• Journal of Korea Water Resources Association
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• v.36 no.5
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• pp.879-892
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• 2003

This study has performed the regionalization of point rainfall which has the hydrological homogeneity for regional frequency analysis of the rainfall. For the study, the recorded rainfall data were collected from 60 rainfall gauge stations distributed all over country of the Korea Meteorological Administration, and 32 rainfall characteristic elements were analyzed from the collected data. Using the principal component analysis to be data reduction technique of the multivariate analysis and the cluster analysis to be grouping technique about many of rainfall characteristic elements of each station, the regionalization of point rainfall was accomplished rationally and efficiently. As the result, hydrological homogeneous regions of point rainfall were divided by 5 regions and 3 other regions, and rainfall characteristics of divided each region were analyzed and compared relatively using regional mean values of each rainfall element data.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.131-144
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• 2002

도로의 그룹핑(Grouping)이란 도고 계획, 설계, 관리, 조사 계획 및 정비 방침 등을 세우기 위해 유사한 성격의 도로 구간을 군집화하는 방법이다. 기존에 일반적으로 적용되고 있는 도로 그룹핑 방법은 그룹 수를 미리 지정함으써 분석가의 주관적 판단이 개입되었고, 그룹핑 변수 선정에 대한 근거가 부족하였다. 이에 본 연구에서는 기존에 일반적으로 적용되고 있는 도로 그룹핑 방법을 개선하여 새로운 방법론을 제시하였다. 또한 새로 제시된 방법론의 검증을 위해 도로 교통량 통계연보에서 제공하고 있는 일반국도의 2000년 294개 상시조사 지전의 교통량 자료를 이용하여 분석하였다. 연구 결과 기존의 월, 요일 변동계수만을 적용한 그룹핑 방법보다는 기타 교통지표(AADT, $\Sigma$K1000(K값의 상위 1000번 순위까지의 누적 값), 중차량 비율, 주야율)를 동시에 적용할 때 좀 더 효율적이면서 세부적으로 분류됨을 알 수 있었다. 또한 기타 교통지표론 적당한 그룹핑 결과로는 5그룹의 국도 기능 분류가 가능함을 알 수 있었다. 그 결과 기존의 소재지역과 기능에 따른 국토의 구분을 지방 산업도로 그룹, 지역 간선도로 그룹, 대도시 주변형 도로 그룹, 중소도시 주변형 및 관광도로 그룹, 관광도로 그룹으로 분류할 수 있었다. 본 연구에서의 도로 그룹핑 결과에 각 지역특성을 추가하여 분석한다면 도로의 계획, 선계, 관리 등에 매우 유용한 자료로 활용되리라 예상한다. 또한 본 연구의 결과를 이용하면 좀 더 효율적으로 설계시간계수 선정, 전역 조사 지점의 AADT추정, 상시 교통량 조사 자료의 누락 데이터 보정 및 교통량 조사의 스케줄링에 많이 활용할 수 있을 것으로 기대된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.198-198
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• 2012

본 연구에서는 서울지방의 최근 10년간 우기시 강우자료를 이용하여 시공간패턴에 따른 강수의 변화를 분석하였다. 이를 위하여 GIS 기법, 강우사상 구분법 및 공간의 상관성 분석 등을 적용하였다. 본 연구의 대상지역인 서울은 북위 $37^{\circ}$34', 동경 $126^{\circ}$59' 부근에 위치하며 남북방향으로 30.3 km, 동서방향으로 36.8km에 걸쳐 있으며 그 면적은 약 $605.41km^2$이다. 또 서울 중앙에서는 한강이 동쪽에서 서쪽으로 흐르며 서울을 강북과 강남으로 양분하고 있으며, 서울을 관통하고 있는 한강으로 수많은 지천이 합류하고 있다. 이러한 지리적 특성들로 인하여 서울 지역의 기후는 매우 복잡한 양상을 나타내고 있다. 과거에는 서울지역에 강우관측소의 수가 매우 적어 이러한 현상을 분석하는데 한계가 있었으나 최근에 자동기상관측소(AWS)들의 확충으로 인하여 자료의 양이 넓어졌다. 본 연구에서는 이러한 자료들을 사용하여 강수의 시공간 패턴을 분석하고자 한다. 이를 위하여 강수의 사상을 구분하기 위한 방법인 IETD법(Inter Event Time Definition)을 적용하였으며, 요인분석 및 군집분석을 이용하여 서울의 강수 지역 구분 및 패턴 분석을 실시하였다. 이러한 분석을 통하여 최종적으로 최근 10년간 서울지방의 강수의 시공간 패턴을 제시하고자 하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.300-300
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• 2016

지점빈도해석은 해당 지점에서 기록된 수문자료를 바탕으로 확률론적 방법을 이용하여 해당 지역의 수문학적 현상을 해석하는 방법이다. 최근 이상 기후현상을 통해 극치 사상이 발생하고 있다. 이러한 극치 사상은 지점빈도해석을 이용하여 확률수문량을 추정하는데 많은 영향을 미친다. 특히 해당 지점의 표본 크기가 작을수록 이러한 영향은 좀 더 크게 반영 될 수 있다. 반면 지역빈도해석은 지점의 표본 수가 적거나 수문자료의 수집이 불가능한 미계측지점인 경우, 해당 지점과 수문학적으로 동질하다고 여겨지는 주변 지점들의 자료를 확보하여 확률수문량을 추정함으로써 상대적으로 지점빈도해석 보다 roubst한 추정값을 얻을 수 있다. 따라서 최근 확률수문량 산정 기법으로 지역빈도해석 방법에 관한 관심이 높아지고 있는 실정이다. 지역구분은 지역빈도해석이 지점빈도해석과 구분 될 수 있는 큰 특징이고 지역구분 결과 따라 지역의 표본 크기가 결정되기 때문에 수문학적으로 동질한 지역을 나누는 방법은 매우 중요하다고 볼 수 있다. 본 연구에서는 한강유역을 대상으로 인공신경망을 이용한 군집분석을 수행하고 구분된 지역을 이용하여 지역빈도 해석을 수행하였다.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.99-118
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• 2012

The aim of this study is to define a correlation between spatial distribution characteristics of FFG(Functional Feeding Groups) of aquatic insects and related environmental factors in the Geum River based on the theory of RCC(River Continuum Concept). For that objective we had used SMRA(Stepwise Multiple Regression Analysis) method to analyze close relationship between the distribution of aquatic insects and the physical and chemical factors that may affect their inhabiting environment in the study area. And then, a probabilistic method named Frequency Ratio Model(FRM) and spatial analysis function of GIS were applied to produce a predictive distribution map of biota community considering their distribution characteristics according to the environmental factors as related variables. As a result of SMRA, the values of decision coefficient for factors of elevation, stream width, flow velocity, conductivity, temperature and percentage of sand showed higher than 0.5. Therefore these 6 environmental factors were considered as major factors that might affect the distribution characteristics of aquatic insects. Finally, we had calculated RMSE(Root Mean Square Error) between the predicted distribution map and prior survey database from other researches to verify the result of this study. The values of RMSE were calculated from 0.1892 to 0.4242 according to each FFG so we could find out a high reliability of this study. The results of this study might be used to develop a new estimation method for aquatic ecosystem with macro invertebrate community and also be used as preliminary data for conservation and restoration of stream habitats.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.225-236
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• 2008

The techniques to calculate the probability precipitation for the design of hydrological projects can be determined by the point frequency analysis and the regional frequency analysis. Probability precipitation usually calculated by point frequency analysis using rainfall data that is observed in rainfall observatory which is situated in the basin. Therefore, Probability precipitation through point frequency analysis need observed rainfall data for enough periods. But, lacking precipitation data can be calculated to wrong parameters. Consequently, the regional frequency analysis can supplement the lacking precipitation data. Therefore, the regional frequency analysis has weaknesses compared to point frequency analysis because of suppositions about probability distributions. In this paper, rainfall observatory in Korea did grouping by cluster analysis using position of timely precipitation observatory and characteristic time rainfall. Discordancy and heterogeneity measures verified the grouping precipitation observatory by the cluster analysis. So, there divided rainfall observatory in Korea to 6 areas, and the regional frequency analysis applies index-flood techniques and L-moment techniques. Also, the probability precipitation was calculated by the regional frequency analysis using variable kernel density function. At the results, the regional frequency analysis of the variable kernel function can utilize for decision difficulty of suitable probability distribution in other methods.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1429-1437
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• 2013

Research articles in food related to climate change were analyzed by implementing a text-mining algorithm, which is one of nonstructural data analysis tools in big data analysis with a focus on frequencies of terms appearing in the abstracts. As a first step, a term-document matrix was established, followed by implementing a hierarchical clustering algorithm based on dissimilarities among the selected terms and expertise in the field to classify the documents under consideration into a few labeled groups. Through this research, we were able to find out important topics appearing in the field of food related to climate change and their trends over past years. It is expected that the results of the article can be utilized for future research to make systematic responses and adaptation to climate change.

• 한국해양학회지
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• v.19 no.1
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• pp.68-81
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• 1984

To characterize community structure and distribution of phytoplankton, cluster analyses are performed on quantitative data of phytoplankton collected from the southwestern sea of Korea in early summer, 1980. The cluster analysis shows that the phytoplankton of the study area consists of three distinct characteristic communities, representing different water masses. The species of the first community, predominant in the southwestern coastal were of the main land, are mostly neritic and cold water diatoms. The second community consists of neritic and oceanic diatoms, a few flagellates and an euglenoid. These species are predominant in the vicinity of Jeju Island with warm and high saline waters which seems to be a branch of the Kuroshio Current. The species of the last community, consisting primarily of small-sized dinoflagellates, are predominant in the rest part of the study area with warm and low saline water. Addition, the vertical distributions of phytoplankton and environmental factors show that high concentration of phytoplankton cells, chlorophyll-a and dissolved oxygen are observed near the seasonal pycnocline in the off-coastal area. Fraction of nanoplankton take the above 90% of the total cell concentration in the surface mixed layer of off-coastal area where the seasonal pycnocline develops in summer.

• Korean Journal of Environmental Agriculture
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• v.27 no.4
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• pp.413-420
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• 2008

The phytosociological study was carried out to investigate the structural characteristics of paddy levee vegetation in South Korea. The vegetation data of total 59 releves were analyzed by the Zurich-Montpellier school's method. 6 syntaxa (3 associations and 3 communities) of paddy levee were recognized : Echinochlo-Digitaretum ciliaris ass. nov. hoc., Artemisia princeps-Erigeron annus community, Imperata cylindrica v. koenigii community, Glycine soja-Humulus scandens community, Miscantheum sinensis f. purpurascens ass. nov. hoc,, Polygonetum thunbergii Lohm. et Miyawaki 1962. Detrended correspondence analysis(DCA) showed that Artemisia princeps-Erigeron annus community and Imperata cylindrica v. koenigii community were positively correlated with soil hardness. Polygonetum thunbergii Lohm. et association and Miscantheum sinensis f. purpurascens ass. nov. hoc. was intimately correlated with high soil total nitrogen.

• Journal of Korea Water Resources Association
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• v.35 no.1
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• pp.109-124
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• 2002

This study is an effort to develop a stochastic model of precipitation series that preserves the pattern of occurrence of precipitation events throughout the year as well as several characteristics of the duration, amount, and intensity of precipitation events. In this study an event cluster model is used to describe the occurrence of precipitation events. A logarithmic negative mixture distribution is used to describe event duration and separation. The number of events within each cluster is also described by the Poisson cluster process. The duration of each event within a cluster and the separation of events within a single cluster are described by a logarithmic negative mixture distribution. The stochastic model for hourly precipitation occurrence process is fitted to historical precipitation data by estimating the model parameters. To allow for seasonal variations in the precipitation process, the model parameters are estimated separately for each month. an analysis of thirty-four years of historical and simulated hourly precipitation data for Seoul indicates that the stochastic model preserves many features of historical precipitation. The seasonal variations in number of precipitation events in each month for the historical and simulated data are also approximately identical. The marginal distributions for event characteristics for the historical and simulated data were similar. The conditional distributions for event characteristics for the historical and simulated data showed in general good agreement with each other.