the Glacier Surface Elevation from the ASTER

Glacier surface changes in the Ulugh Muztagh Mountains were assessed using ASTER in this paper. To verify the accuracy of the glacier surface elevations generated from ASTER images, the results were compared with the DEMs from ICESat and SPOT 5. Firstly, all DEMs were adjusted to the same coordination for comparison. The glacier surface elevation values of the laser point position of ICESat-2 on 4 October 2020 (Figure 1d) were extracted and compared to ASTER DEM on 4 November 2020 (Table 1) in this paper. As shown in Figure 5a, the fitted determining coefficient of the two products was 0.99 and p < 0.0001. Secondly, the elevation profiles of SPOT 5 DEM and ASTER DEM at the validation line shown in Figure 1c were drawn. Their profile lines were very similar (Figure 5b). The elevation changed by 0.09 ± 1.54 m/yr based on the source data of SPOT 5 DEM from 2004 to 2008, while its change was 0.07 ± 1.57 m/yr based on the source data of ASTER DEM from 2000 to 2007 (Figure 5c). In addition, the average surface elevation change was 0.09 ± 0.52 m/yr from 2003 to 2021 when using eight groups of validation sites from ICESat, and the elevation change of the corresponding pixels was 0.23 ± 0.25 m/yr from ASTER DEM. In other words, the generated glacier surface elevations met the accuracy criteria to assess the glacier change in this region.

4.3. Spatial Changes in the Glacier Surface Mass Balance from 2000 to 2020

As shown in Figure 6, the glacier surface mass balance difference was very significant in the Ulugh Muztagh Mountains. The mass balance varied from −23.98 m w.e. to 24.06 m w.e. during the period from 2000 to 2020. The glaciers in the north and west showed significant melting, while the glaciers in the east showed relative accumulation. In addition, the accumulation of glaciers occurred in the middle of the study area, and melt could be found in the surrounding area, which was led by the elevation.
The glacier surface was divided into different zones by intervals of 100 m from 5050 m a.s.l. to 6950 m a.s.l. to analyze the spatial relationship between the glacier surface mass balance and elevation in the region. During the period of 2000–2020, the mass of glaciers melted below 5514 m a.s.l. in the Ulugh Muztagh area, while the mass of the glacier accumulated above 5514 m a.s.l. (Figure 7a). Hence, the equilibrium line altitude (ELA) of the glacier mass balance was recorded as 5514 m a.s.l. in the region during the period of 2000–2020. The maximum elevation changes in the zone of accumulation and the loss for glacier mass balance were 6750–6850 m a.s.l. and 4950–5050 m a.s.l., with a mass change of 25.16 m w.e. and −30.78 m w.e. from 2000 to 2020, respectively. The ELAs of the glaciers in the region were different over different timespans; i.e., 5460 m a.s.l. for 2000–2007, 5452 m a.s.l. for 2007–2011, 5523 m a.s.l. for 2011–2015, and 5537 m a.s.l. for 2015–2020 (Figure 7b). Overall, the ELA was increased by 85 m from 2000 to 2020.

4.4. Glacier Surface Mass Balance in Different Directions and Slope Aspects

To further understand the spatial difference in the Ulugh Muztagh Mountains, four typical glaciers were selected to analyze their mass balances to further explore the spatial difference of glacier surface mass balance, including the Shenshechuan Glacier on the north slope, the Yueya Glacier on the east slope, the Linglong Glacier located on the south slope, and the Yulinchuan Glacier located on the west slope (Figure 1d). As shown in Figure 8, the annual mass balance ranged from −0.37 m w.e. to 0.95 m w.e. in the Linglong Glacier between 2000 and 2020, with an average annual mass balance of 0.13 ± 0.49 m w.e. The annual mass balance ranged from −1.64 m w.e. to 1.39 m w.e. in the Shenshechuan Glacier with an average annual mass balance of −0.05 ± 0.36 m w.e. The annual mass balance ranged from −1.70 m w.e. to 1.13 m w.e. in the Yulinchuan Glacier with an average annual mass balance of −0.34 ± 0.47 m w.e. The annual mass balance ranged from −1.65 m w.e. to 1.49 m w.e. in the Yueya Glacier with an average annual mass balance of 0.34 ± 0.51 m w.e. The Yulinchuan Glacier showed the most significant mass loss, while the Yueya Glacier showed the most significant mass accumulation. Combined with Figure 6, it can be inferred that the glacier mass loss in the Ulugh Muztagh Mountains was mainly caused by the western and northern slopes.
We counted glaciers by slope aspect (Figure 9). The glaciers in the east slope and the northwest slope accounted for the largest areas, 25.19% and 21.25%, respectively. The glacier mass balance in the eastern, southern, and southeastern slopes was cumulative, and the rest was in an ablation state. The glacier mass loss in the northwest slope was the most severe, with a cumulative loss of −7.13 m w.e. from 2000 to 2020.

5. Discussion

5.1. Climate Change in the Ulugh Muztagh Mountains

From 2000 to 2020, the monthly average temperature in the summer in the Ulugh Muztagh Mountains fluctuated between −5.86 °C and −2.84 °C, with an average temperature of −4.32 °C. The monthly average temperature in winter fluctuated between −21.21 °C and −16.28 °C, with an average temperature of −17.48 °C from 2000 to 2020. The monthly average temperature in summer and winter exhibited no obvious change trends (Figure 10a). The annual average temperature fluctuated between −14.49 °C and −11.85 °C, with an average temperature of 13.09 °C. The annual average temperature rate of increase was 0.05 ± 0.03 °C/yr (Figure 10b). The average annual precipitation of the Ulugh Muztagh Mountains was 347.18–531.19 mm, with an average precipitation of 426.48 mm. The average annual precipitation fluctuated from 2000 to 2020 and exhibited a significant increase from 2015 to 2016. The annual average summer precipitation accounted for 57.30–72.82% of the annual average total precipitation with an average ratio of 64.16%. The average annual solid precipitation in the Ulugh Muztagh Mountains was 308.92–398.84 mm, with an average precipitation of 355.12 mm. The annual average solid precipitation accounted for 73.25–91.39% of the annual average total precipitation, with an average ratio of 83.33%. The annual average solid precipitation showed a fluctuating state (Figure 10c). There were no significant trends in the summer temperature, winter temperature, average annual precipitation, or average annual solid precipitation during the study period. We also used ERA5-Land data to directly explore the temperature and precipitation changes from 2000 to 2020. As shown in Figure 11a, the 2-m surface temperature of glaciers in the Muztag Mountains in November 2020 was generally higher than that in November 2000, exhibiting an increase of 0.71–1.32 °C. As shown in Figure 11b, the total glacier precipitation in the Muztag Mountains in November 2020 was lower than that in November 2000, with a decrease of −20.93 to −119.36 mm.
Research by Houghton et al. [63] also showed an increase in the temperature and precipitation in the region. Zhang et al. [64] assessed the sensitivity of the Shiyi glacier mass balance to climate change in the Qilian Mountains. The sensitivity of mass balance to temperature change (±1 °C) was ±0.74 m w.e./yr °C, and the sensitivity of mass balance to precipitation was calculated to be ±18.10 m w.e. for a 10% change. Jiang, Zhang, and Zhang [18] found that temperature and precipitation showed an increasing trend. The temperature rise rate was 0.02–0.04 °C/yr, and the precipitation increase rate was 3.4–6.3 mm/yr from 2000 to 2011 in the Ulugh Muztagh Mountains. The interannual variations of glaciers were mainly caused by rising temperatures, the variability of precipitation, and the resulting different atmospheric circulation patterns [65]. Temperature plays a dominant role in glacier melt, and precipitation is the next important factor over a specific range.
The reasons for the overall stability of the glaciers in the Ulugh Muztagh Mountains were as follows: (1) The elevation of the Ulugh Muztagh Mountains is relatively high. Although the temperature was slightly increased, it was generally maintained at a very low level. There was no significant change in summer and winter temperatures, and the mass changes during the glacier melt period and the glacier accumulation period were stable. (2) Precipitation showed no obvious change in trend from 2000 to 2020. The overall change in precipitation was very small and also provided conditions for glacier mass balance. (3) Although the glaciers on the northern and western slopes melted, the glacier mass balance on the southern and eastern slopes was cumulative, offsetting the changes, resulting in a stable mass balance in the glaciers in the Ulugh Muztagh Mountains in the period 2000–2020.

5.2. Glacier Mass Balance Change in the Ulugh Muztagh Mountains and around the Region

The mass balance of the Shenshechuan Glacier was greatly lost when the temperature rose in 2015–2017. The Shenshechuan Glacier is more sensitive to temperature changes due to its lower elevation (5119 m a.s.l.). According to Figure 8, we found that the Shenshechuan Glacier and the Yulinchuan Glacier had the same trend as the Ulugh Muztagh Mountains glaciers, while the Linglong Glacier and the Yueya Glacier slightly increased from 2000 to 2020. The glaciers in this area are affected by the thermal low pressure of the Qinghai–Tibet Plateau in summer. The warm air is uplifted under the control of the westerly circulation and the mountainous terrain, resulting in precipitation and supplying the glaciers [16]. Warm air from the east and south tends to produce topographic rainfall, which supplements glaciers in the east and south. Therefore, the glacier mass in the east and south accumulated, and the glacier mass in the west and north melted, which indicates that the increase in precipitation made up for the loss of glacier mass to some extent [66]. The glacier surface elevation decrease trend became slow from 2016 to 2020 in the Ulugh Muztagh Mountains, which may have been caused by the increase in precipitation [18].
There was a small discrepancy in a different study on the glacier mass change in the Ulugh Muztagh Mountains due to the difference in the study period and data source. For example, Brun, Berthier, Wagnon, Kaab, and Treichler [26] concluded that the mass balance in the East Kunlun Mountains was estimated to be −0.01 ± 0.07 m w.e./yr during 2000–2016, which is consistent with the glacier mass balance of −0.0072 ± 0.46 m w.e./yr for 2000–2020 in the Ulugh Muztagh Mountains in this paper. Jiang, Zhang, and Zhang [18] concluded that the change in the mass balance of the Ulugh Muztagh Mountains was 0.02 ± 0.04 m w.e./yr from 2000 to 2011, while the mass balance was at 0.06 ± 0.84 m w.e./yr from 2000 to 2011 in this study. Liang, Wang, Yang, Chen, Hua, Li, and Yang [19] reported that the change in the mass balance in the Ulugh Muztagh Mountains was −0.09 ± 0.05 m w.e./yr from 2000 to 2013, and the result for this was 0.06 ± 0.84 m w.e./yr from 2000 to 2011 in this paper. This may be due to the different data acquisition times. The data acquisition times of this paper were October and November. The glacier mass balance of the dataset of Hugonnet et al. [67] from 2000 to 2020 was 0.03 ± 0.04 m w.e./yr, while the result was −0.0072 ± 0.46 m w.e./yr for 2000–2020 in the Ulugh Muztagh Mountains in this paper [9]. Although the results were slightly different, they had the same change trend, which was to increase first and then decrease (Figure 12). Therefore, our method is reasonable and our conclusion is credible.

5.3. Typical Glacier Surge in the Ulugh Muztagh Mountains

The mass balance of the Ulugh Muztagh Mountains glaciers was related to glacier collapse, glacier advance, surge, and changes in temperature and precipitation. For example, there was a glacier collapse and mass movement in the Yulinchuan Glacier from 2007 to 2011 (Figure 13). From 2007 to 2011, the maximum mass balance change in the upper reaches of the Yulinchuan Glacier was −21.22 m w.e. and the downstream mass balance accumulated 21.72 m w.e. The area of mass loss was about 7.13 km2, and the elevation range was from 5350 m a.s.l. to 5875 m a.s.l. The area with increased mass balance was about 5.49 km2, and the elevation range was from 5150 m a.s.l. to 5350 m a.s.l. Based on Landsat data, Guo et al. [17] found that the two ends of the middle branch of the Yulinchuan Glacier significantly advanced from 2007 to 2010, with the western front advancing by 170 ± 34 m and the northern front advancing by 548 ± 34 m. From October 2008 to September 2010, the rapid movement of the middle branch of the glacier led to the severe fragmentation of the glacier surface, and its maximum visual velocity reached 13.3 ± 1.5 m/d in the middle of the glacier. Jiang, Zhang, and Zhang [18] found that the Muztagh glacier and Congliu glacier had advanced many times. The Muztagh glacier advanced 100 m from 1972 to 1986, 25 m in 1993, 33 m from 1994 to 1999, 46 m from 1999 to 2004, and 20 m from 2004 to 2008. The Congliu glacier moved 50 m from 1992 to 1993, 20 m from 1994 to 1999, and 10 m from 1999 to 2011. This is not only true of the Ulugh Muztagh Mountains, as global glacier surges are becoming more frequent due to rising temperatures and extreme events [68,69,70].

5.4. Deficiency and Outlook

ASTER images are optical remote sensing images. There are error factors in optical remote sensing images, which are often affected by clouds, resulting in a decline in data quality. To avoid the influence of clouds, we chose ASTER data in the winter, which may have affected our results. In addition, a very important parameter for the generation of DEMs from optical images is resolution. The resolution affects the accuracy of DEMs in glacier mass balance monitoring, thus affecting the accuracy of the results [51]. Due to the lack of glacier elevation measurement data and measured meteorological data, the results and analysis would be more accurate if they were combined with RTK (real-time kinematic) meteorological data [71].
ASTER images are optical remote sensing images, and SPOT 5 images are also optical remote sensing images. They cannot penetrate snow. The ICESat-1/2 product data set for glaciers also cannot penetrate snow [72]. In this way, the research in this paper avoided the errors caused by radar and microwave remote sensing penetrating snow and could obtain more accurate surface mass balance [26,73]. The altimetry data, such as ICESat-1/2, have accurate elevation and are often used to monitor glaciers at high latitudes and in the polar regions. However, the distribution at medium and low latitudes is relatively sparse. If the data are densely distributed, this will become a convenient, fast, and accurate method for HMA glacier monitoring.

6. Conclusions

In this work, the surface elevation changes in the Ulugh Muztagh Mountains were studied in detail based on the registered ASTER DEMs from 2000 to 2020. The results indicated that the glacier surface elevation change rate was −0.0085 ± 0.54 m/yr during the period of 2000–2020. The annual mass balance of the glaciers was −0.0072 ± 0.46 m w.e./yr from 2000 to 2020, which showed a weak negative mass loss in the Ulugh Muztagh Mountains. The equilibrium line altitude (ELA) of the glacier mass balance was 5514 m a.s.l. from 2000 to 2020. The glacier surface mass balance exhibited an obvious spatial difference in the region. In general, the glacier mass losses in the west and north slopes were more significant than those in the east and south slopes. The annual average temperature rise rate in the Ulugh Muztagh Mountains was 0.05 ± 0.03 °C/yr, and there was no significant change trend in terms of the precipitation. There was a phenomenon of glacier surges in the Yulinchuan Glacier, which caused the mass to transfer from upstream to downstream.

Author Contributions

Conceptualization, Y.C. and M.Z.; methodology, Y.C.; software, L.G.; validation, L.G., Y.C. and L.C.; formal analysis, Y.C. and L.C.; investigation, L.G.; resources, M.Z.; data curation, L.G.; writing—original draft preparation, L.G.; writing—review and editing, Y.C., Y.Z. and X.M.; visualization, L.G.; supervision, Y.C.; project administration, M.Z.; funding acquisition, M.Z. and Y.C. 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. 2021xjkk0101), National Natural Science Foundation of China (Grant No. 42101135), Key Laboratory of Resource Environment and Sustainable Development of Oasis, Gansu Province (Grant No. GORs202103), and Science and Technology Research Project of Jiangxi Provincial Department of Education (Grant No. GJJ2201708).

Data Availability Statement

The datasets generated and analyzed during the current study are not publicly available but are available from the corresponding author upon reasonable request.

Acknowledgments

We sincerely thank our colleagues at Northwest Normal University for their help with field and laboratory work. The CGI-2 dataset was provided by the National Tibetan Plateau Data Center (http://data.tpdc.ac.cn (1 January 2022)). We sincerely thank the NASA Earthdata Search website for providing remote sensing images, as well as the OpenAltimetry website for providing data and the ECWMF for providing the meteorological data.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Bhattacharya, A.; Bolch, T.; Mukherjee, K.; King, O.; Menounos, B.; Kapitsa, V.; Neckel, N.; Yang, W.; Yao, T. High Mountain Asian glacier response to climate revealed by multi-temporal satellite observations since the 1960s. Nat. Commun. 2021, 12, 4133. [Google Scholar] [CrossRef]
  2. Jacob, T.; Wahr, J.; Pfeffer, W.T.; Swenson, S. Recent contributions of glaciers and ice caps to sea level rise. Nature 2012, 482, 514–518. [Google Scholar] [CrossRef]
  3. Zemp, M.; Huss, M.; Thibert, E.; Eckert, N.; McNabb, R.; Huber, J.; Barandun, M.; Machguth, H.; Nussbaumer, S.U.; Gärtner-Roer, I.; et al. Global glacier mass changes and their contributions to sea-level rise from 1961 to 2016. Nature 2019, 568, 382–386. [Google Scholar] [CrossRef] [Green Version]
  4. Lamsal, D.; Sawagaki, T.; Watanabe, T.; Byers, A.C. Assessment of glacial lake development and prospects of outburst susceptibility: Chamlang South Glacier, eastern Nepal Himalaya. Geomat. Nat. Hazards Risk 2016, 7, 403–423. [Google Scholar] [CrossRef] [Green Version]
  5. Wang, S.; Yang, Y.; Che, Y. Global Snow-and Ice-Related Disaster Risk: A Review. Nat. Hazards Rev. 2022, 23, 03122002. [Google Scholar]
  6. Shugar, D.H.; Burr, A.; Haritashya, U.K.; Kargel, J.S.; Watson, C.S.; Kennedy, M.C.; Bevington, A.R.; Betts, R.A.; Harrison, S.; Strattman, K. Rapid worldwide growth of glacial lakes since 1990. Nat. Clim. Chang. 2020, 10, 939–945. [Google Scholar] [CrossRef]
  7. Kääb, A.; Treichler, D.; Nuth, C.; Berthier, E. Brief Communication: Contending estimates of 2003–2008 glacier mass balance over the Pamir–Karakoram–Himalaya. Cryosphere 2015, 9, 557–564. [Google Scholar] [CrossRef] [Green Version]
  8. Millan, R.; Mouginot, J.; Rabatel, A.; Morlighem, M. Ice velocity and thickness of the world’s glaciers. Nat. Geosci. 2022, 15, 124–129. [Google Scholar] [CrossRef]
  9. Hugonnet, R.; McNabb, R.; Berthier, E.; Menounos, B.; Nuth, C.; Girod, L.; Farinotti, D.; Huss, M.; Dussaillant, I.; Brun, F.; et al. Accelerated global glacier mass loss in the early twenty-first century. Nature 2021, 592, 726–731. [Google Scholar] [CrossRef]
  10. Immerzeel, W.W.; Lutz, A.F.; Andrade, M.; Bahl, A.; Biemans, H.; Bolch, T.; Hyde, S.; Brumby, S.; Davies, B.J.; Elmore, A.C.; et al. Importance and vulnerability of the world’s water towers. Nature 2020, 577, 364–369. [Google Scholar] [CrossRef]
  11. Gardner, A.S.; Moholdt, G.; Cogley, J.G.; Wouters, B.; Arendt, A.A.; Wahr, J.; Berthier, E.; Hock, R.; Pfeffer, W.T.; Kaser, G.; et al. A Reconciled Estimate of Glacier Contributions to Sea Level Rise: 2003 to 2009. Science 2013, 340, 852–857. [Google Scholar] [CrossRef] [Green Version]
  12. Shen, C.; Jia, L.; Ren, S. Inter- and Intra-Annual Glacier Elevation Change in High Mountain Asia Region Based on ICESat-1&2 Data Using Elevation-Aspect Bin Analysis Method. Remote Sens. 2022, 14, 1630. [Google Scholar] [CrossRef]
  13. Che, Y.; Zhang, M.; Li, Z.; Li, H.; Wang, S.; Sun, M.; Zha, S. Glacier mass-balance and length variation observed in China during the periods 1959–2015 and 1930–2014. Quat. Int. 2017, 454, 68–84. [Google Scholar] [CrossRef]
  14. Jouberton, A.; Shaw, T.E.; Miles, E.; McCarthy, M.; Fugger, S.; Ren, S.; Dehecq, A.; Yang, W.; Pellicciotti, F. Warming-induced monsoon precipitation phase change intensifies glacier mass loss in the southeastern Tibetan Plateau. Proc. Natl. Acad. Sci. USA 2022, 119, e2109796119. [Google Scholar] [CrossRef]
  15. Gardelle, J.; Berthier, E.; Arnaud, Y. Slight mass gain of Karakoram glaciers in the early twenty-first century. Nat. Geosci. 2012, 5, 322–325. [Google Scholar] [CrossRef]
  16. Chen, Y.N.; Wang, Y.S.; Wang, Z.C. Distribution, quantity and types of modern glaciers in the Muztag peak area, eastern Kunlun. Arid Zone Res. 1985, 2, 56–61. [Google Scholar]
  17. Guo, W.; Liu, S.; Xu, J.; Wei, j.; Ding, l. Monitoring Recent Surging of the Yulinchuan Glacier on North Slopes of Muztag Range by Remote Sensing. J. Glaciol. Geocryol. 2012, 34, 765–774. [Google Scholar]
  18. Jiang, Z.; Zhang, J.; Zhang, Z. Glacier change and mass balance (1972—2011) in Ulugh Muztagh, eastern Kunlun Mountains, monitored by remote sensing. Remote Sens. Land Resour. 2019, 31, 128–136. [Google Scholar] [CrossRef]
  19. Liang, Q.; Wang, N.; Yang, X.; Chen, A.; Hua, T.; Li, Z.; Yang, D. The eastern limit of ‘Kunlun-Pamir-Karakoram Anomaly’ reflected by changes in glacier area and surface elevation. J. Glaciol. 2022, 68, 1167–1176. [Google Scholar] [CrossRef]
  20. Guillet, G.; King, O.; Lv, M.; Ghuffar, S.; Benn, D.; Quincey, D.; Bolch, T. A regionally resolved inventory of High Mountain Asia surge-type glaciers, derived from a multi-factor remote sensing approach. Cryosphere 2022, 16, 603–623. [Google Scholar] [CrossRef]
  21. Ren, S.; Menenti, M.; Jia, L.; Zhang, J.; Zhang, J.; Li, X. Glacier Mass Balance in the Nyainqentanglha Mountains between 2000 and 2017 Retrieved from ZiYuan-3 Stereo Images and the SRTM DEM. Remote Sens. 2020, 12, 864. [Google Scholar] [CrossRef] [Green Version]
  22. Zhou, Y.; Li, Z.; Li, J.; Zhao, R.; Ding, X. Glacier mass balance in the Qinghai–Tibet Plateau and its surroundings from the mid-1970s to 2000 based on Hexagon KH-9 and SRTM DEMs. Remote Sens. Environ. 2018, 210, 96–112. [Google Scholar] [CrossRef]
  23. Moholdt, G.; Nuth, C.; Hagen, J.O.; Kohler, J. Recent elevation changes of Svalbard glaciers derived from ICESat laser altimetry. Remote Sens. Environ. 2010, 114, 2756–2767. [Google Scholar] [CrossRef]
  24. Rignot, E.; Echelmeyer, K.; Krabill, W. Penetration depth of interferometric synthetic-aperture radar signals in snow and ice. Geophys. Res. Lett. 2001, 28, 3501–3504. [Google Scholar] [CrossRef] [Green Version]
  25. Wang, D.; Kaab, A. Modeling Glacier Elevation Change from DEM Time Series. Remote Sens. 2015, 7, 10117–10142. [Google Scholar] [CrossRef] [Green Version]
  26. Brun, F.; Berthier, E.; Wagnon, P.; Kaab, A.; Treichler, D. A spatially resolved estimate of High Mountain Asia glacier mass balances from 2000 to 2016. Nat. Geosci. 2017, 10, 668–673. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Berthier, E.; Cabot, V.; Vincent, C.; Six, D. Decadal Region-Wide and Glacier-Wide Mass Balances Derived from Multi-Temporal ASTER Satellite Digital Elevation Models. Validation over the Mont-Blanc Area. Front. Earth Sci. 2016, 4, 63. [Google Scholar] [CrossRef] [Green Version]
  28. Farinotti, D.; Immerzeel, W.W.; de Kok, R.J.; Quincey, D.J.; Dehecq, A. Manifestations and mechanisms of the Karakoram glacier Anomaly. Nat. Geosci. 2020, 13, 8–16. [Google Scholar] [CrossRef]
  29. Quincey, D.J.; Braun, M.; Glasser, N.F.; Bishop, M.P.; Hewitt, K.; Luckman, A. Karakoram glacier surge dynamics. Geophys. Res. Lett. 2011, 38, L18504. [Google Scholar] [CrossRef] [Green Version]
  30. Wang, Y.; Hou, S.; Huai, B.; An, W.; Pang, H.; Liu, Y. Glacier anomaly over the western Kunlun Mountains, Northwestern Tibetan Plateau, since the 1970s. J. Glaciol. 2018, 64, 624–636. [Google Scholar] [CrossRef] [Green Version]
  31. Wang, A.; Smith, J.A.; Wang, G.; Zhang, K.; Xiang, S.; Liu, D. Late Quaternary river terrace sequences in the eastern Kunlun Range, northern Tibet: A combined record of climatic change and surface uplift. J. Asian Earth Sci. 2009, 34, 532–543. [Google Scholar] [CrossRef]
  32. Guo, W.; Liu, S.; Wei, J.; Bao, W. The 2008/09 surge of central Yulinchuan glacier, northern Tibetan Plateau, as monitored by remote sensing. Ann. Glaciol. 2013, 54, 299–310. [Google Scholar] [CrossRef] [Green Version]
  33. Liu, S.; Yao, X.; Guo, W.; Xu, J.; Shangguan, D.; Wei, J.; Bao, W.; Wu, L. The contemporary glaciers in China based on the Second Chinese Glacier Inventory. Acta Geogr. Sin. 2015, 70, 3–16. [Google Scholar]
  34. Fujisada, H. Overview of ASTER Instrument on EOS-AM1 Platform; SPIE: Bellingham, WA, USA, 1994; Volume 2268. [Google Scholar]
  35. Fujisada, H. ASTER Level-1 data processing algorithm. IEEE Trans. Geosci. Remote Sens. 1998, 36, 1101–1112. [Google Scholar] [CrossRef]
  36. Zwally, H.J.; Schutz, B.; Abdalati, W.; Abshire, J.; Bentley, C.; Brenner, A.; Bufton, J.; Dezio, J.; Hancock, D.; Harding, D.; et al. ICESat’s laser measurements of polar ice, atmosphere, ocean, and land. J. Geodyn. 2002, 34, 405–445. [Google Scholar] [CrossRef] [Green Version]
  37. Smith, B.; Fricker, H.A.; Gardner, A.S.; Medley, B.; Nilsson, J.; Paolo, F.S.; Holschuh, N.; Adusumilli, S.; Brunt, K.; Csatho, B.; et al. Pervasive ice sheet mass loss reflects competing ocean and atmosphere processes. Science 2020, 368, 1239–1242. [Google Scholar] [CrossRef]
  38. Markus, T.; Neumann, T.; Martino, A.; Abdalati, W.; Brunt, K.; Csatho, B.; Farrell, S.; Fricker, H.; Gardner, A.; Harding, D.; et al. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2): Science requirements, concept, and implementation. Remote Sens. Environ. 2017, 190, 260–273. [Google Scholar] [CrossRef]
  39. Brunt, K.M.; Neumann, T.A.; Smith, B.E. Assessment of ICESat-2 Ice Sheet Surface Heights, Based on Comparisons Over the Interior of the Antarctic Ice Sheet. Geophys. Res. Lett. 2019, 46, 13072–13078. [Google Scholar] [CrossRef] [Green Version]
  40. Shepherd, A.; Ivins, E.R.; A, G.; Barletta, V.R.; Bentley, M.J.; Bettadpur, S.; Briggs, K.H.; Bromwich, D.H.; Forsberg, R.; Galin, N.; et al. A Reconciled Estimate of Ice-Sheet Mass Balance. Science 2012, 338, 1183–1189. [Google Scholar] [CrossRef] [Green Version]
  41. Munoz-Sabater, J.; Dutra, E.; Agusti-Panareda, A.; Albergel, C.; Arduini, G.; Balsamo, G.; Boussetta, S.; Choulga, M.; Harrigan, S.; Hersbach, H.; et al. ERA5-Land: A state-of-the-art global reanalysis dataset for land applications. Earth Syst. Sci. Data 2021, 13, 4349–4383. [Google Scholar] [CrossRef]
  42. Zhao, P.; He, Z.B. A First Evaluation of ERA5-Land Reanalysis Temperature Product Over the Chinese Qilian Mountains. Front. Earth Sci. 2022, 10, 907730. [Google Scholar] [CrossRef]
  43. Guo, W.; Liu, S.; Xu, J.; Wu, L.; Shangguan, D.; Yao, X.; Wei, J.; Bao, W.; Yu, P.; Liu, Q.; et al. The second Chinese glacier inventory: Data, methods and results. J. Glaciol. 2015, 61, 357–372. [Google Scholar] [CrossRef] [Green Version]
  44. Liu, S.; Guo, W.; Xu, J. The Second Glacier Inventory Dataset of China (Version 1.0) (2006–2011); National Tibetan Plateau Data Center, Ed.; National Tibetan Plateau Data Center: Beijing, China, 2012. [Google Scholar] [CrossRef]
  45. Korona, J.; Berthier, E.; Bernard, M.; Rémy, F.; Thouvenot, E. SPIRIT. SPOT 5 stereoscopic survey of Polar Ice: Reference Images and Topographies during the fourth International Polar Year (2007–2009). ISPRS J. Photogramm. Remote Sens. 2009, 64, 204–212. [Google Scholar] [CrossRef] [Green Version]
  46. Toutin, T. Elevation modelling from satellite visible and infrared (VIR) data. Int. J. Remote Sens. 2001, 22, 1097–1125. [Google Scholar] [CrossRef]
  47. Hirano, A.; Welch, R.; Lang, H. Mapping from ASTER stereo image data: DEM validation and accuracy assessment. ISPRS J. Photogramm. Remote Sens. 2003, 57, 356–370. [Google Scholar] [CrossRef]
  48. Toutin, T. Three-dimensional topographic mapping with ASTER stereo data in rugged topography. IEEE Trans. Geosci. Remote Sens. 2002, 40, 2241–2247. [Google Scholar] [CrossRef] [Green Version]
  49. Madani, A.A. Accuracy assessment of digital elevation model from aster data using automatic stereocorrelation technique, east Luxor, Egypt. J. King Abdulaziz Univ. Earth Sci. 2012, 23, 23–33. [Google Scholar] [CrossRef]
  50. Shean, D.E.; Bhushan, S.; Montesano, P.; Rounce, D.R.; Arendt, A.; Osmanoglu, B. A Systematic, Regional Assessment of High Mountain Asia Glacier Mass Balance. Front. Earth Sci. 2020, 7, 363. [Google Scholar] [CrossRef] [Green Version]
  51. Girod, L.; Nuth, C.; Kääb, A.; McNabb, R.; Galland, O. MMASTER: Improved ASTER DEMs for Elevation Change Monitoring. Remote Sens. 2017, 9, 704. [Google Scholar] [CrossRef] [Green Version]
  52. San, B.T.; Suzen, M.L. Digital elevation model (DEM) generation and accuracy assessment from ASTER stereo data. Int. J. Remote Sens. 2005, 26, 5013–5027. [Google Scholar] [CrossRef]
  53. Deilami, K.; Mohd, M.I.S.; Atashpareh, N. An accuracy assessment of ASTER stereo images-derived digital elevation model by using rational polynomial coefficient model. Sci. Eng. Fac. 2012, 55, 128–135. [Google Scholar]
  54. Lang, H.; Welch, R.; Miyazaki, Y.; Bailey, G.B.; Kelly, G. ASTER Along-Track Stereo Experiment: A Potential Source of Global DEM Data in the Late 1990s. In Proceedings of the SPIE’s 1996 International Symposium on Optical Science, Engineering, and Instrumentation, Denver, CO, USA, 21 October 1996; Volume 2817. [Google Scholar]
  55. Nuth, C.; Kääb, A. Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change. Cryosphere 2011, 5, 271–290. [Google Scholar] [CrossRef] [Green Version]
  56. Nuimura, T.; Sakai, A.; Taniguchi, K.; Nagai, H.; Lamsal, D.; Tsutaki, S.; Kozawa, A.; Hoshina, Y.; Takenaka, S.; Omiya, S.; et al. The GAMDAM glacier inventory: A quality-controlled inventory of Asian glaciers. Cryosphere 2015, 9, 849–864. [Google Scholar] [CrossRef] [Green Version]
  57. Zhao, F.Y.; Long, D.; Li, X.D.; Huang, Q.; Han, P.F. Rapid glacier mass loss in the Southeastern Tibetan Plateau since the year 2000 from satellite observations. Remote Sens. Environ. 2022, 270, 112853. [Google Scholar] [CrossRef]
  58. Sochor, L.; Seehaus, T.; Braun, M.H. Increased Ice Thinning over Svalbard Measured by ICESat/ICESat-2 Laser Altimetry. Remote Sens. 2021, 13, 2089. [Google Scholar] [CrossRef]
  59. Qin, C.; Chen, C.; Yang, N.; Gao, Y.; Wang, M. Elevation Accuracy Evaluation and Correction of SRTM and ASTER GDEM in Shandong Province based on ICESat/GLAS. J. Geo-Inf. Sci. 2020, 22, 351. [Google Scholar] [CrossRef]
  60. Zhou, Y.; Li, X.; Zheng, D.; Li, Z. Evolution of geodetic mass balance over the largest lake-terminating glacier in the Tibetan Plateau with a revised radar penetration depth based on multi-source high-resolution satellite data. Remote Sens. Environ. 2022, 275, 113029. [Google Scholar] [CrossRef]
  61. Huss, M. Density assumptions for converting geodetic glacier volume change to mass change. Cryosphere 2013, 7, 877–887. [Google Scholar] [CrossRef] [Green Version]
  62. Gardelle, J.; Berthier, E.; Arnaud, Y.; Kääb, A. Region-wide glacier mass balances over the Pamir-Karakoram-Himalaya during 1999–2011. Cryosphere 2013, 7, 1263–1286. [Google Scholar] [CrossRef] [Green Version]
  63. Houghton, J.T.; Meira Filho, L.G.; Callander, B.A.; Harris, N.; Katternberg, A.; Maskell, K.; Lakeman, J.A. Climate Change 1995: The Science of Climate Change; Cambridge University Press, for the Intergovernmental Panel on Climate Change: Cambridge, UK, 1996. [Google Scholar]
  64. Zhang, H.; Li, Z.; Zhou, P. Mass balance reconstruction for Shiyi Glacier in the Qilian Mountains, Northeastern Tibetan Plateau, and its climatic drivers. Clim. Dyn. 2021, 56, 969–984. [Google Scholar] [CrossRef]
  65. Yao, T.; Thompson, L.; Yang, W.; Yu, W.; Gao, Y.; Guo, X.; Yang, X.; Duan, K.; Zhao, H.; Xu, B.; et al. Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings. Nat. Clim. Chang. 2012, 2, 663–667. [Google Scholar] [CrossRef]
  66. Zhang, M.J.; Wang, S.J.; Li, Z.Q.; Wang, F.T. Glacier area shrinkage in China and its climatic background during the past half century. J. Geogr. Sci. 2012, 22, 15–28. [Google Scholar] [CrossRef]
  67. Hugonnet, R.; McNabb, R.; Berthier, E.; Menounos, B.; Nuth, C.; Girod, L.; Farinotti, D.; Huss, M.; Dussaillant, I.; Brun, F.; et al. Accelerated Global Glacier Mass Loss in the Early Twenty-First Century—Dataset; Theia, Ed.; Service d’Observation en Environnement Atmosphérique/Observatoire Midi-Pyrénées: Toulouse, France, 2021. [Google Scholar] [CrossRef]
  68. Quincey, D.J.; Glasser, N.F.; Cook, S.J.; Luckman, A. Heterogeneity in Karakoram glacier surges. J. Geophys. Res.-Earth Surf. 2015, 120, 1288–1300. [Google Scholar] [CrossRef] [Green Version]
  69. Zhang, Z.; Liu, S.; Zhang, Y.; Wei, J.; Jiang, Z.; Wu, K. Glacier variations at Aru Co in western Tibet from 1971 to 2016 derived from remote-sensing data. J. Glaciol. 2018, 64, 397–406. [Google Scholar] [CrossRef] [Green Version]
  70. Kääb, A.; Leinss, S.; Gilbert, A.; Bühler, Y.; Gascoin, S.; Evans, S.G.; Bartelt, P.; Berthier, E.; Brun, F.; Chao, W.-A.; et al. Massive collapse of two glaciers in western Tibet in 2016 after surge-like instability. Nat. Geosci. 2018, 11, 114–120. [Google Scholar] [CrossRef] [Green Version]
  71. Rivera, A.; Casassa, G.; Bamber, J.; Kääb, A. Ice-elevation changes of Glaciar Chico, southern Patagonia, using ASTER DEMs, aerial photographs and GPS data. J. Glaciol. 2005, 51, 105–112. [Google Scholar] [CrossRef] [Green Version]
  72. Fan, Y.B.; Ke, C.Q.; Zhou, X.B.; Shen, X.Y.; Yu, X.N.; Lhakpa, D. Glacier mass-balance estimates over High Mountain Asia from 2000 to 2021 based on ICESat-2 and NASADEM. J. Glaciol. 2022, 1–13. [Google Scholar] [CrossRef]
  73. Round, V.; Leinss, S.; Huss, M.; Haemmig, C.; Hajnsek, I. Surge dynamics and lake outbursts of Kyagar Glacier, Karakoram. Cryosphere 2017, 11, 723–739. [Google Scholar] [CrossRef] [Green Version]
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Figure 1. (a) The location of the Ulugh Muztagh Mountains in the Qinghai–Tibetan plateau. Picture (b) was taken when we surveyed the Shenshechuan Glacier in May 2022. (c) The location of the Ulugh Muztagh Mountains and the coverage of the main data used in this paper. (d) Glacier distribution in the study region and graph of the Ulugh Muztagh Mountains’ elevation and distribution according to ICESat. Picture (e) is an actual picture of the east side of the Shenshechuan Glacier and was taken in May 2022.
Figure 1. (a) The location of the Ulugh Muztagh Mountains in the Qinghai–Tibetan plateau. Picture (b) was taken when we surveyed the Shenshechuan Glacier in May 2022. (c) The location of the Ulugh Muztagh Mountains and the coverage of the main data used in this paper. (d) Glacier distribution in the study region and graph of the Ulugh Muztagh Mountains’ elevation and distribution according to ICESat. Picture (e) is an actual picture of the east side of the Shenshechuan Glacier and was taken in May 2022.
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Figure 2. The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer stereo pair imaging schematic.
Figure 2. The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer stereo pair imaging schematic.
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Figure 3. Process of major processing programs used in this paper. Rectangles in different colors show different data processing stages.
Figure 3. Process of major processing programs used in this paper. Rectangles in different colors show different data processing stages.
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Figure 4. (a) Changes in glacier surface elevation and its regression analysis over the Ulugh Muztagh region. (b) Changes in glacier surface mass balance and its regression analysis over the Ulugh Muztagh region.
Figure 4. (a) Changes in glacier surface elevation and its regression analysis over the Ulugh Muztagh region. (b) Changes in glacier surface mass balance and its regression analysis over the Ulugh Muztagh region.
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Figure 5. (a) Comparison of selected intersection points in the ICESat and ASTER corresponding points. (b) The elevation profiles of SPOT 5 DEM and ASTER DEM at the same location. (c) Changes in glacier surface elevation of ASTER and SPOT 5.
Figure 5. (a) Comparison of selected intersection points in the ICESat and ASTER corresponding points. (b) The elevation profiles of SPOT 5 DEM and ASTER DEM at the same location. (c) Changes in glacier surface elevation of ASTER and SPOT 5.
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Figure 6. Glacier surface mass balance changes in the Ulugh Muztagh Mountains for different periods.
Figure 6. Glacier surface mass balance changes in the Ulugh Muztagh Mountains for different periods.
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Figure 7. (a) Relationship between glacier surface mass balance and elevation and their regression analysis in the Ulugh Muztagh Mountains for 2000–2020. (b) Relationship between glacier surface mass balance and elevation in the Ulugh Muztagh Mountains for 2000–2007, 2007–2011, 2011–2015, 2015–2020.
Figure 7. (a) Relationship between glacier surface mass balance and elevation and their regression analysis in the Ulugh Muztagh Mountains for 2000–2020. (b) Relationship between glacier surface mass balance and elevation in the Ulugh Muztagh Mountains for 2000–2007, 2007–2011, 2011–2015, 2015–2020.
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Figure 8. Mass balance changes in different directions of the Ulugh Muztagh Mountains. Plots (a–d) denote the annual and cumulative mass balances of the Linglong Glacier, Shenshechuan Glacier, Yulinchuan Glacier, and Yueya Glacier and their regression analyses, respectively.
Figure 8. Mass balance changes in different directions of the Ulugh Muztagh Mountains. Plots (a–d) denote the annual and cumulative mass balances of the Linglong Glacier, Shenshechuan Glacier, Yulinchuan Glacier, and Yueya Glacier and their regression analyses, respectively.
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Figure 9. The cumulative change in mass balance in different slope directions of the Ulugh Muztagh Mountains glaciers from 2000 to 2020.
Figure 9. The cumulative change in mass balance in different slope directions of the Ulugh Muztagh Mountains glaciers from 2000 to 2020.
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Figure 10. Climate change in the Ulugh Muztagh Mountains. (a) Summer season air temperature and winter season air temperature in the Ulugh Muztagh Mountains change and regression analysis. (b) Annual air temperature in the Ulugh Muztagh Mountains change and regression analysis. (c) Average annual precipitation and average annual solid precipitation in the Ulugh Muztagh Mountains change and regression analysis.
Figure 10. Climate change in the Ulugh Muztagh Mountains. (a) Summer season air temperature and winter season air temperature in the Ulugh Muztagh Mountains change and regression analysis. (b) Annual air temperature in the Ulugh Muztagh Mountains change and regression analysis. (c) Average annual precipitation and average annual solid precipitation in the Ulugh Muztagh Mountains change and regression analysis.
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Figure 11. (a) Temperature and (b) precipitation changes in the Ulugh Muztagh Mountains.
Figure 11. (a) Temperature and (b) precipitation changes in the Ulugh Muztagh Mountains.
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Figure 12. The glacier mass balance results in this paper were compared with those of Brun, Berthier, Wagnon, Kaab, and Treichler [26]; Jiang, Zhang, and Zhang [18]; Liang, Wang, Yang, Chen, Hua, Li, and Yang [19]; and Hugonnet, McNabb, Berthier, Menounos, Nuth, Girod, Farinotti, Huss, Dussaillant, Brun, and Kääb [9].
Figure 12. The glacier mass balance results in this paper were compared with those of Brun, Berthier, Wagnon, Kaab, and Treichler [26]; Jiang, Zhang, and Zhang [18]; Liang, Wang, Yang, Chen, Hua, Li, and Yang [19]; and Hugonnet, McNabb, Berthier, Menounos, Nuth, Girod, Farinotti, Huss, Dussaillant, Brun, and Kääb [9].
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Figure 13. Yulinchuan Glacier mass balance change during 2007–2011.
Figure 13. Yulinchuan Glacier mass balance change during 2007–2011.
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Table
Table 1. The basic information of ASTER images used in this article.
Table 1. The basic information of ASTER images used in this article.
CodeFile NameAcquisition TimeCloud CoverUsage
1AST_L1A_0031028200005225328.10.200010%DEM/2000
2AST_L1A_0031028200005230228.10.20003%
3AST_L1A_0031101200705091201.11.20073%DEM/2007
4AST_L1A_0031117200705090217.11.20079%
5AST_L1A_0031117200705091117.11.20076%
6AST_L1A_0031128201105084728.11.20114%DEM/2011
7AST_L1A_0031128201105085628.11.20112%
8AST_L1A_0031107201505100007.11.20156%DEM/2015
9AST_L1A_0031107201505100907.11.20156%
10AST_L1A_0031012202005031612.10.20202%DEM/2020
11AST_L1A_0031104202005091404.11.20207%
12AST_L1A_0031120200505023020.11.20204%
Table
Table 2. The information of validation sites.
Table 2. The information of validation sites.
CodeCategoryAcquisition TimeLongitudeLatitudeElevation (m)Group
1ICESat-110.10.200387.35197436.4180606249.89001
2ICESat-214.04.201987.35153436.4182336270.6895
3ICESat-110.10.200387.35250536.4211586421.60402
4ICESat-214.04.201987.35214036.4211856415.4270
5ICESat-110.10.200387.33981936.3482485783.93303
6ICESat-204.10.202087.33971836.3483185782.0796
7ICESat-110.10.200387.33955036.3466955785.69104
8ICESat-210.04.202087.33952836.3467025783.5347
9ICESat-110.10.200387.33927936.3451395784.74705
10ICESat-210.04.202087.33934236.3450805782.8230
11ICESat-110.10.200387.33679136.3311045668.75506
12ICESat-210.04.202087.33671436.3311275668.0386
13ICESat-110.10.200387.33651236.3295485660.03207
14ICESat-210.04.202087.33652536.3295085658.8433
15ICESat-110.10.200387.35144536.4149596043.76008
16ICESat-203.07.202187.35075436.4149806048.1650
Table
Table 3. ICESat-1/2 information for calibration and validation.
Table 3. ICESat-1/2 information for calibration and validation.
CodeCategoryTrack IDTimeUsage
1ICESat-12652003–2009Calibration
2ICESat-111802003–2009Calibration
3ICESat-13172003–2009Calibration
4ICESat-112472003–2009Calibration
5ICESat-21574 October 2020Validation
Table
Table 4. SPOT 5 information for validation.
Table 4. SPOT 5 information for validation.
CodeFile NameAcquisition TimeUsage
1004-008_S5_224-277-0_2004-09-13-05-05-30_HRS-1_S_MX_KK13 September 2004Verify ASTER DEM
2004-008_S5_224-277-0_2004-09-13-05-07-01_HRS-2_S_MX_KK13 September 2004
3002-003_S5_223-277-0_2008-07-18-04-54-43_HRS-1_S_MX_KK18 July 2008Verify ASTER DEM
4001-003_S5_223-276-7_2008-07-18-04-56-06_HRS-2_S_MX_KK18 July 2008
Table
Table 5. The DEM correction values.
Table 5. The DEM correction values.
ASTER DEMCorrected Value in X Direction (m)Corrected Value in Y Direction (m)Corrected Value in Z Direction (m)
DEM/2000--10.57
DEM/2007−1.007.402.49
DEM/2011−9.5047.8015.64
DEM/2015−41.40−12.50−8.77
DEM/2020−5.601.3015.38
Table
Table 6. Glacier surface elevation change results.
Table 6. Glacier surface elevation change results.
CodeDataChange in Glacier Surface Elevation (m)Standard Deviation (m)
128 October 2000–17 November 20070.52±10.99
217 November 2007–28 November 20110.23±10.70
328 November 2011–07 November 2015−0.52±11.75
407 November 2015–04 November 2020−0.40±9.51
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Gu, L.; Che, Y.; Zhang, M.; Chen, L.; Zhou, Y.; Ma, X. Slight Mass Loss in Glaciers over the Ulugh Muztagh Mountains during the Period from 2000 to 2020. Remote Sens. 2023, 15, 2338. https://doi.org/10.3390/rs15092338

AMA Style

Gu L, Che Y, Zhang M, Chen L, Zhou Y, Ma X. Slight Mass Loss in Glaciers over the Ulugh Muztagh Mountains during the Period from 2000 to 2020. Remote Sensing. 2023; 15(9):2338. https://doi.org/10.3390/rs15092338

Chicago/Turabian Style

Gu, Lailei, Yanjun Che, Mingjun Zhang, Lihua Chen, Yushan Zhou, and Xinggang Ma. 2023. "Slight Mass Loss in Glaciers over the Ulugh Muztagh Mountains during the Period from 2000 to 2020" Remote Sensing 15, no. 9: 2338. https://doi.org/10.3390/rs15092338

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