• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.4
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• pp.385-393
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• 2001

Urban land use information is the base data for the urban planning, district-level planning, traffic impact assessment and environmental impact assessment, etc. The level of detail of the current land use information is not enough to analysis and planning. In this study, the status and problems of the current land use information is analysed. The advanced abroad cases, such as LBCS(Land Based Classification System) of American Planning Association, are studied. The purpose of this study is to develop the coding system for urban land use information classification. Through this system, it is anticipated to standardization of land use classification system and improvement of data compactability.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.277-277
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• 2012

국립기상연구소(National Institute of Meteorological Research; NIMR)는 기상청 이중편파 레이더 현업운영에 대비하여 2009년 X-band 연구용 이중편파 레이더를 도입하였고, 편파변수의 산출과 대기수상체 분류를 포함한 강수추정 등의 효용 가능성에 대한 연구를 지난 2년간 수행하고 있다. 이중편파 레이더는 반사도( )뿐만 아니라 차등반사도($Z_R$), 비차등 위상($K_{DP}$), 상관계수($_v$)등의 편파 변수의 산출로 강우감쇠보정과 기상에코-비기상의 에코(ground clutter, insects, birds, chaff)의 구별이 가능하다. 이러한 장점들을 이용해 레이더 자료품질 개선과 정량적 강수추정의 상당한 개선에 도움이 된다. 본 연구에서는 강수추정 관계식 R-Z, 감쇠 보정된 R-Z, R-$K_{DP}$ 관계식을 이용하여 레이더 관측 반경 내에 존재 하는 81개의 지상 우량계 자료와 강수량 추정의 정확도 비교 검증을 실시하였다. 그리고 Fuzzy logic 기법을 이용한 대기수상체 분류 알고리즘을 사용하였고 관측사례는 2011년 수도권 관측을 통해 강설/강수 에코 구별과 우박에코 사례를 분석하였다. 본 연구를 통해 이중 편파 레이더에서 산출된 고품질의 레이더기상자료를 기반으로 현업 예보지원 및 정량적 강우예측 향상에도 기여할 것으로 사료된다.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.799-803
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• 2007

In this paper, we propose a new fuzzy membership function for FSVM(Fuzzy Support Vector Machines). We apply a fuzzy membership to each input point of SVM and reformulate SVM into fuzzy SVM (FSVM) such that different input points can make different contributions to the learning of decision surface. The proposed method enhances the SVM in reducing the effect of outliers and noises in data points. This paper compares classification and estimated performance of SVM, FSVM(1), and FSVM(2) model that are getting into the spotlight in time series prediction.

• Proceedings of the KAIS Fall Conference
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• 2010.11b
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• pp.759-762
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• 2010

본 연구는 당뇨인지환자들의 당뇨 조절에 관계되는 요인들을 포괄적으로 반영하는 집단으로 분류한 후 이를 기반으로 보다 효율적인 당뇨관리사업을 할 수 있는 기초자료를 제공하기 위해 수행되었다. 연구를 위해 2007년, 2008년도 국민건강영양조사를 통해 검진에 참여한 당뇨인지환자 666명의 자료를 수집하여 분석하였다. 당뇨인지환자의 관리행태에 대한 군집분류는 K-means 기법을 이용하였다. 당뇨인지환자의 군집은 건강행태사업 대상군, 중점관리사업 대상군, 합병증검사사업 대상군으로 분류되었다. 당뇨 조절율을 높이기 위해서는 각 군집의 특성에 따라 보다 특화된 당뇨관리 프로그램이 적용되어야 할 것이다.

• Korean Journal of Environment and Ecology
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• v.13 no.2
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• pp.129-142
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• 1999

생태도시계획의 핵심토대로서 UBM(Urban Biotope Mapping)과 BIS(Biotope Information System)는 총 5단계로 구성된다. 본 연구는 2단계의 연구로서 독일 도르트문트시를 사례지로 한 도시비오톱 유형분류방법을 규명해 보고 우리 나라 적용가능성을 타진해 보는 데 목적이 있었다. 유형분류결과 biotope group complex는 총 12개, biotope group은 총 67개, detail biotope은 총 1,120개로 나타났다. 면적점유율 및 분포현황의 분석결과 습지초원 및 반건초지 초원비오톱(전체 면적 0.8%)이 희귀비오톱으로 분류되었으며, 분구원지역비오톱(전체 면적의 2.8%)의 다양도가 가장 높게 나타났다. 또한 적용가능성이란 측면에서 볼 때 서로 다른 도시발전형태에 따른 토지이용패턴의 상이성보완이 필요하고, 더불어 기타 도시생태관련자료에서 지형(적)도(1 : 5,000) 및 적외선 칼라항공사진(1 : 5,000)은 최소한의 자료로 준비되어야 할 것으로 사료되었다.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.21-28
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• 2012

In this study, detection of icebergs that have various scattering characteristics around Wilkinson glacier in West Antarctica is investigated using C-band fully-polarimetric RADARSAT-2 SAR data. Various polarimetric analyses including Freeman-Durden decomposition, H/A/$\bar{\alpha}$ decomposition, entropy (H) and anisotropy (A) method, and Wishart unsupervised classification, were applied for the RADARSAT-2 data used in this study. The polarimetric decomposition methods were successfully classified most of the iceberg, yet some iceberg with similar intensity of volume and surface scattering as sea ice were indistinguishable. Unsupervised classification with a combination of the polarimetric parameter, [1-H][1-A], gave a possibility to distinguish those unclassified iceberg.

• Journal of Environmental Impact Assessment
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• v.7 no.2
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• pp.103-112
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• 1998

Nature-friendly river project has became common practice in Japan. In order to make it available for the conservation and rehabilitation of desirable water environment, water criteria for water environmental assessment must be established. Especially, the criteria estimating the effects on ecosystem in and around river should be constructed. In this paper, classification method for water quality has been developed using biological indices and applied to observed data in Honmyo River, Nagasaki, Japan. Modified PI method (BI') has been suggested and those of three most abundant species resulted effective estimate for an overall water quality with comparatively simple procedure. Extensive database management code was prepared for the comprehensive ecological monitoring of river basin, which includes various biota. That system enables easy access of all the ecological data for a dissemination of a sound and sustainable water environment. The result of this study could improve knowledge base, serve making consensus for citizens, and help river management plans. In Japan, citizen's realization and action are the most critical factor for nature-friendly river restoration project.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.4
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• pp.471-476
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• 2010

This study aimed at monitoring, mapping, and assessing the land degradation in the desert area. In this research, the Landsat TM and ETM+ imageries to assess the extent of land degradation for study area during the period from 1991 to 2007. Were used to study supervized, unsupervized classfication and NDVI land cover changes in the desert area in Mongolia. The classified map consists of five classes of water, vegetation, slight desertification, middle desertification and sever desertification. It shows that for determination classfication methods and NDVI, desertification map of the study area are prepared. The result showed accounting for a clear deterioration in vegetative cover, an increase of sever desertification and a decrease in middle desertification and slight desertification respectively of the total study area.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.677-687
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• 2017

In this paper, we propose the use of hierarchical classification for winter crop mapping based on satellite imagery. A hierarchical classification is a classifier that maps input data into defined subsumptive output categories. This classification method can reduce mixed pixel effects and improve classification performance. The methodology are illustrated focus on winter cropsin Gimje city, Jeonbuk with Landsat-8 imagery. First, agriculture fields were extracted from Landsat-8 imagery using Smart Farm Map. And then winter crop fields were extracted from agriculture fields using temporal Normalized Difference Vegetation Index (NDVI). Finally, winter crop fields were then classified into wheat, barley, IRG, whole crop barley and mixed crop fields using signature from Unmanned Aerial Vehicle (UAV). The results indicate that hierarchical classifier could effectively identify winter crop fields with an overall classification accuracy of 98.99%. Thus, it is expected that the proposed classification method would be effectively used for crop mapping.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.495-509
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• 2015

We study a classification problem of significant differences in the proportion of two groups known as the unbalanced classification problem. It is usually more difficult to classify classes accurately in unbalanced data than balanced data. Most observations are likely to be classified to the bigger group if we apply classification methods to the unbalanced data because it can minimize the misclassification loss. However, this smaller group is misclassified as the larger group problem that can cause a bigger loss in most real applications. We compare several classification methods for the unbalanced data using sampling techniques (up and down sampling). We also check the total loss of different classification methods when the asymmetric loss is applied to simulated and real data. We use the misclassification rate, G-mean, ROC and AUC (area under the curve) for the performance comparison.