• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.4
• /
• pp.267-275
• /
• 2015

Those land cover maps have widely been used in various fields, such as environmental studies, military strategies as well as in decision-makings. This study proposes a method to extract training data, automatically and classify the cover using ingle satellite images and national land cover maps, provided by the Ministry of Environment. For this purpose, as the initial training data, those three were used; the unsupervised classification, the ISODATA, and the existing land cover maps. The class was classified and named automatically using the class information in the existing land cover maps to overcome the difficulty in selecting classification by each class and in naming class by the unsupervised classification; so as achieve difficulty in selecting the training data in supervised classification. The extracted initial training data were utilized as the training data of MLC for the land cover classification of target satellite images, which increase the accuracy of unsupervised classification. Finally, the land cover maps could be extracted from updated training data that has been applied by an iterative method. Also, in order to reduce salt and pepper occurring in the pixel classification method, the MRF was applied in each repeated phase to enhance the accuracy of classification. It was verified quantitatively and visually that the proposed method could effectively generate the land cover maps.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.1D
• /
• pp.45-51
• /
• 2010

Traffic volume is essential data for traffic control or maintenance and rehabilitation planning. The volume especially with respect to the type of vehicles can facilitate to those road operations. In this research, a method for vehicle classification was developed using skewed sensors which can generate traffic signatures. In order to characterize vehicle types, the method investigates whether the second axle of each vehicle consists of dual tires. The presence of dual tire is determined by the discriminate function obtained from discriminant analysis. The validation using 1,878 vehicles recorded from a highway using a CCTV camera indicated significantly accurate results: 96.92% for class 1, 82.91% for class 3 and 79.13% for class 4.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.9
• /
• pp.4192-4198
• /
• 2011

Terrestrial LiDAR is a high precision positioning technique to monitor the behavior and change of structures and natural slopes, but it has depended on subjective hand intensive tasks for the classification(surface and vegetation or structure and vegetation) of positioning data. Thus it has a couple of problems including lower reliability of data classification and longer operation hours due to the surface characteristics of various geographical and natural features. In order to solve those problems, the investigator developed a technique of using the NDVI, which is a major index to monitor the changes on the surface(including vegetation), to categorize land covers, combining the results with the terrestrial LiDAR data, and classifying the results according to items. The application results of the developed technique show that the accuracy of convergence was 94% even though there was a problem with partial misclassification of 0.003% along the boundaries between items. The technique took less time for data processing than the old hand intensive task and improved in accuracy, thus increasing its utilization across a range of fields.

• Journal of Korean Society of Archives and Records Management
• /
• v.18 no.4
• /
• pp.99-124
• /
• 2018

This study suggests the development of a classification system for the Independent Movement Records of the Ministry of Patriots and Veterans Affairs based on the collection of Gonghun Digital Archive based on sources, subjects, and media types. First, the classification system by source is organized by hierarchy, and the records classified by source are classified into the second category based on the related keyword. Then, the records are classified into 17 media types. Finally, it is described in the citation order of "source-subject-media type." In addition, a meaningful collection using inductive methods based on the subject words is derived. Finally, Gonghun Digital Archive collections are categorized by media types, sources, and subjects so that users can easily find the records. The result of this study is a classification system to support records retrieval of an independent movement collection, and it will become a basis for expanding the accessibility of the user and the service of independent movement records.

• The Korean Journal of Applied Statistics
• /
• v.34 no.5
• /
• pp.711-721
• /
• 2021

In this paper, we propose the method of adjusting thresholds using impurity indices in classification analysis on imbalanced data. Suppose the minority category is Positive and the majority category is Negative for the imbalanced binomial data. When categories are determined based on the commonly used 0.5 basis, the specificity tends to be high in unbalanced data while the sensitivity is relatively low. Increasing sensitivity is important when proper classification of objects in minority categories is relatively important. We explore how to increase sensitivity through adjusting thresholds. Existing studies have adjusted thresholds based on measures such as G-Mean and F1-score, but in this paper, we propose a method to select optimal thresholds using the chi-square statistic of CHAID, the Gini index of CART, and the entropy of C4.5. We also introduce how to get a possible unique value when multiple optimal thresholds are obtained. Empirical analysis shows what improvements have been made compared to the results based on 0.5 through classification performance metrics.

• Journal of Korean Library and Information Science Society
• /
• v.39 no.4
• /
• pp.215-235
• /
• 2008

The purpose of this study aims to provide possible suggestions for the improvement of the literature classification number system as the search and browsing device on the library homepage. After analyzing and evaluating literature classification number system as the search and browsing device on the homepage of library adopting DDC, suggestions for the improvement were proposed. For the purpose of maximizing the effectiveness of literature classification number system as the browsing device, DDC third summary(the thousand section) which is suited to domestic circumstances was prepared.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2011.05a
• /
• pp.355-355
• /
• 2011

토지피복의 분류는 토지표면의 물리적인 지표면의 상태를 나타내는 자료로 환경, 행정, 수자원, 재해 등 다방면으로 이용되고 있다. 특히 수자원과 관련하여 식생의 증산과 토양의 증발을 통칭하는 증발산과 유출, 토양수분 등과 연관되어 있다. 광범위한 토지피복의 산정에는 경제성 및 주기성 등의 장점으로 인하여 인공위성 영상을 이용하는 기법이 적합하다. 위성영상분류법은 훈련지역의 선정 여부에 따라 감독분류와 무감독 분류로 나누어지며 각각의 알고리즘의 특성에 따라 더욱 세분화된다. 본 연구에서는 Landsat-TM (Thematic Mapper) 영상을 이용하여 감독 분류와 무감독 분류를 각각 적용하여 한강유역의 토지피복을 수역, 시가, 나지 습지, 초지, 산림, 농지의 7가지 부분으로 대분류로 산정하고 비교하였다. 두 경우의 정확도는 각각 91.6%, 90.9%의 비슷한 정확도를 나타내었으며, 세부적으로 우리나라의 대부분의 면적에 분포하는 산림, 농지, 시가, 수역의 정확도가 높게 나타났다. 또한 각 항목별로 정확도를 비교하였을 때 감독분류가 무감독분류에 비해 다소 정확한 것을 확인할 수 있었다. 추후 외부자료를 도입하면 비교적 낮은 정확도를 나타낸 초지, 습지, 나지의 정확도를 보완할 수 있을 것이다.

• Korean Journal of Remote Sensing
• /
• v.33 no.5_2
• /
• pp.689-698
• /
• 2017

In this paper, a new classification method based on the combination of semi-supervised learning with spatial similarity of adjacent pixels is presented for crop classification in inaccessible areas. Iterative classification based on semi-supervised learning is applied to extract reliable training data from both the initial classification result with a small number of training data, and classification results of adjacent pixels are also considered to extract new training pixels with less uncertainty. To evaluate the applicability of the proposed method, a case study of the classification of field crops was carried out using multi-temporal Landsat-8 OLI acquired in the Daehongdan region, North Korea. From a case study, the misclassification of crops and forests, and isolated pixels in the initial classification result were greatly reduced by applying the proposed semi-supervised learning method. In addition, the combination of classification results of adjacent pixels for the extraction of new training data led to the great reduction of both misclassification results and isolated pixels, compared to the initial classification and traditional semi-supervised learning results. Therefore, it is expected that the proposed method would be effectively applied to classify areas in which it is difficult to collect sufficient training data.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2003.04a
• /
• pp.596-601
• /
• 2003

위성영상으로부터 수계영역을 분류하는 일은 홍수관련 분석을 위해서 매우 중요한 일이다. 본 연구에서는 홍수 발생시 취득된 RADARSAT 영상을 이용해서 산악지역의 수계영역의 분류를 목적으로 하였다. SAR 영상은 능동적 영상취득을 수행하므로 광학영상에 비해서 수계영역이 확실하게 나타나는 반면에 지형의 기복에 따른 여러 가지 왜곡현상이 발생한다. 본 연구에서는 RADARSAT 영상으로부터 수계영역의 분류를 위해 방사보정, 그림자 효과제거, 고도자료 및 경사도 자료의 활용 등의 경우로 구분하여 연구를 수행하였다. 그 결과 RADARSAT 영상만을 활용할 경우 분류의 정확도에 한계를 보였으며, RADARSAT 영상에 지형정보를 추가로 활용함으로서 정확한 수계영역을 분류할 수 있었다. 특히 RADARSAT 영상과 경사도 자료를 동시에 활용하여 수계지역을 분류하는 것이 가장 효과적임을 알 수 있었다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10b
• /
• pp.314-318
• /
• 2006

인터넷의 비약적인 발전으로 많은 강의 자료가 존재하게 되었으며, 어느 누구나 손쉽게 강의 자료를 구할 수 있게 되었다. 하지만 사용자는 단순히 많은 정보만을 원하는 것이 아니라 정확한 정보를 얻기를 원한다. 이에 본 논문에서는 기존의 단어 빈도수 기반의 분류 방식이 아닌 개념적 분류 방식으로 온톨로지를 이용하여 코스웨어를 분류해보고자 한다. 온톨로지로는 어휘적 온톨로지의 일종인 WordNet의 과목에 대한 계층적 구조를 활용하였다. 실험 데이터로는 강의 자료 중 파워포인트로 작성된 코스웨어를 이용하였으며, 코스웨어의 메타데이터들과 과목들간의 개념적 거리 및 밀도를 측정하여 코스웨어를 분류하였다. 또한 WordNet상의 어휘 확장을 통하여 분류과목 확장이 가능함을 보였다.