多光谱遥感影像大气校正与悬沙浓度反演——以曹妃甸近岸海域为例

Atmospheric correction and suspended sediment concentration retrieval based on multi-spectral remote sensing images: A case study of Caofeidian offshore area

遥感影像的大气校正是遥感定量化研究的难点之一。以曹妃甸近岸海域为研究区,以水体悬浮泥沙浓度(suspended sediment concentration,SSC)定量反演为目标,采用6S(second simulation of the satellite signal in the solar spectrum)模型和FLAASH模型对研究区MODIS影像的大气校正方法进行对比实验,对2个模型校正前后的影像质量以及对目标地物信息的校正效果进行了评价。研究结果表明:2种模型均能在一定程度上削弱大气对水体信息的影响;相比之下,6S模型校正后影像质量优于FLAASH模型,能更真实地反映目标地物,可更好地实现对近岸海域遥感影像的高精度大气校正;将6S模型大气校正后的MODIS影像应用于悬浮泥沙浓度的遥感反演,反演结果的平均相对误差为24.79%,均方根误差为4.32 mg/L。研究结果可为近岸海域Ⅱ类水体大气校正方法的选择提供依据,为深化泥沙运移规律研究及水质、水环境评价提供技术支持。

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 case Ⅱ waters, thereby laying a foundation for the study of sediment transport law as well as evaluation of water quality and water environment.