• Economic and Environmental Geology
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• v.41 no.2
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• pp.225-242
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• 2008

The site effect for 23 broadband seismic stations in the southern Korean Peninsula was estimated by using the spectral ratio of coda waves. In principle, the site effect means the pure amplification below the station excluding effects of seismic source and attenuation in the wave transmission. However, the site effect determined in this study is equivalent with the relative site amplification factor to the mean amplification for all stations. A total of 500 three-component seismograms from 35 earthquakes, of which magnitude ranged from 2.5 to 5.1 occurred from January, 2001 to January, 2007 was used to obtain the site amplification factor. The site amplification factors were estimated for the frequency bands centered at 0.2, 0.5, 1, 2, 5, 10, 15, and 20 Hz. It was found that the factors for two horizontal components of transverse and radial records were concordant with each other in the all frequency bands. However, the factor for the vertical component was found to be systematically lower than those for two horizontal components. The factors obtained in the low frequency band below 2 Hz ranged from 0.5 to 1.5 in all seismic stations except for KMA and KIGAM stations in Bagryeongdo (BRD1 and BRD2) of which factor showed high value above 1.5. Some stations such as SEO, SNU, HKU, NPR, and GKPI showed high value above 1.5 in the high frequency band from 5 to 20 Hz. Especially, the factors of GKP1 station represented extremely high value ranging from 1.8 to 7.8. Also, the factors for stations of KWJ, SND, and ULJ showed low value below 0.5. The spatial distribution for the relative amplification factor represented a tendency of being approximately lower in north-eastern area than south-western area in the southern Korean Peninsula.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.655-667
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• 2023

Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R²), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R² of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.

• Korean Journal of Remote Sensing
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• v.27 no.5
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• pp.613-623
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• 2011

This study assessed the feasibility to apply Two-band and Three-band reflectance models for chlorophyll-a estimation in turbid productive waters whose scale is smaller and narrower than ocean using a high spatial resolution image. Those band ratio models were successfully applied to analyzing chlorophyll-a concentrations of ocean or coastal water using Moderate Imaging Spectroradiometer(MODIS), Sea-viewing Wide Field-fo-view Sensor(SeaWiFS), Medium Resolution Imaging Spectrometer(MERIS), etc. Two-band and Three-band models based on band ratio such as Red and NIR band were generally used for the Chl-a in turbid waters. Two-band modes using Red and NIR bands of RapidEye image showed no significant results with $R^2$ 0.38. To enhance a band ratio between absorption and reflection peak, We used red-edge band(710 nm) of RapidEye image for Twoband and Three-band models. Red-RE Two-band and Red-RE-NIR Three-band reflectance model (with cubic equation) for the RapidEye image provided significance performances with $R^2$ 0.66 and 0.73, respectively. Their performance showed the 'Approximate Prediction' with RPD, 1.39 and 1.29 and RMSE, 24.8, 22.4, respectively. Another three-band model with quadratic equation showed similar performances to Red-RE two-band model. The findings in this study demonstrated that Two-band and Three-band reflectance models using a red-edge band can approximately estimate chlorophyll-a concentrations in a turbid river water using high-resolution satellite image. In the distribution map of estimated Chl-a concentrations, three-band model with cubic equation showed lower values than twoband model. In the further works, quantification and correction of spectral interferences caused by suspended sediments and colored dissolved organic matters will improve the accuracy of chlorophyll-a estimation in turbid waters.