IEEE Geoscience and Remote Sensing Magazine - March 2019 - 31

still many doors open for further investigation, both
from the theoretical and application perspectives, even
though the field of remote sensing data fusion is mature.
We hope this review reveals new possibilities for readers to further explore the remaining issues in developing
sophisticated fusion approaches suitable for the applications at hand.
AcknOwLEDGmEnTs
This research was supported by the Helmholtz-Zentrum
Dresden-Rossendorf High Potential Program (specifically supporting Pedram Ghamisi), the Natural Science
Foundation of China under contract 71331005, and the
State Key Research and Development Program of China
under contract 2016YFE0100300. In addition, we would
like to thank the National Center for Airborne Laser Mapping at the University of Houston for providing the CASI
Houston data set and the IEEE Geoscience and Remote
Sensing Society's Image Analysis and Data Fusion Technical Committee for organizing the 2013 Data Fusion Contest. Moreover, we wish to thank Dr. Claas Grohnfeldt for
processing J-SparseFI-HM.
AUThOr inFOrmATiOn
pedram Ghamisi (p.ghamisi@gmail.com) received his B.Sc.
degree in civil (survey) engineering from the Tehran South
Campus, Azad University, Iran, in 2008; his M.Sc. (first-class
honors) degree in remote sensing from the K.N. Toosi University of Technology, Tehran, Iran, in 2012; and his Ph.D.
degree in electrical and computer engineering from the University of Iceland, Reykjavik, in 2015. Since early 2018, he
has worked as the head of the machine-learning group at
Helmholtz-Zentrum Dresden-Rossendorf. He received the
Best Researcher Award for M.Sc. students from the K.N. Toosi University of Technology during the 2010-2011 academic
year. In 2017, he won the Data Fusion Contest organized by
the Image Analysis and Data Fusion Technical Committee
of the IEEE Geoscience and Remote Sensing Society. He was
the winner of the 2017 IEEE Geoscience and Remote Sensing Letters Best Reviewer Prize. He received the prestigious
Alexander von Humboldt Fellowship in 2015 and is an associate editor of IEEE Geoscience and Remote Sensing Letters.
He is a Senior Member of the IEEE. For more info, please see
http://pedram-ghamisi.com/.
behnood rasti (behnood@hi.is) received his B.Sc.
and M.Sc. degrees in electrical and electronics engineering from the University of Guilan, Rasht, Iran, in 2006
and 2009, respectively, and his Ph.D. degree in electrical
and computer engineering from the Department of Electrical and Computer Engineering, University of Iceland,
Reykjavik, Iceland, in 2014. From 2015 to 2016, he was
a post-doctoral researcher with the University of Iceland.
From 2016 to 2018, he was with the Keilir Institute of
Technology, Reykjanesbaer, Iceland. He is currently with
the Department of Electrical and Computer Engineering,
University of Iceland. His research interests include signal
march 2019

ieee Geoscience and remote sensing magazine

and image processing, hyperspectral image analysis, remote sensing data fusion, biomedical engineering, biomedical data analysis, control systems, and robotics. He is
a Member of the IEEE.
naoto yokoya (naoto.yokoya@riken.jp) received his
M.Sc. and Ph.D. degrees in aerospace engineering from the
University of Tokyo in 2010 and 2013, respectively. From
2012 to 2013, he was a research fellow with the Japan Society for the Promotion of Science, Tokyo. From 2013 to 2017,
he was an assistant professor with the University of Tokyo.
From 2015 to 2017, he was an Alexander von Humboldt
Research Fellow with the German Aerospace Center, Oberpfaffenhofen, and the Technical University of Munich,
Germany. Since 2018, he has been the leader of the Geoinformatics Unit at the RIKEN Center for Advanced Intelligence Project, Tokyo. His research interests include image
analysis and data fusion in remote sensing. In 2017, he won
the Data Fusion Contest organized by the Image Analysis
and Data Fusion Technical Committee (IADF TC) of the
IEEE Geoscience and Remote Sensing Society (GRSS). He
is currently a cochair of the IEEE GRSS IADF TC and the
secretary of the IEEE GRSS All Japan Joint Chapter. He is a
Member of the IEEE.
qunming wang received his Ph.D. degree from Hong
Kong Polytechnic University, China, in 2015. He is now a
professor in the College of Surveying and Geo-Informatics
at Tongji University, Shanghai, China. He was a lecturer (assistant professor) and senior research associate in the Lancaster Environment Centre at Lancaster University, United
Kingdom, from 2017 to 2018 and 2015 to 2017, respectively. His three-year Ph.D. study was supported by the Hong
Kong Ph.D. fellowship, and his Ph.D. thesis was awarded as
the outstanding thesis in the faculty. His research interests
focus on remote sensing, image processing, and geostatistics. He has published more than 40 peer-reviewed articles
in international journals such as Remote Sensing of Environment, IEEE Transactions on Geoscience and Remote Sensing
and ISPRS Journal of Photogrammetry and Remote Sensing. He
serves as a reviewer for 30 international journals, including
almost all international journals in remote sensing. He is
now an associate editor for Photogrammetric Engineering and
Remote Sensing and Computers and Geosciences. He is a Member of the IEEE.
bernhard höfle (hoefle@uni-heidelberg.de) received
his Ph.D. degree with excellence in the field of physical geography and geoinformatics at the University of Innsbruck,
Austria, in 2007. He was a junior professor of GIScience
and 3D spatial data processing at the Institute of Geography, Heidelberg University, Germany, from 2011 to 2017. In
2017, he became professor of 3D spatial data processing at
the Institute of Geography and head of the 3DGeo research
group at the Interdisciplinary Center for Scientific Computing at Heidelberg University, Germany. Since 2014, he has
been the cochair of the working group Geoinformatics of
the German Society for Photogrammetry, Remote Sensing, and Geoinformation. His research interests include the
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IEEE Geoscience and Remote Sensing Magazine - March 2019

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