• Korean Journal of Environment and Ecology
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• v.27 no.5
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• pp.625-641
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• 2013

This study is analyzed the environmental ecological status of Suncheon Bay and its applicable possibility to the selection criteria of UNESCO World Natural Heritage (hereafter Criteria). The study shows that the formation process of the tidal-flats in Suncheon bay could apply to the Criteria VIII, "to be outstanding examples representing major stages of earth's history." The landscape pattern of Suncheon Bay is deduced various patterns based on 5 biotope types: tidal-flat, rice-paddy, field area, coniferous natural forest, and broadleaf natural forest. Its landscape characteristic is a harmonized composition of various landscape including mountains, rivers, fields, and tidal-flats. It is judged that the unique landscape of Suncheon Bay falls under the criteria VII, "areas of exceptional natural beauty and aesthetic importance." In addition, Suncheon Bay, the habitat of the Hooded Crane as internationally endangered species, comes under the criteria X, "the most important and significant natural habitats for in-situ conservation of threatened species." The study shows, however, that any other designation for protected area including national park or biosphere reserve is a prerequisite for designation of World Nature Heritage. In particular, it could evaluate whether it is qualified of the Criteria after the integrated conservation and management to the Sucheon bay as well as the southwestern tidal-flat is preceded.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.21-31
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• 2002

This study applied each Neural Networks theory and Fuzzy Set theory to improve accuracy in remotely sensed images. Remotely sensed data have been used to map land cover. The accuracy is dependent on a range of factors related to the data set and methods used. Thus, the accuracy of maps derived from conventional supervised image classification techniques is a function of factors related to the training, allocation, and testing stages of the classification. Conventional image classification techniques assume that all the pixels within the image are pure. That is, that they represent an area of homogeneous cover of a single land-cover class. But, this assumption is often untenable with pixels of mixed land-cover composition abundant in an image. Mixed pixels are a major problem in land-cover mapping applications. For each pixel, the strengths of class membership derived in the classification may be related to its land-cover composition. Fuzzy classification techniques are the concept of a pixel having a degree of membership to all classes is fundamental to fuzzy-sets-based techniques. A major problem with the fuzzy-sets and probabilistic methods is that they are slow and computational demanding. For analyzing large data sets and rapid processing, alterative techniques are required. One particularly attractive approach is the use of artificial neural networks. These are non-parametric techniques which have been shown to generally be capable of classifying data as or more accurately than conventional classifiers. An artificial neural networks, once trained, may classify data extremely rapidly as the classification process may be reduced to the solution of a large number of extremely simple calculations which may be performed in parallel.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2960-2965
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• 2013

Customized services for individuals in analysis of recently collected GPS information have been investigated in various aspects. As the size of collected GPS data gets larger, a variety of services is being released accordingly. Existing studies, however, are limited to presenting service models for users while there is little study on developing intelligent computing technologies in the introduction of GPS information into the system. This study suggests an algorithm to analyze traffic information by introducing GPS information into the system in order to take the lead among intelligent computing technologies. The suggested algorithm analyzes a map by means of the collected vehicle GPS information and sectional traffic information interpretation method; thus, the computer judges the traffic information collected by humans. The experiment result shows that the traffic information was properly analyzed upon the utilization of the given data. Although a small quantity of analyzed data was less reliable, the system maintained high reliability as the data was sufficient.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1037-1052
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• 2019

We had developed in preceding study a classification model for the Korean pine and Larch with an accuracy of 98 percent using Hyperion and Sentinel-2 satellite images, texture information, and geometric information as the first step for tree species mapping in the inaccessible North Korea. Considering a share of major tree species in North Korea, the classification model needs to be expanded as it has a large share of Oak(29.5%), Pine (12.7%), Fir (8.2%), and as well as Larch (17.5%) and Korean pine (5.8%). In order to classify 5 major tree species, national forest type map of South Korea was used to build 11,039 training and 2,330 validation data. Sentinel-2 data was used to derive spectral information, and PlanetScope data was used to generate texture information. Geometric information was built from SRTM DEM data. As a machine learning algorithm, Random forest was used. As a result, the overall accuracy of classification was 80% with 0.80 kappa statistics. Based on the training data and the classification model constructed through this study, we will extend the application to Mt. Baekdu and North and South Goseong areas to confirm the applicability of tree species classification on the Korean Peninsula.

• Journal of Korea Water Resources Association
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• v.40 no.6 s.179
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• pp.447-458
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• 2007

In this study, the coastal urban flood prediction and warning system based on HEC-RAS and SWMM were investigated to evaluate a watershed of On-Cheon stream in Busan which has characteristics of costal area cased by flooding of coastal urban areas. The basis of this study is a selection of various geological data from the numerical map that is a watershed of On-Cheon stream and computation of hydrologic GIS data. Thiessen method was used for analyzing of rainfall on the On-Cheon stream and 6th regression equation, which is Huff's Type II was time-distribution of rainfall. To evaluate the deployment of flood prediction and warning system, risk depth was used on the 3 selected areas. To find the threshold runoff for hydraulic analysis of stream, HEC-RAS was used and flood depth and threshold runoff was considered with the effect of tidal water level. To estimate urban flash flood trigger rainfall, PCSWMM 2002 was introduced for hydrologic analysis. Consequently, not only were the criteria of coastal urban flood prediction and warning system decided on the watershed of On-Cheon stream, but also the deployment flow charts of flood prediction and warning system and operation system was evaluated. This study indicates the criteria of flood prediction and warning system on the coastal areas and modeling methods with application of ArcView GIS, HEC-RAS and SWMM on the basin. For the future, flood prediction and warning system should be considered and developed to various basin cases to reduce natural flood disasters in coastal urban area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.1
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• pp.73-83
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• 2008

For spatial analysis and decision-making based on territorial and urban information, technologies on 3D GIS with digital image data and photo-realistic 3D image models to visualize 3D modeling are being rapidly developed. Currently, satellite images, aerial images and aerial LiDAR data are mostly used to build 3D models and textures from oblique aerial photographs or terrestrial photographs are used to create 3D image models. However, we are in need of quality 3D image models as current models cannot express topographic and features most elaborately and realistically. Thus, this study analyzed techniques to use aerial photographs, aerial LiDAR, terrestrial photographs and terrestrial LiDAR to create a 3D image model with artificial features and special topographic that emphasize spatial accuracy, delicate depiction and photo-realistic imaging. A 3D image model with spatial accuracy and photographic texture was built to be served via 3D image map services systems on the Internet. As it was necessary to consider intended use and display scale when building 3D image models, in this study, we applied the concept of LoD(Level of Detail) to define 3D image model of buildings in five levels and established the models by following the levels.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1803-1818
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• 2021

As the frequency of drought increases due to climate change, it is very important to have a monitoring system that can accurately determine the situation of widespread drought. However, while ground-based meteorological data has limitations in identifying all the complex droughts in Korea, satellite remote sensing data can be effectively used to identify the spatial characteristics of drought in a wide range of regions and to detect drought. This study attempted to analyze the possibility of using remote sensing data for drought identification in South Korea. In order to monitor various aspects of drought, remote sensing and ground observation data of precipitation and potential evapotranspiration, which are major variables affecting drought, were collected. The evaluation of the applicability of remote sensing data was conducted focusing on the comparison with the observation data. First, to evaluate the applicability and accuracy of remote sensing data, the correlations with observation data were analyzed, and drought indices of various aspects were calculated using precipitation and potential evapotranspiration for meteorological drought monitoring. Then, to evaluate the drought monitoring ability of remote sensing data, the drought reproducibility of the past was confirmed using the drought index. Finally, a high-resolution drought map using remote sensing data was prepared to evaluate the possibility of using remote sensing data for actual drought in South Korea. Through the application of remote sensing data, it was judged that it would be possible to identify and understand various drought conditions occurring in all regions of South Korea, including unmeasured watersheds in the future.

• Economic Analysis
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• v.27 no.2
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• pp.71-123
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• 2021

In this study, we present a methodology and model to estimate land prices and the value of land assets in North Korea in the absence of any data about land characteristics from North Korean authorities. Using this framework, we experimentally make market price-based estimates for land assets across the entire urban area of North Korea. First, we estimate the determinants of land prices in South Korea using data on market prices of land from the late 1970s, when it was estimated that the income level gap between South Korea and North Korea wasn't relatively large, and from the early 1980s, when urbanization levels in both of them were similar. Second, we calculate land prices and their relative ratios for each city and urban area in North Korea around 2015 by substituting proxy variables of determinants of land prices derived through a geographic information analysis of North Korea into the function of land prices that we have already estimated. Finally, we estimate the value of land assets in urban areas across North Korea by combining the ratio of housing transaction prices surveyed in several cities in North Korea with the relative prices estimated in this research. As a result, land prices in urban areas in North Korea, looking at the relative ratio of price by city, are estimated to be the highest, at 100.00, in Tongdaewon district of Pyongyang, and to be the lowest, at 1.70, in Phungso county, Ryanggang Province. Meanwhile, the value of land assets in urbanized areas was estimated at $21.6 billion in 2015, which was 1.2 to 1.3 times the GDP of North Korea that year. This ratio is similar to South Korea's in the 1978-1980 period, when the South Korean economy grew at an average rate of 6%. Considering North Korea's growth rate of about 1% in the 2013-2014 period, its ratio of land assets to GDP appears very high.

• 한국체육학회지인문사회과학편
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• v.55 no.6
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• pp.661-676
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• 2016

The purpose of this study is to draw a systematic access method of career intervention for dance majors. This study conducted Delphi survey and Analytic Hierarchy Process(AHP). As a result of study, 16 elements of career intervention were produced in total 4 areas. Results show that vocational guidance puts emphasis on the understanding of the various vocations, career education on the career planning and goal, career counseling on the macro-narrative to the life and career intervention network on the dance job fair and workshop. In the complex weight of all factors, ratings of weight show that dance vocation guidance and career education are demanded significantly. Results show that expansion of career alternatives, application of diversified dance career development road map to the curriculum, development of test tool and outcome standard, dance educators' systematic career intervention education and systematization of network for career support were suggested as measures for dance career intervention. This study discussed about dynamic reality and systematic access method for dance majors based on theories of Holland(1997), Super(1990), and Savickas(2005).

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.1
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• pp.75-88
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• 2024

It would be advantageous to predict acreage and yield of crops in major grain-exporting countries, which would improve decisions on policy making and grain trade in Korea. A climate suitability model can be used to assess crop acreage and yield in a region where the availability of observation data is limited for the use of process-based crop models. The objective of this study was to determine the climate suitability index of wheat by province in Ukraine, which would allow for the spatial assessment of acreage and yield for the given crop. In the present study, the official data of wheat acreage and yield were collected from the State Statistics Service of Ukraine. The EarthStat data, which is a data product derived from satellite data and official crop reports, were also gathered for the comparison with the map of climate suitability index. The Fuzzy Union model was used to create the climate suitability maps under the historical climate conditions for the period from 1970 to 2000. These maps were compared against actual acreage and yield by province. It was found that the EarthStat data for acreage and yield of wheat differed from the corresponding official data in several provinces. On the other hand, the climate suitability index obtained using the Fuzzy Union model explained the variation in acreage and yield at a reasonable degree. For example, the correlation coefficient between the climate suitability index and yield was 0.647. Our results suggested that the climate suitability index could be used to indicate the spatial distribution of acreage and yield within a region of interest.