• Journal of Forest and Environmental Science
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• 제32권4호
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• pp.384-391
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• 2016

In this study, regions infected by pine wilt disease were extracted by using object-based classification method (OB-infected region), and the characteristics of special distribution about OB-infected region were figured out. Scale 24, Shape 0.1, Color 0.9, Compactness 0.5, and Smoothness 0.5 was selected as the objected-based, optimal weighted value of OB-infected region classification. The total accuracy of classification was high with 99% and Kappa coefficient was also high with 0.97. The area of OB-infected region was approximately 90 ha, 16% of the total area. The OB-infected region in Age class V and VI was intensively distributed with 97% of the total. Also, The OB-infected region in Middle and Large DBH class was intensively distributed with 99% of the total. In terms of the topographic characteristics of OB-infected region, the damages occurred approximately 86% below the altitude of 200 m, and occurred 91% with a slope less than 10 degree. The damage occurred a lot in low hilly mountain and undulating slope. In addition, the accessibility to road and residential area from OB-infected region was less than 300 m in large part. Overall, it was figured out that artificial effect is stronger than natural effect with regard to the spread of pine wilt disease.

• 상하수도학회지
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• 제26권5호
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• pp.637-647
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• 2012

Recent series of flooding events in urban area has brought a growing concern on storage facilities as a major stormwater management method. The Korean Ministry of Environment has announced diverse plans to tackle the problem, including plans for multi-purpose storages which deal both the stormwater and wastewater. Even though storages can be categorized for different perspectives, classification of possible storages in urban area has not been throughly studied so far. This study investigated diverse references of urban storages and suggested systematic classifications on structural, functional and some other basis. Structural classification mainly concerns structural shape of facilities and includes (1)Cisterns & Rain barrels, (2)Forebays, (3)Dry basins, (4)Wet basins and (5)Constructed wetland. Those functions can be (1)flood prevention (2)water quality control and (3)reuse of stored water. Other criteria that categorize storages depend on (1)height, (2)location, (3)configuration, (4)depth, (5)site of the installation and (6)shape.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.341-344
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• 2007

A major obstacle to classify and validate Land Cover maps is the high cost of generating reference data or multiple thematic maps for subsequent comparative analysis. In case of inaccessible area such as North Korea, the high resolution satellite imagery may be used as in situ data so as to overcome the lack of reliable reference data. The objective of this paper is to investigate the possibility of utilizing QuickBird (0.6m) of North Korea obtained from Google Earth data provided thru internet. Monthly NDVI images of nine months from the summer of 2004 were classified into L=54 cluster using ISODATA algorithm, and these L clusters were assigned to 7 classes; coniferous forest, deciduous forest, mixed forest, paddy field, dry field, water and built-up area. The overall accuracy and Kappa index were 85.98% and 0.82, respectively, which represents about 10% point increase of classification accuracy than our previous study based on GCP point data around North Korea. Thus we can conclude that Google Earth may be used to substitute the traditional in situ data collection on the site where the accessibility is severely limited.

• Journal of the Korean Wood Science and Technology
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• 제49권5호
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• pp.491-503
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• 2021

Wood identification is regularly performed by observing the wood anatomy, such as colour, texture, fibre direction, and other characteristics. The manual process, however, could be time consuming, especially when identification work is required at high quantity. Considering this condition, a convolutional neural networks (CNN)-based program is applied to improve the image classification results. The research focuses on the algorithm accuracy and efficiency in dealing with the dataset limitations. For this, it is proposed to do the sample selection process or only take a small portion of the existing image. Still, it can be expected to represent the overall picture to maintain and improve the generalisation capabilities of the CNN method in the classification stages. The experiments yielded an incredible F1 score average up to 93.4% for medium sample area sizes (200 × 200 pixels) on each CNN architecture (VGG16, ResNet50, MobileNet, DenseNet121, and Xception based). Whereas DenseNet121-based architecture was found to be the best architecture in maintaining the generalisation of its model for each sample area size (100, 200, and 300 pixels). The experimental results showed that the proposed algorithm can be an accurate and reliable solution.

• 한국환경복원기술학회지
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• 제6권5호
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• pp.9-20
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• 2003

The purpose of this study is to construct a database for landscape ecological planning with evaluation and analysis of structure of biotope of city center area for the preservation of species and biotope examining Jung-gu district of Daegu Metropolitan City which is the most extremely and rapidly urbanizing area. The assumption of this study is that the biotope structure of a city center area would be different from the other city area. The results of this study were as follows. 1) The results of the biotope type classification is that there were 11 biotope type groups and 41 detailed biotopes. 2) The primary evaluation is the process for grading general value of classified biotope types, and the result of primary evaluation is that there were 5 biotope types that were greater than third grade besides the biotope type of artificial riverbank with abundant green high water level land. The first grade of biotope type have not appeared in this area, however the fifth grade of biotope type have appeared total of 19 biotope types with the biotope type of the general shopping area with scarce green fields. 3) The secondary evaluation is the process for searching biotopes which are special value, and the result of secondary evaluation is that there were 2 biotopes for la, 7 biotopes for 1b, 2 biotopes for 2a, 1 biotope for 2b and there was no biotope for 2c, and for example, la is the large area that has many magor biotope site in terms of the living space. 4) Finally. scientific method for biotope type classification, the derailed investigation plan of high value biotope and the improvement plan based on the biotope map of city center area must be continued.

• 터널과지하공간
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• 제4권3호
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• pp.215-227
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• 1994

Rock Mass classifications have been developed in many European countries. The most widely used classification methods are the Rock Mass Rating (RMR) system proposed by Bieniawski(1973) and the Q-system developed By Barton et al. (1974). These methods are also adopted at many mountain tunnels and subway sites in our country. Here, a geomechanical classification for slopeds in rock, the "Slope Mass Rating"(SMR) is presented for the preliminary assessment of slope stabiliyt. This method can be applied to excavation and support design in the front part of tunnel and cutting area as a guide line and recommendation on support methods which allow a systemmetic use of geomechanical classification for rock slopes.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 춘계학술대회 학술발표 논문집
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• pp.248-251
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• 1997

In this paper, We propose the concept of approximate Classification in the field of two group discriminan analysis. In our approach, an attribute space is divided into three subspaces. Two subspaces are for given two group and one subspace is for a boundary area between the two groups. We propose Approximate Pattern Classification with Rough set. We also propose learning procedures of neural networks for approximate classification. We propose two weighting methods which lead to possibility analysis and necessity analysis. We illustrate the proposed methods by numerical examples.

• 대한원격탐사학회지
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• 제36권1호
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• pp.29-39
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• 2020

Forest fire is a critical disaster that causes massive destruction of forest ecosystem and economic loss. Hence, accurate estimation of the burned area is important for evaluation of the degree of damage and for preparing baseline data for recovery. Since most of the area size damaged by wildfires in Korea is less than 1 ha, it is necessary to use satellite or drone images with a resolution of less than 10m for detecting the damage area. This paper aims to detect wildfire-damaged area from a Kompsat-3 image using the indices such as NDVI (normalized difference vegetation index) and FBI (fire burn index) and to examine the classification characteristics according to the methods such as Otsu thresholding and ISODATA(iterative self-organizing data analysis technique). To mitigate the salt-and-pepper phenomenon of the pixel-based classification, a gaussian filter was applied to the images of NDVI and FBI. Otsu thresholding and ISODATA could distinguish the burned forest from normal forest appropriately, and the salt-and-pepper phenomenon at the boundaries of burned forest was reduced by the gaussian filter. The result from ISODATA with gaussian filter using NDVI was closest to the official record of damage area (56.9 ha) published by the Korea Forest Service. Unlike Otsu thresholding for binary classification,since the ISODATA categorizes the images into multiple classes such as(1)severely burned area, (2) moderately burned area, (3) mixture of burned and unburned areas, and (4) unburned area, the characteristics of the boundaries consisting of burned and normal forests can be better expressed. It is expected that our approach can be utilized for the high-resolution images obtained from other satellites and drones.

• 대한원격탐사학회지
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• 제30권4호
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• pp.493-503
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• 2014

이 논문에서는 대규모 작물 재배 지역의 작물 분류도의 조기 제작을 목적으로 분광학적 혼재를 줄이고, 과거 토지피복도의 작물 재배 패턴을 반영할 수 있는 계층적 분류 방법론을 제안하였다. 특히 작물 생육 주기로부터 다른 분광 특성을 고려한 계층적 분류 접근을 적용하고, 과거 작물 재배 패턴으로부터 추출된 시간적 문맥 정보를 함께 고려함으로써 분광 혼재가 두드러진 화소의 영향을 줄일 수 있다. 제안 분류 기법의 적용성을 평가하기 위해 미국 아이오와 주 전체를 대상으로 시계열 MODIS 250 m 정규식생지수 자료와 과거 crop data layer를 사용하는 사례 연구를 수행하였다. 사례 연구를 통해 다른 분류 단계와 과거 작물 재배 패턴을 고려함으로써 대상 지역의 주요 재배 작물이면서 분광학적 유사도가 두드러진 콩과 옥수수를 효과적으로 구분할 수 있었다. 그리고 분광 정보만을 이용한 분류 결과에 비해 제안 기법이 최소 7.68%p에서 최대 20.96%p의 향상된 분류 정확도를 보였다. 또한 분류 단계에서 시간적 문맥 정보를 결합함으로써 사용 NDVI 자료의 수에 영향을 덜 받는 가장 높은 분류 정확도(최대 전체 정확도: 86.63%)를 얻을 수 있었다. 따라서 제안 분류 기법은 주요 곡물 수입국의 대규모 작물 구분도의 조기 제작에 유용하게 사용될 수 있을 것으로 기대된다.

• 정보관리학회지
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• 제28권4호
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• pp.33-48
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• 2011

본 연구는 복합적인 주제 영역인 이민정책에 관한 다양한 정보를 효과적으로 조직하고 최적의 정보 서비스를 제공할 수 있는 분류표를 개발하기 위해 관련 문헌 연구와 다양한 문헌분류표를 조사하였다. 먼저, 문헌 연구를 통해 이민정책의 학문적 개념과 범주를 정의하고, 이를 바탕으로 핵심 주제 영역을 선정하였다. 다음으로, 듀이십진분류표, 미의회도서관분류표, 한국십진분류표, 국제십진분류표에서 이민정책 분야의 구조와 전개 항목, 특성을 비교 분석하였다. 그리고 이들 분류표 중 전 세계적으로 가장 많이 사용하고 있으며, 정기적으로 개정되고 있는 DDC 23판을 바탕으로 이민정책 분야를 수정 전개하기 위한 설계 원칙과 본표, 보조표를 제안하였다. 수정 전개된 듀이십진분류표는 이민정책을 다루는 주요 분야에 적용될 수 있으며, 이민 정책 관련 전문 연구기관이나 도서관에서 소장 자료를 효과적으로 분류하고 조직하며 이민정책 전문 정보를 통합 관리하기 위한 기초 자료로 활용될 것이다.