MERIS US Workshop, Silver Springs, 14th July 2008
MERIS US WorkshopVicarious Calibration Methods and Results
Steven Delwart
MERIS US Workshop, Silver Springs, 14th July 2008
Recent results1. CNES methods
Deserts, Sun Glint, Rayleigh Scattering2. Inter-sensor Uyuni 3. MOBY-AAOT 4. Vicarious Adjustment methodologyOlder results1. Dark Water2. SIMBADA Ocean3. Rail Road Valley Playa4. Comparison with AATSR5. Comparison with SCIAMACHY6. Snow Targets
Presentation Overview
MERIS US Workshop, Silver Springs, 14th July 2008
Deserts, Sun Glint, Rayleigh Scattering(Claire Tinel, Patrice Henry, Olivier Hagolle - CNES)
RayleighDeserts Sun glint
Calibration of MERISusing natural targets
These calibration methods are used operationally at CNESfor POLDER 1, 2, 3, VEGETATION 1 and 2,
for SPOT satellites, MERIS, FORMOSAT-2 and KOMPSAT-2
MERIS US Workshop, Silver Springs, 14th July 2008
• Definitions– Meris on board calibration is the nominal calibration method– Meris is calibrated against t.o.a. reflectance
• k: Spectral band• DN : Digital Number (Meris Level 0, corrected for
instrumental defects)• r : Reflectance• Ak : Sensitivity of instrument for spectral band k
– Calibration results are expressed this way
(Method)ñ
ñ=
A
A=ÄA
predictedk,
1)measured(Lk,
L1k,
methodk,k
)(èñA=DN skkk .cos.
Calibration of MERISusing natural targets
MERIS US Workshop, Silver Springs, 14th July 2008
• Initial objectives :– In orbit vicarious calibration to assess :
• Multiangular calibration (detectors normalization in the f.o.v.)• In time calibration monitoring (on-board calibration verification)• Intercalibration of sensors
• Main characteristics of the requested sites :• Stable in time : no vegetation…• Easy to access : low cloud coverage, good atmospheric conditions• High reflectance : to reduce the impact of atmospheric effects• Low directional effects
⇒ Choice : Desert sites
Desert Calibration
MERIS US Workshop, Silver Springs, 14th July 2008
• Sites selection :– Spatial uniformity
• Better than 2% for 100x100 km2 area• Statistics using Meteosat acquisitions
– Stability over time (seasonal effect)• Stability better than 20% (after atmospheric
effect filtering)• 1 year of Meteosat data (1 per day)
– Low directional effect• Directional effects less than 15%• 1 month of AVHRR data completed with
Meteosat data• Sites characterization :
– Ground truth measurements in Algeria (1993)
Desert Calibration Sites
MERIS US Workshop, Silver Springs, 14th July 2008
• Systematic collect of satellite acquisitions over the 20 sites :Operational monitoring of CNES sensors calibration (on a monthly basis) :– SPOT(s)/High Resolution– SPOT(s)/Vegetation-1&2– PARASOL
Calibration monitoring and intercalibration of other sensors on a regular basis (through cooperation agreements with international space agencies)
– High resolution : Formosat-2 (Taiwan NSPO), Kompsat-2 (South Korea KARI)– Medium resolution : MERIS (ESA), MODIS (soon to come)
Archive of POLDER1&2, SeaWiFS, AVHRR, MISR, MODIS, ATSR2 data.• Storage in a data base :
• SADE data base : “Structure d’Accueil de Données d’Etalonnage”(Calibration Data Repository)
• Easy data management• Link between satellite measurements and calibration results (traceability)
• Nota : the SADE data base also includes calibration measurements over ocean, sunglint, clouds and snow covered sites.
SADE Data Base
MERIS US Workshop, Silver Springs, 14th July 2008
– Compare two sensors :• One sensor as reference• Comparison at TOA level
Reference Sensor
Spectral resampling
Surface reflectancefor sensor 2
Surface reflectancefor reference sensor
Simulated ToAreflectance for sensor 2
Comparison :ΔAk
Sensor 2 MeasurementTOA
SURFACE ♦ Need to account for:• Directional effects• Atmospheric conditions• Spectral discrepancies
Atmospheric correctionto ToA reflectance
Atmospheric correctionto surface reflectance
Desert CalibrationMethod
MERIS US Workshop, Silver Springs, 14th July 2008
• Directional effects :– Direct comparison of measurements in the same geometry (qs, qv, f)– Use of reciprocity principle to extend field of matching geometries
Desert CalibrationGeometry
MERIS US Workshop, Silver Springs, 14th July 2008
• Atmospheric correction :– Atmospheric correction performed using SMAC and meteo data :
• Rayleigh scattering correction• Water vapour• Ozone• Other contributors : CO2, CO, NO2, CH4 (climatologies)
– Problem : aerosol correction…• Aerosol optical thickness t =0.2• Statistically solved through the use of a lot of data:
no significant bias, but dispersion for short wavelengths
Desert CalibrationProcessing
MERIS US Workshop, Silver Springs, 14th July 2008
490
560
665
Cross-calibration with PARASOL as afunction of time (20 sites)
No significant variation with time
2002 2007
POLDER Comparison
865
MERIS US Workshop, Silver Springs, 14th July 2008
• Observe the atmosphere over ocean (dark)• Absolute calibration of bands < 700 nm• Rayleigh scattering : > 80% of signal• TOA reflectance well predicted using:
– Successive Orders of Scattering– Smile effect correction
• Main error sources– ocean surface reflectance :
• predicted using climatology derived from SeaWiFS (1998-1999)• only over very stable oceanic zones (oligotrophic zones)
– aerosols : estimated using 865 nm band• Only optical thickness < 0.1 are kept
• Accuracy : 4 to 5% (3s) – 2 to 3 % (RMS)
Rayleigh Calibration
MERIS US Workshop, Silver Springs, 14th July 2008
Choice of oligotrophic areas with 2 years of SeaWiFS datamade in 2001 with ACRI and LOV (CLIMZOO zones)
Rayleigh Calibration Sites
MERIS US Workshop, Silver Springs, 14th July 2008
No discrepancy greater than 2.5%
0,9
0,92
0,94
0,96
0,98
1
1,02
1,04
1,06
1,08
1,1
400 450 500 550 600 650 700
wavelength
delta_Ak
Rayleigh/M98
Rayleigh CalibrationResults
MERIS US Workshop, Silver Springs, 14th July 2008
• Sun glint calibration– observe the white reflection of the sun over the ocean surface– interband calibration w.r.t. a reference spectral band– TOA reflectance predicted using SOS code
– Main error sources• Reference band calibration errors• ocean surface : SeaWiFS climatology• aerosols : fixed model used (M98, AOT :0.08)
– daily SeaWiFS aerosol product used to discard cases when aerosol properties differ from reference model
• Accuracy : 3 to 4.5% (3s) - 1.5 to 2% (RMS)
Calibration of MERISusing natural targets
MERIS US Workshop, Silver Springs, 14th July 2008
Comparison of sun glint resultsusing different reference bands
0,985
0,990
0,995
1,000
1,005
1,010
1,015
1,020
400 500 600 700 800 900
Glint / 620 Glint / 665 Glint / 709
Sun Glint Calibration Results
σ∆Akσ∆Ak0.022
0.020
0.016
0.016
0.021
-
0.008
0.008
0.013
0.130
0.011
0.026
0.0240.029
0.031
0.042
0.031
0.013
0.010
0.013
-
0.004
0.007
0.010
0.017
0.019
1.0161.010885
1.0231.012865
1.0151.004778
1.0211.015753
-0.993708
1.0191.010681
1.0171.008665
1.007-620
1.0081.001560
0.9970.990510
1.0131.005490
1.0000.993442
1.0071.001412
Ref Band 708Ref Band 620Band
MERIS US Workshop, Silver Springs, 14th July 2008
Still no discrepancy greater than 2.5%
0,9
0,92
0,94
0,96
0,98
1
1,02
1,04
1,06
1,08
1,1
400 500 600 700 800 900 1000
wavelength
delta_ak
glint / (620)
Rayleigh/M98Sun glintReference
spectral band
Error barscorrespondto standarddeviation of
results
Rayleigh / Sun Glint
MERIS US Workshop, Silver Springs, 14th July 2008
• Conclusions– MERIS instrument seems well calibrated– Rayleigh + glint + deserts
• measurements agree with MERIS level 1 calibration (within 2 %)– Very good agreement between Rayleigh and sun glint calibration methods– no significant degradation with time– thanks to :
» MERIS calibration device» MERIS good spectral calibration
– Simultaneous validation of :• MERIS calibration• CNES calibration methods
• Perspective– Multitemporal calibration monitoring of 412 and 443 nm bands– MERIS/MODIS intercalibration over deserts
Calibration of MERISusing natural targets
MERIS US Workshop, Silver Springs, 14th July 2008
Inter-sensor at Uyuni
Sensor IntercomparisonMERIS, MODIS, AATSR, PARASOL
Salar de Uyuni (Bolivia)Geometric selection criteria 10 deg > √ [ (SZA(i)- SZA(j))2+ (VZA(i)- VZA(j))2+ 1/4x(abs(RAA(i))- abs( RAA(j)))2]
(Equvalent to a difference of 5 deg for VZA & SZA and ±10 for RAA.)
Data Selection Criteria: Reciprocaland identical doublets are kept iffrom the same day or differing by
one day
MODIS vs MERIS Very good agreement
865nmAvrDif=0.38% STD=2.11%
560nmAvrDif=0.22% STD=2.64%
MERIS US Workshop, Silver Springs, 14th July 2008
LISE AnalysisMoby, AAOT
Good agreement in the blue,questionable in the NIR do to
dominant backscattering geometryavailable from Moby.
MERIS US Workshop, Silver Springs, 14th July 2008
Older results• Dark Water• SIMBADA Ocean• Rail Road Valley Playa• Comparison with AATSR• Comparison with SCIAMACHY• Snow Targets
Older Vicarious Results
MERIS US Workshop, Silver Springs, 14th July 2008
Dark Water (LISE)
884 nm-2.2 %
864 nm-1.4 %
778 nm+0.9%
664 nm-2.5%
680 nm-1.0%
753nm+1.4%
MERIS US Workshop, Silver Springs, 14th July 2008
bands Ak(mean)
412 0.991
443 0.987
490 0.991
510 0.996
560 0.988
620 0.992
SIMBADA (LOA)
• 23 independant pixels from 14 scenes• AOT max : 0.15• Within 3 hours from satellite overpass• Case 2 waters rejected
MERIS US Workshop, Silver Springs, 14th July 2008
Rail Road Valley PlayaCollaboration RSL & UofA
MERIS US Workshop, Silver Springs, 14th July 2008
Rail Road Valley PlayaCollaboration JPL & UofA
MERIS US Workshop, Silver Springs, 14th July 2008
Surface 560 nm 670 nm 870 nm
Deserts (Smith) 1.041 1.001 1.037
Greenland (Smith) 1.034 1.012 1.037
Clouds (Poulsen) 1.047 1.026 1.054
Longyeardyen 1.026 1.024 1.038
Barrows 1.024 1.001 1.023
MODTRAN 3.5 - Mid Summer
0
0.2
0.4
0.6
0.8
1
1.2
0.500 0.550 0.600 0.650 0.700 0.750 0.800 0.850 0.900
Wavelength !m
Tra
nsm
issio
n
"0 Degrees"
"20 Degrees"
"40 Degrees"
"60 Degrees"
"AATSR SpectralResponse"
"ATSR-2 SpectralResponse"
"MERIS SpectralResponse"
Comparison with AATSR
MERIS US Workshop, Silver Springs, 14th July 2008
0.9760.9800.9850.9850.988
0.9870.9880.9900.9880.990
0.9880.9890.9900.9920.993Corr.
0.0130.0100.0020.000-0.004
-0.012-0.020-0.023-0.022-0.022
-0.027-0.023-0.024-0.023-0.026Offset
1.151.121.121.091.10
1.201.191.171.161.15
1.2571.211.191.171.18Slope
• Given the current state of knowledge, we (KNMI) propose that it is the reflectance data of SCIAMACHY instead of MERIS, that should be corrected.
Comparison with SCIAMACHY
MERIS US Workshop, Silver Springs, 14th July 2008
-10
-9
-8
-7
-6
-5
-4
-3
-2
-1
0
1
2
3
4
5
400 500 600 700 800 900
Wavelength in nm
(R-R
_M
ER
IS_
11
:26
)/R
_M
ER
IS_
11
:26
(in
%)
MERIS 11:26
MERIS 13:03
SeaWiFS
11:19
SeaWiFS
12:57
SeaWiFS
14:35
SeaWiFS
16:11
AATSR Nadir
11:26
MODIS 8:50
MODIS 10:30
Longyearbyne (ESA) Barrows (JAXA)
Snow Targets
MERIS US Workshop, Silver Springs, 14th July 2008
Vicarious AdjustmentPrinciple
MERIS US Workshop, Silver Springs, 14th July 2008
Vicarious Gain Computation
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