总悬浮物浓度是水质评价的重要参数之一, 传统的遥感反演估算模型忽视了光学性质多变、 复杂的二类水体的差异性。 本研究基于太湖、 巢湖的星地同步实验, 针对环境1号卫星多光谱数据, 设立了水体光学分类方法, 将研究水体分为二种类型, 进而建立了适用于不同类型水体总悬浮物浓度的反演估算模型。 得出以下结论: （1）基于光谱分类的方法可以提高总悬浮物浓度的反演估算精度; （2）对于类型一和类型二水体, 分别使用指数模型和线性模型可以较好地反映总悬浮物浓度与反演估算因子之间的关系。

Total suspended matter concentration is one of the important parameters of water component. Traditional retrieval model ignored the difference of case 2 water which has complex optical properties. In the present study, we developed a method of water classification based on optical classification using HJ-1 multispectral data. We divided the water into two types and developed a retrieval model suitable for different water type. The results indicate: (1) the accuracy of retrieved results based on spectral classification has been improved; (2) exponential model reflects the relationship between suspended sediment concentration and retrieved factor and is better for type Ⅰ water, while linear model is better for type Ⅱ water.