Transcript assumptions and uncertainties, K. Ruddick (MUMM

Atmospheric correction of ocean color data in coastal waters
Wimereux, 13-14 June 2012
Atmospheric correction of ocean colour data for
extremely turbid waters:
assumptions and uncertainties
Kevin Ruddick (MUMM/RBINS, Belgium)
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© Kevin Ruddick, MUMM/RBINS, 2012
Atmospheric correction of ocean color data in coastal waters
Wimereux, 13-14 June 2012
Objectives of presentation
 Aerosol correction over turbid waters
– Summarise approaches
– Link algorithm assumptions to performance
– Assess uncertainties theoretically
 Scope of presentation
– Just the extra problems of turbid waters
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© Kevin Ruddick, MUMM/RBINS, 2012
Atmospheric correction of ocean color data in coastal waters
Wimereux, 13-14 June 2012
Approaches to aerosol correction
 1. Dark/bright pixel aerosols
– estimated at long wavelength with zero/simple marine refl.
– extrapolated to shorter wavelengths
– e.g. [Gordon and Wang, 1994]
 2. Multispectral matching
– best fit to coupled ocean/atmosphere model
– e.g. [Doerffer and Fischer, 1994]
 3. Polynomial atmospheric path radiance (also for sunglint!)
– atmospheric path radiance = Rayleigh + c0 + c1*λ-1 + c2*λ-4
– [Steinmetz, 2011]
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© Kevin Ruddick, MUMM/RBINS, 2012
Atmospheric correction of ocean color data in coastal waters
Wimereux, 13-14 June 2012
Dark/bright pixel approaches - notation
 Gordon and Wang [GW1994]:
– Rayleigh and gas corrections => “Rayleigh-corr.” reflectance
– Aerosol estimation in near infrared (NIR)
– Extrapolate aerosol reflectance to blue (412nm-670nm)
 RC
TOA
     aT O A     T0 Tv  w0    
0
w here
0
w 
 Drop TOA and “0+” notation
 For this presentation, approx. T0  TV  1
 RC      a      w   
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 If two wavelengths where  w    is known then
can estimate two aerosol properties, e.g.
 a  1  and   1 ,  2    a  1   a   2 
© Kevin Ruddick, MUMM/RBINS, 2012
 Lw
0
Ed
Atmospheric correction of ocean color data in coastal waters
Wimereux, 13-14 June 2012
Dark/bright pixel – A bit of history
 [Gordon, 1978] assume dark red:
 w  670 nm   0
– BUT for moderately turbid waters bright red
– [Guan et al, 1985] propose  w  550 nm    w  670 nm   0
 [GW1994] dark NIR:
 w  765 nm    w  865 nm   0
– BUT for turbid waters bright NIR
– [Ruddick et al, 2000] propose  w  765 nm  /  w  865 nm   
– AND [Moore et al, 1999; Hu et al, 2000; Stumpf et al, 2003; ...]
 [Wang/Shi, 2005] dark SWIR:
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 w 1240 nm    w 1640 nm   0
– BUT for extremely turbid waters bright SWIR
 w 1240 nm   0
– [Shi and Wang, 2009] find
– AND [Knaeps et al, 2012] measure in situ  w 1020 nm   0
© Kevin Ruddick, MUMM/RBINS, 2012
Atmospheric correction of ocean color data in coastal waters
Wimereux, 13-14 June 2012
Pure water absorption and “similarity spectrum”
 NIR/SWIR marine reflectance has simple form:
 e.g. “similarity spectrum” model [Ruddick et al, 2006]
w   
 f '
Q
« Constant »
1 0 .0 0
  
*
* bb   0  * 

aw   

 0 
1
Spectral
shape
Magnitude
W a te r-le a v in g re fle c ta n c e
n o rm a lis e d a t 7 8 0 n m
 w  780 nm 
Particle
size/type
In situ
9 .0 0
w  
n
8 .0 0
7 .0 0
6 .0 0
5 .0 0
… SWIR
4 .0 0
3 .0 0
2 .0 0
[SeaSWIR project]
1 .0 0
0 .0 0
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650
© Kevin Ruddick, MUMM/RBINS, 2012
700
750
800
W a ve le n g th (n m )
850
900
Atmospheric correction of ocean color data in coastal waters
Wimereux, 13-14 June 2012
Dark/Bright pixel – spatial homogeneity?
 Assumption of spatial homogeneity of aerosol type
(Angstrom coefficient,τa, “model”) from clear water pixels
can replace marine assumption(s)
e.g. [GW1994] and [Stumpf et al, 2003] have:
– no assumptions for aerosol type
– two assumptions for marine reflectance
 [Ruddick et al, 2000 for NIR; Wang, 2007 for SWIR] has:
– spatially fixed aerosol type
– one assumption for marine reflectance
 Variable/Fixed aerosol type approaches – which is best?
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© Kevin Ruddick, MUMM/RBINS, 2012
Atmospheric correction of ocean color data in coastal waters
Wimereux, 13-14 June 2012
Dark/Bright pixel - classification
 Propose to classify all (?) Dark/Bright pixel approaches as:
– Variable or Fixed aerosol type
– Two wavelengths used for aerosol
– Marine reflectance model/assumptions
Algorithm
Aerosol type
Wavelengths
Marine model
Gordon and
Wang, 1994
V
765nm, 865nm
w(NIR)=0
Ruddick et al,
2000
F
765nm, 865nm
Stumpf et al, 2003
V
765nm, 865nm
Wang and Shi,
2005
V
1240nm, 1640nm
w(SWIR)=0
etc.
…
…
…
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© Kevin Ruddick, MUMM/RBINS, 2012
Atmospheric correction of ocean color data in coastal waters
Wimereux, 13-14 June 2012
Dark/Bright pixel – from assumptions to uncertainty
 [Ruddick et al, 2000] assumes
 7 ,8 
a a   F
7
8
 
 w  w    
7
8
 giving uncertainty for SeaWiFS band i (7=765nm, 8=865nm)
Marine reflectance
error
i
  w  
 i ,8 
1
 i 8

8
K  a  



w
 7 ,8 


 


Fixed
aerosol error
Atmospheric
reflectance
Extrapolation
factor
w h ere
K
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© Kevin Ruddick, MUMM/RBINS, 2012
i

1

 7 ,8 
Marine
model error
Marine
reflectance
Marine/aerosol
spectral diff.
 8  i 
1


 7 ,8 






7 
 8
“Leverage”
amplification
Atmospheric correction of ocean color data in coastal waters
Wimereux, 13-14 June 2012
Conclusions
For the dark/bright pixel algorithms we can estimate marine
reflectance spectral error if we can estimate marine model
error(s) at NIR/SWIR wavelengths
 can theoretically compare different:
Marine model assumptions
Wavelength choices
Fixed/Variable aerosol assumptions
(also propagate impact of noise, digitisation, etc.)
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© Kevin Ruddick, MUMM/RBINS, 2012
Atmospheric correction of ocean color data in coastal waters
Wimereux, 13-14 June 2012
The Challenges
 Can we estimate marine model error(s) at NIR/SWIR
wavelengths for all dark/bright pixel algorithms?
 Can we estimate errors for other types of algorithm
(multispectral fitting, polynomial)?
 Do theoretical error estimates fit in situ validation results?
 What are remaining unknowns for NIR/SWIR marine
reflectance models?
– particulate backscatter spectral slope
– non-linear reflectance models for high bb/a
– salinity/temperature variation of pure water absorption
 … and NIR/SWIR aerosol models??
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© Kevin Ruddick, MUMM/RBINS, 2012
Atmospheric correction of ocean color data in coastal waters
Wimereux, 13-14 June 2012
Acknowledgement and references
 Belgian Science Policy Office for BELCOLOUR (2006-11)
and BEL-AERONET (2012) funding
 References
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© Kevin Ruddick, MUMM/RBINS, 2012