• Journal of Wetlands Research
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• v.19 no.2
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• pp.223-229
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• 2017

This study analyzed the relationship between environmental factors and the temporal changes of the bird populations during the every January from 1999 to 2016 (18 years) in Donglim reservoir. 'Winter Waterbird Census of Korea' data by National Institute of Biological Resources were used for the bird population data, and principal component analysis and cluster analysis were used to analyze the changes of annual population. The average temperature of January and the average storage rate of the reservoir were used as environmental factors. According to the results of the study, the population changes in the study area can be explained by the increase and decrease of two water bird groups and a mountain bird group. The average temperature of the years when the population of water bird groups increased was more than $1.4^{\circ}C$ in comparison with the year when mountain birds increased. On the other hand, the influence of the water content was not clear. The visiting of Baikal Teal affected by temperature was a factor affecting the other group of water bird and a mountain bird group. The results of this study suggest that the temperature change affects the global spatial distribution of birds and the migration of large population species such as Baikal Teal affects species composition and populations of birds at local scale. Therefore, understanding of environmental changes at large scale and spatial distribution of species and flock contributes to understand the temporal variation of the bird population at regional or local scales.

• 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.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1461-1473
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• 2021

The purpose of this study is to ascertain how the level of resolution of land cover data affects on the local distribution and diffusion of fine dust. the CALPUFF model, which considers the spatio-temporal terrain conditions and changes in weather conditions, was used to estimate PM10 concentration in the Pyeongchon, Anyang-si, Gyeonggi-do. Three different resolutions of land cover data including 20 m, 50 m, and 100 m were compared as the input of the modeling. Using higher resolution land cover data (20 m), the wind speed of the simulated region was the largest and the PM10 concentration was the lowest. Through this study, we confirm that the resolution level of land-use/cover data can affect the local distribution and diffusion of fine dust, which can be detected by CALPUFF. Therefore, when using CALPUFF to simulate fine dust in the future, it can be suggested that checking the impact on spatial resolution according to the form of land cover in advance and proceeding with the simulation can achieve mote accurate results.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.171-183
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• 2011

Temporal and spatical surface runoff by heavy rainfall during 25~28 July, 2011 causing urban flooding at Seoul were analyzed using Long-Term Hydrologic Impact Assessment (L-THIA). L-THIA was calibrated for 1988~1997 and validated for 1998~2007 using monthly observed data at Hangangseoul watershed which covers 90 % of Seoul city. As a results of calibration and validation of L-THIA at Hangangseoul watershed, Nash-Sutcliffe coefficients were 0.99 for calibration and 0.99 for validation. The simulated values were good agreement with observed data and both calibrated and validated levels were "very good" based on calibration criteria. The calibrated curve number (CN) values of residential and other urban area represented 87 % and 93 % of impervious area, respectively, which were maximum percentage of impervious area. As a result of L-THIA application at Seoul city during 25~28 July, 2011, most of rainfall (54 %, 287.49 mm) and surface runoff (65 %, 247.32) were generated at 27 July, 2011 and a significant amount of rainfall and surface runoff were occurred at southeastern Seoul city. As a result of bi-hourly spatial and temporal analysis during 27 July, 2011, surface runoff during 2:00~4:00 and 8:00~10:00 were much higher than those during other times and surface runoff located at Seocho-gu during 6:00~8:00 represented maximum value with maximum rainfall intensity which caused landslide from Umyun mountain.

• Journal of Fisheries and Marine Sciences Education
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• v.25 no.5
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• pp.1046-1054
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• 2013

Spatial and temporal variations of sea surface temperature (SST), abundances of copepods, euphausiids, amphipods, and chaetognaths were investigated in the western waters of the Korean Peninsula. Zooplankton and SST were monitored at 63 stations arrayed in six transects ($124^{\circ}00^{\prime}-126^{\circ}30^{\prime}E$, $34^{\circ}00^{\prime}-37^{\circ}00^{\prime}N$) in February, April, June, August, October, and December during 1978-2010. In general, SST increased $0.7-3.8^{\circ}C$ during the last three decades with spatio-temporal variations. SST was lowest in February and highest in August. SST was highest in the northernmost transect and declined gradually along transects to the south. The general pattern of interannual variations of SST was similar to the global pattern, which has been increasing. Trends of abundances of all zooplankton groups slightly increased interannually and peaked seasonally in June and August, except chaetognaths, which fluctuated around the long-term mean value with a seasonal peak in August and October. Abundances of zooplankton groups were highest in the northernmost transect while those of euphausiids were highest in the southern transect. We discuss the distribution patterns of SST and zooplankton groups in relation to oceanographic characteristics in the study area.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.4
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• pp.245-252
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• 2013

Leaf area index (LAI) is important in explaining the ability of crops to intercept solar energy for biomass production, amount of plant transpiration, and in understanding the impact of crop management practices on crop growth. This paper describes a procedure for estimating LAI as a function of image-derived vegetation indices from temporal series of RapidEye imagery obtained from 2010 to 2012 using empirical models in a rice plain in Seosan, Chungcheongnam-do. Rice plants were sampled every two weeks to investigate LAI, fresh and dry biomass from late May to early October. RapidEye images were taken from June to September every year and corrected geometrically and atmospherically to calculate normalized difference vegetation index (NDVI). Linear, exponential, and expolinear models were developed to relate temporal satellite NDVIs to measured LAI. The expolinear model provided more accurate results to predict LAI than linear or exponential models based on root mean square error. The LAI distribution was in strong agreement with the field measurements in terms of geographical variation and relative numerical values when RapidEye imagery was applied to expolinear model. The spatial trend of LAI corresponded with the variation in the vegetation growth condition.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.134-134
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• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.2
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• pp.1-20
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• 2020

The purpose of this study was to analyze the distribution characteristics of spatial and temporal PM_2.5 in urban areas of Changwon-si, and to identify the causes of PM_2.5 by comparing the characteristics of land-use, and to suggest the direction of reduction measures. As the basic data, the every hour average from September 2017 to August 2018 of Airpro data, which has measurement points in kindergartens, elementary schools, and some middle and high schools in Changwon-si was used. Also, by using IDW method among spatial interpolation methods of GIS, monthly and time-slot distribution maps were constructed, and based on this, spatial and temporal PM_2.5 distribution characteristics were confirmed. First, to verify the accuracy of the Airpro data, the correlation with AirKorea data managed by the Ministry of Environment was confirmed. As a result of the analysis, R² was 0.75~0.86, showing a very high correlation and the data was judged that it was suitable for the study. In the monthly analysis, January was the highest year, and August was the lowest. As a result of analysis by time-slot, The clock-in time at 06-09 was the highest, and the activity time at 09-18 was the lowest. By administrative district, Sangnam-dong, Happo-dong, and Myeonggok-dong were the most severe regions of PM_2.5 and Hoeseong-dong was the lowest. As a result of analyzing the land-use characteristics by administrative area, it was confirmed that the ratio of traffic area and commercial area is high in the serious area of PM_2.5. In conclusion, the results of this study will be used as basic data to grasp the characteristics of PM_2.5 distribution in Changwon-si. Also, it is thought that the severe regions and the direction of establishing reduction measures derived from this study can be used to prepare more effective policies than before.

• Journal of the Korean earth science society
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• v.31 no.7
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• pp.720-737
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• 2010

This study is to analyze the temporal and spatial distributions of solar radiation in South Korea. Solar radiation data is observed every minute at 22 KMA (Korea Meteorological Administration) stations using pyranometer from January 2000 to August 2007. These data were calibrated using intensive comparative observation and solar radiation model. Intensive comparative observations are accomplished at 22 KMA stations between KNU (Kangnung (Gangneung-Wonju) National University) standard and station instruments during the month of August 2007. The solar radiation of a clear sky mainly is affected by precipitable water, solar altitude and geological height. Also old (raw) data is corrected by the solar radiation model only about clear day and is revised based on the temporal trend of instrument's sensitivity decrease. At all periods and all stations, differences between raw data (13.31 MJ/day) and corrected data (13.75 MJ/day) are 0.44 MJ/ day. So, the spatial distribution of solar radiation is calculated with seasonal and annual mean, and is the relationship with cloud amount is analyzed. The corrected data show a better consistency with the cloud amount than the old data.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.340-354
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• 2021

The aim of this study was to investigate the spatial and temporal distribution of phytoplankton biomass and community composition in Jinhae Bay on the southern coast of Korea. Phytoplankton pigment analysis was conducted using ultra performance liquid chromatography (UPLC) were conducted from April to December 2019 at seven stations. Temperature, salinity, and dissolved oxygen (DO) and inorganic nutrients (dissolved nitrogen, dissolved phosphorus, and orthosilicic acid) were measured to investigate the environmental factors associated with the structure of phytoplankton community. Phytoplankton biomass (Chl-a) was the highest in July (mean 15.4±4.3 ㎍/L) and the lowest in December (mean 3.5±0.6 ㎍/L). Fucoxanthin was the most abundant carotenoid and showed a similar variation pattern to Chl-a, peridinin, and Chl-b. Phytoplankton community composition analysis showed that diatoms were a predominant group with an average abundance of 70 % whereas chlorophytes, cryptophytes, and dinoflagellates often appeared with lower averages. Further, the dominance of diatoms was closely correlated with water temperature and N:P ratio, which might be influenced by high temperatures in the summer and nutrient loading from the land. Additionally, freshwater and nutrient input by rainfall was estimated to be the most important environmental factor. Hence, the spatial and temporal variations in the composition of phytoplankton pigments and phytoplankton community were correlated with physicochemical and environmental parameters.