• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2000.11a
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• pp.307-308
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• 2000

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.268-273
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• 1998

This study applies an on-line system, which employes an adaptive reconstruction technique to monitor and forecast ocean surface changes. The system adaptively generates an appropriate synthetic time series with recovering missing measurements for sequential images. The reconstruction method incorporates temporal variation according to physical properties of targets and anisotropic spatial optical properties into image processing techniques. This adaptive approach allows successive refinement of the structure of objects that are barely detectable in the observed series. The system sequentially collects the estimated results from the adaptive reconstruction and then statistically analyzes them to monitor and forecast the change in surface characteristics.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2002.11a
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• pp.430-431
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• 2002

기상변동에 대한 적절한 해석을 위하여 장기관측을 통한 다양한 지표 생태계에서의 수분 및 에너지 순환에 대한 연구가 진행(Grelle, et al., 1997: Wilson and Baldocchi, 2000)되고 있으며, 모형을 이용한 연구에서도 이에 대한 검증과 보다 정확한 자료의 산출을 위해서 양질의 관측자료가 절대적이라 할 수 있다. 또한 대기에 비하여 상대적으로 그 영향이 오래 지속되는 토양특성에 대한 정확한 토양수분 자료를 사용할 경우 기후 및 기상 예측의 정확도 향상에 크게 기여하는 것으로 알려져 있다(Atlas et al. 1993). (중략)

• Proceedings of the Zoological Society Korea Conference
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• 1999.10b
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• pp.114.1-114
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• 1999

No Abstract, See Full Text

• Economic and Environmental Geology
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• v.39 no.3 s.178
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• pp.255-268
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• 2006

Recent 22-year (1981-2002) meteorological data of 58 Korea Meteorological Adminstration (KMA) station were analyzed to investigate spatial and temporal variation of surface air temperature (SAT) and ground surface temperature (GST) in Korea. Based on the KMA data, multiple linear regression (MLR) models, having two regression variables of latitude and altitude, were presented to predict mean surface air temperature (MSAT) and mean ground surface temperature (MGST). Both models showed a high accuracy of prediction with $R^2$ values of 0.92 and 0.94, respectively. The prediction of MGST is particularly important in the areas of geothermal energy utilization, since it is a critical parameter of input for designing the ground source heat pump system. Thus, due to a good performance of the MGST regression model, it is expected that the model can be a useful tool for preliminary evaluation of MGST in the area of interest with no reliable data. By a simple linear regression, temporal variation of SAT was analyzed to examine long-term increase of SAT due to the global warming and the urbanization effect. All of the KMA stations except one showed an increasing trend of SAT with a range between 0.005 and $0.088^{\circ}C/yr$ and a mean of $0.043^{\circ}C/yr$. In terms of meteorological factors controlling variation of GST, the effects of solar radiation, terrestrial radiation, precipitation, and snow cover were also discussed based on quantitative and qualitative analysis of the meteorological data.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.2
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• pp.67-74
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• 2017

The D-InSAR is a technique for precisely measuring the subsidence of subsidence using difference of two SAR images. In order to calculate the subsidence using D-InSAR, a high coherence between master image and the slave image is essential. Since the existing D-InSAR method calculates the displacement based on the total coherence, the accuracy of the subsidence is lowered when the coherence map contains mountains or bare-land. In order to solve this problem, in this study, a point having a temporal coherence and spatial coherence of 0.7 or more was extracted to form TIN, and the subsidence was calculated based on this TIN. In addition, we compared the existing D-InSAR technique with the new D-InSAR technique considering spatial and temporal coherence. As a result, the new D-InSAR technique showed smaller standard deviation, relative variance, variation coefficient and quadrature deviation than the existing D-InSAR technique. It is also easy to grasp the trend of the subsidence.

• Journal of Ocean Engineering and Technology
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• v.17 no.4
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• pp.23-30
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• 2003

This study investigates the seasonal variation and spatial distribution characteristics of pollutant load, as executing the quality valuation of pollutant load inflowing into Yeong-il Bay from on-land including the Hyeong-san River. Annual total pollutant generating rate from Yeong-il Bay region are 202ton-BOD/day, 620ton-SS/day, 42ton-TN/day, and 16ton-TP/day, respectively. Particularly, the generating ration of the pollutant loads from the Hyeong-san River is greater than that of any other watershed of the Yeong-il Bay, of which BOd is about 78.2％, SS 88.5％, T-N 62.5％, T-P 73.1％, As calculating Tank model with input value of daily precipitation and evaporation of 2001 year in drainage basin of the Hyeong-san River, the estimated result of the annual river discharge effluence from this river is 830106㎥, As a result to estimating annual effluence rate outflowing at the rivers from each drainage basin. annual inflow pollutant rates are 10,633ton-BOD/year, 19,302ton-SS/year, 15,369ton-TN/year, 305ton-TP/year, respectively. The population congestion region of the Pohang-city is a greater source of pollutant loads than the Neang-Chun region with wide drainage area. Therefore, the quantity of TN inflowing into Yeong-il Bay is much more than T-P. The accumulation of pollutant load effluenced from on-land will happen at the inner coast region of Yeon-il Bay. Finally, We would make a prediction that the water quality will take a bad turn.

• Spatial Information Research
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• v.15 no.1
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• pp.25-33
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• 2007

The purpose of this study is to assess spatio-temporal variation of Imha Dam water quality according to suspended sediment algorithm using Landsat and SPOT 5 data. In order to learn synchronous suspended sediment concentrations(SSC) in Imha Dam waters, the satellite remote sensing data are analyzed. The key procedure of this research is that we should know the relationships between suspended sediment concentrations and satellite-detected reflectance. However, the SSC algorithm has the limitation that it must be compared calculated SSC with synchronous ground-truth data in the Dam water. Based upon the linear response from satellite-detected reflectance, SSC algorithm validated an efficient algorithm to estimate proportional factor and then derived an empirical equation far SSC estimations.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.1
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• pp.4-14
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• 2005

CarboKorea and HydroKorea are the domestic projects aiming to improve our understanding of carbon and water cycles in a typical Korean forest located in a complex terrain with a watershed connected to large rivers. The ultimate goal is to provide a nowcasting of these cycles for the whole Peninsula. The basic strategy to achieve such goal is through the inter- and multi-disciplinary studies that synthesize the in-situ field observation, modeling and remote sensing technology. The challenge is the fact that natural ecosystems are nonlinear and heterogeneous with a wide range of spatio-temporal scales causing the variations of mass and energy exchanges from a leaf to landscape scales. Our paradigm now shifts from temporal variation at a point to spatial patterns and from spatial homogeneity to complexity of water and carbon at multiple scales. Yet, a large portion of our knowledge about land-atmosphere interactions has been established based on tower observations, indicating that the development of scaling logics holds the key to the success of CarboKorea and HydroKorea. Here, we review the pioneering work of FIFE (First ISLSCP Field Experiment) on scaling issues in a temperate grassland and discuss the lessons from it for the application to Gwangneung forest site.

• Ocean and Polar Research
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• v.32 no.3
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• pp.187-201
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• 2010

The purpose of this study was to investigate the temporal and spatial variability of taxonomic groups and major species of the mesozooplankton community in Lake Shihwa, Korea. Monthly collections were carried out at five stations in Lake Shihwa for a period of one year. The mesozooplankton community showed distinct seasonal variability with water temperature and salinity. Major mesozooplankton species in each seasonal community were derived from non-metric MDS and SIMPER as follows: winter community (Acartia hongi and Eurytemora pacifica), spring community (Acartia hudsonica and Polychaeta larvae), summer community (Acartia sinjiensis, Pavocalanus crassirostris, Evadne tergestina and Cirripedia nauplii) and fall community (Paracalanus indicus and Podon leuckarti). The succession of the seasonal species, A. hudsonica and A. sinjiensis, was the most remarkable event during the seasonal changes of the mesozooplankton community. The species response curve of these species fitted with the logistic regression in relation to water temperature and salinity. The curve also correctly represented the characteristics of the occurrence of A. hudsonica and A. sinjiensis in Lake Shihwa.