Suspended sediment (SS) concentration, also known by other names such as total suspended solids (TSS) concentration or total suspended matter (TSM), is an important index of water quality in shallow water areas such as coastal water regions, river estuaries, lagoons, and bays. By studying suspended sediment concentration, we can better understand the coastal ecosystem and environment, the marine biochemical processes, oceanic topography, geomorphology, etc. Therefore, in this study, the author carried out two independent research topics using satellite images to study SS characteristics in the northern coastal area of Taiwan and a Bay in northern Vietnam. Firstly, the author considers monitoring the spatial-temporal distribution of SS in the coastal area of Taiwan impacted by Typhoon Soudelor in 2015. The purpose of this study is to indicate geostationary satellite images with high resolution can be a possible solution to monitor the change in suspended sediment concentration due to a typhoon influence. By using the Geostationary Ocean Color Imager (GOCI) satellite images with 500m resolution and eight images/day, the study shows that GOCI can be used to monitor suspended sediment concentrations before and after a typhoon. Specifically, we used hourly image data of three different periods before and after the typhoon to generate a non-linear model to monitor the change in the spatial distribution of suspended sediment along the coastal water in the north of Taiwan. The results show that the SSC quickly increased to the highest level 3-4 days after the typhoon and then gradually decreased to its status before the typhoon about 15-20 days later. In addition, it also indicates that river discharges are a source of SSC after typhoons to coastal areas. The Daan, Tam Sui, and Lanyang rivers are the three largest sources of SS in the northern coastal area of Taiwan. Secondly, we propose to use Formosat-5 (FS5) satellite images to study suspended sediment concentrations in Ha Long Bay, Vietnam. This study aims to evaluate whether FS5 image could be used for mapping SS in coastal water.
The research problem is that there is no atmospheric correction method and suspended sediment concentration algorithm developed for FS5, therefore, the author focuses on evaluating and choosing a simple approach to solve these two problems. The results show that using linear regression is a suitable solution to convert the Digital Number (DN) to Remote sensing reflectance (Rrs) based on reference data of ground targets from the Landsat-8 Operational Land Imager (OLI) image. OLI reference images were processed by using the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) model and downloaded from the United States Geological Survey (USGS) website providing good results for this solution. To overcome the limitation of no TSM algorithm, we choose two different algorithms that use the red band and then compare the results to find out which algorithm can be used for FS5. The algorithms include an international algorithm developed by Nechad et al., suitable for Vietnamese waters and an algorithm developed by Richard et al. for the previous sensor Formosat-2 (FS2). The FS5-derived TSM is compared with the reference data of the OLI-derived TSM image based on the histogram, accuracy assessment with RMSE, and spatial distribution map. The results show that the Nechad et al. algorithm can be used to estimate the suspended sediment concentration in Ha Long Bay.

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