1. D e v e l o p m e n t o f t h e M N I R-S W I R a n d AA a t m o s p h e r I c c o r r e c t I o n a n d s u s p e n d e d s e d I m e n t
c o n c e n t r a t I o n a l g o r I t h m s a n d t h e I r v a l I d a t I o n I n t h e c o a s t a l w a t e r s o f t h e E a s t C h I n a Sea
Leonid Sokoletsky, Fang Shen, and Xianping Yang
East China Normal University
ABSTRACT
Mapping of suspended sediment concentration (SSC) can be achieved from the modern space-based optical sensors such as MODIS, MERIS, SeaWiFS, and GOCI using reliable atmospheric correction and SSC algorithms. We have developed two different atmospheric correction (AC) and one SSC algorithms. The both AC algorithms, namely, modified near-infrared―short-wave infrared (MNIR-SWIR) and analytical approximation (AA), and SSC algorithm as well, were validated in the coastal waters of the East China Sea (Fig. 1).
The algorithms developed were compared for the spectral surface remote-sensing reflectance Rrs(l) and SSC both with in situ measurements and the atmospheric radiative transfer Second Simulation of a Satellite Signal in the Solar Spectrum (6S) algorithm. We show validation results and give recommendations for the further use of satellite ocean color algorithms.
ATMOSPHERIC CORRECTION ALGORITHMS
The 6S is one of the most widely used numerical algorithm for AC (Kotchenova et al., 2006, 2008; Kotchenova and Vermote, 2007), and it was used as a benchmark for validation of AC algorithms developed for various waters of the East China coast.
The MNIR-SWIR algorithm has been developed by Yang Xianping (2016) based on the NIR-SWIR (Wang and Shi, 2007) combined AC model. The main feature of this new algorithm is using the same aerosols parameters (aerosol optical depth and Ångström exponent) for the turbid coastal waters as for the adjacent more clear waters, quite far off the Chinese coast.
The AA algorithm is a recent attempt Sokoletsky et al., 2014) to use meticulous accounting optical effects in atmosphere expressed in the form of analytical expressions. This is differs AA from the 6S and MNIR-SWIR algorithms which use very complicate computations and the look-up-tables formed on the base of preliminary radiative transfer computations.
RESULTS
Comparison results between in situ measurements of Rrs(l) and Rrs(l) derived from the three remote sensing algorithms shown on Fig. 2 for five different samples.
Fig. 2. Rrs(l) comparison results for five different samples collected in moderate (d), turbid (a, c, e), and extremely turbid (b) waters, respectively.
Fig. 3 shows logarithmic relative errors for SSC:
Fig. 1. Turbidity classification map for the East China coastal waters. Blue, green, yellow, and red colors refer to clear, moderate, turbid, and extremely turbid waters, respectively.
Fig. 3. Logarithmic relative errors for SSC.
Conclusion
The simple AA atmospheric correction & SSC algorithms yield the best results comparing with in situ and 6S.
REFERENCES
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Kotchenova S.Y. and E.F. Vermote Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part II. Homogeneous Lambertian and anisotropic surfaces. Appl. Opt., 46(20):
Kotchenova S.Y., E.F. Vermote, R. Levy, and A. Lyapustin Radiative transfer codes for
atmospheric correction and aerosol retrieval: intercomparison study. Appl. Opt., 47(13):
Sokoletsky, L., X. Yang, and F. Shen MODIS-Based Retrieval of Suspended Sediment Concentration and Diffuse Attenuation Coefficient in Chinese Estuarine and Coastal Waters. Proc. SPIE Asia Pacific Remote Sensing, 9261: –
Wang M. and W. Shi The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing. Optics Express, 15(24):
Yang X Evaluation of Suspended Sediment Concentration and Diffuse Attenuation Coefficient by in situ and Satellite Remote Sensing Methods in Yangtze River Estuary and Adjacent Coastal Area. M.Sc. Thesis. East China Normal University, Shanghai, China.