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Digital Imaging and Remote Sensing Laboratory
An Atmospheric CorrectionAlgorithm for Hyperspectral
Imagery
Ph.D. Dissertation Defense by:
Lee C. Sanders
Advisor: Dr. John R. Schott
Digital Imaging and Remote Sensing Laboratory
Outline
Radiometry OverviewOverview of atmospheric correctionElevation,column water vapor, and aerosol extraction methods:
NLLSSFAPDARIMAC
Inversion from sensor radiance to ground reflectanceContribution from the surround using the phase functionResultsSummary
Digital Imaging and Remote Sensing Laboratory
Hyperspectral Data
Digital Imaging and Remote Sensing Laboratory
Radiative Transfer Paths
Trapping Effect Environmental/Adjacency Effect
Digital Imaging and Remote Sensing Laboratory
Radiative Transfer Paths
Upwelled Radiance Downwelled Radiance
Digital Imaging and Remote Sensing Laboratory
Radiative Transfer Paths
Direct Solar
Digital Imaging and Remote Sensing Laboratory
The Governing Radiative Transfer Equation
Lsensor=
ρ Lgrnd +LD( )1−ρS( )
+Lenvρ+Lu
Digital Imaging and Remote Sensing Laboratory
MODTRAN 4 Look-Up Table
Surface ElevationWater Vapor AmountVisibilityChannel # Lgrnd Lu S Ld Lenv
1 0.3970 0.002090 0.002636 0.3270 0.009838 0.01263 2 0.4003 0.003521 0.004220 0.3238 0.01614 0.02048 3 0.4036 0.003754 0.004298 0.3207 0.01680 0.02111 4 0.4069 0.003828 0.004173 0.3176 0.01671 0.02076 5 0.4103 0.004131 0.004294 0.3146 0.01759 0.02163 6 0.4137 0.004340 0.004309 0.3116 0.01805 0.02196 7 0.4171 0.004393 0.004169 0.3087 0.01785 0.02151 8 0.4205 0.004350 0.003944 0.3057 0.01726 0.02059 9 0.4240 0.004342 0.003765 0.3028 0.01684 0.01989 10 0.4276 0.004077 0.003389 0.3000 0.01547 0.01811
Digital Imaging and Remote Sensing Laboratory
Outline
Radiometry OverviewOverview of atmospheric correctionElevation,column water vapor, and aerosol extraction methods:
NLLSSFAPDARIMAC
Inversion from sensor radiance to ground reflectanceContribution from the surround using the phase functionResultsSummary
Digital Imaging and Remote Sensing Laboratory
Why Atmospheric Correction?
Make better quantitative estimates of absolute surface reflectances.
Improve existing climatology models for weather forecasting.
Monitor pollution. Determine how atmospheric chemistry
impacts the trend of global warming.
Digital Imaging and Remote Sensing Laboratory
Atmospheric Correction1) Determine terrain elevation by surface pressure
depth in 760nm oxygen band using NLLSSF.
2) Determine the visibility for a given aerosol type
using a NLLSSF over the .4-.7µm range or use
the RIMAC method from .55-.7µm range.
3) Determine atmospheric column water vapor
content using the NLLSSF technique or the
APDA technique on the .940µm absorption
band.
4) From the calculated aerosol profile, determine
the phase function-derived convolution kernel.
Digital Imaging and Remote Sensing Laboratory
Outline
Radiometry OverviewOverview of atmospheric correctionElevation,column water vapor, and aerosol extraction methods:
NLLSSFAPDARIMAC
Inversion from sensor radiance to ground reflectanceContribution from the surround using the phase functionResultsSummary
Digital Imaging and Remote Sensing Laboratory
Non-Linear Least-Squared Spectral Fit (NLLSSF) Technique
ρg: Lambertian ground reflectance
LSE = Lsensor - ( LU + Lenv ρg + [Eocos()12+ Ld2 ]ρg/ (1-Sρg) )
Minimize the difference between the sensor radiance and the MODRAN-derived sensor radiance by changing parameters in the governing radiative transfer equation:
Digital Imaging and Remote Sensing Laboratory
NLLSSF Flex Parameters
.760µm Oxygen Band
surface elevation
.94µm H2O Band
water vapor
.4-.70 µm Aerosol Band
visibility
Digital Imaging and Remote Sensing Laboratory
NLLSSF Model of Reflectance
ρ=++(H2Ol)
In the case of the aerosol and water vapor bandsthe equation includes a non-linearity for liquid water :
In the .760µm oxygen band, thetarget reflectance is assumed linear with
ρ = +
Digital Imaging and Remote Sensing Laboratory
General Flow Chart of Algorithm
Input ConstantParameters(i.e geometry,particle density,etc)
Solve for TotalColumn Water Vapor Using the .94µm band.
Using all Solved Parameters, Invert Governing Radiometric Equation and Calculate Ground Reflectance.
Input Image Pixel:Solve for SurfacePressure Depth in.76µm O2 band.
Solve for AtmosphericVisibility Given an Aerosol Type Using.4-7µm bands
Digital Imaging and Remote Sensing Laboratory
Surface Pressure Elevation
0.015
0.0175
0.02
0.0225
0.025
0.0275
0.03
0.745 0.75 0.755 0.76 0.765 0.77 0.775 0.78 0.785
HYDICE Channel Center Wavelength (micron)
Radiance (W/cm^2/sr/micron)
HYDICE Sensor
MODTRAN Calculated
Digital Imaging and Remote Sensing Laboratory
NLLSSF Curve Fit
0
0.005
0.01
0.015
0.02
0.025
0.84 0.86 0.88 0.9 0.92 0.94 0.96 0.98 1 1.02
HYDICE Channel Center Wavelength (microns)
Radiance (W/cm^2/sr/micron)
HYDICE Sensor
MODTRAN Calculated
Digital Imaging and Remote Sensing Laboratory
The APDA (Atmospheric Pre-Corrected Differential Absorption)
Technique
A water vapor band depthratio method that relatesan Rapda value to a atmospheric columnar water vapor value.
Digital Imaging and Remote Sensing Laboratory
The APDA TechniqueThe single channel/band Rapda:
Rapda =Lm−Latm,m(PW)
ω 1r (L 1r −Latm, 1r )+ω 2r (L 2r −Latm, 2r )
which can be extended to more channels:
RAPDA =
[Lm −Latm ,m] i
LIR ([ r ] j , [Lm −Latm ,m] j ) |[ m]i
Digital Imaging and Remote Sensing Laboratory
The APDA Technique
Relate R ratio with the corresponding water vapor amount (PW)
wv(PW) = RAPDA = e -(+(PW))
Solving for water vapor:
PW(RAPDA)= ( -ln (RAPDA) -
)1/
Digital Imaging and Remote Sensing Laboratory
The Regression-Intersection Method for Aerosol Correction (RIMAC)
• RIM depends on classification of homogenous areas with varying spectral contrasts.
• Band pair by band pair, the DCs for each class are regressed toward the origin and the intersections of all the classes are determined.
• Intersections below the “toe” of the histogram are discarded. The mean intersection becomes the estimate of total upwelling radiance.
Digital Imaging and Remote Sensing Laboratory
Regression Intersection Method (RIM)Regression Intersection Method (RIM)R.E. Crippen (1987)R.E. Crippen (1987)
DCband1
DCband2
DCu1
DCu2
class a
class b
• Extrapolate data to intersection representing zero ground reflectance and upwelled radiance.
• Intersections determined for many classes in each band pair.
Digital Imaging and Remote Sensing Laboratory
Regression Intersection Method for Regression Intersection Method for Aerosol Correction (RIMAC)Aerosol Correction (RIMAC)
Structural regression of bispectral classes.
Classified Image
Intersect class lines by extrapolationto zero reflectance point.
Fit to MODTRAN LUT
Extract spectral upwelled radiance from intersections’ averages.
Digital Imaging and Remote Sensing Laboratory
Finding Atmospheric Visibility
• The total upwelled radiance is a combination of atmospheric upwelled scattered and environmental radiance.
• The average reflectance of the background is estimated either by Kaufman’s correlation with the 2.1µm band or by a simple linear fit to RIM total upwelled radiance estimate given an aerosol visibility.
Ltotal_upwelled=Lenvρavg+Latmos_upwelled
Digital Imaging and Remote Sensing Laboratory
Finding Atmospheric Visibility
• The visibility estimate is that which gives the minimum squared spectral radiance error compared to the RIM-derived total upwelled radiance.
MSSE= LRIM _ upwelled−(Lu +Lenvρavg)∑
MODTRAN-Derived
Digital Imaging and Remote Sensing Laboratory
Outline
Radiometry OverviewOverview of atmospheric correctionElevation,column water vapor, and aerosol extraction methods:
APDANLLSSFRIMAC
Inversion from sensor radiance to ground reflectanceContribution from the surround using the phase functionResultsSummary
Digital Imaging and Remote Sensing Laboratory
Digital Imaging and Remote Sensing Laboratory
First Pass Solve for Reflectance
Lsensor=
ρ Es cos12 + LD2[ ]1.0 −ρS( )
+ Lenvρ+ L u
Once the atmospheric parameters have been set, theradiometric terms can be extracted from the MODTRAN 4 Look-Up Table and the sensor radiancecan be inverted to ground reflectance for each pixel.
Digital Imaging and Remote Sensing Laboratory
Second Pass Solve for Reflectance
Lsensor=
ρ Es cos12 + L D2[ ]1.0 −ρavgS( )
+ Lenvρavg + L u
In the first pass, the surround reflectance was set tobe equal to the target reflectance. To be rigorous,an approach had to be derived that estimatedthe aggregate reflectance contribution of the surround and the magnitude of the adjacency radiance.
Digital Imaging and Remote Sensing Laboratory
Outline
Radiometry OverviewOverview of atmospheric correctionElevation,column water vapor, and aerosol extraction methods:
APDANLLSSFRIMAC
Inversion from sensor radiance to ground reflectanceContribution from the surround using the phase functionResultsSummary
Digital Imaging and Remote Sensing Laboratory
Environmental Contribution• Light from the target surround is scattered into
the sensor path• The intensity distribution of radiance depends
on the angle from sensor optical path and the aerosol phase function.
• The magnitude of the radiance depends on the target reflectance, the aerosol particle density, and the aerosol scattering cross-section.
Lenv_total ( ) = (L θ,φ,)θ=0
π2
∫φ=0
2π
∫ layer(1)
layer(h)
∫ P(θ,, H)T2 (θ, )ρ (θ,φ, )d (sinθ )dθ dφ
Digital Imaging and Remote Sensing Laboratory
Scattering FromSurround IntoThe Sensor PathIs Governed ByThe AerosolPhase Function
Single AtmosphericLayer Diagram
Digital Imaging and Remote Sensing Laboratory
The scattering function for aunit layer is weightedby the solid anglesubtended by the layerpixel at altitude h.
Sensor IFOV of An AtmosphericLayer
Digital Imaging and Remote Sensing Laboratory
Atmospheric Layers
1
2
3
4
5
6
Digital Imaging and Remote Sensing Laboratory
Calculating Average Reflectance• The scattering contributions are summed over all the
atmospheric layers:
• For this algorithm, the real interest is the fractional reflectance contribution of each pixel in the surround:
PSFunnorm(i, j) = (P θ, )Ω( ,i )j e-( 2aecθ+2b)Δyeρyeρ∑
PSF(i, j) =
(P θ, )Ω( ,i )j e-( 2asecθ+ 2b)
layers∑
(P θ, )Ω( ,i )j e-( 2asecθ+2b)
layers∑
j∑
i∑
Digital Imaging and Remote Sensing Laboratory
0.400µm & 2.1µm Scattering Kernels of HYDICE Run 29
Digital Imaging and Remote Sensing Laboratory
Western Rainbow Scattering Kernel
Digital Imaging and Remote Sensing Laboratory
Adjacency Effect Radiance for HYDICE Run 29
0
0.002
0.004
0.006
0.008
0.01
0.012
0.4 0.65 0.9 1.15 1.4 1.65 1.9 2.15 2.4
Wavelength (µm)
Digital Imaging and Remote Sensing Laboratory
Second PassOnce a ρavg map is created, the algorithm
can proceed using the first pass atmospheric parameters as initial estimates.
The atmospheric parameters are re-calculated using the same methodology as the first pass except a different radiative transfer equation is used.
Final output is the reflectance map of the scene and the solved atmospheric parameters.
Digital Imaging and Remote Sensing Laboratory
Outline
Radiometry OverviewOverview of atmospheric correctionElevation,column water vapor, and aerosol extraction methods:
APDANLLSSFRIMAC
Inversion from sensor radiance to ground reflectanceContribution from the surround using the phase functionResultsSummary
Digital Imaging and Remote Sensing Laboratory
Ground Target Layout
Digital Imaging and Remote Sensing Laboratory
Error in Recovered Reflectance for HYDICE Run 29 Using Def_RIMAC_NL Options
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
Wavelength (µm)
Reflectance Error
2% Delta r4% Delta r8% Delta r16% Delta r32% Delta r64% Delta r
Digital Imaging and Remote Sensing Laboratory
Error in Second Pass Recovered Reflectance for HYDICE Run 29 Using Def_RIMAC_NL Options
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
Wavelength (µm)
Reflectance Error
2% Delta r4% Delta r8% Delta r16% Delta r32% Delta r64% Delta r
Digital Imaging and Remote Sensing Laboratory
Error in Recovered Reflectance for HYDICE Run 29 Using All NLLSSF Options
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
Wavelength (µm)
Reflectance Error
2% Delta r4% Delta r8% Delta r16% Delta r32% Delta r64% Delta r
Digital Imaging and Remote Sensing Laboratory
Error in Second Pass Recovered Reflectance for HYDICE Run 29 Using All NLLSSF Options
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
Wavelength (µm)
Reflectance Error
2% Delta r4% Delta r8% Delta r16% Delta r32% Delta r64% Delta r
Digital Imaging and Remote Sensing Laboratory
Recovered Reflectance Second Pass Comparison for Total Inversion Using ALL NLLSSF Options on HYDICE Run 29
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4
Wavelength (µm)
Reflectance
Truth 2%Tot_Inv 2%Truth 4%Tot Inv 4%Truth 8%Tot Inv 8%Truth 16%Tot Inv 16%Truth 32%Tot Inv 32%Truth 64%Tot Inv 64%
Digital Imaging and Remote Sensing Laboratory
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
2 4 8 16 32 64
ARMs Site Gray Panel Nominal Reflectance
RMS Reflectance Error
Default
NLLSSF
Def_RIMAC_NL
NLavg_RIMAC_NL
NLLSSF 2nd Pass
Def_RIMAC_NL 2nd Pass
Digital Imaging and Remote Sensing Laboratory
Error in Recovered Reflectance for cr08m33 Using NLavg_RIMAC_NL Options on Old Panels
-0.1
-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0.1
400 600 800 1000 1200 1400 1600 1800
Wavelength (nm)
Reflectance Error
2% Delta r12% Delta r24% Delta r36% Delta r48% Delta r60% Delta r
Digital Imaging and Remote Sensing Laboratory
Error in Second Pass Recovered Reflectance for cr08m33 Using NLavg_RIMAC_NL Options on Old Panels
-0.1
-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0.1
400 600 800 1000 1200 1400 1600 1800
Wavelength (nm)
Reflectance Error
2% Delta r12% Delta r24% Delta r36% Delta r48% Delta r60% Delta r
Digital Imaging and Remote Sensing Laboratory
0
0.01
0.02
0.03
0.04
0.05
0.06
2 12 24 36 48 60Yuma Site Gray Panel Nominal Reflectance
Old Panels Run cr08m33
RMS Reflectance Error
Default
NLLSSF
Def_RIMAC_NL
NLavg_RIMAC_NL
NLLSSF 2nd Pass
NLavg_RIMAC_NL 2ndPass
Digital Imaging and Remote Sensing Laboratory
Error in Recovered Reflectance for cr15m50 Using NLLSSF Options for New Panels
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
400 600 800 1000 1200 1400 1600 1800
Wavelength (nm)
Reflectance Error
2% Delta r12% Delta r24% Delta r36% Delta r48% Delta r60% Delta r
Digital Imaging and Remote Sensing Laboratory
Error in Second Pass Recovered Reflectance for cr15m50 Using NLLSSF Options for New Panels
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
400 600 800 1000 1200 1400 1600 1800
Wavelength (nm)
Reflectance Error
2% Delta r12% Delta r24% Delta r36% Delta r48% Delta r60% Delta r
Digital Imaging and Remote Sensing Laboratory
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.1
0.11
0.12
2 12 24 36 48 60Yuma Site Gray Panel Nominal Reflectance
New Panels Run cr15m50
RMS Reflectance Error
Default
NLLSSF
Def_RIMAC_NL
NLavg_RIMAC_NL
Default_2nd Pass
NLLSSF 2nd Pass
Def_RIMAC_NL 2nd Pass
NLavg_RIMAC_NL 2ndPass
Digital Imaging and Remote Sensing Laboratory
Estimated Average Image-Wide Reflectance Error for HYDICE Run 29 from Def_RIM_NLLSSF 2nd Pass
(average of all panel reflectances less than 18%)
-0.05
-0.045
-0.04
-0.035
-0.03
-0.025
-0.02
-0.015
-0.01
-0.005
0
0.005
0.01
0.015
0.02
0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8
Wavelength (µm)
Digital Imaging and Remote Sensing Laboratory
Estimated Average Image-Wide Reflectance Error for HYDICE Run cr08m33 from NLLSSF 2nd Pass
(average of all Old panel reflectances less than 18%)
-0.05
-0.045
-0.04
-0.035
-0.03
-0.025
-0.02
-0.015
-0.01
-0.005
0
0.005
0.01
0.015
0.02
400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800
Wavelength (nm)
Digital Imaging and Remote Sensing Laboratory
Estimated Average Image-Wide Reflectance Error for HYDICE Run cr15m50 from NLLSSF 2nd Pass
(average of Old panel reflectances less than 18%)
-0.05
-0.045
-0.04
-0.035
-0.03
-0.025
-0.02
-0.015
-0.01
-0.005
0
0.005
0.01
0.015
0.02
400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800
Wavelength (nm)
Digital Imaging and Remote Sensing Laboratory
Outline
Radiometry OverviewOverview of atmospheric correctionElevation,column water vapor, and aerosol extraction methods:
APDANLLSSFRIMAC
Inversion from sensor radiance to ground reflectanceContribution from the surround using the phase functionResultsSummary
Digital Imaging and Remote Sensing Laboratory
Summary
• A modular algorithm for inverting hyperspectral imagery from sensor radiance to ground reflectance has been constructed and validated.
• A new method for in-scene determination of aerosol-dependent visibility called RIMAC has been developed and tested.
• A new concept for adjacency-effect correction using the atmospheric scattering phase function has been implemented.
Digital Imaging and Remote Sensing Laboratory
Possible Future Upgrades
Make option to take in DEM for surface elevation.
Incorporate Henyey-Greenstein phase function for multiple scattering.
Explore ratio technique on 760nm oxygen band for surface elevation.
Include a spectral correlation method to correct for spectral mis-matches in sensor radiance.
Digital Imaging and Remote Sensing Laboratory
Acknowledgements
Advisor: Dr. John R. SchottStaff Scientists: Rolando Raqueño and Scott Brown
Special Thanks To:
Dr. Robert Green, JPL (NLLSSF)Dr. Daniel Schlaepfer (APDA)Christopher Borel (APDA)Lex Berk and Dr. Stephen Adler-Golden, Spectral Sciences, Inc.Dr. Eric Crist, ERIM International, Inc.Sue Michel and Bob Krzaczek, Center for Imaging Science
Digital Imaging and Remote Sensing Laboratory
Radiometric Parameters for HYDICE Run 29
0
0.005
0.01
0.015
0.02
0.025
0.03
0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4
Wavelength (µm)
Lgrnd
Lu
Ld
Lenv
Ltrap
Digital Imaging and Remote Sensing Laboratory
Amoeba Algorithm
Digital Imaging and Remote Sensing Laboratory
-0.07
-0.06
-0.05
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8
Wavelength (µm)
Reflectance Unit Error
Average Reflectance Error for HYDICE Run 29 2-64% Gray Panels
Digital Imaging and Remote Sensing Laboratory
Error in Recovered Reflectance for Four Ground Truth Sites in AVIRIS Boreas Imagery (NLLSSFavg_RIMAC_NLLSSF Multiple Scattering Model)
-0.14
-0.12
-0.1
-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
400 450 500 550 600 650 700 750 800 850 900
Wavelength (nm)
Diff 535_97
Diff 193_256Diff 250_290
Diff 144_195
Digital Imaging and Remote Sensing Laboratory
Error in Recovered Reflectance (Second Pass) for Four Ground Truth Sites in AVIRIS Boreas Imagery (NLLSSFavg_RIMAC_NLLSSF Multiple
Scattering Model)
-0.14
-0.12
-0.1
-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
400 450 500 550 600 650 700 750 800 850 900
Wavelength (nm)
Diff 535_97
Diff 193_256Diff 250_290
Diff 144_195
Digital Imaging and Remote Sensing Laboratory
Comparison of Different Inversion Techniques from AVIRIS Boreas Image in Multiple Scattering Model
0.00
0.01
0.02
0.03
0.04
0.05
0.06
Diff 535_97 Diff 193_256 Diff 250_290 Diff 144_195
Truth Pixel Evaluated
RMS Error in Reflectance
NLavg_RIMAC_NL
Def_RIMAC_NL
NLLSSF
NLavg_RIMAC_NL 2nd Pass
NLLSSF 2nd Pass
Digital Imaging and Remote Sensing Laboratory
Comparison of Recovered Reflectance for the 64% Gray Panel from HYDICE Run 29
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
Wavelength (µm)
Truth
NLLSSF_avg
NLLSSF_Flat_avg
Digital Imaging and Remote Sensing Laboratory
Amoeba Algorithm in Simplex Space
Digital Imaging and Remote Sensing Laboratory
Compute LUTw/ LT(wv,h,)@ρ=0.4 and Latm (wv,h,)
Calculate RAPDA foreach MODTRAN runby applying APDAequation to the LUT.
Fit ratio values toPW and store theregressionparameters.
Assume startingPW1 and subtractheight dependentLu from image.
Calculate APDA ratioand transform RAPDA
values to PW2 usinginverse mapping eq.
Substitute the Latm
in eq. with newPW dpndt valuesderived from LUT.
Calculate RAPDA a2nd time and trans-form to final PW3(x,y).
General APDA Procedure
Digital Imaging and Remote Sensing Laboratory
The purpose of this research is to contributeto the precision and accuracy of atmospheric characterization by developing an algorithmic approach that will:
Be computationally feasible,
Be radiometrically sound,
Include column water vapor determination
Be able to use in-scene techniques that preclude using
radiosonde or ground truth.
Atmospheric Correction