Estimation of Suspended Sediment Concentration Changes in Taihu Lake Based on Multi-temporal MODIS Image Data

The concentration of Suspended Sediment (SS) is and important indicator of inland takes trophic state. Using Taihu Lake, China as a case study and multi-temporal MODIS images as data resources, this paper focuses on developing and applying MODIS algorithms to detect the changes of Suspended Sediment concentration in Taihu Lake. Field survey data and MODIS images are acquired in different seasons. Using linear regression and nonlinear regression, send-empirical models for these seasons are developed respectively by relating field data to different MODIS hand combinations. And then, the changes of SS concentration in different seasons are determined and evaluated by applying these models to corresponding MODIS images. The study result shows that multi-temporal MODIS image data is suitable to monitor such change. Its high temporal resolution is advantaged in this research.