IEEE Geoscience and Remote Sensing Magazine - June 2020 - 115

Equation (2) can convert the phase to the average
phase rate,
{p - {p - 1
vp = tp - tp - 1 ,

(2)

and a new matrix equation (3) is obtained:
B V = d{.

(3)

B is an M # N matrix. The strategy of multimaster images tends to cause the rank defect of matrix B, and the
SVD method is adopted for matrix B to further obtain
the minimum norm solution of the velocity vector. Finally,
the displacement value of each time period can be obtained
by integration in the time period.
There are also many successful applications of SBAS
technology in ground deformation monitoring. For example, in 2013, Chaussard et al. [67] used SBAS technology
to monitor nine cities with rapid subsidence in the coastal
areas of western Indonesia and analyzed its causes. Hu et al.
[68] used SBAS technology to analyze the ground subsidence in Beijing and compared the results with the leveling
results. Their research found that the long-term subsidence
estimation results obtained by the SBAS method are in
good agreement with the development trend of groundwater overexploitation. In 2014, Chaussard et al. [69] used
2007-2011 ALOS data to monitor land subsidence throughout central Mexico with SBAS technology. They used the
correlation between subsidence and land utilization to
confirm that groundwater exploitation is the leading cause
of subsidence. In 2015, Grzovic et al. [70] used SBAS and
PSInSAR to evaluate the land subsidence caused by underground coal mining in Springfield, Illinois. The study
revealed several subsidence locations that may be caused
by the collapse of abandoned underground roadways. The
study also revealed that one of the advantages of satellite
monitoring is the discovery of unknown areas of deformation. In 2017, Zhou et al. [17] used SBAS to make a spatial
and temporal analysis of land subsidence in Beijing based
on 47 TerraSAR-X SAR images from 2010 to 2015.
In 2008, Hooper [71] proposed the multitemporal InSAR (MT-InSAR) algorithm based on SBAS and PSInSAR
technologies. MT-InSAR greatly expands the application
range of InSAR in the field of deformation monitoring
and increases the applicability of InSAR technology. For
example, Gao et al. [72] used the MT-InSAR technique to
investigate the land deformation on the Beijing Plain from
2003 to 2013. The algorithms developed based on the
PSInSAR idea mainly include IPTA [51], STUN, StaMPS
[73], [74], PSP [75], SqueeSAR [76], QPS [77], geodetic
PSInSAR, SL1MMER [78], and tomo-PSInSAR [79], among
others. The algorithms developed based on the SB concept
mainly include SBAS [67], CT [80], StaMPS, TCP-InSAR
[81] and PSIG [82]. In 2011, Ferretti et al. [76] proposed the
SqueeSAR method, which compensates for the limitations
of the PSInSAR method for extracting target points with
high coherence and phase stability, and pointed out that
JUNE 2020

IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

the SqueeSAR method processes the permanent scatterer
point and the distributed scatterer point together. StaMPS
technology applies to areas with large gradient sinking and
dense vegetation and can obtain stable and reliable settlement monitoring results, mainly because it does not have
model constraints on the deformation, and the technique
selects the permanent scatterer point according to the stability of the interference phase and the spatial correlation
principle [73], [74]. Using the StaMPS software developed
by Stanford University, the velocity field of deformation
can be obtained.
In recent years, more and more researchers have been
working on the InSAR deformation monitoring method.
However, traditional InSAR technology has some drawbacks. For example, these methods are almost all based on
SB InSAR PU, which is limited by the phase continuity assumption. However, in reality, especially in complex surface
deformation monitoring, many terrains do not satisfy this
assumption, so the traditional InSAR technology is greatly
challenged in actual monitoring. The emergence of the
multibaseline (MB) InSAR PU
THIS ARTICLE AIMS TO
has eliminated the limitation
IMPROVE AWARENESS OF
of this assumption. This MB
THE FEASIBILITY AND
InSAR PU is suitable for monPOTENTIAL OF InSAR
itoring areas where terrain
TECHNOLOGY IN OIL
information is discontinuous
and strong phase variation
PRODUCTION DEFORMATION
exists [83]. However, most of
MONITORING BY USING A
the currently proposed MB
REAL APPLICATION CASE.
InSAR PU methods still have
defects. These methods have
been extended and improved
by many scholars. For example, Yu et al. [84] transplanted
the MB InSAR PU method into traditional three-pass D-InSAR and improved the defect of most MB InSAR PU methods, which is that the terrain height of the corresponding
pixels in different interferograms must be the same. They
proposed a novel MB InSAR PU methodology-based threepass terrain deformation estimation approach called the
MTDA method. Experiments have also proven that MTDA is
an effective deformation estimation method.
It can be seen that, with the development of InSAR technology, researchers apply it to different fields and various
types of land deformation monitoring, and they carry out
a large number of experiments and demonstrations, which
provide a rich experience for the application of InSAR
technology. With the continuous expansion of the application field, the technology has been gradually improved,
which provides the possibility that InSAR technology can
be widely used in the area of oil and gas exploitation. The
continuous spatial coverage and high-resolution features
of InSAR technology are not available in traditional monitoring methods. Combining this technology with conventional techniques can achieve higher precision and more
efficient results.
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IEEE Geoscience and Remote Sensing Magazine - June 2020

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