QUANTITATIVE EVALUATION OF LANDSAT 7 ETM+ SLC-OFF IMAGES FOR
SURFACE VELOCITY ESTIMATION OF MOUNTAIN GLACIERS a
Yongling SUN 1,2); Liming JIANG 1); Lin LIU 1,2); Sisheng WANG 1,2); Gang Li 3）；Hansheng WANG 1)
1）State Key Laboratory of Geodesy and Earth‘s Dynamics, Institute of Geodesy and Geophysics, CAS，Wuhan 430077
2）University of Chinese Academy of Sciences，Beijing 100049
3）Institute of Space and Earth Information Science, The Chinese University of HongKong
Introduction & objectives The Landsat mission series (Landsat 1-5, 7 and 8) provide the only
detailed and consistent data source for mapping and monitoring the
global glacier changes over the last 40 years. However, the scan-line
corrector (SLC) of the ETM+ sensor on board Landsat-7 permanently
failed at 31 May 2003, which formed wedge-shaped data gaps from the
nadir path in any SLC-off images, resulting in roughly 22% of the pixels
to be missed. The SLC failure has left a serious problem for the glacial
applications of ETM+ data, particularly for monitoring long-term glacier
dynamics in High Asian Mountain where has few available data due to
the frequently cloudy covers.
In this study, we aim to evaluate the potential of the Landsat-7 SLC-off
images to derive surface velocities of mountain glaciers.
Study area
We select the
Siachen glacier as our
test site, which is
located in the central
Karakoram. At about
72km long, it is the
longest glacier in the
Karakoram and the
second largest valley
glacier in the world
outside the polar
region. Figure 1.
shows the study area
location. The black
solid line is the border
of the Siachen glacier.
The black dashed
(AA’) line is the center
line.
Results
Conclusions and perspectives
The work in this paper was supported by National Key Basic Research Program of China (973 Program, grant No. 2012CB957702), National Natural Science Foundation of China (Grant No.
41274024) and the Hundred Talents Program of the Chinese Academy of Sciences (Grant No.
Y205771077). The authors thanks NASA for providing the used Landsat TM/ETM+ imagery and SRTM DEM.
ESA – MOST China Dragon Cooperation, 2015 DRAGON SYMPOSIUM, 22 to 26 June 2015, Interlaken, Switzerland
Figure 3. Comparison of the glacier annual average surface velocity. (a)
Velocities estimated with Landsat TM images; (b), (c)Velocities estimated
with Landsat ETM + SLC-off images recovered by LLHM and WLR,
respectively; (d) Surface velocities along center line(AA’ in Figure 1).
Data and method
In the study, a pair of SLC-off images acquired on 12 Aug 2009 and 31
Aug 2010 were used for the purpose of evaluating the potential of the
Landsat-7 SLC-off images in deriving surface velocities of mountain
glaciers. Moreover, another pair of SLC-off images acquired on 27 Jul
2009 and 2 Oct 2010 were used to repair the above corresponding
images. Due to lack of the in situ measurements, we utilized glacier
velocity from two Landsat TM images acquired on 4 Aug 2009 and 23
Aug 2010 to verify the results of the recovered SLC-off images.
The main processing chain consists of three steps: (1) Two typical
filling-gap methods, the localized linear histogram match (LLHM)[1] and
the weighted liner regression (WLR)[2], were utilized to recover the
mentioned SLC-off images. (2) These two recovered pairs were
respectively applied for deriving glacier-surface velocities with the
COSI-Corr feature tracking procedure. (3) The resulting glacier
velocities were quantitatively compared with that of a pair of Landsat-5
TM images which were acquired nearly at the same time with the SLC-
off pair.
Figure 2. Comparison of a SLC-off
image before and after filling-gap. (a)
Landsat ETM+ SLC-off image
acquired on 12 Aug 2009; (b),(c) the
results recovered by LLHM and WLR,
respectively. The Landsat ETM+ SLC-
off image is recovered well by both
the LLHM and WLR methods. But the
WLR method achieves a better
performance of gap recovering than
the LLHM method.
◄Ice velocity
vector
References Acknowledgee
[1] USGS (2004).Phase2 gap-fill algorithm: SLC-off gap-filled products gap-fill algorithm methodology.
Available online at landsat.usgs.gov/documents/L7SLCGapFilledMethod.pdf
[2] Zeng, C., H. Shen and L. Zhang (2013). "Recovering missing pixels for Landsat ETM+ SLC-off imagery
using multi-temporal regression analysis and a regularization method." Remote Sensing of Environment
131: 182-194.
Email: [email protected]
A
A’
a
c
b
a
c
b
d
The recovered results show that the WLR method achieves a better
performance of gap recovering than the LLHM method.
The surface velocities estimated with the recovered SLC-off images are
highly agreement with those of the TM images, which demonstrates
that Landat ETM+ SLC-off data can be utilized to estimate the surface
velocities of mountain glaciers.
The annual mean velocity of the Siachen glacier is approximately 70
m/yr between 2009 and 2010 with a maximum of 280 m/yr close to the
glacial equilibrium line that are similar with the results in previous
studies.
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