• Journal of Navigation and Port Research
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• v.44 no.3
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• pp.219-226
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• 2020

The container terminal operators established a re-marshalling plan to reduce the loading operation time and the release operation time. Re-marshalling is to rearrange the containers in the container yard to the advantageous position to shorten the working time using the spare time of the automated yard crane. This study assumed the automated container terminal with a perpendicular layout and deals with the inter-bay re-marshalling planning problem in a yard block. The inter-bay re-marshalling plan determines the container to be moved, the location to be relocated, and the sequence of relocation operations. This study presents a mixed integer programming model that simultaneously determines the storage location and the operation sequence while satisfying the spatial availability during the re-marshalling. Numerical experiments are conducted to understand re-marshalling operation using a beam search method.

• Journal of Korean Society of Rural Planning
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• v.28 no.2
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• pp.87-96
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• 2022

As part of strengthening energy security and responding to climate change, the government has promoted various renewable energy measures to increase the development of renewable energy facilities. As a result, small-scale solar installations in rural areas have increased rapidly. The number of complaints from local residents is increasing. Therefore, in this study, deep learning technology is applied to high-resolution aerial images on the internet to detect solar power plants installed in rural areas to determine whether or not solar power plants are installed. Specifically, I examined the solar facility detector generated by training the YOLO(You Only Look Once) v2 object detector and looked at its usability. As a result, about 800 pieces of training data showed a high object detection rate of 93%. By constructing such an object detection model, it is expected that it can be utilized for land use monitoring in rural areas, and it can be utilized as a spatial data construction plan for rural areas using technology for detecting small-scale agricultural facilities.

• Journal of Korean Society of Rural Planning
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• v.30 no.1
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• pp.57-66
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• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.83-88
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• 2011

Rapid transition to aging society faces many problems. Also there are so many issues related people with disabilities. Disabled and elderly population growth is causing serious social problems. The purpose of this study is to solve the graying society-problem and improve old people's quality of life as well as the disabled's. The main goal of this study is the design of the master plan for ubiquitous-city by referring the 'Ubiquitous urban planning guidelines' of MLTM(Ministry of Land, Transport and Maritime Affairs). For research and development, there is divided by a spatial scope and content scope. As reference model-type, the spatial scope is to pursue maximum function by using minimum system organization and virtual city-set. The content scope consists of services for the disabled and aged, information management, construction management, compatible & connection and Executive Management. The result of this study will contribute to solve the social problems with aged and disabled and advance ubiquitous-environment by improving people's quality of life.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.4
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• pp.1-9
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• 2015

The development of drought index that provides detailed-spatial-resolution drought information is essential for improving drought planning and preparedness. The objective of this study was to develop the concept of using satellite-based hybrid drought index called the Vegetation Drought Response Index in South Korea (VegDRI-SKorea) that could improve spatial resolution for monitoring local and regional drought. The VegDRI-SKorea was developed using the Classification And Regression Trees (CART) algorithm based on remote sensing data such as Normalized Difference Vegetation Index (NDVI) from MODIS satellite images, climate drought indices such as Self Calibrating Palmer Drought Severity Index (SC-PDSI) and Standardized Precipitation Index (SPI), and the biophysical data such as land cover, eco region, and soil available water capacity. A case study has been done for the 2012 drought to evaluate the VegDRI-SKorea model for South Korea. The VegDRI-SKorea represented the drought areas from the end of May and to the severe drought at the end of June. Results show that the integration of satellite imageries and various associated data allows us to get improved both spatially and temporally drought information using a data mining technique and get better understanding of drought condition. In addition, VegDRI-SKorea is expected to contribute to monitor the current drought condition for evaluating local and regional drought risk assessment and assisting drought-related decision making.

• Spatial Information Research
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• v.23 no.1
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• pp.69-77
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• 2015

The aim of this study is to examine the research trends of global scientific production of Geospatial Information (GI) papers from 1998 to 2013 by using keyword network analysis. This study constructed keyword network model through papers and keywords related to GI research retrieved from the Web of Science DB and performed keyword network analysis such as Degree Centrality, Betweenness Centrality, and Closeness Centrality. The results show that GI has been steadily applied to various fields, and also the research trends of GI techniques could be quantitatively characterized through keyword network analysis. This study result can be applied to establish the policies and the national R&D planning of geospatial information.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.6
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• pp.2323-2326
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• 2015

It is urgently necessary to be aware of the distribution and risk areas of liver fluke, Opisthorchis viverrini, for proper allocation of prevention and control measures. This study aimed to investigate the human behavior, and environmental factors influencing the distribution in Surin Province of Thailand, and to build a model using stepwise multiple regression analysis with a geographic information system (GIS) on environment and climate data. The relationship between the human behavior, attitudes (<50%; $X_{111}$), environmental factors like population density ($148-169pop/km^2$; $X_{73}$), and land use as wetland ($X_{64}$), were correlated with the liver fluke disease distribution at 0.000, 0.034, and 0.006 levels, respectively. Multiple regression analysis, by equations OV= -0.599 + 0.005(population density ($148-169pop/km^2$); $X_{73}$) + 0.040 (human attitude (<50%); $X_{111}$) +0.022 (land used (wetland; X64), was used to predict the distribution of liver fluke. OV is the patients of liver fluke infection, R Square= 0.878, and, Adjust R Square= 0.849. By GIS analysis, we found Si Narong, Sangkha, Phanom Dong Rak, Mueang Surin, Non Narai, Samrong Thap, Chumphon Buri, and Rattanaburi to have the highest distributions in Surin province. In conclusion, the combination of GIS and statistical analysis can help simulate the spatial distribution and risk areas of liver fluke, and thus may be an important tool for future planning of prevention and control measures.

• Spatial Information Research
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• v.19 no.5
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• pp.47-52
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• 2011

Recently damage scale by local winds and typhoon has dramatically increased. Korea has the terrain over 70% of the land and the planning of the wind load is necessary to estimate reflecting appropriately the change of the wind-speed according to the characteristic of the terrain and in the Korean Building Code(2009), this is stated and it reflects to the design process. However, in order to estimate the topographic factor of the wind speed considering the topographic characteristics in the structure design actually, it has many difficult points including the local topographic survey, etc. In this paper, the Digital Elevation Model(DEM) is created using TIN interpolation method in the form of the digital map and then the interface was designed and implemented which can automatically estimate the topographic factor of wind speed by using ESRI(R)ArcObjectTM and the Visual Basic programing language. By applying it to the terrain which positioned in the downtown area, the practicality of the topographic factor of wind speed estimation interface was checked.

• Spatial Information Research
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• v.21 no.5
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• pp.7-14
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• 2013

Recently, BIM(Building Information Model) is widely applied to all stages of SOC (Social Overhead Capital)facilities life cycle from planning to maintenance. While BIM is an analysis tool focussing the inner space of facilities, GIS is principally applied to analyzing relationship between facilities. Therefore, integrating BIM and GIS, we expect to get a potential synergy effect in aspects of effective information management and various analysis for SOC facilities. This paper deals with prioritizing SOC facilities for applying BIM/GIS integrating platform to local governments. First, investigate facilities required by law, and identify SOC facilities suitable for SOC characteristics. Second, analyze the effectiveness and applicability of BIM/GIS integrating platform applying each facility. For the purpose, we quantify effectiveness and applicability in aspects of UIS management and GIS functions. Lastly, prioritize the SOC facilities applying BIM/GIS integrating platform.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.693-700
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• 2017

The mines in our country are complex in geography and shape and because of its small scale, accurate surveying performance and 3D modeling are necessary for mine development and management and mining plans. However, due to the data acquisition and processing technology and economy, the existing methods are currently used. The structure, mining, and mining area of the mine are recorded and managed based on the 2D drawings. As a result, it is true that there is risk of accidents caused by problems of accuracy as well as waste of personnel and time. In recent years, research data on geology and geospatial information on mines have been integrated into a database in foreign countries, and they are used for mine management and mining planning. In this study, we tried to construct spatial information for mining management and mining plan using laser scanner. Through research, spatial information about the mine was effectively obtained and produced data modeled through data processing. The 3D model for mining mines is expected to be a valuable tool for establishing and operating a safe mining plan for mines.