• Ocean and Polar Research
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• v.32 no.4
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• pp.449-462
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• 2010

Ongoing port baseline surveys are essential for developing ballast water management procedures in order to control unwanted or potentially risky species. Seasonal distributional patterns of marine dinoflagellate Noctiluca scintillans internationally recognized as harmful species and the related environmental factors were surveyed at Incheon, Gwangyang and Ulsan seaports in Korea from 2007 to 2009. The above three seaports were chosen because of their status as the busiest in Korea and characterized by their different bioregions. Average temperature ranged from $2.08^{\circ}C$ in winter to $26.39^{\circ}C$ in summer at Incheon, $7.22^{\circ}C$ in winter to $25.77^{\circ}C$ in summer at Gwangyang, and $11.59^{\circ}C$ in winter to $21.67^{\circ}C$ in summer at Ulsan during the study period. Average salinity varied from 26.88 in winter to 31.25 in summer at Incheon, 22.83 in winter to 33.41 in summer at Gwangyang, and 30.04 in winter to 33.90 in summer at Ulsan. Noctiluca scintillans appeared consistently at all ports during the study period, indicating its eurythermal and euryhaline nature. The highest abundances (21,813 to 41,753 $inds{\cdot}m^{-3}$) of N. scintillans were observed in May 2008 and 2009 at the outer stations of Incheon port. Abundances of between 10,000 and 30,000 $inds{\cdot}m^{-3}$ were only observed at the innermost station of Ulsan in May, while abundances of between 10,000 and 40,000 $inds{\cdot}m^{-3}$ were frequently observed throughout all stations at Gwangyang during the study period, coinciding with consistently high concentration of chlorophyll-a (hereafter chl-a) ($4.32-8.24\;{\mu}g\;l^{-1}$) compared to other ports. Spatio-temporal variation of chl-a concentration was not significantly correlated with abundances of N. scintillans (p>0.01). However, relatively high chl-a concentrations were consistently recorded along with high abundances of N. scintillans throughout all stations at Gwangyang compared to other ports. Abundances of N. scintillans observed at the three surveyed ports did not significantly (p>0.01) affect the concentration of dissolved oxygen in the surface mixed layer, indicating that the species abundances were not enough to cause reduction of dissolved oxygen during the study period. Presented results indicated that the Gwangyang seaport may provide the most suitable environment for a wide range of N. scintillans blooming compared to other ports.

• Journal of Korea Water Resources Association
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• v.46 no.11
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• pp.1129-1140
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• 2013

Precipitation is one of the important factors in the hydrological cycle. It needs to understand accurate of spatial precipitation field because it has large spatio-temporal variability. Precipitation data obtained through the Tropical Rainfall Monitoring Mission (TRMM) 3B43 product is inaccurate because it has 25 km space scale. Downscaling of TRMM 3B43 product can increase the accuracy of spatial precipitation field from 25 km to 1 km scale. The relationship between precipitation and the normalized difference vegetation index(NDVI) (1 km space scale) which is obtained from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor loaded in Terra satellite is variable at different scales. Therefore regression equations were established and these equations apply to downscaling. Two renormalization strategies, Geographical Difference Analysis (GDA) and Geographical Ratio Analysis (GRA) are implemented for correcting the differences between remote sensing-derived and rain gauge data. As for considering the GDA method results, biases, the root mean-squared error (RMSE), MAE and Index of agreement (IOA) is equal to 4.26 mm, 172.16 mm, 141.95 mm, 0.64 in 2009 and 17.21 mm, 253.43 mm, 310.56 mm, 0.62 in 2011. In this study, we can see the 1km spatial precipitation field map over Korea. It will be possible to get more accurate spatial analysis of the precipitation field through using the additional rain gauges or radar data.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.707-718
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• 2007

Recently, much studies for providing mobile users with suitable and useful content services, LBS(Location Based Service) corresponding to the change of users' location, are actively going on. First and foremost, this is basically owing to the progress of location management technologies such as GPS, mobile communication technology and the spread of personal devices like PDA and the cellular phones. Besides, the research scope of LBS has been changed from vehicle tracking and navigation services to intelligent and personalized services considering the changing information of conditions or environment where the users' are located. For example, it inputs the information such as heavy traffic, pollution, and accidents. The query languages which effectively search the stored vehicle and environment information have been studied depending on the increase of the information utilization. However, most of existing moving object query languages are not enough to provide a recommendation service for a user, because they can not be tested and evaluated in real world and did not consider changed environment information. In order to retrieve not only a vehicle location and environment condition but also use them, we suggest a moving object query language for recommendation service and implement a moving object query process system for supporting a query language. It can process a nearest neighbor query for recommendation service which considers various attributes such as a vehicle's location and direction, environment information. It can be applied to location based service application which utilizes the recommended factors based on environmental conditions.

• Journal of Wetlands Research
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• v.23 no.4
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• pp.296-306
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• 2021

Elasticity is a statistical technique that interprets the changing pattern of another variable according to a change in one variable as a quantitative numerical value and provides more information than correlation analysis and is widely used in climate change research. In this study the elasticity was calculated and sensitivity analysis was performed using air temperature and water quality data of the major tributaries of the Nakdong River. In addition the confidence interval for the elasticity was calculated using the T-Test and the validity of the elasticity was examined. The strength of elasticity shows high strength in the order of summer>fall>spring>winter and the direction shows regional characteristics with both negative and positive elasticity. After performing hierarchical cluster analysis on monthly observation data they were classified into 5 clusters and the characteristics of each cluster were visually analyzed using a parallel coordinate graph. The direction and intensity of the air temperature elasticity show regional characteristics due to the relatively high population density and complex influencing factors such as sewage treatment plants, small-scale livestock houses and agricultural activities. In the case of TP it shows great regional variability according to the circulation of nutrients in the ecosystem caused by algae growth and death according to temperature changes. Since the air temperature elasticity of the major tributaries of the Nakdong River is over weak and is valid at the significance level of 5%, it was analyzed that there is a change in water quality according to the air temperature change.

• Journal of Wetlands Research
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• v.23 no.2
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• pp.122-132
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• 2021

We reviewed the methods employed in Korean tidal flat surveys to measure the local abundance of the endangered wildlife and marine protected species, the fiddler crab, Austruca lactea. A complete census for infinite population is impossible even in a limited habitat within a tidal flat, and density estimates from samples strongly vary due to diverse biological and ecological factors. The habitat boundaries and areas shift with periodicities or rhythmic activities of organisms as well as measurement errors. Hence the local abundance calculated from density and habitat areas should be regarded as transient. This conjecture was valid based on the spatio-temporal variations of the density averages, standard error ranges, and spatial distribution of the crab, A. lactea observed for 3 years (2015-2017) in Songdo tidal flat in Incheon. We proposed the potential habitat areas using the occurrence probability of 50% from logistic regression model, reflecting the importance of habitat conservation value as an alternative to local abundance. The spatial shape of potential habitat predicted from a generalized model would remain constant over time unless the species' critical environmental conditions change rapidly. The species-specific model is expected to be used for the introduction of desired species in future habitat restoration/creation projects.

• Economic and Environmental Geology
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• v.55 no.5
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• pp.541-550
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• 2022

A pre-existing landform is created by weathering and erosion along the bedrock fault and the weak zone. A neotectonic landform is formed by neotectonic movements such as earthquakes, volcanoes, and Quaternary faults. It is difficult to clearly distinguish the landform in the actual field because the influence of the tectonic activity in the Korean Peninsula is relatively small, and the magnitude of surface processes (e.g., erosion and weathering) is intense. Thus, to better understand the impact of tectonic activity and distinguish between pre-existing landforms and neotectonic landforms, it is necessary to understand the development process of pre-existing landforms depending on the bedrock characteristics. This study used a two-dimensional numerical landscape evolution model (LEM) to study the spatio-temporal development of landscape according to the different erodibility under the same factors of climate and the uplift rate. We used hill-slope indices (i.e., relief, mean elevation, and slope) and channels (i.e., longitudinal profile, normalized channel steepness index, and stream order) to distinguish the difference according to different bedrocks. As a result of the analysis, the terrain with high erosion potential shows low mean elevation, gentle slope, low stream order, and channel steepness index. However, the value of the landscape with low erosion potential differs from that with high erodibility. In addition, a knickpoint came out at the boundary of the bedrock. When researching the actual topography, the location around the border of difference in bedrock has only been considered a pre-existing factor. This study suggested that differences in bedrock and various topographic indices should be comprehensively considered to classify pre-existing and active tectonic topography.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.6008-6014
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• 2013

This study aimed to understand seasonal variation of physico-chemical factors and biomass of size-fractionated phytoplankton at Ulsan seaport during the period from February 2007 to November 2009. Water temperature, salinity, dissolved oxygen (DO), pH, chemical oxygen demand (COD) and total suspended solid (TSS) varied in the range of 8.94-$24.26^{\circ}C$, 25.06-34.54 psu, 4.30-10.73 mg/L, 7.97-8.53, 0.66-40.70 mg/L and 57.4-103.3 mg/L, respectively. These factors showed no clear spatial variation unlike spatial pattern of inorganic nutrients and total chlorophyll-a (chl-a) concentration as biomass. Concentration of phosphate, nitrate and silicate ranged from 0.01 to 3.03 ${\mu}M$, 0.05 to 21.62 ${\mu}M$, and 0.01 to 27.82 ${\mu}M$, respectively, with 2 times higher concentration at inner stations than that at outer stations during the study period. Within the range of total chl-a concentration (0.36-7.11 ${\mu}gL^{-1}$), higher concentration (avg. 1.88 ${\mu}gL^{-1}$) of total chl-a were observed at inner stations compared to that (avg. 0.90 ${\mu}gL^{-1}$) at outer stations. Micro-sized phytoplankton dominated total biomass of phytoplankton in spring (34.0-81.2%), summer (35.1-65.6%) and winter (3.9-62.0%). Nano- and pico-sized phytoplankton contributed 58.2-74.5% and 22.4-38.2% to total biomass of phytoplankton in autumn, respectively. However, contribution in biomass of size-fractionated phytoplankton to total phytoplankton biomass showed no clear difference between inner and outer stations. Consequently, these results indicated that spatio-temporal distribution of phytoplankton biomass at Ulsan seaport was dominated by micro-phytoplankton (avg. 52.3%) during the study period except autumn, which was closely dependent on the concentration of inorganic nutrients (p<0.05).

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.4
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• pp.223-233
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• 2010

Spatio-temporal variations of long-term water qualities (COD, SS, $Chl-{\alpha}$, N-related nutrients (TN, TDN, $NO_3^-$, $NH_4^+$), P-related nutrients (TP, TDP, $PO_4^{3-}$)) at two stations (St. SD, St. GG) in the Geumgang Reservoir were investigated from August 2001 to July 2008. Statistical methods such as t-test, factor analysis, and multi-regression analysis were applied to the water quality data in the reservoir as well as mass balances on TP. From the temporal comparisons of the water qualities between 2002 and 2007, average concentrations of $NH_4^+$, $PO_4^{3-}$, and TDP gradually decreased down by 60%, 24%, 52% in 2007. However, those of TP and $Chl-{\alpha}$ increased to 99% and 423% during the period. From the spatial comparisons between the two stations, St. GG showed higher concentrations for all of the N- and P-related nutrients than in St. SD, while opposite result for the $Chl-{\alpha}$. The factor analysis showed that "the seasonal variations of N- and P-related nutrients" were the two dominant factors occupying 49% of total variances of water qualities. Based on this result, multi-regression analysis executed for the two most influential parameters (TP and $Chl-{\alpha}$) focusing on the seasonal variations of these parameters: SS and $Chl-{\alpha}$ has contributed decisively to the concentrations of TP during the wet and dry season, respectively. On the other hand, COD and TP has been important for the $Chl-{\alpha}$ during the wet and dry season, respectively. From the established mass balances of TP loadings in the Geumgang Reservoir, Other Sources (60%) occupied the greatest contribution and Fluvial Input (38%) and Sediment (1%) during the wet season. However, both Fluvial Water (48%) and Other Sources (47%) supplied comparable amount of inputs and Sediment (5%) showed significantly increased input during the dry seasons. Recently especially during the dry winter seasons, migrating bird's excretion was estimated to contribute up to 8% of total TP input and 21% of Other Sources.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.28 no.4
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• pp.475-488
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• 1995

In order to see the seasonal variation of nutrients and the limiting factors to the primary production in Deukryang Bay, both dissolved inorganic nutrients and salinity were measured in the surface waters during the periods from July 1992 to March 1993. The mean value of salinity was the lowest in ?all and the highest in early spring. Dissolved inorganic nitrogen (DIN) was the highest in winter and the lowest in summer. However, both phosphate and silicate were the highest in summer and the lowest in fall. Salinity was generally higher in the outer region than in the inner region of the bay.DIN content was nearly depleted (less than $2{\mu}M$) in summer. From fall to spring, DIN content was nearly depleted in the inner region and relatively high in the outer region of the Day. Phosphate was the highest in summer showing an opposite distribution pattern to salinity, and it was nearly depleted (less than $0.1{\mu}M$) in fall and winter. In spring, however, phosphate content was slightly high in the outer region. Silicate content showed an opposite distribution pattern to salinity in summer. in other seasons, However, the distribution pattern of silicate was similar to the salinity. DIN seemed to be a limiting factor for the primary production at all area of the bay in summer and at the inner region in other season. However, phosphate seemed to be a limiting factor at all area of the bay in fall and winter and at the inner region in spring. Silicate may limit the production of diatoms at the inner region of the bay in winter and spying. Both phosphate and silicate showed a good inverse relationship with salinity in summer, which indicates inputs of these nutrients from the freshwater runoff. In the other seasons, both nitrate and silicate showed a positive linear relationship with salinity in the outer region of the bay, suggesting that these two nutrients were mainly supplied by the inflow of the offshore costal water which had high nitrate content associated with vertical mixing.

• Spatial Information Research
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• v.22 no.1
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• pp.55-63
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• 2014

Near surface air temperature data which are one of the essential factors in hydrology, meteorology and climatology, have drawn a substantial amount of attention from various academic domains and societies. Meteorological observations, however, have high spatio-temporal constraints with the limits in the number and distribution over the earth surface. To overcome such limits, many studies have sought to estimate the near surface air temperature from satellite image data at a regional or continental scale with simple regression methods. Alternatively, we applied various Kriging methods such as ordinary Kriging, universal Kriging, Cokriging, Regression Kriging in search of an optimal estimation method based on near surface air temperature data observed from automatic weather stations (AWS) in South Korea throughout 2010 (365 days) and MODIS land surface temperature (LST) data (MOD11A1, 365 images). Due to high spatial heterogeneity, auxiliary data have been also analyzed such as land cover, DEM (digital elevation model) to consider factors that can affect near surface air temperature. Prior to the main estimation, we calculated root mean square error (RMSE) of temperature differences from the 365-days LST and AWS data by season and landcover. The results show that the coefficient of variation (CV) of RMSE by season is 0.86, but the equivalent value of CV by landcover is 0.00746. Seasonal differences between LST and AWS data were greater than that those by landcover. Seasonal RMSE was the lowest in winter (3.72). The results from a linear regression analysis for examining the relationship among AWS, LST, and auxiliary data show that the coefficient of determination was the highest in winter (0.818) but the lowest in summer (0.078), thereby indicating a significant level of seasonal variation. Based on these results, we utilized a variety of Kriging techniques to estimate the surface temperature. The results of cross-validation in each Kriging model show that the measure of model accuracy was 1.71, 1.71, 1.848, and 1.630 for universal Kriging, ordinary Kriging, cokriging, and regression Kriging, respectively. The estimates from regression Kriging thus proved to be the most accurate among the Kriging methods compared.