This paper discusses the use of a Geostationary Ocean Color Imager (GOCI) to monitor the spatial–temporal distribution of suspended sediment (SS) along the coastal waters of northern Taiwan which was affected by Typhoon Soudelor from 8 to 10 August 2015. High temporal resolution satellite images derived from GOCI were processed to generate four-day average images of SS for pre- and post-typhoon periods. By using these four-day average images, characteristics of SS along the north of Taiwan coastal water can be tracked. The results show that SS concentration increased in the four-day average image immediately after the typhoon (11–14 August), and then decreased in the four-day average image 9 to 12 days after the typhoon (19–22 August). The mouths of the Dajia River and Tamsui River were hotspots of SS, ranging from 9 to 15 g/m3 during the two post-typhoon periods. Moreover, the maximum suspended sediment (SSmax) and its corresponding time (tmax) can be computed using GOCI hourly images for the post-typhoon period from 08:30 on 11 August to 08:30 on 22 August. The results show that SSmax occurred in the west coastal water within 4 days post-typhoon, and SSmax occurred in the east coastal water 9 to 12 days post-typhoon. Furthermore, an exponential decay model was used to compute the time when 90% of typhoon-induced SS was dissipated after Typhoon Soudelor (t90). It was found that t90 in the mouths of the Tamsui River and Heping River was the longest among all coastal waters of our study area, with a range of 360–480 h. River discharge and ocean currents with suspended sediment concentration are discussed.

This study proposes the use of spatial high-resolution Formosat-5 (FS5) images for estimating total suspended matter (TSM) concentrations in a coastal region. Although many atmospheric correction methods are available, none of them are proposed to apply to FS5. Therefore, to remove the atmospheric effect, we performed a linear regression between the digital number (DN) of an FS5 image and the Landsat-8 Operational Land Imager (OLI) level-2 remote-sensing reflectance (Rrs) by using 160 samples of five ground targets. The ground targets, namely roof material, asphalt, water, vegetation, and other materials (sand and soil), were assumed to have negligible differences within 24 h. The results show that the linear model used for computing FS5 reflectance exhibited good coefficients of determination (R2) ranging from 0.87 to 0.96 for blue, green, red, and near-infrared bands. Next, in situ TSM measurements were not collected during the FS5 overpassing in Ha Long Bay, Vietnam, so we used two existing algorithms with a red band to estimate the TSM concentration. These algorithms developed for different coastal waters exhibited satisfactory agreement between derived field data and observed TSM concentrations with R2 ranging from 0.86 to 0.95. We also cross-checked the accuracy of the FS5-derived TSM concentration through comparison with an OLI-derived TSM image. The OLI-derived TSM image was validated and discussed for Vietnamese coastal waters, including Ha Long Bay. Lastly, based on comparisons between FS5- and OLI-derived TSM images in terms of spatial distribution, histograms, and root mean square error, we indicated the FS5 images after the removal of atmospheric effects could be totally used for estimating TSM in coastal water regions.