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Proceedings Paper

Calculation of the water-leaving reflectance based on aerosol information retrieved from NIR/SWIR bands
Author(s): Lin Zhu; Fanlin Yang; Xinghua Zhou; Qingshan Xu; Lei Yang; Huan Yin
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Paper Abstract

Compare with the reflectance of land surface, ocean water is much less. And, the contribution of atmospheric molecules and aerosols plays an vital importance on the water-leaving reflectance inversion. In order to simplify the inversion process, we generate a look-up-table(LUT) that contains the observation geometry information, the aerosol optical depth(AOD), the exponent of Junge power law(V) and the other factors used to calculate the water-leaving reflectance. The AOD and V are determined using our previous iterative algorithm from dual near-infrared(NIR) and dual shortwave infrared( SWIR) channels, respectively. We compare the retrieved AOD and V with Aerosol Robotic Network(AERONET) measurement data to ensure the precision of aerosol information. The AERONET AOD at 550nm is 0.0876, and the inversed AOD from dual-NIR and dual-SWIR is 0.05-0.325 and 0.0373-0.98, respectively. For dual- NIR, there are 31.97% and 57.18% pixels with the AOD absolute relative error less than 10% and 20%, respectively. For dual-SWIR, there are 31.01% and 59.79%. Then, we use the retrieved aerosol information together with the observation geometry information to get the factors used to calculate the water-leaving reflectance through interpolation. Finally, we use the MODIS ocean color product to verify the water leaving reflectance calculated based on aerosol retrieved from NIR and SWIR, and the two calculated water-leaving reflectance are marked as ρNIR and ρSWIR. In the visible and near-infrared region, both of them are smaller than the product values. Despite the ρSWIR is larger than ρNIR, the overcorrection is much more serious in ρNIR.

Paper Details

Date Published: 31 January 2020
PDF: 10 pages
Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 114272G (31 January 2020);
Show Author Affiliations
Lin Zhu, Shandong Univ. of Science and Technology (China)
Fanlin Yang, Shandong Univ. of Science and Technology (China)
National Administration of Surveying, Mapping and Geoinformation of China (China)
Xinghua Zhou, The First Institute of Oceanography, SOA (China)
Qingshan Xu, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences (China)
Lei Yang, The First Institute of Oceanography, SOA (China)
Huan Yin, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences (China)
DFH Satellite Corporation Ltd. (China)


Published in SPIE Proceedings Vol. 11427:
Second Target Recognition and Artificial Intelligence Summit Forum
Tianran Wang; Tianyou Chai; Huitao Fan; Qifeng Yu, Editor(s)

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