An Objectively Optimized Observing System

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An Objectively Optimized Observing System

• David John Lary
• NASA GSFC/UMBC GEST

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Overview

• Automated validation, bias detection, and cross
  calibration.
• Objectively optimized observation direction for a
  sensor network.
• Applications.

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Automating Validation, Bias-Detection and
Cross-Calibration
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Geophysical insights
c.a. 3000 B.C. Who can understand his errors?
Psalms 1912
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Aura validation
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Validation using PDFs
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How shall we correct these biases?Can we
correct them on the fly?
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Neurological algorithms
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An example neural network
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An example neural network
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Instrument Inter-calibration
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http//www.ndvicentral.info/
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Moving towards autonomy
Goal Observing the right place at the right time!
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Purpose
Wisdom is profitable to direct!
Wisdom is profitable to direct!

• Scientific discovery through Inter-disciplinary
  research, observation and a high level of
  automation in the generation of state of the art
  models, visualization and data mining to
  facilitate understanding.
• So far this work has won five NASA awards, a
  Royal Society Fellowship, an Alon Fellowship, a
  NASA Distinguished Goddard Fellowship in Earth
  Science and over 2.5 million dollars of funding.

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Benefit Statement

• Allows a focus on the key issue(s) whether they
  are
• The societal needs/policy decisions
• The decision support criteria
• The scientific goals

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Integrated Earth Observation

• As we move to more comprehensive observing
  systems there will be more need for reusable
  intelligent observation direction systems.
• These systems will respond in real time to the
  observation requirements.

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Integrated Earth Observation

• The requirements will be varied depending on the
  application.
• The observing system will contain many
  components, orbital and suborbital.

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Sensor WebA dynamic network of sensors working
to achieve a common goal.
Mosaic of Anacapa Island obtained using the DCS
camera during the Altair Channel Islands flight
The Ultra Long Duration Balloon (ULDB) is a
pumpkin-shaped balloon designed for durations
up to 100 days.

• We are moving towards much more distributed
  observation systems with constellations of
  satellites and suborbital platforms, including
  autonomous vehicles.
• There is a need for an intelligent observation
  direction system.

Current Altair payload
Altair information courtesy of Jim Elkins
http//uas.noaa.gov/altair/index.html
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Observation scheduling

• With flexible pointing instruments
• What is the optimum real time pointing?
• With flexible mode instruments
• What is the optimum real time use of zoom in
  mode?
• When should balloons be launched?
• What is the optimum trajectories for UAVs and
  aircraft?

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How do we achieve this?What do we optimize for?
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The knowledge of ignorance is the beginning of
knowledge
The knowledge of ignorance is the beginning of
knowledge

• The system envisioned will dynamically adapt the
  what, where, when and mode (e.g. global survey or
  zoom-in) of the observations made in an online
  fashion to maximize information content and
  minimize uncertainty in characterizing the
  systems state vector for a given observation
  capability.

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Autonomous Observing Systems

• Put simply, we use measures of what we do not
  know to direct our future observations, and use
  measures of how important it is to know it to
  determine the scheduling priority of
  observations.
• What we do not know is quantified by state vector
  uncertainty supplied by the assimilation system.
• How important it is to know it is quantified by
  information content also supplied by the
  assimilation system.
• The geographic extent of the uncertainty maxima
  is one metric that can be used to determine
  whether zoom in or survey mode is required.

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Geophysical insights
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Chemical Data Assimilation
Uncertainty information is included
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Key Features
Won 5 NASA awards

• Rapidly reconfigurable
• Automatic Code generation

• Self documenting
• Functionality
• Results (automatic web site creation).

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Interface

• STK interface that can be used for prototyping or
  real time control.
• Automatic web site creation for online
  data-mining and presentation.
• Accessible for specialists and policy makers.

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Hydrocarbon oxidation
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Hydrocarbon oxidation
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Health ApplicationsSimulation courtesy of Jay
Boris NRL
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Logan Airport
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Decision Support Systems

• Using
• NASA earth observing data (in this case
  including OMI HCHO)
• EPA observing network
• Navy Research Laboratory street level model
• AutoChem chemistry scheme

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Street level modeling
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Wisdom is profitable to direct! (Solomon 3000
bp) The knowledge of ignorance is the beginning
of knowledge.