IEEE Geoscience and Remote Sensing Magazine - March 2020 - 156

Contest Data
The data of the 2020 GRSS Data Fusion Contest will remain available to the
GRSS community for benchmarking algorithms and publishing research works.
The data are usable free of charge for scientific purposes, but the contest terms
and conditions on the contest website remain applicable (http://www.grss-ieee
.org/community/technical-committees/data-fusion/2020-ieee-grss-data-fusion
-contest/). Please read them carefully.

Join the GRSS IADF TC
You can contact the GRSS Image Analysis and Data Fusion Technical
Committee (IADF TC) chairs at iadf_chairs@grss-ieee.org. If you are interested
in joining the IADF TC, please complete the form on our website (http://www
.grss-ieee.org/community/technical-committees/data-fusion/), or send an
email to the chairs including your
◗◗ first and last name
◗◗ institution/company
◗◗ country
◗◗ IEEE membership number (if available)
◗◗ email address.
Members receive information regarding research and applications on image
analysis and data fusion topics as well as updates concerning the annual Data
Fusion Contest and all other IADF TC activities. Membership in the IADF TC is
free! You may also join the LinkedIn GRSS data fusion discussion forum: http://
www.linkedin.com/groups/IEEE-GRSS-Data-Fusion-Discussion-3678437.

-Journal of Selected Topics in Applied Earth Observations and Remote Sensing. To maximize impact and promote research in
global land cover mapping with weak supervision, the open
access option will be used for these submissions. The GRSS
will cover the costs related to the open access fees as well as
the winning teams' participation in the awards banquet and
will also sponsor the prizes for the winning teams.
ACKNOWLEDGMENTS
The contest is organized in collaboration with the Research
Group for Signal Processing in Earth Observation (SiPEO)
at the Technical University of Munich (TUM). The IADF
TC chairs would like to thank TUM-SiPEO for providing
the competition data and the GRSS for continuously supporting the Data Fusion Contest through funding and resources. The Copernicus Sentinel 2019 data are available
from the European Space Agency (https://sentinel.esa
.int/). The land cover maps derived from the moderate-resolution imaging spectroradiometer are available from the
Land Processes Distributed Active Archive Center (https://
lpdaac.usgs.gov/).
AUTHOR INFORMATION
Naoto Yokoya (naoto.yokoya@riken.jp) received his M.Eng.
and Ph.D. degrees in aerospace engineering from the University of Tokyo in 2010 and 2013, respectively. He is the
leader of the Geoinformatics Unit at the Riken Center for
Advanced Intelligence Project, Tokyo. Previously, he was
an assistant professor with the University of Tokyo and an
Alexander von Humboldt research fellow with the German
Aerospace Center, Oberpfaffenhofen, and the Technical
156

University of Munich, Germany. His research interests include the development of image processing, data fusion,
and machine-learning algorithms for understanding remote sensing images, with applications to disaster management. He is currently chair of the IEEE Geoscience and
Remote Sensing Society (GRSS) Image Analysis and Data
Fusion Technical Committee and also secretary of the IEEE
GRSS All Japan Joint Chapter. He is an associate editor of
IEEE Journal of Selected Topics in Applied Earth Observations
and Remote Sensing and a Member of the IEEE.
Pedram Ghamisi (p.ghamisi@gmail.com) received his
M.Sc. degree (Hons.) 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. In addition,
in 2015, he was an Alexander von Humboldt research fellow with the Technical University of Munich, Germany,
and Heidelberg University, Germany. From 2015 to 2018,
he was a research scientist with the German Aerospace
Center, Oberpfaffenhofen. Since 2018, he has been head
of the machine-learning group, Helmholtz-Zentrum Dresden-Rossendorf. He is also chief technology officer and cofounder of VasoGnosis Inc., Milwaukee, Wisconsin, where
he is involved in the development of advanced diagnostic
and analysis tools for brain diseases using cloud computing and deep learning algorithms. He is also vice-chair of
the IEEE Image Analysis and Data Fusion Technical Committee. His research interests include interdisciplinary research on remote sensing and machine (deep) learning,
image and signal processing, and multisensor data fusion.
He is a Senior Member of the IEEE and an associate editor of MDPI-Remote Sensing and IEEE Geoscience and Remote
Sensing Letters.
Ronny Hänsch (rww.haensch@gmail.com) received his
undergraduate degree in computer science and his Ph.D.
degree from the Technische Universität Berlin, Germany, in
2007 and 2014, respectively. His research interests include
computer vision, machine learning, object detection, neural networks, and ensemble theory. He works in the field of
image-based object detection and classification with a focus on remote sensing data and, in particular, polarimetric
synthetic aperture radar images. His current research interests focus on ensemble methods for image analysis. He is
cochair of the IEEE Geoscience and Remote Sensing Society
Image Analysis and Data Fusion Technical Committee and
the International Society for Photogrammetry and Remote
Sensing Working Group II/1 (Image Orientation). He is an
associate editor of IEEE Geoscience and Remote Sensing Letters.
Michael Schmitt (m.schmitt@tum.de) received his Dipl.Ing. degree in geodesy and geoinformation, his Dr.-Ing.
degree in remote sensing, and his habilitation in data
fusion from the Technical University of Munich (TUM),
Germany, in 2009, 2014, and 2018, respectively. Since
2015, he has been a senior researcher and deputy head at
the Professorship for Signal Processing in Earth Observation at TUM; in 2019 he was additionally appointed adjunct
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

MARCH 2020

http://www.grss-ieee.org/community/technical-committees/ http://www.grss-ieee.org/community/technical-committees/ http://www.grss-ieee.org/community/technical-committees/ http://www.grss-ieee.org/community/technical-committees/data-fusion/ http://www.grss-ieee.org/community/technical-committees/data-fusion/ http://www.linkedin.com/groups/IEEE-GRSS-Data-Fusion-Discussion-3678437 http://www.linkedin.com/groups/IEEE-GRSS-Data-Fusion-Discussion-3678437 https://sentinel.esa.int/web/sentinel/home https://sentinel.esa.int/web/sentinel/home https://lpdaac.usgs.gov/ https://lpdaac.usgs.gov/

IEEE Geoscience and Remote Sensing Magazine - March 2020

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