• The Journal of the Petrological Society of Korea
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• v.25 no.4
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• pp.325-334
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• 2016

Both 1900 years of historic literature and recent instrumental seismic records indicate the Korean Peninsula has repeatedly experienced small and large earthquakes. This study has used historical and instrumental records of Korea to investigate the characteristics of earthquakes in the peninsula. Results of GIS spatial analyses indicate Pyongyang, the capital of North Korea, is more vulnerable to the earthquake hazard than that of other regions in the Korean Peninsula. It is also noted that Pyongyang is exposed to high risks of other natural and social disasters because of the high population density and concentrated infra structures. Scenario shake map drawn up assuming a magnitude 6.7 earthquake, which was experienced in A.D. 502 in the area, indicates that 51.1% of the city are exposed to PGA 0.24 g or higher. Recent statistics by the Statistics Korea also indicates the North Korea is far more vulnerable to disasters than those in the South Korea. Results of the preliminary study provide essential information for comprehensive understanding of earthquake hazard estimation in Korea including the North Korea.

• Spatial Information Research
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• v.15 no.3
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• pp.203-218
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• 2007

The purpose of this article is to set up the scientific and reasonable norm of location and service area determination instead of the pro-administrative lacking availability, so as to propose more practical and reasonable standard of space unit for the location of facilities. This article has accepted the method of Voronoi Diagram as a new scientific and reasonable criteria. The article chooses and realizes a model that can propose a new service area, transform and apply to improve its reality, and assesses which has more reality and compatibility by comparing the models. The result from this procedure can be adapted in objectification of the service area determination and formation of the standard space unit.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.188-188
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• 2016

The Mekong which is one of the world's most significant rivers plays an extremely important role to South East Asia. Lying across six riparian countries including China, Myanmar, Thailand, Laos, Cambodia and Vietnam and being a greatly biological and ecological diversity of fishes, the river supports a huge population who living along Mekong Basin River. Therefore, much attention has been focused on the giant Mekong Basin River, particularly, the soil erosion and sedimentation problems which rise critical impacts on irrigation, agriculture, navigation, fisheries and aquatic ecosystem. In fact, there have been many methods to calculate these problems; however, in the case of Mekong, the available data have significant limitations because of large area (about 795 00 km2) and a failure by management agencies to analyze and publish of developing countries in Mekong Basin River. As a result, the Universal Soil Loss Equation (USLE) model in a GIS (Geographic Information System) framework was applied in this study. The USLE factors contain the rainfall erosivity, soil erodibility, slope length, steepness, crop management and conservation practices which are represented by raster layers in GIS environment. In the final step, these factors were multiplied together to estimate the soil erosion rate in the study area by using spatial analyst tool in the ArcGIS 10.2 software. The spatial distribution of soil loss result will be used to support river basin management to find the subtainable management practices by showing the position and amount of soil erosion and sediment load in the dangerous areas during the selected 56- year period from 1952 to 2007.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.121-128
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• 2016

Many studies are focused on image data and classifier for comparison or improvement of classification accuracy. Therefore studies are needed aspect of the training samples on supervised classification which depend on reference data or skill of analyst. This study tries to assess usability of field spectra as training samples on supervised classification. Classification accuracies of hyperspectral and multispectral images were assessed using training samples from image itself and field spectra, respectively. The results shown about 90% accuracy with training sample collected from image. Using field spectra as training sample, accuracy was decreased 10%p for hyperspectral image, and 20%p for multispectral image. Especially, some classes shown very low accuracies due to similar spectral characteristics on multispectral image. Therefore, field spectra might be used as training samples on classification of hyperspectral image, although it has limitation for multispectral image.

• Geomechanics and Engineering
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• v.7 no.6
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• pp.589-612
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• 2014

This study includes determination of liquefaction potential in Erzincan city center. Erzincan Province is situated within first-degree earthquake zone on earthquake map of Turkey. In this context, the earthquake scenarios were produced using the empirical expressions. Liquefaction potential for different earthquake magnitudes (6.0, 6.5, 7.0) were determined. Liquefaction potential was investigated using Standard Penetration Test (SPT). Liquefaction potential analyses are determined in two steps: geotechnical investigations and calculations. In the first steps, boreholes were drilled to obtain disturbed and undisturbed soil samples and SPT values were obtained. Laboratory tests were made to identify geotechnical properties of soil samples. In the second step, liquefaction potential analyses were examined using two methods, namely Seed and Idriss (1971), Iwasaki et al. (1981). The liquefaction potential broadly classified into three categories, namely non-liquefiable, marginally liquefiable and liquefiable regions. Additionally, the liquefaction potential index classified into four categories, namely non-liquefiable, low, high and very high liquefiable regions. In order to liquefaction analysis complete within a short time, MATLAB program were prepared. Following the analyses, liquefaction potential index is investigated by Iwasaki et al. (1982) methods. At the final stage of this study, liquefaction potential maps and liquefaction potential index maps of the all study area by using IDW (inverse distance weighted) interpolation method in Geostatistical Analyst Module of ArcGIS 10.0 Software were prepared for different earthquake magnitudes and different depths. The results of soil liquefaction potential were evaluated in ArcGIS to map the distributions of drillings with liquefaction potential. The maps showed that there is a spatial variability in the results obtained which made it difficult to clearly separate between regional areas of high or low potential to liquefy. However, this study indicates that the presence of ground water and sandy-silty soils increases the liquefaction potential with the seismic features of the region.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.53-59
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• 2009

The general urban plan is the plane plan which limits general and uniformed constructions; however, the district unit plan is the solid plan that can leads various constructions by discriminating by plot, housing area and lot. Therefore, for the zone plan, not only the two-dimensional plot information such as plot usage plan, but also the three-dimensional plot information needs to be used to analyze lighting, sewerage and directions. To fulfill such requirements, the information can be gathered using GIS and photogrammetric method for the reasonable and efficient zone plan. In this research, the information about the testing area for the zone plan has been gathered using GIS method, and the three-dimensional model about the area has been built using the satellite image and DEM. As the result, plot usage analysis, direction analyst, water system analysis, and slope analysis has been done and used efficiently to build the district unit plan. Also, after the result after applying the analyzed result to the actual area says this is very appropriate and efficient.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.168-178
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• 2006

In recent years, an ingress of mass jellyfish into cooling water intake system causes interruption of electric power production at the Uljin nuclear power plant. Therefore, monitering and forecast on the mass ingress of marine organisms are demanded as one of the early preventing measurements. Sea water movement is a major factor on the ingress of marine organisms like Moon jellyfish which has weak self-mobile ability. When sea surface flow direction adjacent to the Uljin is the northwest, the jellyfish on the Tsushima warm currents move to the Uljin power plant. To detect the direction of sea surface warm flows, the spatial range with $25km{\times}25km$ is set up and NOAA sea surface temperature(SST) data are collected in this area. For the statistical analysis, the SST data are made as GIS point data and geostatistical analysis of ArcGIS is used. Analyzing directional semivariogram, the anisotropy of the SST point data are calculated and warm flow direction is detected. This experimental results are expected to use as an element technology for the early warning system development of mass jellyfish ingress in power plant.

• Journal of Korean Society for Geospatial Information Science
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• v.1 no.1 s.1
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• pp.193-201
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• 1993

In a number of areas, there are important benefits to be gained when we bring both the detection and monitoring abilities of remote sensing as well as the philosophical approach and analytic capabilities of a geographic information system to bear on a problem. A key area in the joint applications of remote sensing technology and GIS is to identify change. Whether this change is of interest for its own sake, or because the change causes us to act (for example, to update a map), remote sensing provides an excellent suite of tools for detecting change. At the same time, a GIS is perhaps the best analytic toot for quantifying the process of change. There are two alternative methods for quantifying changes. The conceptually simple approach is to un the pixel values in each of the images. This method is practical but may be too simple to identify the variety of changes in a complex scene. The common alternative is called symbolic change detection. The analyst first decides on a set of thematic categories that are important to distinguish for the application. This approach is useful only if accurate landuse/cover classifications can be obtained. Persons conducting digital change detection must be intimately familiar with the environment under study, the quality of the data set and the characteristics of change detection algorithms. Also, much work remains to identify optimum change detection algorithms for specific geographic areas and problems.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.461-469
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• 2022

This paper presents a novel training data extraction approach using semi-supervised learning (SSL)-based classification without the analyst intervention for time-series land-cover mapping. The SSL-based approach first performs initial classification using initial training data obtained from past images including land-cover characteristics similar to the image to be classified. Reliable training data from the initial classification result are then extracted from SSL-based iterative classification using classification uncertainty information and class labels of neighboring pixels as constraints. The potential of the SSL-based training data extraction approach was evaluated from a classification experiment using unmanned aerial vehicle images in croplands. The use of new training data automatically extracted by the proposed SSL approach could significantly alleviate the misclassification in the initial classification result. In particular, isolated pixels were substantially reduced by considering spatial contextual information from adjacent pixels. Consequently, the classification accuracy of the proposed approach was similar to that of classification using manually extracted training data. These results indicate that the SSL-based iterative classification presented in this study could be effectively applied to automatically extract reliable training data for time-series land-cover mapping.