• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3B
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• pp.295-303
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• 2010

The variability of vegetation is strongly related to the variability of hydrometeorological factors such as precipitation, temperature, runoff and so on. Analysis of the variability of vegetation will aid to understand the regional impact of climate change. Thus we analyzed the spatial-temporal variability of NOAA(National Oceanic and Atmospheric Administration)/AVHRR(Advanced Very High Resolution Radiometer) NDVI(Normalized Difference Vegetation Index). In the results from Mann-Kendall test, there is no significant linear trend of annual NDVI from 1982 to 2006 in the most area except the downward trend on the significance level 90% in the Guem-river basin area. In addition, using EOF(Empirical Orthogonal Function) analysis, the variability of NDVI in the region of higher latitude and altitude is higher than that in the other region since the spatial variability of NDVI follows the latitudinal gradient. Also we could get higher NDVI in June, July, August and September. We had the highest NDVI in Han-river basin area and the lowest in Je-Ju island.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.191-198
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• 2010

Assessing seasonality of precipitation is necessarily required to establish future plans and policies for water resources management. In this regard, a main objective of the study is to introduce an effective approach for assessing the seasonality of the precipitation and evaluate the seasonality through the proposed one. We have used circular statistics to characterize the seasonality on the precipitation in Korea. The circular statistics allow us to effectively assess changes in timing of the seasonality in detail. It was found that peak time on monthly rainfall occurred between end of June and early July in southern coastal area while the timing was delayed in northern part of Korea because of monsoon moving in from south to north. In case of annual daily peak precipitation, spatio-temporal variation of the peak time was increased. It is mainly because of geophysical effects, frequency and paths of typhoons. Finally, temporal variations on the timing of the peak seasons were evaluated through circular statistics by 30-year moving average data. The peak season in the Northen part of Korea (e.g. Seoul and Gangrung) has been moved back from early July to end of July while the peak season has been moved up from middle of July to early July in the Southern part of Korea (e.g. Busan and Mokpo). It seems that changes in seasonality are mostly modulated by variability in the east-asia monsoon system.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.24 no.6
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• pp.437-449
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• 1991

Time series of barometrically adjusted sea level at Pusan, Izuhara and Hakada are analyzed to study the fluctuations of the Tsushima Current through the Korea Strait. Variability of sea levels and their differences is divided into two parts with respect to the frequency of 0.01 or 0.02 cycles per day(cpd) At lower frequency, both of sea levels and sea level difference(SLD) are coherent and in phase to each other. Pusan has smaller seasonal variations in sea level than other two stations because the effects of geostrophic current and prevailing wind have a negative influence on the seasonal thermosteric contribution to sea level change. Low frequency variability of SLD thus of the Tsushima Current is much greater in the western channel. For higher frequency parts, SLD in the eastern channel has larger variability and is not coherent with that of the western channel. Sea levels at Pusan and Izuhara are $180^{\circ}$ out of phase with SLD in the western and eastern channel respectively, whereas the Hakada level is in phase. This result indicates that eastern channel has a normal response to the along-channel winds and cross-channel geostrophy because Izuhara faces the eastern channel.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.544-544
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• 2016

최근 지구온난화 등 기후변화에 따른 돌발 홍수가 계절과 관계없이 빈번하게 발생하고 있으며, 국지성 호우 및 태풍의 영향으로 인한 홍수피해가 매년 발생하고 있다. 이와 같은 피해를 저감하기 위해서는 정확한 강우 관측 및 홍수량 산정이 매우 중요하기 때문에 많은 수문학적 연구와 기술 발달이 이루어지고 있다. 그 중 강우의 변화를 실시간으로 관측 가능한 레이더영상 자료의 활용성이 증대되어 활발한 연구가 진행되고 있으나, 제주도의 경우 다른 지역에 비해 연구가 미흡한 실정이다. 이에 따라, 제주도 유역을 대상으로 유역의 공간적 특성을 격자기반으로 분석하고 매개변수 산정 시 경험적 요인을 제거할 수 있는 분포형 모형인 Vflo와 기상청에서 제공하는 레이더 영상자료 및 강우자료를 활용하여 연구를 수행하였다. 본 연구에서는 Arc-GIS를 이용하여 제주도 도심하천인 외도천 유역의 지형적 지리적 특성(DEM, 토양도, 토지피복도 등)을 $30m{\times}30m$ 격자크기로 분석하고, 레이더영상 자료로부터 강우 자료를 추출하였으며, 분포형 모형(Vflo)을 활용하여 유출량을 모의하였다. FSIV기법을 통해 현장 관측한 유출량과 비교 분석하였으며, 레이더 영상자료로부터 추출한 강우자료는 AWS자료를 활용하여 제주도에 적합한 강우보정계수를 산정하였다. 이와 같은 연구를 통해 향후 제주도 미계측 유역의 홍수량 산정이 가능할 것으로 판단되며, 하천기본계획 및 유역종합치수계획 등 치수계획 수립 시 많은 활용이 될 것으로 기대한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.288-288
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• 2020

우리나라의 1시간 간격으로 측정되고 있는 지하수 관측망의 지하수위의 변동성은 강우, 양수, 하천, 지표피복에 의한 영향 등 다양하게 나타날 수 있다. 현재 한국수자원공사 및 한국농어촌공사에서 운영중인 지하수 관측망 중에서 지하수위의 변동 양상이 일반적(계절변동, 강우반응 변동 등)이지 않은 것으로 파악되는 101개소(국가지하수관측망 62개, 4대강보 주변 관측망 5개, 해수침투 관측망 15개, 농촌지하수관리관측망 19개)를 대상으로 현장조사를 실시하고 관측정 주변의 특성과 지하수위 변화와의 관계를 정성적으로 분류하여 보았다. 현장 조사는 지하수 관측정 주변 반경 100 m를 대상으로 하였으며, 기존 우물의 존재 및 규모, 지표 피복 상태, 인근 하천과의 관계(표고차, 하천의 규모, 보의 존재 등), 지형적 이상 특성, 저수지 분포 등을 조사하였다. 조사 대상 지하수 관측정 중에서 주변의 인위적인 요인(양수 영향, 하천수위 조절 영향, 지표 피복 변화, 저수지 수위 조절 등)에 의한 변동으로 확인된 것은 총 89개에 해당한다. 이와 같은 지하수위의 이상 데이터는 지하수 모델링, 함양량 산정과 같은 추가적인 분석에 오류를 발생할 수 있으므로 인공신경망 또는 통계 기법을 활용하여 보정하는 과정이 필요해 보인다.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.661-676
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• 2017

This study suggests a new method not only to produce the 1 km-resolution seasonal prediction but also to improve the seasonal prediction skill of temperature over South Korea. This method consists of four stages of experiments. The first stage, EXP1, is a low-resolution seasonal prediction of temperature obtained from Pusan National University Coupled General Circulation Model, and EXP2 is to produce 1 km-resolution seasonal prediction of temperature over South Korea by applying statistical downscaling to the results of EXP1. EXP3 is a seasonal prediction which considers the effect of temperature changes according to the altitude on the result of EXP2. Here, we use altitude information from ASTER GDEM, satellite observation. EXP4 is a bias corrected seasonal prediction using genetic algorithm in EXP3. EXP1 and EXP2 show poorer prediction skill than other experiments because the topographical characteristic of South Korea is not considered at all. Especially, the prediction skills of two experiments are lower at the high altitude observation site. On the other hand, EXP3 and EXP4 applying the high resolution elevation data based on remote sensing have higher prediction skill than other experiments by effectively reflecting the topographical characteristics such as temperature decrease as altitude increases. In addition, EXP4 reduced the systematic bias of seasonal prediction using genetic algorithm shows the superior performance for temporal variability such as temporal correlation, normalized standard deviation, hit rate and false alarm rate. It means that the method proposed in this study can produces high-resolution and high-quality seasonal prediction effectively.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1523-1535
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• 2020

In order to produce crop information using remote sensing, we use classification and growth monitoring based on crop phenology. Therefore, time-series satellite images with a short period are required. However, there are limitations to acquiring time-series satellite data, so it is necessary to use fusion with other earth observation satellites. Before fusion of various satellite image data, it is necessary to overcome the inherent difference in radiometric characteristics of satellites. This study performed Korea Multi-Purpose Satellite-3 (KOMPSAT-3) cross calibration with Landsat-8 as the first step for fusion. Top of Atmosphere (TOA) Reflectance was compared by applying Spectral Band Adjustment Factor (SBAF) to each satellite using hyperspectral sensor band aggregation. As a result of cross calibration, KOMPSAT-3 and Landsat-8 satellites showed a difference in reflectance of less than 4% in Blue, Green, and Red bands, and 6% in NIR bands. KOMPSAT-3, without on-board calibrator, idicate lower radiometric stability compared to ladnsat-8. In the future, efforts are needed to produce normalized reflectance data through BRDF (Bidirectional reflectance distribution function) correction and SBAF application for spectral characteristics of agricultural land.

• Journal of the Korean earth science society
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• v.34 no.2
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• pp.120-135
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• 2013

To investigate the changes in depositional environment around Gangneung Harbor, we analyzed the surface sediment textural parameters and topography data collected five times from February 2007 to February 2009. In the study area, sediments were mainly composed of sand and its sediment size became finer at offshore sites. During summer time, however, the sand grains became coarser than winter season near Namhangjin Beach, inside the harbor, and offshore areas. On the other hand, the grain size of Anmok Beach showed a gradual finer trend with time. Compared with the previous studies conducted before the completion of Gangneung Harbor construction, the mean grain size became finer on Anmok Beach, while it was coarser on Namhangjin Beach. The bathymetric changes observed over a 2-year period showed predominant erosion in the area of 5 to 10 m water depths and deposition in 2 to 5 m water depths. The shallower area less than 2 m water depths showed an alternating trend and yet slightly more dominant erosion process. The sediment textural parameters and the distribution of erosion and deposition have changed continuously. Results imply that such changes show long-term trends as well as seasonal variations in which the trend may have been formed after the completion of Gangneung Harbor construction.

• Journal of The Geomorphological Association of Korea
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• v.18 no.2
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• pp.39-51
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• 2011

In this study, the shape of the Baramarae beach, Anmyeondo Area in West Coast of Korea and the changes in the sedimentation and erosion environment were analyzed in time series. As a result of the time series analysis of the shape of the Baramarae beach using aerial photographs from 1967 to 2009, the sand spit that developed in the southern part of Halmi Island was found to have had an EEN direction, but it was changed to a NNS direction, as reflected in the 2009 aerial photographs, as it gradually shifted to the west. In the onsite measurement, the H-3, H-4, H-5, and H-6 spots showed a superior sedimentation environment and the H-7, H-8, and H-9 spots showed a superior erosion environment. It was thus found that sedimentation is superior in the southwest beach and that erosion is superior in the northeast beach. The results in the spots between H-3 and H-6 indicate that the sand in the beach could not move to the northeast beach of Halmi Island due to the bank that had been established in the southwest beach of the island. On the other hand, it seems that superior erosion takes place in spots H-7 to H-9 in the northeast beach, where sand is not provided from the southwest beach of Halmi Island. It was found from the seasonal analysis that the season when superior sedimentation takes place in all the spots is autumn, and that the season when superior erosion takes place is summer. Superior sedimentation takes place in winter and spring in the southeast side and in summer in the northwest side.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.256-256
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• 2020

하천의 유출률은 하천의 경사, 연장, 강우특성 및 규모 등에 따라 크게 영향을 받으므로, 제주도의 지역별 고도별 토양 및 강우 특성과 독특한 지형에 따른 간헐하천의 유출특성을 고려할 때 관측에 의해 유출특성을 파악하는 것은 현실적으로 어렵다. 특히나 홍수시 관측되는 유량의 불확실성과 지역별·고도별 강우량의 편차를 고려한다면 강수대비 정확한 관측유출률의 산정 자체가 쉽지 않다. 이는 기존 관측된 유출률이 하천유역별로 대상기간별로 차이가 크게 나타나는 것을 통해서도 알 수 있다. 따라서 특정 지점에서의 몇 개의 강우사상에 대한 유출률이 아닌 다양한 사상과 지역적 특성을 고려한 유출특성을 파악하기 위해서는 모델링에 의한 접근법이 필요하다. 본 연구에서는 제주도 하천유역에서의 건천화 현상과 간헐적 유출특성을 모의하는데 최적화된 제주형 SWAT-K 모형을 기반으로 제주도 11개 하천유역(유역면적 30 ㎢ 이상)에 대한 유출특성을 분석하였다. 유출률을 중심으로 계절별, 지역별, 하천유역별 차이를 비교 분석함으로써 강우규모에 따른 유출 특성과 시·공간적 유출률 변화를 평가하였다. 1992~2013년 기간에 대해 분석한 결과 제주도 전역에 대한 연간 유출률은 13.3%~30.5% (평균 21.8%)로 나타났다. 하천유역별로는 천미천(31.6%), 가시천(31.1%), 화북천(29.3%), 창고천(27.4%), 의귀천(27.1%)의 유출률이 상대적으로 크게 나타났으며, 효돈천(18.9%)와 도순천(19.0%)은 상대적으로 낮은 것으로 분석되었다. 11개 하천유역에 대한 월별 평균 유출률은 강수량이 많은 8월에 가장 높은 유출률(26.1%)을 보였다.