IEEE Geoscience and Remote Sensing Magazine - March 2023 - 97

no. 6, pp. 1709-1724, Jun. 2019, doi: 10.1109/JSTARS.2019.
2911113.
[3] S. Kunwar et al., " Large-scale semantic 3D reconstruction:
Outcome of the 2019 IEEE GRSS data fusion contest
- Part A, " IEEE J. Sel. Topics Appl. Earth Observ. Remote
Sens., vol. 14, pp. 922-935, 2021, doi: 10.1109/JSTARS.2020.
3032221.
[4] Y. Lian et al., " Large-scale semantic 3D reconstruction: Outcome
of the 2019 IEEE GRSS data fusion contest - Part B, "
IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 14,
pp. 1158-1170, 2021, doi: 10.1109/JSTARS.2020.3035274.
[5] C. Robinson et al., " Global land-cover mapping with
weak supervision: Outcome of the 2020 IEEE GRSS data
fusion contest, " IEEE J. Sel. Topics Appl. Earth Observ. Remote
Sens., vol. 14, pp. 3185-3199, Mar. 2021, doi: 10.1109/
JSTARS.2021.3063849.
[6] Y. Ma et al., " The outcome of the 2021 IEEE GRSS data fusion
contest - Track DSE: Detection of settlements without
electricity, " IEEE J. Sel. Topics Appl. Earth Observ. Remote
Sens., vol. 14, pp. 12,375-12,385, Nov. 2021, doi: 10.1109/
JSTARS.2021.3130446.
[7] R. Hänsch et al., " Report on the 2022 IEEE Geoscience
and Remote Sensing Society data fusion contest: Semisupervised
learning, " IEEE Geosci. Remote Sens. Mag. (Replaces
Newslett.), early access, Nov. 2022, doi: 10.1109/
MGRS.2022.3219935.
IRENA HAJNSEK
2022 Earth Observation and Sustainable
Development Goals Contest Winners
T
he Technical Committee Remote Sensing Environment,
Analysis, and Climate Technologies (REACT)
of the IEEE Geoscience and Remote Sensing Society
(GRSS) is proud to announce the winners of the 2022
Earth Observation and Sustainable Development Goals
(EO4SDG) contest. The miniprojects for the Sustainable
Development Goals competition are an initiative
of the Technical Committee REACT to support science
and to motivate local students to work together on a
specific topic related to EO4SDG. The focus is on local
regional problems and how remote sensing can help
to identify and quantify environmental/societal impacts
of a changing Earth. More details can be found at
www.grss-ieee.org/resources/news/new-react-eo4sdg
-competition/.
The winning team this year is a group from the Remote
Sensing and Spatial Analytics Lab of the Information Technology
University in Lahore, Pakistan, with a miniproject
entitled: " Deep Learning for Mapping Glacial Lakes in Hindu
Kush & Himalayas using Sentinel-2 Multi-Spectral Data "
from Abdul Basit, research associate, Ehtasham Naseer, Ph.D.
fellow, and Nida Qayyum, research associate (Figure 1).
Digital Object Identifier 10.1109/MGRS.2023.3243872
Date of current version: 31 March 2023
MARCH 2023 IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
FIGURE 1. The winning team of the EO4SDG contest: Abdul Basit,
research associate, Ehtasham Naseer, Ph.D. fellow, and Nida
Qayyum, research associate.
The abstract of their miniproject is that glacial lake outburst
floods (GLOFs) are recurrent phenomena in high
mountain regions around the globe. They are caused by
rapid discharge of millions of cubic meters of melt water
and ice debris in a short interval of time. They are one of
the major environmental threats for local communities
residing downstream. Recent decades have witnessed
a rapid increase in the number of glacial lakes and subsequent
GLOFs, which requires continuous monitoring
of expansion of existing glacial lakes and formation of
new ones (Figure 2). With the availability of open-source
remote sensing data, it is now possible to monitor potentially
dangerous zones at a large scale. Moreover, deep
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IEEE Geoscience and Remote Sensing Magazine - March 2023

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