IEEE Geoscience and Remote Sensing Magazine - March 2020 - 85

loss of mining deformation observations in those areas
with high gradients and/or large magnitudes (e.g., the central part of a subsidence basin). This dramatically reduces
the accuracy of the model parameter inversion and deformation prediction [8] due to the high nonlinearity of the
deformation in space. Admittedly, to some extent it should
be possible to improve the accuracy of model parameter
inversion by fusing InSAR measurements having severe
phase decorrelation with ground-based geodetic deformation observations (e.g., 3D laser scanner or leveling) [80],
[113]. Nevertheless, this strategy cannot work in cases of a
lack of ground-based deformation observations (which is
very common). It is therefore important to inverse model
parameters from SAR-based deformation measurements
over those mining areas with phase decorrelation only.
In addition, improving the estimation steps of InSARbased model parameter inversion is a potential research
topic for those mining areas with high coherence. The
previous InSAR-based methods first selected the deformation model and then inversed the related model parameters with InSAR measurements from a single viewing geometry. However, the model errors of the selected
model and the single-geometry deformation observations
would potentially limit the accuracy of the model parameter estimates, thus reducing the reliability of 3D mining
deformation prediction and mining-related geohazard assessment conducted on the basis of inversed model parameters (see the "InSAR Based 3D Mining Displacement
Prediction and Damage Assessment" section). Hence, testing and/or developing deformation models and introducing all available multisource (e.g., spaceborne, airborne,
and ground-based) deformation observations are likely to
present a promising way to improve the accuracy of model
parameter inversion.
POTENTIAL APPLICATION EXPLORATION FROM InSAR
3D MINING DISPLACEMENTS
As discussed previously, most prior studies have focused
on InSAR-based 1D/2D mining deformation retrieval and
3D mining displacement reconstruction. In addition, a few
InSAR-based applications have been attempted for InSAR
model parameter inversion, 3D displacement prediction,
and geohazard assessments in mining areas. Consequently,
the greater potential of InSAR measurements should be explored in the future, given the advantages of InSAR over
traditional geodetic techniques (e.g., high spatial resolution, low cost, and large spatial coverage). Several potential
applications are as follows:
◗◗ Denser InSAR deformation observations would be very
useful for interpreting the complex mechanism of mining deformation.
◗◗ Deformation observations over time could be applied
to the modeling of mining deformation evolution by
mathematical modeling or machine learning.
◗◗ InSAR-derived historic deformation could be used to
guide land reclamation and reuse in mining areas.
MARCH 2020

IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

CONCLUSIONS
In this article, the development and application of SAR/InSAR
techniques in mining areas over the past two decades were
systematically reviewed. Prior to the generation of the first
mining deformation map by DInSAR in 1996, most previous
studies had focused on accurate retrieval of 1D/2D LOS and/
or azimuth displacements using SAR/InSAR methods due
to some of the distinct technique advantages of InSAR over
mining areas (e.g., severe phase decorrelation, high deformation gradients, and large deformation magnitudes). In recent
years, attempts were made to reconstruct full 3D mining displacements from InSAR 1D/2D displacement measurements
to overcome the inherent limitation of 1D/2D displacement
observations, because they cannot completely reveal real
mining deformation patterns in a 3D space. In addition, the
potential of InSAR measurements in model parameter inversion, mining displacement prediction, and mining-induced
geohazard assessment was explored.
Finally, some main challenging issues that hinder SAR/InSAR-based 1D/2D displacement monitoring, such as InSAR
phase decorrelation, the mitigation of the APS, and large deformation retrieval, were discussed. In the future, some open
problems in the robust estimation of InSAR 3D mining displacements, processing improvement of InSAR-based model
parameter inversion, and potential exploitation of InSAR in
mining areas could be focused on and addressed to broaden
the application scope of InSAR in mining areas.
ACKNOWLEDGMENTS
This work was partly supported by the National Key R&D
Program of China (grant 2018YFC1503603), the National Science Fund for Distinguished Young Scholars (grant
41925016), the National Natural Science Foundation of
China (under grants 41904005 and 41474008), the Innovation Leading program of Central South University
(grant 506030101), and the Talents Gathering program of
Hunan Province China (grant 2018RS3013).
AUTHOR INFORMATION
Zefa Yang (yangzf@csu.edu.cn) received his bachelor's

and Ph.D. degrees in surveying engineering from the China
University of Mining and Technology, Xuzhou, and Central South University, Changsha, China, in 2011 and 2018,
respectively. From October 2015 to 2017, he was an exchange Ph.D. candidate in geodesy and survey engineering at RWTH Aachen University, Germany. He is currently
a full professor with the Department of Surveying and
Remote Sensing, School of Geosciences and Info-Physics,
Central South University. His research interests include interferometric synthetic aperture radar and its applications
for monitoring and modeling ground surface deformation
associated with underground extraction. He has published
more than 20 papers in international peer-reviewed journals. He is a Member of the IEEE.
Zhiwei Li (zwli@csu.edu.cn) received his bachelor's and
master's degrees in surveying engineering from the Central
85

IEEE Geoscience and Remote Sensing Magazine - March 2020

Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - March 2020