• Atmosphere
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• v.27 no.3
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• pp.261-276
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• 2017

The main objectives of this study are to introduce Global Seasonal forecasting system version5 (GloSea5) of KMA and to evaluate the performance of ensemble prediction of system. KMA has performed an operational seasonal forecast system which is a joint system between KMA and UK Met office since 2014. GloSea5 is a fully coupled global climate model which consists of atmosphere (UM), ocean (NEMO), land surface (JULES) and sea ice (CICE) components through the coupler OASIS. The model resolution, used in GloSea5, is N216L85 (~60 km in mid-latitudes) in the atmosphere and ORCA0.25L75 ($0.25^{\circ}$ on a tri-polar grid) in the ocean. In this research, we evaluate the performance of this system using by RMSE, Correlation and MSSS for ensemble mean values. The forecast (FCST) and hindcast (HCST) are separately verified, and the operational data of GloSea5 are used from 2014 to 2015. The performance skills are similar to the past study. For example, the RMSE of h500 is increased from 22.30 gpm of 1 week forecast to 53.82 gpm of 7 week forecast but there is a similar error about 50~53 gpm after 3 week forecast. The Nino Index of SST shows a great correlation (higher than 0.9) up to 7 week forecast in Nino 3.4 area. It can be concluded that GloSea5 has a great performance for seasonal prediction.

• Journal of Korean Society of Rural Planning
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• v.12 no.1 s.30
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• pp.37-48
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• 2006

The objectives of this study were to develop an evaluation method of regional vulnerability to agricultural drought and to classify the vulnerability patterns. In order to test the method, 24 city or county areas of Gyeonggi-do were chose. First, statistic data and digital maps referred for agricultural drought were defined, and the input data of 31 items were set up from 5 categories: land use factor, water resource factor, climate factor, topographic and soil factor, and agricultural production foundation factor. Second, for simplification of the factors, principal component analysis was carried out, and eventually 4 principal components which explain about 80.8% of total variance were extracted. Each of the principal components was explained into the vulnerability components of scale factor, geographical factor, weather factor and agricultural production foundation factor. Next, DVIP (Drought Vulnerability Index for Paddy), was calculated using factor scores from principal components. Last, by means of statistical cluster analysis on the DVIP, the study area was classified as 5 patterns from A to E. The cluster A corresponds to the area where the agricultural industry is insignificant and the agricultural foundation is little equipped, and the cluster B includes typical agricultural areas where the cultivation areas are large but irrigation facilities are still insufficient. As for the cluster C, the corresponding areas are vulnerable to the climate change, and the D cluster applies to the area with extensive forests and high elevation farmlands. The last cluster I indicates the areas where the farmlands are small but most of them are irrigated as much.

• Journal of Korean Society on Water Environment
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• v.36 no.1
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• pp.36-47
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• 2020

Three large scale weirs were constructed 2010 - 2011 in the Namhan river, Korea. The purpose of this study was to investigate the spatial distribution of benthic macroinvertebrates and the influence of environmental factors at the weirs 2014 - 2015. The number of species was higher in the riparian zone than in the transition or the limnetic zone. This seems to be because of the diversification of microhabitats and food sources according to the development of littoral zones. From the riparian zone to the limnetic zone, the individual abundance proportion of gathering collectors among functional feeding groups decreased, and that of filtering collectors increased. In the limnetic zone, sprawlers and climbers among habitat orientation groups decreased, and burrowers increased. This means that coarse particulate organic matter originated from land or riparian zone was transformed to fine particulate organic matter in the limnetic zone. Asian clam (Corbicula fluminea) and chironomids were dominant species based on individual abundance. Asian clam, a major taxon considering biomass, was abundant toward the limnetic zone. This is becasue of the shallow depth, suitable water current, slightly coarse substrate, and good water quality. There was no significant relationship between the water quality and the characteristics of the benthic macroinvertebrate community because the water quality was spatially not heterogenous. The more influential factors for benthic community were physical factors, especially water depth. Water depth showed a markedly significant correlation with Shannon-Weaver's species diversity (r=-0.90), Margalef's species richness (r=-0.82), and McNaughton's dominance (r=0.86). Water depth showed a positive correlation (r=0.68) with the Kong and Kim BMSI (Bentic Macroinverebrates Streambed Index), and this may be related to the coarse substrate of the limnetic zone.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.405-410
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• 2004

In mid-90's, the Korean government introduced the GIS(Geographic Information System) to digitalize every topography of national land and thereby, index locations and attributes of various urban facilities to construct a system whereby every information could be managed and operated in an integrated way, but the reliability of such geographic information has yet to be tested, much less its modification, complementation and maintenance. Under such circumstances, this study was aimed at constructing a reference point infrastructure for Seoul and Kyonggi area and comparing the data obtained from the GPS operation and various facility location data with the existing GIS data to address the problems of GIS operation and suggest their solutions. As a result of calculating the GPS reference point data and analyzing the deviations of the unknown point data in comparison with the fixed point ones, it was found that the horizontal location values were reliable within +/- 5cm, but that the above-sea level values varied as much as 1.4m depending on the deployment of pre-set fixed points determined by the direct level gauging. In addition, as a result of directly surveying major facilities around the roads based on the coordinates of the urban reference points networked with such a reference point system to check their conformity to existing data, it was confirmed that the difference was as wide as 2m. Such differences may be attributable to the fact that the data with their geographic information not confirmed are used as basic data for GIS. Hence, this study suggests the ways to set the absolute geographic data based on reference points and test the reliability of existing data and thereby, suggests a methods to solve the problems.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.181-189
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• 2017

The purpose of this research is to set a standard for deciding competitive marketing prices of new supplying apartment houses and to analyze decision factors in sale price of supplying apartment houses with Analytic Hierarchy Process; the resulted model does not use the method that joins the land cost and the cost of construction together, but the method that compares the sales prices of surrounding apartments. This research tries to set a standard for decision of the prices of newly supplying apartment houses by classifying the determinants into the $1^{st}$ step(4 factors), the $2^{nd}$ step(9 factors), and the $3^{rd}$ step(25 factors). According to the process, the relative importance of decision factors in the sale prices is determined and this should be used as the index of sale prices for newly supplying apartment houses when the houses are provided. In addition, through the $2^{nd}$ step including 9 factors, the comparative model for sale prices is defined and the model is presented to be applied in the real business. Subsequent study additionally considering the factors apart from marketing which tries to find a generalized standard needs to be conducted.

• Journal of Integrative Natural Science
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• v.13 no.1
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• pp.27-33
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• 2020

The unsustainable human activities like increased use of automobiles, heavy industrialization and the use of large volumes of fertilizers, chemicals and pesticides in the agricultural land cause climate change problems in one way or another. Under normal circumstances, the heat radiations from the sun will be reflected back. An excessive volume of GHGs in the atmosphere would prevent these radiations from reflecting back. East Asia is facing severe climate change issues in recent times. A lot of climate change problems such as hurricanes and floods have been reported from this region in the last couple of decades. The study aimed at investigating the climate change in East Asia with changing Sea Surface Temperature (SST). The study adopted a quantitative research method with a case study research design where a deliberate focus was made on the East Asia Region. Secondary data was gathered and analyzed to yield both descriptive and inferential statistics. The study concluded that the impact of East Asia Climate variability was significant mainly for some extreme events. Also, the study concluded that there was a significant link between the change of the East Asia climate variability and that of the sea surface temperature. Further, the study concluded that a linear relationship existed between the sea surface temperature and the climate of East Asia. Hence, a linear regression was a significant predictor of the East Asia Climate (EAC) based on changing sea surface temperature. The model revealed that 37.4% of the variations in the climate change index were explained by the changes in the sea surface temperature. The climate was expected to change with a value of 49.48 for a unit change in the sea surface temperature.

• Korean Journal of Remote Sensing
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• v.31 no.1
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• pp.29-38
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• 2015

The coastline influenced naturally and artificially changes dynamically. While the long-term change is influenced by the rise in the surface of the sea and the changes in water level of the rivers, the short-term change is influenced by the tide, earthquake and storm. Also, man-made thoughtless development such as construction of embankment and reclaimed land not considering erosion and deformation of coast has been causes for breaking functions of coast and damages on natural environment. In order to manage coastal environment and resources effectively, In this study is intended to analyze and predict erosion in coastal environment and changes in sedimentation quantitatively by detecting changes in coastal line from data collection for satellite images and aerial LiDAR data. The coastal line in 2007 and 2012 was extracted by manufacturing Digital Surface Model (DSM) with Aviation LiDAR materials. For the coastal line in 2009 and 2010, Normalized Difference Vegetation Index (NDVI) method was used to extract the KOMPSAT-2 image selected after considering tide level and wave height. The change rate of the coastal line is varied in line with the forms of the observation target but most of topography shows a tendency of being eroded as time goes by. Compared to the relatively monotonous beach of Taean, the gravel and rock has very complex form. Therefore, there are more errors in extraction of coastlines and the combination of transect and shoreline, which affect overall changes. Thus, we think the correction of the anomalies caused by these properties is required in the future research.

• Journal of Korea Water Resources Association
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• v.39 no.4 s.165
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• pp.363-372
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• 2006

Many methods have been used to estimate evapotranspiration. However, there is little information about the evapotranspiration from river basins with complicated topographies and variable land use. Remote sensing technique is a probable means to estimate distribution of the evapotranspiration in connection with regional characteristics of vegetation and landuse. The evapotranspiration not only depends on meteorological circumstances but also on the condition of the vegetation. The latter effect can be expressed in terms of NDVI(Normalized Difference Vegetation Index) obtained by NOAA/AVHRR datasets. In this paper, a simple method to estimate evapotranspiration of the Keum river basin is proposed based on NDVI and temperature data.

• Journal of fish pathology
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• v.18 no.2
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• pp.187-195
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• 2005

Effluent of aquaculture industry has caused a growing concern regarding its environmental impact. We assessed the use of flounder farming sewage as supplement of diet, to minimize the impact of aquaculture on the environment or also establish the technique for the recycling of effluent sediment derived from land-based seawater fish farm. In order to investigate the effects of a fermented aquaculture waste on biochemical responses of olive flounder (Paralichthys olivaceus), fermented products of aquaculture wastes were used as test compounds that cause hepatic and renal stress through the induction of oxidative stress in liver and kidney. Hepatosomatic index (HSI), glutathione content and glutathione dependent enzyme were not significantly different and no correlation was found within the different types of fermentation condition or supplement concentration, except for significant increases in 50% fermentation group and 50% concentration group in case of glutathione peroxidase activity and HSI value, respectively. These results showed addition of fermented aquaculture sewage may be an economic artificial sources of diet for fish aquaculture practices without affecting the function and safety in view of biochemical examination.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.221-234
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• 2016

In Korea, most industrial parks and major cities are located in coastal areas, which results in serious environmental problems in both coastal land and ocean. In order to effectively manage such problems especially in coastal ocean, water quality should be monitored. As there are many factors that influence water quality, the Korean Government proposed an integrated Water Quality Index (WQI) based on in situmeasurements of ocean parameters(bottom dissolved oxygen, chlorophyll-a concentration, secchi disk depth, dissolved inorganic nitrogen, and dissolved inorganic phosphorus) by ocean division identified based on their ecological characteristics. Field-measured WQI, however, does not provide spatial continuity over vast areas. Satellite remote sensing can be an alternative for identifying WQI for surface water. In this study, two schemes were examined to estimate coastal WQI around Korea peninsula using in situ measurements data and Geostationary Ocean Color Imager (GOCI) satellite imagery from 2011 to 2013 based on machine learning approaches. Scheme 1 calculates WQI using estimated water quality-related factors using GOCI reflectance data, and scheme 2 estimates WQI using GOCI band reflectance data and basic products(chlorophyll-a, suspended sediment, colored dissolved organic matter). Three machine learning approaches including Random Forest (RF), Support Vector Regression (SVR), and a modified regression tree(Cubist) were used. Results show that estimation of secchi disk depth produced the highest accuracy among the ocean parameters, and RF performed best regardless of water quality-related factors. However, the accuracy of WQI from scheme 1 was lower than that from scheme 2 due to the estimation errors inherent from water quality-related factors and the uncertainty of bottom dissolved oxygen. In overall, scheme 2 appears more appropriate for estimating WQI for surface water in coastal areas and chlorophyll-a concentration was identified the most contributing factor to the estimation of WQI.