IEEE Geoscience and Remote Sensing Magazine - March 2020 - 33
Shijingshan, and Haidian districts. The coverage is roughly 680 km 2 and the resolution is 2.3 m × 13.9 m. The
subsidence results were superimposed on Google Earth.
Forty-five SAR images were acquired from the Sentinel-1
satellite during a descending orbit, spanning 8 January
2017 to 7 August 2018. A large subsidence area is visible
in the northern part of the map near Shangzhuang Town
in the northeastern part of the Haidian district, with a
maximum deformation rate of −30 mm per year. Here,
the subsidence is caused mainly by groundwater exploitation. The other areas, such as the Mentougou, Fengtai,
Shijingshan, and Fangshan districts, showed a relatively
stable surface environment without extensive geological
subsidence. Figure 14(b) shows the linear deformation
rate intuitively using a 3D graph.
RAILWAYS
Roads, railways, and bridges are important infrastructures
that are widely distributed in cities and characterized by a
wide and line-infrastructure distribution. These infrastructures often undergo relatively large deformations. Longterm vehicle rolling, subsidence caused by self-weight, or
deformation caused by geological changes may cause instability in these facilities, bringing serious harm. Therefore,
it is importance to monitor whether they operate healthily and safely. To monitor targets such as railways, highresolution SAR images are necessary (e.g., TerraSAR). Such
monitoring also requires very high precision and accuracy
and describes the deformation process during the whole
observation period.
There have been numerous related applications and
analysis cases. For instance, the authors in [101] employed
the time-series InSAR technique to monitor the 3,000-km
railway network throughout the Netherlands using hundreds of SAR images from 2010 to 2015. In [102], Duan et al.
obtained the deformation results of the Beijing-Tianjin
intercity railway and analyzed its deformation along the
railway. Chen et al. [103] acquired the deformation results
of the Qinghai-Tibet railway using the SBAS method and
analyzed the influence of permafrost on railway facilities.
The authors in [104] analyzed the deformation of the Lantau Expressway in Hong Kong, China. Yu et al. [105] used
high-resolution SAR images to analyze the deformation of
the railway and road network in the Xiqing district of Tianjin, China.
We conducted a case study of railway deformation monitoring using the time-series InSAR technique. Figure 15 depicts a section of the Beijing-Tianjin railway deformation
results, totaling 6.3 km long. The data used were 23 SAR
images acquired from the TerraSAR-X satellite, spanning
9 June 2014 to 19 December 2016. The resolution was 2 m
× 1 m. For the sake of reliability and stability, we estimated
the deformation of the whole region and finally extracted
the deformation of the railway part separately and superimposed it on Google Earth.
From the deformation results presented in Figure 15, it
can be seen that there are five subsidence areas in this section of railway line, and the maximum deformation rate
is roughly −22 mm per year. Then, we drew its cumulative
deformation map. From this, it is clear that the maximum
cumulative deformation was greater than 70 mm during
the more than two-year observation period.
LANDSLIDES
Landslides are powerful, widespread natural disasters
that cause great damage, enormous economic losses,
and loss of life [106], [107]. Accordingly, monitoring
and predicting landslides is very important. Presently,
only a wide range of investigation and postdisaster assessment can be achieved, and accurate prediction cannot be done. Using the time-series InSAR application,
medium-resolution and large-scale images are suitable.
Deformation Rate (mm/Year)
N
0
Deformation Rate (mm/Year)
-30
30
60
40
20
0
-20
-40
800
(a)
600
400
200
600
400
Azimuth
200
Range
(b)
FIGURE 14. (a) The subsidence rate map of Beijing City. (b) A 3D graph showing the linear deformation rate.
MARCH 2020
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
33
IEEE Geoscience and Remote Sensing Magazine - March 2020
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