1. Atmospheric Correction for Ocean Color Remote Sensing Geo 6011 Eric Kouba Oct 29, 2012

2. Ocean Color Overview Measured dataTop of Atmosphere Radiance Need to doAtmospheric Correction Desired signalWater-Leaving Radiance orRemote Sensing Reflectance **************************************************************************** Use other equations and methods... Proxy parametere.g. Chlorophyll-A concentration Biological parameterPhytoplankton primary productivity Desired goalInformation about health of the ocean

3. Sunlight to Surface to Sensor 1. Solar spectrum at top of atmosphere 2. Atmospheric absorption, scattering, etc 3. Clouds Thin clouds allow some visibility 4. Reflection from top layer of ocean Case 1 clear waters (tens of meters) Case 2 turbid waters (less penetration) 5. Atmospheric absorption, scattering, etc 6. Radiance measured by satellite sensor Only 10% to 20% of signal comes from ocean waters

4. Ocean Color Sensors and Satellites CZCS sensor on Nimbus-7 satellite SeaWiFS sensor on OrbView-2 satellite MODIS sensor on Terra satellite MERIS sensor on ENVISAT satellite MODIS sensor on Aqua satellite ETM+ sensor on LANDSAT satellite

5. Sensors and Satellites - Past www.ioccg.org

6. Sensors and Satellites - Current www.ioccg.org

7. Sensors and Satellites - Planned www.ioccg.org

8. Major types of correction methods Know which one your software uses Dark object subtraction Invariant object subtraction Histogram matching Cosine estimation of atmospheric transmittance Contrast reduction Path extraction Spectral shape matching method -> CAAS Others

9. SeaWiFS seadas.gsfc.nasa.gov

10. SeaDAS Atmospheric Correction Wavelength dependent equation ρ T (λ i ) = ρ R + ρ A + ρ C + ρ SG + ρ WC + transmittance surf-sensor * ρ W ρ T Top of atmosphere reflectanceSensor ρ RA Rayleigh scattering Not difficult ρ AS Aerosol scatteringDifficult ρ CPL Coupled Rayleigh-Aerosol effectsAssume zero ρ SG Sun glintAssume zero ρ WC Whitecaps (wind on sea surface)Less than 7 m/s ρ W Water-leaving reflectanceDesired Basically a dark object subtraction, with additions Assumes NIR (765 and 865 nm) should be zero 12 aerosol models -> 25000 simulation runs -> Lookup tables Works well for deep, clear, and low growth water Fails in shallow, turbid, and high growth water

11. Options when standard correction fails Flag and ignore regions that are difficult to process If available, use SWIR instead of NIR for dark subtraction butMODIS has SWIR signal to noise problem Simultaneous spectroradiometer measurements in field of view butNot practical for daily operations Take spectroradiometer measurements nearby butAtmospheric parameters vary in time and space Use other algorithm with standard atmospheres butAtmospheric parameters vary in time and space Use algorithm to get aerosol correction from within image data e.g.Shanmugam (2012)

12. aeronet.gsfc.nasa.gov

13. CAAS - Basic Equation L T (λ i ) = L R + L A + L C + trans sun-surf * L SG + L WC + trans surf-sensor * L W L T Top of atmosphere reflectanceSensor L R Rayleigh scattering Not difficult L A Aerosol scatteringEstimated L C Coupled Rayleigh-Aerosol effectsEstimated L SG Sun glintEstimated L WC Whitecaps (wind on sea surface)Ignored for now L W Water-leaving reflectanceDesired Use Rayleigh-corrected Radiance to derive Aerosol correction Spectral shape matching method See Shanmugam (2012) pg 205-207 for math discussion

17. Conclusions NIR dark subtraction fails in shallow, turbid, and high growth water Like counting worldwide trees, but failing in the jungle Aerosol modeling remains difficult Atmospheric correction is important... Choose wisely

18. Questions?