IEEE Geoscience and Remote Sensing Magazine - March 2020 - 7

The next three tutorial/review articles focus on deformation-monitoring applications. "Monitoring Buildings at
Landslide Risk With SAR" provides a review of current InSAR
satellite data resources and processing methodologies for application to landslide risk, with an emphasis on the monitoring of buildings. At the end of the article, the authors argue
that future small-satellite constellations planned to provide
very-high-resolution SAR images with daily revisit time will
supply more capability and inspire research in the development of new ideas in InSAR signal processing.
The feasibility of applying InSAR over floodplains and
wetlands has been tested using interferometric coherences.
"Interferometric SAR for Wetland Hydrology" reviews innovative applications of InSAR to hydraulic and hydrologic
analysis of floodplains and wetlands, such as mapping 2D
water-level changes. "Entering the Era of Earth ObservationBased Landslide Warning Systems" offers a tutorial for landslide forecasting and early warning using InSAR deformation-monitoring technology. In particular, the article uses
two recent landslides in China as examples to demonstrate
that 1) satellite radar observations can be used to detect deformation precursors to catastrophic landslide occurrences
and 2) early warning can be achieved with real-time, in
situ observations.
Previewing the June special issue, we move on to two
articles on SAR tomography (TomoSAR) techniques, which
extend and improve on traditional InSAR. "From Interferometric to Tomographic SAR" provides an overview of TomoSAR with a particular focus on its application in urban
areas. The article provides several graphical summaries to
give the readers a comprehensive view of TomoSAR. "Forest SAR Tomography" surveys single and polarimetric TomoSAR approaches with reference to the robustness of the
reconstruction and reliability of extracted information. In
addition, the article shows several application examples,
including results obtained with the different processing
techniques provided to summarize the efficiency of forest
monitoring using TomoSAR.
Topics in InSAR ground moving-target indication (GMTI),
polarimetric InSAR (Pol-InSAR), and interferometric phase
denoising are included in the final three articles. "AlongTrack Interferometric SAR systems for Ground-Moving
Target Indication" reviews the techniques of GMTI using
along-track interferometry. "InSAR Phase Denoising" gives a
comprehensive overview of phase-denoising methods, classifying the established and emerging algorithms into four
main categories: traditional local, transformed-domain,
nonlocal, and sparsity-driven filters. "Polarimetric SAR
Interferometry" briefly reviews the relevant techniques
involved in system-parameter analysis of Pol-InSAR and
presents a case study-based tutorial demonstrating how
to analyze the impact of system parameters on the performance of an end application and so further optimize the
system design.
The selected articles informally explain InSAR technology, but they do not shy away from demonstrating practical
MARCH 2020

IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

applications. Our hope is that, by addressing both aspects,
readers of all levels will be able to gain a better understanding of the foundation of InSAR and the "when, how, and
why" of applying this technology.
AUTHOR INFORMATION
Mengdao Xing (xmd@xidian.edu.cn) received his B.S. and
Ph.D. degrees from Xidian University, China, in 1997 and
2002, respectively. He is currently a professor with the National Laboratory of Radar Signal Processing at Xidian University and associate dean of the Academy for Advanced Interdisciplinary Studies. He received the honor-nomination
of National Excellent Doctoral Dissertation Award in 2004
and the Shaanxi Province Nature Science Award in 2018.
Currently, he serves as associate editor for synthetic aperture
radar (SAR) research for IEEE Transactions on Geoscience and
Remote Sensing. He has also served as guest editor for special
issues of IEEE Geoscience and Remote Sensing Magazine and
Sensors. His research interests include SAR, inversed SAR,
sparse signal processing, and microwave remote sensing. He
is a Fellow of the IEEE.
Vito Pascazio (vito.pascazio@uniparthenope.it) received
his B.S. degree (cum laude) in electronic engineering from
the University of Bari, Italy, in 1986 and his Ph.D. degree in
electronic engineering and computer science from the the
Department of Electronic Engineering, University of Napoli
"Federico II," Italy, in 1990. That same year, he joined the
Università di Napoli "Parthenope," Italy, where he is currently a full professor of telecommunications. In 1990, he was
awarded the Philip Morris Prize for Scientific and Technological Research. He has published approximately 200 technical papers, and he served as general cochair of the 2105
IEEE International Geoscience and Remote Sensing Symposium (IGARSS) and as member of the technical committees
of several IGARSS meetings. His research interests include
synthetic aperture radar image processing, microwave tomographic image reconstruction, biomedical image processing,
and linear and nonlinear statistical signal processing. He is a
Senior Member of the IEEE.
Hanwen Yu (yuhanwenxd@gmail.com) received his B.S.
and Ph.D. degrees in electronic engineering from Xidian
University, Xi'an, China, in 2007 and 2012, respectively,
and his M.S. degree in computer science from the University of Memphis, Tennessee. He is currently a postdoctoral
research fellow with the Department of Civil and Environmental Engineering, National Center for Airborne Laser
Mapping, University of Houston, Texas. He has authored or
coauthored more than 20 research papers in high-impact,
peer-reviewed journals, including IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Image Processing, and Remote Sensing of Environment. He has served as guest
editor of special issues of IEEE Geoscience and Remote Sensing
Magazine and Sensors. His research interests include phase
unwrapping, algorithm design, and synthetic aperture radar
interferometry signal processing and applications.
GRS

IEEE Geoscience and Remote Sensing Magazine - March 2020

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