Estimation of suspended sediment concentrations in inland waters using Terra\ASTER images

Suspended sediments are the most common pollution in both scale of weight and volume in surface fresh waters and they can play a key role in the environmental processes. Therefore, use of higher spectral and spatial resolution satellite sensors can help us to monitor and quantify the suspended sediments in a more accurate way. In the present study, remote sensing techniques have been employed to obtain suspended sediment concentration (SSC) map in Bahmanshir River estuary. Due to great and special attitudes of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) in water quality monitoring, it was used in this investigation. In situ data were collected during several missions while the satellite sensor was passing over study area. Preprocessing stages including radiometric, geometric and atmospheric corrections were done on ASTER digital data. Both regression analysis and artificial neural network (ANN) were applied in order to establish a proper relationship between SSC and remote sensing reflectance. Results obtained by ANN model were remarkable and it was realized that it is more accurate than the regression models to estimate SSC in inland waters.