07-Glacier elevation change during two periods in the Lenglongling mountains derived from bistati

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Glacier elevation change during two periods in the
Lenglongling mountains derived from bistatic SAR
interferometry
Qibing Zhang, Li Zhang, Zhiwei Ouyang, Zhefu Chen, Di Zhao & Wei Chen
To cite this article: Qibing Zhang, Li Zhang, Zhiwei Ouyang, Zhefu Chen, Di Zhao & Wei Chen
(2023) Glacier elevation change during two periods in the Lenglongling mountains derived
from bistatic SAR interferometry, Geocarto International, ahead-of-print:ahead-of-print, 1-14,
DOI: 10.1080/10106049.2022.2146762
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Glacier elevation change during two periods in the
Lenglongling mountains derived from bistatic SAR
interferometry
Qibing Zhanga, Li Zhanga, Zhiwei Ouyanga, Zhefu Chena, Di Zhaoa and
Wei Chenb
aCollege of Geography and Tourism, Hunan University of Arts and Science, Changde, China; bHunan
Sanan Semiconductor Co., Ltd., Changsha, China
ABSTRACT
Bistatic SAR interferometry is a feasible technique of deriving gla-
cier height changes. Early studies on glacier change in the Qilian
Mountains showed that the glacier area declined, terminus
retreated, and flow velocity slowed down. In this study, five pairs
of X-band bistatic TerraSAR-X/TamDEM-X images from 2014 to
2019 and an iterative D-InSAR method respect to SRTM DEM of
2000 were employed, which improved the reliability and accuracy
of glacier height changing observations. From 2000 to 2014, the
height of glaciers in the Lenglonglin Mountains decreased by
(–0.64±0.06) m year�1. Glaciers in the Gangshika peak and its
surrounding region thinned at the rate of (–0.68 ± 0.09) m year�1
from 2014 to 2019. The values observed using remote sensing
was in accordance with RTK–GPS measured values. Stable precipi-
tation and increasing temperature since 1990 could be respon-
sible for the quick glacier mass loss.
ARTICLE HISTORY
Received 26 May 2022
Accepted 7 November 2022
KEYWORDS
Glacier elevation change;
InSAR; Lenglongling
Mountains; TanDEM-
X images
Introduction
Global and regional climate changes have triggered changes in glacier area, elevation, snow
line altitude, and velocity, which in turn have considerably impacted sea level altitude and
water resources in arid areas (Gardner et al. 2013; Dehecq et al. 2019; Wei et al. 2021; Yue
et al. 2021). As the mean yearly precipitation in the north-west arid region of China is lower
than 400mm, glacier and snow-melt in the Qilian Mountains can guarantee water for irriga-
tion, hydraulic power, and drinking (Li et al. 2010; Zhang and Kang 2021).
It is dangerous and laborious to evaluate glacier storage change by using traditional field
measurements of stake or RTK–GPS (Real-Time Kinematic Global Positioning System); fur-
thermore, only small areas can be monitored. Recently, remote sensing has gained popular-
ity for the observation of glacier height change over time through multitemporal surface
digital terrain difference (the geodetic method) and its low cost and wide swath coverage,
CONTACT Qibing Zhang 2391512238@qq.com
� 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/
licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is
properly cited.
GEOCARTO INTERNATIONAL
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which make it suitable for consistently surveying large areas (Brun et al. 2017; Bhattacharya
et al. 2021). Satellite laser altimetry or optical photogrammetry were used to calculate glacier
height changes in most previous studies. The former has a coarse spatial resolution and is
easily affected by clouds; the latter has a low contrast on the glacier accumulation zone.
Bistatic SAR interferometry is an alternative remote sensing method to optical photogram-
metry and altimetry. TanDEM-X (TDX) was launched in 2010 to join its twin satellite
TerraSAR-X (TSX), and they operate in the bistatic mode. This observation mode over-
comes the temporal decorrelation and atmospheric delay disturbance associated with con-
ventional repeat-pass interferometry. TanDEM-X was successfully applied to detect glacier
elevation change (Braun et al. 2019; Li et al. 2021).
Glaciers in the Lenglongling Mountains (LLM) have been experiencing rapid shrinkage.
The mean rate of change in glacier surface elevation for overall LLM was (–0.43 ± 0.03) m
year�1 during the 1976–2016 period based on topographic maps and ZY-3 data and geo-
detic methodology (Cao et al. 2019). Based on the comparison of topographic map in
1972 with DEM from RTK–GPS in 2010, the Ningchan No. 1 Glacier has an annual ele-
vation change of �0.76m year�1 (–0.65m w.e. year�1). Additionally, a mean annual mass
balance of (–0.90 ± 0.5) m w.e. was obtained during the period 2010–2015 using the stake
(glaciological) methodology (Cao et al. 2017, 2019) and �1.16m year�1 (–0.98m w.e.
year�1) during 2010–2020 (Pan et al. 2021). The Ningchan No.1 glacier changes displayed
in the digital surface models from unmanned aerial vehicles show a mass balance of
(–1.22 ± 0.1) m w.e. year�1 from 2017 to 2020 (Cao et al. 2021). When comparing the
two DEMs generated from topographic maps and RTK–GPS data, the mean surface eleva-
tion decreased by 0.64m year�1 for nine glaciers in the Ningchan and Shuiguan rivers
sources between 1972 and 2010 (Cao et al. 2014). The mean annual mass balance of the
Shuiguan No. 4 Glacier was �0.51m w.e. year�1 from 2010 to 2013, based on stake
observations (Cao et al. 2017).
This study used bistatic image pairs of TerraSAR-X/TanDEM-X with medium perpen-
dicular baselines, aided by the differential SAR interferometry (hereinafter referred to as
D-InSAR) method, to research glacier height changes in the LLM during the periods
2000–2014 and 2014–2019. To overcome SAR distortion errors, we eliminate the fore-
shortening, layover, and shadow regions induced by SAR’s side-looking geometry. The
relationship between glacier elevation and climate change was analysed.
Study area and data
Study area
The LLM (Figure 1), located in the north of the Tibetan Plateau, are approximately
250 km in length, 30–50 km in width, have an altitude of approximately 3000–5254m, the
mean elevation is greater than 4000m asl and the Gangshika peak (5254.5m) is the high-
est point with a gentle southern slope, a steep northern slope, and the area governed by
an arid to semi-arid climatic regime (Cao etal. 2010; Tian et al. 2012). A total of 161 gla-
ciers above 4000m asl in the LLM were documented in the Second Chinese Glacier
Inventory, covering a total area of 58.66 km2. The volume storage is 1.88 km3 as most gla-
ciers are small, 144 of them are smaller than 1 km2 (Liu et al. 2015). Glaciers in this area
are mainly influenced by the combined effects of the East Asian monsoon and the
Westerlies, and are classified as subcontinental-type glaciers (Cao et al. 2010; Tian et al.
2012). The mean annual air temperature during the period 1980–2010 was 1.17 �C and
the mean precipitation was 700–800mm, as recorded at the Menyuan Meteorological
2 Q. ZHANG ET AL.
Station (37�230N, 101�370E, 2924m asl); the precipitation mainly concentrated during the
May–September period. The glaciers belong to the summer-accumulation-type mountain
glacier, and the ablation and accumulation period overlap (Li et al. 2010; Cao et al. 2014;
Liu et al. 2015). The glaciers on the southwest-facing slope of the LLM feed the drainage
basin of the Datong River—a tributary of the Yellow River. The glaciers dominating the
northeast-facing slopes of the LLM feed a few inland drainage basins, such as the XiYing
river basin—this river is a tributary of the Shiyang River.
Data
To study glacier elevation changes in the LLM during the periods 2000–2014 and
2014–2019, the X band (3.1 cm) and C band (5.6 cm) SRTM DEM were exploited, aided
by Bi-static X band TerraSAR-X/TamDEM-X (TSX/TDX) images (Table 1). The void-
filled SRTM-C DEM of 30m resolution was downloaded from the United States
Geological Survey (USGS) website (https://www.usgs.gov/); it was taken as glacier eleva-
tion on February 2000, and as the reference DEM in differential interferometry. The X
band SRTM DEM of 30m resolution was acquired from DLR (http://eoweb.dlr.de:8080/
free_SRTM_X-band_data.html); it was compared with C band SRTM DEM to calculate
the C band penetration depth into snow and ice.
TSX/TDX images can minimize temporal decorrelation on glacier surface. In the strip-
map mode, they have a resolution of 2–3m in azimuth and range, and a swath of
30� 50 km. We acquired five scenes of co-registered Single Look Slant Range Complex;
four images acquired around 2014 almost cover the study area. However, only one image
in 2019 was applicable, and it covers the Gangshika peak and its surroundings. The effect-
ive baseline was 96–163m. Considering similar acquisition seasons, the penetration depth
Figure 1. Geographic distribution of the Lenglongling Mountains.
GEOCARTO INTERNATIONAL 3
https://www.usgs.gov/
http://eoweb.dlr.de:8080/free_SRTM_X-band_data.html
http://eoweb.dlr.de:8080/free_SRTM_X-band_data.html
differences between the two epochs of TanDEM-X DEM were waived. All TSX/TDX
acquisitions and SRTM used in this study were observed in the winter, which can avoid
seasonal fluctuation of glacier mass balance and/or penetration depth difference.
To discuss glacier area changes in this region, we downloaded two Landsat images of
30m resolution from the USGS: one was Landsat 5 TM acquired on 14 August 2001;
another was Landsat 8 OLI_TIRS acquired on 18 August 2014. They were orthorectified
LIT (level 1 terrain corrected) products.
Temperature and precipitation were the two main factors controlling glacier change:
annual precipitation determines glacier accumulation in a year, and mean temperature in
summer controls glacier yearly ablation. We obtained climatological variables recorded at
the Mengyuan Meteorological Station (37�230, 101�370, 2882m) from the National
Meteorological Information Center (http:/data.cma.cn), and analysed the variation trend
of annual precipitation and mean summer temperature. Due to a lagged and superim-
posed response of glacier mass balance to temperature, data acquired time began at 1990.
Methods
Deriving glacier elevation change
We followed the D-InSAR approach (Figure 2) to derive glacier elevation changes during
2000–2014 (Zhang and Kang 2021). After removing the flat earth and topographic phase
evaluated by SRTM DEM from TSX/TDX interferometry, the remaining comprised the
topographic residual phase mainly were induced by glacier height changes. When assuming
that no height changes occurred in the off-glacier area of the entire TSX/TDX coverage, the
phase ramp can be removed by fitting the bi-linear polynomial value on off-glacier areas.
We performed the D-InSAR operation iteratively to suppress the phase ramp. After the
third iteration, the topographic residual phase was converted to height changes. We
removed areas with strong distortions including foreshortening, layover, and shadow where
the incidence angle of microwave was less than 18 degrees and greater than 72 degrees (Li
and Lin 2017). We applied multi-look numbers of 4 and 5 to range and azimuth direction
of TSX/TDX, respectively, and an oversample rate of 3 to the DEM (1 arc second).
Therefore, the resolution of output geocoded height change maps was 0.33 arc second or
�10m. The result was modified with the consideration of penetration depths.
Table 1. Specifications of TanDEM-X images used in the study.
Data
Effective
perpendicular
baseline (m)
Height of
ambiguity (m)
Average
coherence Pass Relative orbit.
Incidence
angle (degree)
20
December
2013
96.59 70.90 0.75 D 74 39.26
20
December
2013
96.59 70.90 0.71 D 74 37.11
31
December
2013
106.21 55.70 0.75 D 74 41.36
11
January
2014
114.80 55.50 0.68 D 74 41.39
11
January
2019
162.96 –43.6 0.50 D 74 42.63
4 Q. ZHANG ET AL.
When deriving glacier elevation changes between 2014 and 2019, the TanDEM-X DEM
of 2014 were regarded as the reference DEM when performing D-InSAR processing to
the TSX/TDX acquisitions observed in 2019. An iterative D-InSAR also was applied. The
multi-look numbers and oversample rate were the same as for the procedure of deriving
glacier height changes between 2000 and 2014.
Evaluating penetration depth
Penetration differences between C- and X-band radar were estimated by comparing C-
and X-band SRTM DEM as they were the only available datasets that observed simultan-
eously. The height systems were different for C- and X-band SRTM: the former was
EGM96 geoid orthometric height; the latter, WGS-84 ellipsoidal height (Marschalk et al.
2004). This difference of geoidal surface was adjusted using data from online (UNAVCO
2021). Given that glacier height changes between 2014 and 2019 were derived by
TanDEM-X DEM, no penetration depth correction has been performed. We binned the
penetration depth in every 50m elevation.
Accuracy estimations
The errors in glacier elevation changes include systematic and penetration depth errors.
We assess systematic errors through elevation change in off-glaciers, and adopt the fol-
lowing Eqs. (1) and (2) to calculate the systematic error (Bolch et al. 2011):
e ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
SE2 þMED2
p
(1)
SE ¼ STDVno glacffiffiffi
n
p (2)
where e refers to systematic error, SE refers to standard error, and MED stands for mean
elevation difference between SRTM and TanDEM-X in off-glacier areas. The SE was
determined based on the SD of elevation change (STDVno glac) and square root of the
pixel number (n), both in off-glacier areas. The error of the penetration depth difference
can be calculated using Eq. (3) (Li et al. 2018).
Errpd ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
rcxonffiffiffiffiffiffiffiffiffiffiffiffiffi
Neffcxon
p� �2
þ rcxoffffiffiffiffiffiffiffiffiffiffiffiffiffi
Neffcxoff
p� �2
s
(3)
where Errpd is the error of the penetration depth difference, (rcxon ) is the root mean
square error (RMSE) of the penetration depth difference, and Neffcxon is the number of
effective measurements on glaciers. rcxoff is the RMSE of the penetration depth difference,
and Neffcxoff
is the number of effective measurements off-glaciers. A totalerror Errtot was
calculated using Eq. (4).
Figure 2. Methodology flow chart.
GEOCARTO INTERNATIONAL 5
Errtot ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
e2 þ Errpd2
q
(4)
Results and discussion
In the Qilian Mountains, the penetration depth difference between the C- and X-band
radars in glacier ice was 1–2m below the altitude of 4500m, 2–3m at altitudes of
4500–4650m, and 3–3.5m above the altitude of 4650m. The region-wide average penetra-
tion depth difference was 3.1m.
Considering the errors from the differencing between TSX/TDX and SRTM-C DEM,
the MED is 0.02m, STDVno glac is 2.27m, autocorrelation distance is set to be 1000m, n
is 15 412, rcxon is 6.4m, and rcxoff is 5m; we obtain a systematic error of 0.03m, the
penetration depth difference error of 0.77m, and total error of 0.8m or 0.06m year�1.
When evaluating the error from two epochs of TSX/TDX SAR images, there are no the
errors from penetration depth difference. In off-glacier areas, the MED was 0.39m, SD of
elevation change was 1.44m, n was 316185, and total error was 0.47m or 0.09m year�1.
The glacier height changes map is presented by Figures 3 and 4. Most parts of glacier
coverage experienced rapid degradation. A small proportion in the accumulation area
shows an increasing of height; the mean elevation of all glaciers decreased by
(–0.64 ± 0.06) m year�1 during the period 2000–2014. Presuming ice density is (850 ± 60)
kg m�3, the geodetic glacier mass balance was (–0.54 ± 0.06) m w.e. (water equivalent).
From 2014 to 2019, the glacier height change for the Gangshika peak and surrounding
region was (–0.68 ± 0.09) m year�1.
Glacier height changes were related to elevation. We subdivided glacier surface with an
elevation bin of 50m, and took average elevation change values of each bins as values in
the bins and the SD error of elevation change as elevation change error. Glacier height
change curves as a function of altitude interval are presented in Figures 5 and 6. During
2000–2014 (Figure 5), below ～4900m, the glacier downwasting rates decreased nearly
linearly with increasing elevation; between 4900 and 5200m, the glacier height changes
values were almost the same, except for the altitude of 5250m. At 5250m, glaciers exhib-
ited a positive mass balance. During 2014–2019 (Figure 6), the height change curve was
similar to that during 2000–2014; positive mass balance also appeared at 5250m.
Glacier elevation changes for Shuiguan Nos. 1–4 and Ningchan Nos. 1–4 and 6 are
presented in Figure 7, meanwhile, the flow line of these glaciers were displayed; nine gla-
ciers experienced mass losses at the rate of �0.61m year�1, which is identical to the val-
ues obtained by the RTK–GPS measurement during 1972–2010 (Cao et al. 2014). The
Shuiguan No. 4 Glacier presented an average downwasting rate of �0.58m year�1, which
was similar to the RTK–GPS measured surface lowering rate of �0.56m year�1 during
1972–2010 (Cao et al. 2014). Both the measuring approaches showed that the thinning
value decreased with increase of altitude. On 6 August 2019, we investigated the
Ningchan No. 3 Glacier surface elevation by RTK–GPS during a field expedition. We
compared the measured values with values from STRM–C DEM on corresponding points,
and calculated elevation changed during 2000–2019 for those points. We performed a lin-
ear–regression analysis between mean annual elevation change values from RTK–GPS and
D-InSAR, and identified a strong correlation coefficient of 0.83 (Figure 8). As presented
in Table 2, the highest thinning rate of 0.76m year�1 was recorded for Shuiguan No. 3
Glacier; however, its mean slope (22.4�) was the smallest among the five glaciers. The
Ningchan No. 4 Glacier had an annual elevation change of 0.55m year�1, which was the
6 Q. ZHANG ET AL.
smallest; however, it had the largest mean slope (24.6�), which suggested a possible weak
negative correlation between glacier elevation change and its slope (Cao et al. 2014).
For the locations of nine glaciers in the LLM, see Figure 1.
Remote sensing observation revealed that glacier coverage in the LLM was 60.77 km2
in 2001 and 53.52 km2 in 2014, and glacier area declined by 13.5% during 2001–2014 and
annual average loss rate was 1.04% year�1. Early studies show that glacier area in the
LLM retreated by 0.98% year�1 (Cao et al. 2010), which is smaller than our results and
represents an increase in glacier area loss rate in recent years. The glacier area in the
Heihe Watershed in the middle Qilian Mountains decreased by 0.62% year�1 during
2000–2010, and that in the Daxue Mountains in the western Qilian Mountains decreased
Figure 3. Map of glacier elevation change in the Lenglongling Mountains during 2000–2014. Maps (a) and (b) pre-
sented for glaciers in the western and eastern parts separately from the manual dividing line in Figure 1.
GEOCARTO INTERNATIONAL 7
by 0.56% year�1 during 2000–2010. The glacier area in the east Qilian Mountains shows
the largest rate of shrinkage—larger than in the middle and west parts; glacier area
changes have a similar spatial heterogenous pattern with elevation change.
When examining the typical glacier area change shown in Figure 9, the Ningchan Nos.
3–4 and Shuiguan Nos. 2–4 glacier area decreased by 5.2, 8.2, 8.2, 18.1, and 5.6%, respect-
ively, during 2001–2014. The Shuiguan No. 3 Glacier area indicated the biggest declining
rate; its elevation lowering rate was also the largest.
Based on the precipitation and temperature data from the Menyuan Meteorological
Station, which was near the study area, we adopted the Mann–Kendall statistical approach
(Mann 1945; Kendall 1975) and Sen’s slope estimator (Sen 1968) to analyse the climate
change trends with the significance (Figures 10 and 11). Temperature showed a consistent
and remarkable increasing during 1990–2014: the increasing rate was 0.084 �C year�1
Figure 5. Glacier elevation changes per year in the Lenglongling Mountains in each elevation bin of 50m dur-
ing 2000–2014.
Figure 4. Map of glacier elevation changes in the Gangshika peak and its surroundings in Lenglongling Mountains
during 2014–2019.
8 Q. ZHANG ET AL.
(p< 0.01); increasing temperature was the main factor of glacier height reduction.
Precipitation in this area was dominated by the East Asian monsoon. Precipitation had a
small fluctuating amplitude during 1990–2014; the annual precipitation registered a slight
increase of 0.33mm year�1 (p> 0.5), which cannot compensate the ice-loss induced by
temperature rise. Each glacier had a difference value in elevation lowering, which reflects
the accumulation and ablation conditions in different glacier catchment, maybe caused by
glacier geomorphology such as slope, aspect, etc. and local meteorological variables.
The glaciers of the Daxue Mountains (including Laohugou No. 12 Glacier) in the west
Qilian Mountains thinned at the rate of (–0.20 ± 0.07) m w.e. year�1 (Sun et al. 2018).
Climate data of this area showed an increasing trend for temperature since the 1950s,
although precipitation too had a slight increase. The mass balance of the Qiyi Glacier in
the middle Qilian Mountains during 2005–2010 was �0.50m w.e. year�1 (Yao et al.
Figure 7. Shuiguan and Ningchan glaciers’ elevation changes during 2000–2014.
Figure 6. Glacier elevation changes per year in the Gangshika peak and its surroundings in the Lenglongling
Mountains in each elevation bin of 50m during 2014–2019.
GEOCARTO INTERNATIONAL 9
Table 2. Glaciers’ parameters and elevation changes in the Ningchan and Shuiguan rivers’ headwater.
Glacier
Ningchan Shuiguan
NO.3 NO.4 NO.2 NO.3 NO.4
Area（km2） 1.22 1.2 2.79 1.34 1.44
Mean slope（�） 22.5 24.6 24.4 22.4 23.3
Mean aspect N NE N NE NE
Altitude range（m） 4151 4228 4123 4188 4264
–4759 –4810 –4905 –4905 –4914
Mean surface elevation change（m） –8.76 –7.71 –9.71 –10.67 –8.07
Mean annual surface elevation change (m year–1) –0.63 –0.55 –0.69 –0.76 –0.58
Figure 9. The typical glacier area change during 2001–2014 in Lenglongling Mountains.Figure 8. Comparison of the annual average elevation changes for the Ningchan No. 3 Glacier, calculated by the
RTK–GPS and differential interferogram.
10 Q. ZHANG ET AL.
2012). The snow line altitude slightly increased during 1990–2010, and summer tempera-
ture and annual precipitation show an increasing trend (Guo et al. 2015). Precipitation
had no obvious change trend in the east Qilian Mountains during 1990–2014; tempera-
ture had a prominent increasing trend, leading to glacier elevation change at the rate of
(–0.54 ± 0.06) m w.e. year�1; and elevation thinned at (0.52 ± 0.06) m w.e. year�1 for the
nine glaciers in the Ningchan and Shuiguan rivers’ catchments. The thinning rate of the
Laohugou No. 12 Glacier in the west Qilian Mountains was smaller than that of the Qiyi
Glacier in the middle Qilian Mountains, and Qiyi Glacier’s retreat rate was smaller than
those of glaciers in the Ningchan and Shuiguan rivers’ catchments. The Menyuan
Meterological Station (east Qilian Mountains) recorded annual mean temperature increase
rate of 0.084 �C year�1 during 1990–2014. The Yeniugou, Tuole, Qilian, and Sunan
Meterological Stations (middle Qilian Mountains) recorded annual mean temperature
increase rate 0.065 �C year�1 during 1990–2010 (Bie et al. 2013); 0.037 �C year�1 was
recorded in the Laohugou Watershed (west Qilian Mountains) during 1957–2013 (Qin
et al. 2015). Temperature increase rate in the eastern part was greater than that in the
Figure 10. Changing trend of mean summer temperature during 1990–2014 recorded at the Menyuan Meteorological
Station in eastern Qilian Mountains.
Figure 11. Changing trend of annual precipitation during 1990–2014 recorded at the Menyuan Meteorological Station
in eastern Qilian Mountains.
GEOCARTO INTERNATIONAL 11
middle and western parts. The annual precipitation increase rate was 0.33mm year�1 in
the eastern part (Mengyuan Meterological Station records), 1.26mm year�1 in the middle
part (the Heihe Watershed records) (Wang et al. 2011), and 1.22mm year�1 in the west-
ern part (the Subei Meteorological Station records) (Wang et al. 2016). The spatial differ-
ence of temperature and precipitation responsible for glacier recession rate in the eastern
part was bigger than that in the middle and western parts.
The patterns of glacier height changes were almost identical before and after 2014; the
iterative D-InSAR with the TerraSAR-X/TanDEM-X images can provide geodetic glacier
mass balance information at sub-decadal and decadal scales.
Conclusions
In this study, TerraSAR-X/TanDEM-X images of high resolution and iteratively D-InSAR
were used to calculate glacier elevation change in the LLM at the decadal and sub-decadal
timescales. The results showed that glaciers thinned by (–0.64 ± 0.06) m year�1 during
2000–2014 in the whole LLM and (–0.68 ± 0.09) m year�1 during 2014–2019 for the
Gangshika peak and its surroundings. With increase in elevation, the lowering value of
elevation decreased, and glacier elevation increased at the elevation bin of 5250m. To val-
idate the above results, we carried on a field expedition to Nichan No.3 Glacier using
RTK–GPS; the value of annual average elevation change from field measurements have a
strong relationship with values from D-InSAR at the corresponding points, and a correl-
ation coefficient of 0.83 was found between them. Glacier thinning values have weak rela-
tionships with the mean slope. Glacier area decreased by 13.5% during 2001–2014; the
average annual decreasing rate was 1.04% year�1, which is greater than that in the middle
and west parts. The heterogeneity of area change was consistent with that of elevation
change. Climate data in this area revealed that since 1990, precipitation showed no obvi-
ous change, temperature displayed a continuous and pronounced increase, glacier reces-
sion has mainly been driven by climate change, and glacier downwasting rate in the LLM
(east Qilian Mountains) was greater than that in the middle and west Qilian Mountains.
Acknowledgments
The TerraSAR-X/TanDEM-X data were obtained under a proposal submitted to the German Aerospace
Centre (DLR) named Glacier Elevation Change in the Pamirs and Tibet Plateau (proposal
ID:NTI_BIST3395).
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
This work was supported by the National Nature Science Foundation of China [41671065]; Key Research
Program of Hunan University of Arts and Science [20ZD03]; Applied Economics [XJT(2018)469]; the
Hunan Nature Science Foundation [2021JJ30474]; Hunan Provincial Social Science Achievement Review
Committee subject [XSP22YBC330].
12 Q. ZHANG ET AL.
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14 Q. ZHANG ET AL.
http://www.unavco.org/community_science/science-support/geoid/geoid.html
	Abstract
	Introduction
	Study area and data
	Study area
	Data
	Methods
	Deriving glacier elevation change
	Evaluating penetration depth
	Accuracy estimations
	Results and discussion
	Conclusions
	Acknowledgments
	Disclosure statement
	Funding
	References