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2005-02-01 Co-Retrieval of Aerosol Color and Surface Color from SeaWiFS Satellite Images
1. Co-Retrieval of Aerosol Color and Surface Color from SeaWiFS Satellite Images Rudolf B. Husar CAPITA, Washington University, St. Louis, MO, October 1999 rhusar@me.wustl.edu
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5. Radiative Transfer Theory for Aerosol-Surface Co-retrieval The sensed radiation is decomposed into scattering and absorption by (1) gases, (2) aerosols as well as reflection from the (3) surfaces and (4) clouds. Air scattering and surface/aerosol reflectance are assumed to be additive, disregarding multiple scattering effects.
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9. Apparent Surface Reflectance, R Aerosols will increase the apparent surface reflectance, R, if P/R 0 < 1. For this reason, the reflectance of ocean and dark vegetation increases with τ. When P/R 0 > 1, aerosols will decrease the surface reflectance. Accordingly, the brightness of clouds is reduced by overlying aerosols. At P~ R 0 the reflectance is unchanged by haze aerosols (e.g. soil and vegetation at 0.8 um). . At large τ (radiation equilibrium), both dark and bright surfaces asymptotically approach the ‘aerosol reflectance’, P The critical parameter whether aerosols will increase or decrease the apparent reflectance, R, is the ratio of aerosol angular reflectance, P, to bi-directional surface reflectance, R 0 , P/ R 0
10. Loss of Contrast The aerosol τ can also be estimated from the loss of surface contrast. Whether contrast decays fast or slow with increasing τ depends on the ratio of aerosol to surface reflectance, P/ R 0 Note: For horizontal vision against the horizon sky, P/R 0 = 1, contrast decays exponentially with τ, C/C 0 =e -τ .
11. Obtaining Aerosol Optical Thickness from Excess Reflectance The perturbed surface reflectance, R, can be used to derive the the aerosol optical thickness, τ , provided that the true surface reflectance R 0 and the aerosol reflectance function, P are known. The excess reflectance due to aerosol is : R- R 0 = (P- R 0 )(1-e - τ ) and the optical depth is: For a black surface, R 0 =0 and optically thin aerosol, τ < 0.1, τ is proportional to excess radiance, τ =R/P. For τ > 0.1, the full logarithmic expression is needed. As R 0 increases, the same excess reflectance corresponds to increasing values of τ. When R 0 ~P the aerosol τ can not be retrieved since the excess reflectance is zero. For R 0 > P, the surface reflectance actually decreases with τ, so τ could be retrieved from the loss of reflectance, e.g. over bright clouds. The value of P is derived from fitting the observed and retrieved surface reflectance spectra. For summer light haze at 0.412 μm, P=0.38. Accurate and automatic retrieval of the relevant aerosol P is the most difficult part of the co-retrieval process. Iteratively calculating P from the estimated τ( λ) is one possibility.
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14. SeaWiFS Images and Spectra at Four Wavelengths (Click on the Images to View) At blue (0.412) wavelength, the haze reflectance dominates over land surface reflectance. The surface features are obscured by haze. Air scattering (not included) would add further reflectance in the blue. The blue wavelength is well suited for aerosol detection over land but surface detection is difficult. At green (0.555) over land, the haze is reduced and the vegetation reflectance is increased . The surface features are obscured by haze but discernable. Due to the low reflectance of the sea, haze reflectance dominates. The green not well suited for haze detection over land but appropriate for haze detection over the ocean and for the detection of surface features. At red (0.67) wavelength over land, dark vegetation is distinctly different from brighter yellow-gray soil. The surface features, particularly water (R 0 <0.01), vegetation (R 0 <0.04), and soil (R 0 <0.30) are are easily distinguishable. Haze reflectance dominates over the ocean. Hence, the red is suitable for haze detection over dark vegetation and the ocean as well as for surface detection over land. In the near IR (0.865) over land, the surface reflectance is uniformly high (R 0 >0.30) over both vegetation and soil and haze is not discernable . Water is completely dark (R 0 <0.01) making land and water clearly distinguishable. The excess haze reflectance over land is barely perceptible but measurable over water. Hence, the near IR is suitable for haze detection over water and land-water differentiation.
15. Haze Effect on Spectral Reflectance over Land The spectral reflectance of vegetation in the visible λ is low at 0.01<R 0 <0.1. Haze significantly enhances the reflectance in the blue but the haze excess in the near IR is small. This is consistent with radiative transfer theory of haze impact.
16. Comparison of Haze Effects on Land and Ocean In the blue (λ=0.412) and red (λ=0.67) both the land and the ocean have low surface reflectance and the excess reflectance is the same. However at green and near IR the excess reflectance over land is lower then over the ocean as expected from radiative transfer theory.
21. Nearly Cloud and Haze-Free Northeast (Click on the Images to View) The haze and cloud-free image was constructed as lowest reflectance from 28 days of data (July15-Aug 15, 1999). Some areas show residues of haze and clouds. The first step is to create cloud and haze-free image of the surface reflectance. In the visible, 0.4 < λ < 0.7 the surface reflectance is relatively low (R=0.01- 0.1) and highly textured. The main colors are green (vegetation), yellow-brown (soil, concrete) and blue-black (water). The residue haze and cloud effects were removed from the ‘minimum image’ (except over the coastal areas). This image was used to calculate excess reflectance due to aerosols .
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23. Hazy and Haze-Corrected Surface Reflectance (Click on the Images to View) Over the ocean with thick haze, the haze correction removes over 90% of the signal Haze correction over land retrieves the vegetation spectral pattern in the visible and near IR. Reflectance with haze removed Total reflectance due to clouds, haze and surface