EOS 840 Hyperspectral Imaging Applications

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EOS 840 Hyperspectral Imaging Applications
September 8, 2004 Week 2
Ron Resmini v 703-735-3899 ronald.g.resmini_at_boein
g.com Office hours by appointment
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Outline

• Scientific principles of HSI RS
• Remote sensing and sensor physics
• Physics of imaging spectroscopy
• Introduction to radiative transfer theory
• Spectral/spatial analysis
• Working in RS
• The ENVI s/w system
• My semester project
• A few project challenges for you

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Primary References
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Scientific Principles of HSI RS

• Key points discussed last week the whys and
  hows
• HSI is based on the measurement of a physical
  quantityas a function of wavelength its
  spectroscopy, writ large
• HSI is based on discerning/measuring the
  interaction oflight (photons, waves) with matter
• The fundamental physical quantities of RS
• Sensors measure radiance as a function of
  wavelength
• Radiance (W/m2.sr.mm) (spectral)
• Spectral radiance is a flux of energy per solid
  angle
• Materials interact with electromagnetic radiation
  (EMR)
• Materials reflect, absorb, and/or transmit EMR

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• Other radiometric quantities, units, definitions
  of RS
• Irradiance (W/m2.mm) (spectral)
• Reflectance (dimensionless...or is it?)
• Emissivity (dimensionless)
• Tables...there are lots of quantities
• Some important constants
• Speed of light, c, 2.9979 x 108 m/sec
• Plancks constant, h, 6.6256 x 10-34 joules.sec
• Boltzmanns constant, k, 1.38 x 10-23 joules/K
• c ln q (energy in a photon)hnhc/l (joules)
• n (cm-1) 1.0 x 104 / l (mm)
• The sun is the source of RS energy

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• Spectral ranges used in RS (see Richards and Jia,
  1999 pg. 3)
• Traditional HSI spectral ranges
• VNIR/SWIR (0.4 to 2.5 mm), MWIR (3 to 5 mm), LWIR
  (7 to 13 mm)
• Determined by h/w considerations and atmospheric
  windows
• Do not be so constrained when considering other
  apps. for HSI
• HSI is really a problem in inversion we sense
  the answerwe work backwards from there we
  sense boundary conditionsin one instant in time
• HSI, BTW, is remote material identification and
  characterization
• Key statement
• The spectrum is the fundamental datumin imaging
  spectrometry

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Remote Sensing and Sensor Physics

• Im not a h/w guybut
• Some practical information you should know to
  survive
• Dispersion the formation of spectra dispersion
  curve
• Prisms, gratings, interference (FTS)
• Imaging spectrometry the formation of images
• Push-broom whisk-broom other (e.g., FTS)
• What you need to know about your data a
  check-list
• Date, time, location, ground elevation, platform
  elevation,heading, GSD, of samples, of
  lines, of bands,band centers, band FWHM, band
  interleaving,byte order be able to calculate
  where the sun isi.e., all RS angles (geometry)

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• Radiometric and spectral calibration
• How theyre accomplished
• When ideally with every collection event
• Sensor drift
• On-going sensor characterization ask for it!
• Spatial sampling spatial resolution
• Spectral sampling SRF spectral resolution
• NESR, NEDr, NEDe, NEDT
• Issues smile, keystone, FPA misregistration,
  vibration,parallax, scattered light,
  self-emission, platformmotion/imaging
  distortions, etc
• Buyer beware - know the roles of the data
  providerand the data analyst

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Physics of Imaging Spectroscopy

• Origin of spectral features
• Electronic, vibrational, vibrational/rotational,
  etc
• Materials reflect, transmit, absorb, scatter
  lightbut first, why? how?
• Optical constants
• index of refraction, n
• imaginary part of refractive index, k
• ...related to absorption absorption coefficient
  isa 4pk/l
• aka complex refractive index, m nik
• This is really a convenience for solving PDEsof
  electromagnetic theory

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• Status check...where are we?
• Sensors measure radiance (spectral radiance)
• Materials interact with light
• m nik
• Whats reflectance?
• Tie it all together...
• The propagation of light
• Electromagnetic theory
• Solution of Maxwells Equations
• The Fresnel equations (pages from Hapke, 1993)
• BTW...Huygens Principle
• Snells Law/Law of Reflection
• Fermats Principle
• Polarization (not today...)
• What do you need to know?

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• For RS The types of scattering e.g.
• diffuse, specular idealized and
  reality(Schott, 1997 pg. 100) all describable
  withFresnel equations (and other...)
• Complicated, real surfaces and materials
• Minerals/rocks/mixtures (BTW...isotropic,uniaxial
  , biaxial)
• Vegetation
• Soils
• Water
• All real surfaces/materials!
• Is it all too complicated? No, spectral
  libraries...
• Mixed pixels (briefly more later in semester)
• The atmosphere(!)

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• So, can HSI (or any RS) help you? You must ask
• Is there a signature?
• How much is expected to be exposed/present?
• Other physical, chemical, radiative
  transferconsiderations
• E.g., littoral zone RS of coral under a turbid
  watercolumn that is under a turbid
  atmosphere...yikes!

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Introduction to Radiative Transfer (RT)
Theory (more next time)

• The RT equation
• Simplified expressions get you gt90 of whatyou
  need to know
• Radiometry and radiation propagation
  thisdiscussion is largely from Schott (1997),
  ch. 4
• Coordinates frames of reference principal
  plane, etc.
• Illumination angle, direction
• View angle, direction
• Phase angle
• Azimuth, relative/absolute

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The Radiative Transfer Equation
Eq. 7.21 on pg. 156 of Hapke (1993).
More next week...
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• VNIR/SWIR i.e., solar-reflective
• Thermal infrared i.e., emissive
• Defer both phenomena occurring together until
  later!
• Status check...where are we?
• What do we actually measure with an HSI sensor?
• We want to get to r or e
• Getting to reflectance (subject of future
  lecture)
• Types of reflectances (Hapke, 1993 pg. 183)

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Spectral/Spatial Analysis

• Current approaches
• Really rather immaturespectrally
• Edge-detection
• Texture
• The role of the FFT spatially
• HySPADE (Resmini, 2004, in press)
• Excellent discussion in Landgrebe (2003)
• More to be said with the ENVI s/w system
• Applications
• Strategies...

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Working in Remote Sensing

• Where are the jobs?
• Government (civil, other), private
  sector,not-for-profit, academia
• Being a subject matter expert is important, too
• Whats expected of you

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• The entire remote sensing problem
• Problem analysis
• Is it pure/applied science? engineering
  analysis?scientific method/statistical design of
  experiment
• Planning
• Tasking
• Ground-truth
• Logistics/persmissions/trespassing/etc...
• Collection platform(s)
• Ancillary data (e.g., DEM)
• HSI data (now the fun begins!)
• Archiving
• Distribution
• A good RS report
• RS products

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• The Scientific literature (This is NOT
  optional...)
• Coin of the realm
• The stock-in-trade of science
• It is the Thing!
• Two types (in RS) peer-reviewed and the
  gray-lit
• Philosophical debates always raging
• Get involved with the literature
• Read it!! At least know the topics of the papers
• Become a peer-reviewer or even an
  editor(peer-reviewed or non-peer-reviewed)
• Contribute papers to it
• Always stay involved with the literature
• Adopt a journal format for your papers/reports

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Peer-Reviewed Journals

• Remote Sensing of Environment
• International Journal of Remote Sensing
• Journal of Geophysical Research
• Solid Earth, Planets, Oceans and Atmospheres
• Icarus
• Remote Sensing Reviews
• Photogrammetric Engineering and Remote Sensing
• Applied Optics
• Journal of the Optical Society of America
• Many others, too perhaps too many!

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Non-Reviewed Journals

• Published conference proceedings
• SPIE
• GMU library subscribes to SPIE
• Abstract services
• AVIRIS conference
• IEEE/IGARSS
• Many others, too perhaps too many!

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• Scientific Societies
• Join one or two (e.g., SPIE, IEEE, AGU, ASPRS)
• Society newsletters/mags are useful sources of
  information
• Conferences/Meetings/Symposia
• SPIE, IEEE/IGARSS, AGU, ASPRS, ISSSR
• Trade rags (subscribe theyre usually free)
• E.g., Photonics Spectra, Advanced Imaging
• Web resources
• Continuing education
• Yes GMU, corporate training, private training
  outfits,self-directed study, brown-bag seminars
  (start one)

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• Conducting your remote sensing career
• Stay current keep abreast of developments in RS
• Know the trends in the field
• Attend conferences/meetings/symposia
• Get involved with the literature
• Write papers/reports...put it in writing
• Always think about fusion with otherdata/informat
  ion sources
• Keep a current CV/resume
• Keep a portfolio of your work
• Be a rebel be rigorously quantitative
• This is actually fairly rare...imho

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The ENVI Software System
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My Semester Project

• Use RS data to determine lava tube roof thickness
• Analyze NASA TIMS at Kilauea Volcano
• Six band TIR MSI from 8 to 12 mm
• Archive data from 1988
• Use analytical and numerical solutions to the
  heatequation in conjunction with RS data
• Determine surface temperature over lava tube
• Use modeling to match surface temperature
  anddetermine roof thickness
• Other parameters to consider e.g., h, heat
  transfercoefficient for Newtons law of cooling
  boundarycondition

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On the following
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My Semester Project Status

• Tools/approach
• Analytical solution(s) to heat equation
• FlexPDE (numerical solution(s) to heat equation)
• ENVI for TIMS data analysis
• Match modeling with data analysis results
• Determine roof thickness
• TIMS data already acquired
• Preliminary modeling analyses on-going

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A Few Project Challenges For You

• N-P Theory sensitivity to spatial/spectral
  subsets
• When is spectral mixing linear v. non-linear?
  I.e., is this evidentfrom the spectra?
• Measure the volume of hyperspace actually
  occupied by real HSI data
• Hughes Phenomenon. It gets mis-applied
  because...
• Spectral angle between spectra and filter
  vectors is the separabilitygreater than angles
  derived from a confusion matrix analysis of
  aspectral library? Use, also, a measure of SCR
• Make Mine Virginia Wine. Characterize VA
  vineyard soils with HyperionHSI and/or field
  spectrometry characterize grape vines
  etc...Does HSI have a role in the VA wine
  business?