利用2009年11月9日城市湖泊青山湖实测的水体高光谱遥感数据和同步水质采样数据,在分析水体固有光学特性的基础上,采用单波段、两波段比值和一阶微分3种算法进行了湖泊水体总悬浮物浓度(TSS)遥感反演研究.结果表明,单波段、两波段比值和一阶微分模型相关系数均较好,688 nm处一阶微分线性回归模型相关系数R为0.932 8,RMSE为2.896 1 mg/L,为最佳的TSS实测光谱遥感反演模型,可以用于青山湖水体TSS浓度的反演.该研究可为水质指标大面积的卫星遥感反演研究提供基础.%According to the measured hyperspectral remote sensing data and synchronous sampling data about the water quality of Qingshan Lake on November 9,2010, the inherent optical properties of the water were analyzed ,based on which the retrieval of total suspended sediment concentration (TSS) in Qingshan Lake was studied by three methods of single band, spectra ratio of two bands and reflectance first-derivative. As indicated by the results ,the three methods appeared to be significantly correlated with total suspended sediment concentration. The correlation coefficient R2 and RMSE of the first-derivative model at 688 nm were 0.932 8 and 2.896 1 mg/L respectively ,therefore it was the best model for the retrieval of TSS concentration in Qingshan Lake. The study provided basis for the retrieval of large-scale water by satellite remote sensing.
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