IEEE Geoscience and Remote Sensing Magazine - September 2021 - 32

and refractivity, thus providing valuable information on
atmospheric temperature and humidity [19]. RO observations
have become an essential part of the EOSC and have
been shown to be critical to forecast skill from NWP by
providing high vertical resolution and accurate profiles of
temperature and water vapor information. They also act as
reference or anchor observations for minimizing the impact
of biases of the satellite radiance measurements on the
model analyses and forecasts [23]-[25]. This same GNSS
signal of opportunity is now the subject of a NASA research
mission called CYGNSS, which extends the use of surfacereflected
GNSS signals (from water, land, and ice surfaces)
to retrieve ocean wind speed, sea ice extent, near-surface
soil moisture, and other variables [12].
Because of the evolving capabilities of the EOSC, the
value of individual components of the system, as well
as the system as a whole, is changing with time. These
values are dependent on the state of our knowledge of
remote sensing techniques, our ability to model the signals
received by the sensors, and the sophistication of
our information-extraction techniques as well as the
evolution and expansion of applications. As these factors
change, additional techniques to turn noise into signals
will be developed. As a result, increases are anticipated in
the capabilities, the number and diversity of users, and
the value of the observing systems. It is expected that the
emergence of new analytics techniques for example, such
as artificial intelligence (AI) including machine learning
(ML) techniques [2], [26], will lead to an increase in the
innovative uses of EOSC data for an ever-larger set of applications.
It should be mentioned that ML and DA have
many commonalities [27]. The evolving capabilities of
the EOSC also complicate the task of assessing the full
lifecycle value of a proposed observing system and its return
on investment (ROI).
THE VALUE CHAIN: FROM MEASUREMENTS TO
DECISION MAKING
Society, including individuals, industries, many sectors of
the economy, and governments, increasingly depend on
meteorological, oceanographic, land/hydrological, and space
weather services, which, in turn, depend on observations.
Without observations, many of these services would not be
possible or their quality would be severely limited. An integrated
approach, encompassing all of the disciplines that
today are sometimes handled disjointly, is emerging in the
development of Earth system models. The most accurate
and useful weather prediction and climate models require
coupled atmospheric, ocean, sea ice, atmospheric chemistry,
and land surface models. To ensure that the satellite
measurements are useful in a wide range of applications,
several steps must be taken. Figure 2 depicts the entire value
chain of processes, from measurements to decisions, with
the black arrows representing the transfer of information.
Phenomena
Observing Platforms
Processing
Calibration
In Situ
Ground Based
Remotely Sensed
Ground Based
Transformation
Aggregation
Validation
Space Based
Quality Monitoring
Applications and
Services
Research and
Understanding
Users
Individuals
Industry
Forecasting
Government
Environmental
Intelligence
International
Decisions
FIGURE 2. The value chain of the measurements from their acquisition by the observing systems, to the different steps needed to process
them into validated scientific information, to their use in several applications that then feed decision-making processes that impact
society at large.
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IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE SEPTEMBER 2021

IEEE Geoscience and Remote Sensing Magazine - September 2021

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