Joo Hyung Ryu

Study on the sediment classification in a tidal flat considering the pattern of channel distribution

We examined the relations of the channel distribution with the sedimentary facies in Geunso-bay tidal flat, Korea. The tidal channel networks were extracted from an aerial photograph. The patterns of the channel distribution were compared with one another for several sites in terms of the fractal analysis, channel density. The channels in each sediment facies showed relatively constant meandering patterns, however, the density and the complexity were distinguishable for each facies. The 2nd fractal dimension which indicates the branch pattern of the tidal channel were 1.87 in the mud flat, 1.41 in the mixed flat, and about 1.30 in the sand flat. The channel density in the mud flat was 0.035-0.06 m/m2 which was the highest among the three sedimentary facies. Using the differences in fractal dimensions and tidal channel densities in each sedimentary facies, we tried to adjust the sedimentary facies classification which had been generated from the interpolation of the surveyed data. For each grain size sampling site, the percentage of sand particles was compared with the channel density. It was shown that the higher the sand percentage, the lower the tidal channel density except at a few points. The locations showing the exceptional pattern were mainly inside the tidal channel or adjacent to the inland. We suggest that those differentiated features of tidal channels among the different sedimentary facies should be applied to the surface sedimentary facies classification in the tidal flat.

Spatiotemporal Variation in Suspended Sediment Concentrations and Related Factors of Coastal Waters Based on Multispatial Satellite Data in Gyeonggi Bay, Korea

ABSTRACT Eom, J.; Choi, J.-K.; Won, J.-S.; Ryu, J.-H.; Doxaran, D.; Ruddick, K., and Lee, S., 2017. Spatiotemporal variation in suspended sediment concentrations and related factors of coastal waters based on multispatial satellite data in Gyeonggi Bay, Korea. The variations in suspended sediment concentration (SSC) in turbid coastal waters around Gyeonggi Bay, Korea were analyzed using multiresolution ocean-color satellite imagery. Geostationary Ocean Color Imager (GOCI) and Land Satellite 7 (Landsat-7) Enhanced Thematic Mapper Plus (ETM+) images were atmospherically corrected, and an empirical algorithm was employed to generate maps of SSCs in the study area and investigate daily and annual variabilities in coastal water turbidity. SSC values were highest around 6 hours before high tide and around low tide, and the maximum values had strong positive relations with the tidal range near the sand ridge and channel (R2 values of 0.74 and 0.72, respectively), which implies that the main driver of the diurnal variability in SSC is resuspension of bottom sediment by tides in areas of shallow water. Annually, the maximum SSC value near the sand ridge was about 400 g m−3, showing remarkable variation over tidal cycles, whereas it was about 10 g m−3 in the open sea, with little variation. The SSC around the sand ridge was higher in winter than in summer, mainly because of stronger resuspension resulting from winds during the NW monsoon in winter. The SSC around the Han River estuary was higher in summer than in winter because of the river discharge, which indicates that suspended sediments supplied by the Han River do not significantly affect SSC variation in the open ocean. This study revealed that application of the high temporal resolution of GOCI, combined with the high spatial resolution of Landsat-7 ETM+, can be useful for monitoring short- and long-term variations in SSC in Korean coastal waters.

In-orbit optical performance assessment of Geostationary Ocean Color Imager

After Geostationary Ocean Color Imager (GOCI) was launched at June 27th, 2010, it is operated to observe the Korean peninsula on the geostationary orbit as one of the three main payloads in COMS satellite. Generally, the performance indicators are Ground Sample Distance (GSD), Modulation Transfer Function (MTF), and Signal to Noise Ratio (SNR) that verify the optical performance of payload. Most of all, the MTF performance is widely used since it is closely related to reliability and accuracy of observational target information in aspects of satellite image application. Especially, in case of ocean color sensor, for confirming the ability of GOCI to separate the slight difference of ocean color information, on-orbit MTF performance test and SNR assessment should be performed.

Control factors of spectral reflectance in tidal flat: a case study in the Gomso Bay, Korea

The objective of this study is to investigate the control factors of spectral reflectance and microwave scattering in tidal flat. The control factors are generally considered as grain size, soil moisture content, local slope, and creeks. We have carried out field data sampling in the Gomso Bay, Korea, including grain size, soil moisture content and its variation with time, surface roughness, ground levelling, and field spectral reflectance measurement. We have analyzed Landsat TM, EOS-Terra ASTER, RADARSAT, ERS-1/2, and JERS-1 SAR data. L- and C-band radar scattering modelling was also conducted. The results show that tidal condition and remnant surface water are important additional parameters. SWIR is shown to be correlated most with sediment grain size. The grain size of 0.0625 mm has normally been considered as a critical size of mud and sand discrimination. But we propose here that 0.25 mm is more practical grain size criterion in optic remote sensing. The radar scattering modelling show variation of less than 15 dB within the tidal flat, and L-band HV-polarization is turned out to be the best for tidal flat observation. The SAR data is also sensitive to the effective exposed area (EEA) effect.

Assessment of TerraSAR-X for mapping salt marsh

This study presents results of assessment of X-band SAR image for mapping salt marsh. Multi-temporal TerraSAR-X data were acquired with different incidence angle (23°, 31°, and 39°) in mono- and dual polarization modes (HH, VH/VV) for backscattering analysis. Backscattering coefficients from industrial areas were used to confirm the calibration. The types of land cover were differentiated based on seasonally averaged backscattering coefficients of classes. The behavior of backscattering coefficients was also analyzed as a function of SAVI (soil adjusted vegetation index). Decision trees were used to build classification rule sets. Accuracy of classification was estimated by reference image generated from field works and ancillary data.

A study of tidal channel influence upon surficial sediment distribution in the Ganghwa-Do southern tidal flat

Spatial relationships between surface sediment distribution and channel networks were estimated for the Ganghwa-Do southern tidal flat, Korea. Tidal channels were extracted from high spatial resolution satellite data and used to derive maps of channel density and distance from channels. The map of surface sediment distribution was produced from grain-size data on sediment samples. Then, for each surface sedimentary facies, the relations with tidal channels were estimated in terms of the fractal analysis, channel density and distance from the channel. The results demonstrate a significant spatial relationship between the distribution of surface sediment in a tidal flat and tidal channel distribution. We conclude that tidal channel should be considered an important factor in mapping surface sedimentary facies in tidal flat environments, and that patterns of tidal channel are a useful adjunct to spectral reflectance in classifying the surface sediment from remotely sensed data with high spatial resolution.

Application of neural networks to waterline extraction in tidal flat from optic satellite images

The waterline extraction is one of the most effective satellite remote sensing tools for studying tidal flat environments and its changes, but has not been investigated in detail. A series of field surveys have been carried out to obtain grain size, moisture contents, field spectrometer measurement, and waterline tracking simultaneously with satellite observation. A neural networks algorithm was developed for extracting waterline in tidal flat from satellite-based remote. sensing data and applied to the Gomso tidal flat, Korea. Characteristics of tidal flats and spectral reflectance associated with waterline were analyzed first. We have chosen three bands as input data of neural networks: NIR reflects the amount of suspended sediment content at lower tidal flats; SWIR is sensitive to moisture content and is seriously affected by remaining surface water in sedimentary structures; and TIR appears to be the best among the three bands but its low spatial resolution reduces its utility. The neural network method developed here is independent of tidal situations and robust. The neural networks not only distinguish between tidal flats and seawater out of the images, but it also provides continuous outputs that represent mixed compositions of both features. The values of 0.3 - 0.4 were turned out to be waterline in neural networks output The neural networks output provided the closest to the ground truth and that of the ETM TIR band.

Estimation of the sedimentation budget in tidal flat using remotely sensed data

The intertidal topography is continuously changed due to morphodynamic processes. The objectives of this study are: (i) to generate an intertidal digital elevation model (DEM) using waterlines extracted from Landsat TM; (ii) to estimate sediment budget and to analyze sediment pattern using generated DEMs 1991 and 2000. The band ratio of (TM4-TM3)/(TM4+TM3) is shown to be most effective. We tested the proposed method in Gomso Bay, Korea, and successfully produced intertidal DEMs with 10.9 cm rms error. The sediment budget and pattern analysis were quantitatively estimated by differencing the two DEMs. A comparison of DEM1991 with DEM2000 deduced from 13 Landsat TM scenes shows sedimentation dominant in the lower flat and no significant changes in the upper flat. The grain size of the surface sediment may not directly be correlated with reflectivity. The results demonstrate that remote sensing is a useful and valuable tool for the intertidal flat studies, and practically the one and only possible way to provide reliable data of the two-dimensional sediment budget and pattern.