IEEE Geoscience and Remote Sensing Magazine - June 2021 - 8

Precision Geoscience
Space Weather
IoT-Based
Seismology
Smart Exploration and
Drilling Data Analysis
Model-Driven Sensing
Extreme Environment
Sensing
Remote Sensing for
Sustainable
Infrastructures
Graph-Based Analytics
and Graph Embedding
Smart Alert Systems
Robotic and Drone
Sampling
FIGURE 1. Trends in using AI and ML in geoscience and remote sensing. IoT: Internet of Things.
between HS remote sensing and interpretable AI models,
with a brief introduction to the research background and
motivation, an emphasis on the resulting methodological
foundations and solutions, and an intuitive clarification of
illustrative examples. At the end of each topic discussion,
the authors also pose the challenges remaining, in terms
of how to completely model issues of complex spectral
vision from the perspective of intelligent ML combined
with physical priors and numerical nonconvex modeling,
and accordingly point out future research directions. This
article aims to create a good entry point to the advanced
literature for experienced researchers, Ph.D. students, and
engineers who already have some background knowledge
in HS remote sensing, ML, and optimization. This can further
help them launch new investigations on the basis of
the previously listed topics and interpretable AI techniques
for their focused fields.
Finally, in this issue's " Perspectives " column, Tuia et al.
outline their agenda for AI in Earth sciences, aiming to inspire
researchers, especially among the younger generations,
to tackle the challenges for a real advance of remote sensing
and geosciences. In recent years, they have witnessed
the fields of geosciences and remote sensing and AI become
closer due to the massive availability of observational data,
improved simulations, and algorithmic advances. These
disciplines have found common objectives and challenges
8
AUTHOR INFORMATION
Sabah Mohammed (sabah.moham
med@lakeheadu.ca) has been a full
professor in the Department of Computer
Science at Lakehead University,
Thunder Bay, Ontario, P7B 5E1,
Canada, since 2002 and is a core professor
in Lakehead's Ph.D. BioTechnology
program. Having trained in
medicine with a computer science
Ph.D. degree in AI, his research interest
is in intelligent systems that
operate in large, nondeterministic,
cooperative, highly connected, survivable,
adaptive, or partially known
domains. His ongoing research is
inspired by his Ph.D. degree work
extending back to 1981 at Brunel University (U.K.) on the
employment of brain activity structures for decision making
(planning and learning) that enable processes (e.g.,
agents and mobile objects) and collaborative processes to
act intelligently in their environments and so achieve
the required goals in a timely manner. Dr. Mohammed
is the founder and editor-in-chief of Journal of Emerging
Technology of Web Intelligence as well as editor-in-chief of
IGI Global's International Journal of Extreme Automation
and Connectivity in Healthcare. He is currently chair of the
Special Interest Research Group on Smart and Connected
Health with the IEEE Communication Society's eHealth
Technical Committee. He is working on the development
of Internet of Things and mobility technologies that impact
improving health-care services in remote areas such as the
Northwestern Ontario region. Dr. Mohammed is a Professional
Engineer of Ontario (PEng), an Information Processing
Professional with the Canadian Information Processing
Society, and a Senior Member of IEEE.
Tai-hoon Kim (taihoonn@empas.com) received his M.S.
and Ph.D. degrees in electrics, electronics, and computer
engineering from Sungkyunkwan University, Korea, and
he earned a second Ph.D. degree in information science
from the University of Tasmania (UTAS), Hobart, Australia.
He was a researcher with the Technical Institute of Shindoricoh
and a senior researcher with the Korea Information
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE JUNE 2021
to advance the modeling and understanding
of the Earth system. Despite
such great opportunities, they
observe a worrying tendency to remain
in disciplinary comfort zones,
applying recent advances from AI
only to well-resolved remote sensing
problems. This column takes a position
on research directions in which
the interface among these fields will
have the greatest impact and become
potential game changers.
Geoscience and Remote Sensing
AI and ML

IEEE Geoscience and Remote Sensing Magazine - June 2021

Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - June 2021