• 한국철도학회:학술대회논문집
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• 한국철도학회 2003년도 추계학술대회 논문집(II)
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• pp.448-453
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• 2003

Most urban transit companies recognize the necessity of classification for facility management Classification for urban transit facility is necessary for standardization of maintenance management. The practical application. however. is not easy because of the absence of standardization of classification for urban transit facility and the difficulty in objectification of breakdown structure. This study suggests a proposal of classification for maintenance management in urban transit facility. This study defines standardization of classification as facility, work, maintenance and attribute to manage urban transit facility. And attribute classification consist of material, equipment and document. The suggested classification can be used as a useful maintenance management tool that enables evaluation of urban transit facility by standardization. The results of this study could be used as references for related urban transit companies.

• 한국측량학회지
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• 제33권3호
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• pp.173-179
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• 2015

In this paper, object-based classification of urban areas based on a combination of information from lidar and aerial images is introduced. High resolution images are frequently used in automatic classification, making use of the spectral characteristics of the features under study. However, in urban areas, pixel-based classification can be difficult since building colors differ and the shadows of buildings can obscure building segmentation. Therefore, if the boundaries of buildings can be extracted from lidar, this information could improve the accuracy of urban area classifications. In the data processing stage, lidar data and the aerial image are co-registered into the same coordinate system, and a local maxima filter is used for the building segmentation of lidar data, which are then converted into an image containing only building information. Then, multiresolution segmentation is achieved using a scale parameter, and a color and shape factor; a compactness factor and a layer weight are implemented for the classification using a class hierarchy. Results indicate that lidar can provide useful additional data when combined with high resolution images in the object-oriented hierarchical classification of urban areas.

• 대한원격탐사학회지
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• 제27권6호
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• pp.637-651
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• 2011

This study presents a rule-based urban image classification method for time series analysis of changes in the vicinity of Asan-si and Cheonan-si in Chungcheongnam-do, using Landsat satellite images (1991-2006). The area has been highly developed through the relocation of industrial facilities, land development, construction of a high-speed railroad, and an extension of the subway. To determine the yearly changing pattern of the urban area, eleven classes were made depending on the trend of development. An algorithm was generalized for the rules to be applied as an unsupervised classification, without the need of training area. The analysis results show that the urban zone of the research area has increased by about 1.53 times, and each correlation graph confirmed the distribution of the Built Up Index (BUI) values for each class. To evaluate the rule-based classification, coverage and accuracy were assessed. When Optimal allowable factor=0.36, the coverage of the rule was 98.4%, and for the test using ground data from 1991 to 2006, overall accuracy was 99.49%. It was confirmed that the method suggested to determine the maximum allowable factor correlates to the accuracy test results using ground data. Among the multiple images, available data was used as best as possible and classification accuracy could be improved since optimal classification to suit objectives was possible. The rule-based urban image classification method is expected to be applied to time series image analyses such as thematic mapping for urban development, urban development, and monitoring of environmental changes.

• 한국조경학회지
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• 제35권5호
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• pp.73-81
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• 2007

The purpose of this study is to derive policy suggestions and new orientations for biotope mapping in Korea from a review of case studies on the classification of biotope typesin Germany. This study was conducted in the following manner: First, the related literature and data on biotopes in Germany was collected. Second, the representative examples at the provincial government level and urban and residential areas were selected. Finally, the characteristics of biotope types, biotope classification systems, and biotope classification criteria were reviewed. The results of reviewing the case examples in Germany are as follows: First, the biotope types at the provincial government level were composed of patterns which existed mostly in natural areas and the corresponding areas of their conditions. Those in urban and residential areas were made up of patterns which were distributed in urban areas and their peripheries. Second, the biotope classification systems at the provincial government level consisted of three steps:large, medium and small. Those in urban and residential areas were made up of two steps: medium and small. However, it is strongly recommended to introduce the biotope classification system composed of three steps. Third, the biotope classification criteria at the provincial government level considered ecological factors and anthropogenic factors except land use forms. Those in urban and residential areas reflected mostly anthropogenic factors and ecological factors. In conclusion, this study suggests that future biotope surveys and mapping in Korea should be investigated not only in urban areas but also in natural and semi-natural areas. In addition, a specified biotope type classification system should be established in Korea.

• 한국조경학회지
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• 제48권5호
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• pp.42-58
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• 2020

본 연구는 도시 화훼경관의 유형화에 관한 연구로서 연구결과, 첫째, 문헌과 사례를 통하여 화훼경관의 개념이 정리되기 위해서는 개념의 핵심 어휘와 문장에 공간적 요소, 형태적 요소, 자연적 요소, 인공적 요소라는 4가지 요소가 포함되어야 함을 선행연구를 통해 발견하였으며, 이 네 가지 요소를 통섭하는 화훼경관 개념을 새롭게 재구성하여 제시하였다. 화훼경관 통합 이론의 기초자료가 될 것이다. 둘째, 화훼경관이 도시경관의 한 장르로 그리고 도시경관의 단위로 정의되고 전문영역으로서 체계 구축을 위해 도시경관이라는 커다란 범주 안에서 도시경관의 개념과 특성, 기능을 고찰하고, 그 안에서 화훼경관과의 위계화 범주를 새롭게 정리하여 화훼경관의 도시경관성을 제시하였다. 셋째, 유형화를 통한 수요자들의 합리적인 선택자료 제시를 위해 화훼분야는 물론, 도시계획, 도시생태 분야까지 확장하여 관련 이론을 고찰하였으며, 유형화 요소 41개를 추출하였고 군집화 과정을 통해 4개의 핵심 유형화 요소를 도출하였으며, 4개의 요소를 분류 준거로 전문가 FGI에서 의견과 검증의 과정을 거쳐 중분류 9개, 소분류 30개 유형을 도출하여 제시하였다. 향후 연구과제로는 유형 적용과정에서 모니터링을 통해 유효한 유형의 추가 설정과 2단계 분류 위계를 3단계 위계로 확장하여, 보다 세분화된 적용 유형의 개발과 정리를 한다면 유형의 체계를 보다 발전시키는 좋은 연구가 될 것으로 보인다.

• 한국측량학회지
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• 제25권6_1호
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• pp.499-505
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• 2007

A method of improving the correctness and confidence in land use classification as well as urban spatial structure analysis of local governments using GIS and satellite imagery is suggested. This study also compares and analyzes LSAS (Land Suitability Assessment System) results using two approaches-LSAS with priority classification, and LSAS using standard estimation factors without priority classification. The conclusions that can be drawn from this study are as follows. First, a method of maintaining up-to-date local government data by updating the LSAS database using high-resolution satellite imagery is suggested. Second, to formulate a scientific and reasonable land use plan from the viewpoint of territory development and urban management, a method of simultaneously processing the two described approaches is suggested. Finally, LSAS was constructed by using varieties of land information such as the cadastral map, the digital topographic map, varieties of thematic maps, and official land price data, and expects to utilize urban management plan establishment widely and effectively through regular data updating and problem resolution of data accuracy.

• 농촌지도와개발
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• 제16권3호
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• pp.557-586
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• 2009

The objective is to find the classification criteria between urban and rural, and to classify the urban and rural area all the country in Korea. For the research objectives, reviews of related literature and statistical yearbooks were used for finding criteria and analysing data. Through reviewing the literature, some indicators were selected in views of rurality and urbanity, and gathered the data from statistical yearbooks. And factor analysis was used to find first and second factor for classifying region. Six factors as a city surrounding(36%), non-farmer household population ratio(28.1%), cultivated acreage(12.48%), agricultural production surrounding (12.40%), the farm family number change(5.58%) and household number rise and fall(5.54%) were finding. And rurality factors were cultivated acreage, agricultural production surrounding, the farm family number change and household number rise and fall, and urbanity factors were city surrounding and non-farmer household population ratio. Based on the first and second factor loaded amount, four type regional classification was followed.

• 대한원격탐사학회지
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• 제21권5호
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• pp.383-392
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• 2005

Vegetation classes, especially grass and tree classes, are often confused in classification when conventional spectral pattern recognition techniques are used to classify urban areas. This paper reports on a study to improve the classification results by using an automated process of considering height information in separating urban vegetation classes, specifically tree and grass, using three-band, high-spatial resolution, digital aerial imagery. Height information was derived photogrammetrically from stereo pair imagery using cross correlation image matching to estimate differential parallax for vegetation pixels. A threshold value of differential parallax was used to assess whether the original class was correct. The average increase in overall accuracy for three test stereo pairs was $7.8\%$, and detailed examination showed that pixels reclassified as grass improved the overall accuracy more than pixels reclassified as tree. Visual examination and statistical accuracy assessment of four test areas showed improvement in vegetation classification with the increase in accuracy ranging from $3.7\%\;to\;18.1\%$. Vegetation classification can, in fact, be improved by adding height information to the classification procedure.

• 로봇학회논문지
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• 제7권2호
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• pp.92-100
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• 2012

A map of complex environment can be generated using a robot carrying sensors. However, representation of environments directly using the integration of sensor data tells only spatial existence. In order to execute high-level applications, robots need semantic knowledge of the environments. This research investigates the design of a system for recognizing objects in 3D point clouds of urban environments. The proposed system is decomposed into five steps: sequential LIDAR scan, point classification, ground detection and elimination, segmentation, and object classification. This method could classify the various objects in urban environment, such as cars, trees, buildings, posts, etc. The simple methods minimizing time-consuming process are developed to guarantee real-time performance and to perform data classification on-the-fly as data is being acquired. To evaluate performance of the proposed methods, computation time and recognition rate are analyzed. Experimental results demonstrate that the proposed algorithm has efficiency in fast understanding the semantic knowledge of a dynamic urban environment.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.388-393
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• 2002

Remote sensing data is collected and analyzed to enhance understanding of the terrestrial surface. Since Landsat satellite was launched in 1972, many researches using multispectral data has been achieved. Recently, with the availability of airborne and satellite hyperspectral data, the study on hyperspectral data are being increased. It is known that as the number of spectral bands of high-spectral resolution data increases, the ability to detect more detailed cases should also increase, and the classification accuracy should increase as well. In this paper, we classified the hyperspectral and multispectral data and tested the classification accuracy. The MASTER(MODIS/ASTER Airborne Simulator, 50channels, 0.4~13$\mu$m) and Landsat TM(7channels) imagery including Yeong-Gwang area were used and we adjusted the classification items in several cases and tested their classification accuracy through statistical comparison. As a result of this study, it is shown that hyperspectral data offer more information than multispectral data.