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REMOTE SENSING FOR LAND & RESOURCES    2016, Vol. 28 Issue (3) : 130-137     DOI: 10.6046/gtzyyg.2016.03.21
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Atmospheric correction and suspended sediment concentration retrieval based on multi-spectral remote sensing images: A case study of Caofeidian offshore area
KONG Jinling1, YANG Jing1, SUN Xiaoming2, YANG Shu1, LIU Futian2, DU Dong2
1. School of Earth Science and Resources, Chang'an University, Xi'an 710054, China;
2. Tianjin Institute of Geology and Mineral Resources, Tianjin 300170, China
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Abstract  

The atmospheric correction of remote sensing image is one of the difficulties in quantitative remote sensing research. In this paper, aimed at the suspended sediment concentration (SSC) levels retrieval in the Caofeidian offshore area, the authors performed a comparative test on atmospheric correction of MODIS image of the study area by 6S and FLAASH models, and then evaluated the corrected image quality and the correction effects of target information(normalized water index, NDWI). The results show that these two models could reduce the atmospheric effect on remote sensing information of water body to some extent. By comparison, the corrected image quality by 6S is better than that by FLAASH and could more truly reflect the target information; therefore, 6S model can better perform atmospheric correction of remote sensing images with a high precision in coastal waters. Subsequently, the MODIS image after atmospheric correction by 6S was applied to invert the SSC in the study area, and the inversion results show that the average relative error(MRE) and the root-mean-square error(RMSE)are 24.79% and 4.32 mg/L, respectively. The results can provide a basis for the selection of atmospheric correction methods in caseⅡwaters, thereby laying a foundation for the study of sediment transport law as well as evaluation of water quality and water environment.

Keywords NPP-VIIRS      night-time light      provincial GDP      land use      GDP spatialization     
:  TP751.1  
Issue Date: 01 July 2016
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LI Feng
MI Xiaonan
LIU Jun
LIU Xiaoyang
Cite this article:   
LI Feng,MI Xiaonan,LIU Jun, et al. Atmospheric correction and suspended sediment concentration retrieval based on multi-spectral remote sensing images: A case study of Caofeidian offshore area[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(3): 130-137.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2016.03.21     OR     https://www.gtzyyg.com/EN/Y2016/V28/I3/130

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