• Atmosphere
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• v.24 no.3
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• pp.343-364
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• 2014

This study presents local and synoptic conditions associated with extreme heavy snowfall events in the Yeongdong region, as well as the temporal and spatial variability of these conditions. During the last 12 years (2001~2012), 3 extreme snowfall events occurred in the Yeongdong region, which recorded daily snowfall greater than 50 cm, respectively. In these events, one of the noticeable features is the occurrence of heavy hourly snowfall greater than 10 cm. It was reported from satellite analysis that these heavy snowfall may be closely related to mesoscale convective clouds. In this paper the 3 extreme events are examined on their synoptic environments associated with the developments of mesoscale convective system using numerical model output. These 3 events all occurred in strongly forced synoptic environments where 500 and 300 hPa troughs and 500 hPa thermal troughs were evident. From the analysis of diagnostic variables, it was found in all 3 events that absolute vorticity and cold air advection were dominant in the Yeongdong region and its surrounding sea at upper levels, especially at around 500 hPa (absolute vorticity: $20{\sim}60{\times}10^{-5}s^{-1}$, cold air advection: $-10{\sim}-20^{\circ}C$ $12hr^{-1}$). Moreover, the spatial distributions of cold advection showed mostly the shape of a narrow band along the eastern coast of Korea. These features of absolute vorticity and cold advection at 500 hPa were sustained for about 10 hours before the occurrence of maximum hourly snowfall.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.250-253
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• 2007

Korean Multi-Purpose SATellite 5 (KOMPSAT-5) will be the first high resolution X-band SAR satellite of Korea. A critical parameter necessary for interpreting SAR images over the ocean is surface wind field. SAR is the only system that can provide a synoptic view of wind fields over the ocean covering large areas. However, there has been no X-band wind retrieval model. In this study, we evaluate the development of an X-band wind retrieval model and show the possibility of KOMPSAT-5 SAR on wind estimations using a combination of theoretical models.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.78-81
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• 2003

The present study illustrates a method for monitoring the urban vegetation around Shaoxing city, Monitoring spatiotemporal changes in urban areas will become increasingly important as the number and proportion of urban residents continues to increase. The synoptic view of urban land cover provided by satellite and airborne sensors is an important complement to in situ measurements of physical, environmental and socioeconomic variables in urban settings. The results obtained have revealed a notable change in the vegetation cover in and around the City premises. In this study, we discussed methodology for measurement of urban vegetation and vegetation distributions based on band ratioing in Shaoxing city using Land sat TM imageries. A systematic analysis of the spatiotemporal dynamics of vegetation in urban areas is required to ensure a healthy sustainable environment.

• Journal of Environmental Impact Assessment
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• v.15 no.2
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• pp.121-127
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• 2006

The conventional water quality measurements by point sampling provide only site specific temporal water quality information but not the synoptic geographic coverage of water quality distribution. To circumvent these limitations in temporal and spatial measurements, the use of remote sensing is increasingly involved in the water quality monitoring research. In other to assess a trophic state of Yongdam reservoir using satellite imagery data, I obtained Landsat ETM data and water quality data on 16th September and 18th October 2001. The approach involved acquisition of water quality samples from boats at 33 sites on 16th September and 30 sites on 18th October 2001, simultaneous with Landsat-7 satellite overpass. The correlation coefficients between the DN values of the imagery and the concentrations of chlorophyll-a were analyzed. The visible bands(band 1,2,3) and near infrared band(band 4) data of September image showed the correlation coefficient values higher than 0.9. The October image showed the correlation coefficient values about 0.7 due to the atmospheric effect and low variation of chlorophyll-a concentration. Regression models between the chrophyll-a concentration and DN values of the Landsat imagery data have been developed for each image. The regression model was determined based on the spectral characteristics of chlorophyll, so the green band(band 2) and near infrared band(band 4) were selected to generate a trophic state map. The coefficient of determination(R2) of the regression model for 16th September was 0.95 and that of the regression model for 18th October was 0.55. According to the trophic state map made based on Aizaki's TSI and chlorophyll-a concentration, the trophic state of Yongdam reservoir was mostly eutrophic state during this study.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.89-94
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• 2003

The formation of a severe snow storm occurred in the mountainous coastal region near Mt. Taegualyang and Kangnung city in the eastern part of Korea was investigate from 0900LST, December 7 through 9, 2002, using MM5 model. As synoptic scale easterly wind induced a great amount of moisture from the East Sea into the inland coastal region and sea-breeze further induced more moisture from the basin toward the top of the mountain side. The lifted moisture toward the mountain top was cooled down along the eastern slope of the mountain and near the mid of the mountain the moisture was much cooled down with relative humidity of 100％ under the air temperature below $O^{\circ}C$, resulting in the formation of snow. Relative humidity of 100％ generally occurred at the 5km away from the coast toward the inland mountain and the band of 100％ RH was parallel to the coastal line. The 100％ band coincided with minimum air temperature band and line.

• Korean Journal of Remote Sensing
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• v.18 no.3
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• pp.141-146
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• 2002

Chlorophyll-a concentration maps of Yongdam reservoir in September and October, 2001 were produced using Landsat ETM imagery and the in-situ water quality measurement data. In-situ water samples were collected on 16th September and 18th October during the satellite overpass. The correlations between the DN values of the imagery and the values of chlorophyll-a concentration were analyzed. The visible bands(band 1, 2, 3) and the near infrared band(band 4) data of September image showed the correlation coefficient values higher than 0.9. The October image showed correlation coefficient values of about 0.7 due to the low variations of chlorophyll-a concentration. Regression models between the DN values of the Landsat ETM image and the chlorophyll-a concentration have been developed for each image. The developed regression models were then applied to each image, and finally the chlorophyll-a distribution maps of Yongdam reservoir were produced. The produced maps showed the spatial distribution of the chlorophyll-a in Yongdam reservoir in a synoptic way so that the tropic state could be easily monitored and analysed in the spatial domain.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.485-493
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• 2006

This study is to combine precipitation data with different spatial-temporal characteristics using an optimal weighting method. This optimal weighting method is designed for combination of AWS rain gage data and S-band RADAR-estimated rain data with weighting function in inverse proportion to own mean square error for the previous time step. To decide the optimal weight coefficient for optimized precipitation according to different training time, the method has been performed on Changma case with a long spell of rainy hour for the training time from 1 hour to 10 hours. Horizontal field of optimized precipitation tends to be smoothed after 2 hours training time, and then optimized precipitation has a good agreement with synoptic station rainfall assumed as true value. This result suggests that this optimal weighting method can be used for production of high-resolution quantitative precipitation rate using various data sets.

• Wind and Structures
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• v.24 no.2
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• pp.185-204
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• 2017

High-resolution wind measurements at 2.25 m in height were used to investigate the mean and turbulence properties of an extreme thunderstorm wind event in West Texas. These data were combined with single Doppler scans from the Texas Tech University Ka-band mobile Doppler radars systems (TTUKa) to provide meteorological context over the surface measurement stations for portions of the outflow. Several features characteristic of a severe wind event were noted in the radar data, including a bowing portion of the thunderstorm complex and a small circulation on the leading edge. These features were reflected in the surface wind time histories and provided natural separation between various regions of the outflow. These features also contributed to the peak 1-s gust at all measurement stations. The turbulence characteristics of each outflow region were also investigated and compared. Reduced values of running turbulence intensity and elevated values of longitudinal integral scales were noted during the period of peak wind speed. Larger scales of turbulence within the outflow were also suggested via spectral analysis.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.177-184
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• 2003

Numerical simulation on marine wind and sea surface elevation was carried out using both three-dimensional hydrostatic and non-hydrostatic models and a simple oceanic model from 0900 LST, August 13 to 0900 LST, August 15, 1995. As daytime easterly meso-scale sea-breeze from the eastern sea penetrates Kangnung city in the center part as basin and goes up along the slope of Mt. Taegullyang in the west, it confronts synoptic-scale westerly wind blowing over the top of the mountain at the mid of the eastern slope and then the resultant wind produces an upper level westerly return flow toward the East Sea. In a narrow band of weak surface wind within 10km of the coastal sea, wind stress is generally small, less than l${\times}$10E-2 Pa and it reaches 2 ${\times}$ 10E-2 Pa to the 35 km. Positive wind stress curl of 15 $\times$ 10E-5Pa $m^{-1}$ still exists in the same band and corresponds to the ascent of 70 em from the sea level. This is due to the generation of northerly wind driven current with a speed of 11 m $S^{-1}$ along the coast under the influence of south-easterly wind and makes an intrusion of warm waters from the southern sea into the northern coast, such as the East Korea Warm Current. On the other hand, even if nighttime downslope windstorm of 14m/s associated with both mountain wind and land-breeze produces the development of internal gravity waves with a hydraulic jump motion of air near the coastal inland surface, the surface wind in the coastal sea is relatively moderate south-westerly wind, resulting in moderate wind stress. Negative wind stress curl in the coast causes the subsidence of the sea surface of 15 em along the coast and south-westerly coastal surface wind drives alongshore south-easterly wind driven current, opposite to the daytime one. Then, it causes the intrusion of cold waters like the North Korea Cold Current in the northern coastal sea into the narrow band of the southern coastal sea. However, the band of positive wind stress curl at the distance of 30km away from the coast toward further offshore area can also cause the uprising of sea waters and the intrusion of warm waters from the southern sea toward the northern sea (northerly wind driven current), resulting in a counter-clockwise wind driven current. These clockwise and counter-clockwise currents much induce the formation of low clouds containing fog and drizzle in the coastal region.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.487-501
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• 2020

As a viable option for retrieval of LST (Land Surface Temperature), this paper presents a DNN (Deep Neural Network) based approach using 148 Landsat 8 images for South Korea. Because the brightness temperature and emissivity for the band 10 (approx. 11-㎛ wavelength) of Landsat 8 are derived by combining physics-based equations and empirical coefficients, they include uncertainties according to regional conditions such as meteorology, climate, topography, and vegetation. To overcome this, we used several land surface variables such as NDVI (Normalized Difference Vegetation Index), land cover types, topographic factors (elevation, slope, aspect, and ruggedness) as well as the T₀ calculated from the brightness temperature and emissivity. We optimized four seasonal DNN models using the input variables and in-situ observations from ASOS (Automated Synoptic Observing System) to retrieve the LST, which is an advanced approach when compared with the existing method of the bias correction using a linear equation. The validation statistics from the 1,728 matchups during 2013-2019 showed a good performance of the CC=0.910~0.917 and RMSE=3.245~3.365℃, especially for spring and fall. Also, our DNN models produced a stable LST for all types of land cover. A future work using big data from Landsat 5/7/8 with additional land surface variables will be necessary for a more reliable retrieval of LST for high-resolution satellite images.