• Journal of the Regional Association of Architectural Institute of Korea
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• v.20 no.6
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• pp.89-96
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• 2018

The purpose of this study is to categorize Commercial area by identifying characteristics of blocks and coding them in order to segment use zoning in Commercial area. The study was conducted as follows. Data from building register, cadastral map, statistics annual report are utilized to identify the physical environment of the block. four types used as code under the physical environment classification code which are classification code of physical environment, detail usage, volume ratio, and height type are set, and combine the classification codes sorted by the four types of code. Through the physical environment classification codes, there are currently 37 different block characteristics of the Old downtown Commercial area. Diversity is not reflected. There are only Central commercial area of regulations in Old downtown commercial areas that are uniformly managed. For the renewal, management and development that can occur in the near future, it is necessary to segment of use district in the commercial area. Consider the current situation and future development direction for the management of sustainable commercial areas. Management is required using physical environment classification codes. It is meaningful that it can be maintained, managed and developed in accordance with the characteristics of each block.

• Fire Protection Technology
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• s.15
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• pp.22-27
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• 1993

The classification of hazardous area is a method of analysing and classifying the environment where explosive gas or vapour atmosphere may be expected to be present. The object of area classification is to enable the proper selection and installation of electical apparatus and other equipments. This report is intended to serve a general reference about the classification procedure of hazardous area with explanations of related Korean Standard.

• Korean Chemical Engineering Research
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• v.58 no.3
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• pp.493-497
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• 2020

Hazardous area classification is designed to prevent chemical plant explosions in advance. Generally, the duration of the explosive atmosphere is used for zone type classification. Herein, IEC code, a quantitative zone type classification methodology, was used to achieve Zone 2 NE, which indicates a practical non-explosion condition. This study analyzed the operating pressure of a vessel handling propane to achieve Zone 2 NE by applying the IEC code via MATLAB. The resulting zone type and hazardous area grades were compared with the results from other design standards, namely API and EI codes. According to the IEC code, the operating pressure of vessels handling propane should be between 101325-116560.59 Pa. In contrast, the zone type classification criteria used by API and EI codes are abstract. Therefore, since these codes could interpret excessively explosive atmospheres, care is required while using them for hazardous area classification design.

• Korean Journal of Remote Sensing
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• v.17 no.3
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• pp.189-197
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• 2001

Generally, remote sensing is useful to obtain the quantitative and qualitative information of a wide area. For monitoring earth resources and environment, land cover classification of remotely sensed data are needed over increasingly larger area. The objective this study is to propose the process for land cover classification method over a wide area using multi-scene satellite data. Land cover of Korean peninsula was extracted from a Landsat TM and ETM+ mosaic created from 23 scenes at 100-meter resolution. Well-known techniques that used to general image processing and classification are applied to this wide area classification. It is expected that these process is very useful to promptly and efficiently grasp of small scale spatial information such as national territorial information.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.387-388
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• 2010

There is no generalized and systematic method yet to data pre-processing for point cloud data classification even if there have been lots of previous studies such as local maxima filter, morphology filter, slope based filter and so on. Main focus of this study is to present classification method for bare ground information from LiDAR data for the mountainous area.

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.671-680
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• 2018

Compared to the imagery produced by traditional satellites, PlanetScope satellite imagery has made it possible to easily capture remotely-sensed imagery every day through dozens or even hundreds of satellites on a relatively small budget. This study aimed to detect changed areas and update a land cover map using a PlanetScope image. To generate a classification map, pixel-based Random Forest (RF) classification was performed by using additional features, such as the Normalized Difference Water Index (NDWI) and the Normalized Difference Vegetation Index (NDVI). The classification result was converted to vector data and compared with the existing land cover map to estimate the changed area. To estimate the accuracy and trends of the changed area, the quantitative quality of the supervised classification result using the PlanetScope image was evaluated first. In addition, the patterns of the changed area that corresponded to the classification result were analyzed using the PlanetScope satellite image. Experimental results found that the PlanetScope image can be used to effectively to detect changed areas on large-scale land cover maps, and supervised classification results can update the changed areas.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.4
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• pp.611-617
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• 2004

Pixel classification is one of basic image processing issues. The general characteristics of the pixels belonging to various classes are discussed and the radical principles of pixel classification are given. At the same time. a pixel classification scheme based on image direction measure is proposed. As a typical application instance of pixel classification, an adaptive multi-level median filter is presented. An image can be classified into two types of areas by using the direction information measure, that is. smooth area and edge area. Single direction multi-level median filter is used in smooth area. and multi-direction multi-level median filter is taken in the other type of area. What's more. an adaptive mechanism is proposed to adjust the type of the filters and the size of filter window. As a result. we get a better trade-off between preserving details and noise filtering.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.3
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• pp.55-64
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• 2014

While utilizing high resolution satellite image for land use classification has been popularized, object-oriented classification has been adapted as an affordable classification method rather than conventional statistical classification. The aim of this study is to extract the paddy field area using object-oriented classification with time series NDVI from high-resolution satellite images, and the RapidEye satellite images of Jaeryung-gun in North Korea were used. For the implementation of object-oriented classification, creating objects by setting of scale and color factors was conducted, then 3 different land use categories including paddy field, forest and water bodies were extracted from the objects applying the variation of time-series NDVI. The unclassified objects which were not involved into the previous extraction classified into 6 categories using unsupervised classification by clustering analysis. Finally, the unsuitable paddy field area were assorted from the topographic factors such as elevation and slope. As the results, about 33.6 % of the total area (32313.1 ha) were classified to the paddy field (10847.9 ha) and 851.0 ha was classified to the unsuitable paddy field based on the topographic factors. The user accuracy of paddy field classification was calculated to 83.3 %, and among those, about 60.0 % of total paddy fields were classified from the time-series NDVI before the unsupervised classification. Other land covers were classified as to upland(5255.2 ha), forest (10961.0 ha), residential area and bare land (3309.6 ha), and lake and river (1784.4 ha) from this object-oriented classification.

• Journal of Korean Library and Information Science Society
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• v.35 no.2
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• pp.135-154
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• 2004

This study was investigated to the geographical categories and arrangement of library classifications and public organizations in ender to understand the geographical category comprehension and canon from the north-west to south-east in Korean library classification and then to develop a Korean geographical classification system Research method was the examination of different type of library classification (DDC, NDC, LCC) and geographical categorizations of the public organizations. The results show that there was not a principle of categorization and arrangement for geographical information. This study proposes to the three hierarchical structures and radial category arrangement from center-area to side area for developing Km geographical classification.

• Journal of Ocean Engineering and Technology
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• v.8 no.2
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• pp.64-79
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• 1994

In this study, terrain classification, which was done by using the quantitative classification parameters and suitable interpolation method was applied to improve the accuracy of digital elevation models, and to increase its practical use of aerial photogrammetry. A terrain area was classified into three groups using the quantitative classification parameters to the ratio of horizontal, inclined area, magnitude of harmonic vectors, deviation of vector, the number of breakline and proposed the suitable interpolation. Also, the accuracy of digital elevation models was improved in case of large grid intervals by applying combined interpolation suitable for each terrain group. As a result of this study, I have an algorithm to perform the classification of the topography in the area of interest objectively and decided optimal data interpolation scheme for given topography.