Presentation on theme: "Atmospheric correction using the ultraviolet wavelength for highly turbid waters State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute."— Presentation transcript:
Atmospheric correction using the ultraviolet wavelength for highly turbid waters State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou, China Xianqiang He, et al.
Principle of the UV-AC In turbid waters, high SPM and CDOM dominate water’s optical properties. Due to particle scattering, Lwn increases rapidly in the VIS and NIR. Meanwhile, strong absorption of detritus and CDOM reduce Lwn in the UV and shortwave of VIS. Changjiang River Spring, 2003 Changjiang River Autumn, 2003 Mississippi River Orinoco River. Lwn at the VIS and NIR increases rapidly with the increase of water turbidity, but it increases very little at the UV. Hypothesis: In highly turbid waters, Lwn at UV can be neglected compared with that at the VIS and even NIR, and we can use the UV band to estimate aerosol scattering radiance. He et al., OE, 2012
Oo et al. (2008) found that water-leaving reflectance ρwn(412nm) is relatively low and stable in the Chesapeake region, and thus they used 412nm band to constrain the aerosol model selection for the SWIR-AC algorithm. Oo et al., AO, 2008
In the Gironde Estuary in the southwest France, it was found that the remote sensing reflectance at 400 nm was quite smaller as compared to visible or even NIR Gironde Estuary, located in southwest France. Doxaran et al., AO, 2003
UV-AC algorithm Step 1: Calculating the Rayleigh-scattering corrected reflectance Total reflectance measured by sensor: Step 2: Assuming ρw at UV band can be neglected, we get aerosol multiple-scattering reflectance at UV band with “(e)” means the estimated value instead of the actual value; Step 3: Estimating the aerosol scattering reflectance at the longer NIR band. where Step 4: Assuming the “white” aerosol scattering, then aerosol scattering reflectance at all bands is equal to
The key of the UV-AC algorithm The critical is the rationality of the empirical estimation of aerosol scattering reflectance at the longer NIR band. First, is always larger than the real value due to the contribution of water-leaving radiance, though the water- leaving reflectance is small at the UV in turbid waters. Second, is generally larger than the real value (He et al., OE, 2012). The compensating effect between and is expected to get a reasonable estimation of aerosol scattering reflectance at longer NIR. The “white” aerosol approximation is rationale for the coastal aerosol and maritime aerosol, which are the dominating aerosol types in the coastal regions.
Validation of the UV-AC (I: theoretical deduce) We have theoretically evidenced that the error of water-leaving radiance (including the atmospheric diffuse transmittance) at the VIS retrieved by the UV-AC algorithm was generally larger than, and less than (He et al., OE, 2012). The average value of Lwn(UV) is about 0.5 mW/(cm2 ⋅ μm ⋅ sr). Also, for a clear to moderately turbid atmosphere, La(UV) is generally less than 0.5 mW/(cm2 ⋅ μm ⋅ sr) for zenith viewing. Therefore, for most cases, the retrieval error of the water- leaving radiance by the UV-AC algorithm is expected to be less than 1.0 mW/(cm2 ⋅ μm ⋅ sr).
We simulated the at nine bands (365, 412, 443, 490, 510, 555, 670, 765 and 865 nm) according to First, the water-leaving reflectance was estimated with the in situ measured Lwn for turbid waters with Lwn(555 )≥2.0. Then, for each in situ Lwn, we simulated the aerosol scattering reflectance and atmospheric diffuse transmittance for different aerosol models, aerosol optical thickness and solar-satellite geometries. The 12 aerosol models in the SeaDAS were used. For each aerosol model and aerosol multiple-scattering reflectance at 865 nm and solar-satellite geometries, we calculated the aerosol single-scattering reflectance at 865 nm according to look-up tables from SeaDAS, and then the aerosol single-scattering reflectance at other eight bands were extrapolated from 865 nm. Finally, the multiple-scattering reflectances at all bands were calculated by the single-scattering reflectance using the look-up tables. Validation of the UV-AC (II: simulation)
We applied UV-AC (365nm) based on 365nm to simulated data. Although UV-AC(365nm) slightly overestimated as a whole, the retrieved values agreed quite well with in situ, especially at longer wavelengths. For most cases, UV-AC(365nm) can retrieve the water-leaving reflectance well (30.8%, 22.9%, 15.9%, 13.1%, 8.9%, 6.0%, 11.5% and 13.7% for 412, 443, 490, 510, 555, 670, 765 and 865 nm). Since past and current sensors have no UV band, and the shortest wavelength is 412 nm. We use same scheme as UV-AC(365nm) but take 412 nm as the reference band. Performance of UV- AC(412nm) is quite similar as the UV- AC(365nm). UV-AC(365nm)UV-AC(412nm) He et al., OE, 2012
Application of UV-AC(412nm) to Aqua/MODIS Lwn retrieved by Aqua/MODIS on 5 April 2003 using UV-AC(412nm) 4 in situ stations on 5 Apr. 2003 (stars); Since Aqua/MODIS saturated in highly turbid coastal waters, there were no effective values in the coasts HD34HD35 HD36HD37 He et al., OE, 2012
Jun.27, 2011 8:28 9:2810:28 11:28 12:2813:28 14:28 15:28 Application of UV-AC(412nm) to GOCI He et al., RSE, 2013
27 June 2011 station A at 9:16 AM. station A at 12:08 PM. station B at 3:21 PM. Comparison of Lwn retrieved by UV-AC(412nm) and in situ value In general, UV-AC(412nm) -retrieved Lwn matches in situ values well in both quantity and spectral, with average absolute relative errors of 25.0% (412 nm), 11.8% (443 nm), 9.9% (490 nm), 6.6% (555 nm), 13.9% (660 nm), 6.8% (680 nm) and 29.1% (745 nm) He et al., RSE, 2013
SPM inversion from GOCI using the UV-AC(412nm) retrieved Lwn in the high turbid Hangzhou Bay Comparing with Buoy data SPM on 5 Apr. 2011 He et al., RSE, 2013
My interesting (or contribution) for the participation to this WG Validate the UV-AC algorithm with the same data sets used by all other turbid water AC algorithms (including the satellite, RT simulated and in situ data). Improve and release the code of the UV-AC algorithm for public use. Generate the RT simulated dataset for validation based on the PCOART (Polarized Coupled Ocean- Atmosphere Radiative Transfer model) (He et al., 2007; He et al. 2010)
PCOART PCOART is a vector radiative transfer model of the coupled ocean-atmosphere system with rough sea- surface, based on the matrix-operator method (or adding-doubling). PCOART has been validated by the RT problem in the Rayleigh atmosphere, underwater, coupled ocean- atmosphere system. In addition, the radiance at the top-of-atmosphere simulated by the PCOART reproduce the satellite observation.
Comparison of the Rayleigh scattering Stokes vector at TOA simulated by PCOART and calculated by the Look-up table of Aqua/MODIS I Q URelative error of I He et al., 2010
The underwater radiance simulated by PCOART meet the requirement of the underwater RT model by Mobley et al. (1993) Underwater RT problem 1: an unrealistically simple problem Underwater RT problem 2: a base problem using realistic inherent optical properties for the ocean He et al., 2007
Underwater RT problem 3: the base problem but with stratified water Underwater RT problem 4: the base problem but with a finite depth bottom Underwater RT problem 5: the base problem but with a rough sea surface He et al., JQSRT, 2010
The radiance in the coupled ocean-atmosphere system simulated by PCOART consists with the scalar RT model COART COART is the scalar radiative transfer code using the discrete ordinates method for rough sea surface,based on the DISTORT. Wind speed of 5m/s Top-of-atmosphere Just above sea surface 5m depth underwater He et al., JQSRT, 2010
PCOART simulation reproduces the linear polarization reflectance measured by POLDER POLDER measured linear polarization reflectance at 443nm on 10 July 2003 PCOART simulated He et al., JQSRT, 2010
Some concerns about the goal (or output) of this WG Systematically understand the advantage, limitation, and application condition of the proposed turbid water AC algorithms. Establish the benchmark for the assessment of the turbid water AC algorithms. Improve and release the codes for the easy use by the community. Give suggestions for the future improvement of the turbid water AC algorithm, and for the design of future ocean color sensors.
Thanks for your attention! State Key Laboratory of Satellite Ocean Environment Dynamics, SIO/SOA, China