• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.77-84
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• 2022

In this paper, we propose a system for monitoring air pollutants such as fine dust using an unmanned aerial vehicle capable of autonomous navigation. The existing air quality management system used a method of collecting information through a fixed sensor box or through a measurement sensor of a drone using a control device. This has disadvantages in that additional procedures for data collection and transmission must be performed in a limited space and for monitoring. In this paper, to overcome this problem, a GPS module for location information and a PMS7003 module for fine dust measurement are embedded in an unmanned aerial vehicle capable of autonomous navigation through flight information designation, and the collected information is stored in the SD module, and after the flight is completed, press the transmit button. It configures a system of one-stop structure that is stored in a remote database through a smartphone app connected via Bluetooth. In addition, an HTML5-based web monitoring page for real-time monitoring is configured and provided to interested users. The results of this study can be utilized in an environmental monitoring system through an unmanned aerial vehicle, and in the future, various pollutants measuring sensors such as sulfur dioxide and carbon dioxide will be added to develop it into a total environmental control system.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.325-340
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• 2022

Amid the unprecedented situation of COVID-19 around the world, online education has established itself as an essential element in the era of zero contact and the importance of various content and changes of the system that are appropriate for the era of the 4^th industrial revolution has increased. Although universities are making their efforts to combine ICT technologies and design and achieve new systems, the recognition and atmosphere for establishing the cloud computing system are falling short. The purpose of this research importance of success factors of "Building a cloud computing system of cyber university in Korea" by classifying the work characteristics and scale, and to derive and analyze the importance cloud rankings considering the organization and individual dimension. Therefore, this study has drawn 14 major factors in the previous researches and models through the survey on experts with knowledge related to the cloud computing. The analysis was conducted to see what differences there are in factors for the successful establishment of the cloud computing system using AHP. It is expected that the factors for success presented through this study would be used as systemic strategies and tools for the purpose of drawing factors for the success of establishing the private cloud computing system for the higher education institutions and public information systems.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.2
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• pp.23-33
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• 2009

Satellite image is very usefully practiced to predict and analyze physical expansion and change of city. Physical expansion and change of city is closely related to the use of land, and continuous growth management focused on the use of land is essential for sustainable city growth. In this research, the change of land cover and land-use were analyzed with basic input data from 1985 to 2000 according to artificial satellite. Moreover, the land-use turnover rate was understood and expansion trend of urban sprawl in Busan metropolitan city and land-use characteristics of the expansion area. The results are, first, the area for urban region was expanded continuously but areas for agriculture area, forest area, and water area had different changes due to administrative district reform of Busan by each year. Second, the urbanization area in Busan was increased by 3.8% from $92.5km^2$ in 1985 to $167.5km^2$ in 2000. Third, the result of analysis on land-use turnover rate showed that agriculture area was turned into urbanized area the most, and forest area was followed by. Fourth, the result of analysis on database and overlay of buildings in Busan established in 2001 showed that agriculture area are had type 1 and 2 neighborhood living facilities (45.63%), apartment house in forest area (18.49%), and factory in water area (31.84%) with high ratio.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.159-169
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• 2012

The purpose of this study was to assess the vulnerability of forest ecosystem to climate change in South Korea using socio-environmental indicators and the results of two vegetation models named as Hydrological and Thermal Analogy Group(HyTAG), and MAPSS-Century 1(MC1). The changing frequency and direction of biome types estimated by HyTAG model was used for quantifying sensitivity and adaptive capacity of forest distribution. Similarly, the variation and changing tendency of net primary production and soil carbon storage estimated by MC1 model was used for quantifying sensitivity and adaptive capacity of forest function. As socio-environmental indicators, many statistical data such as financial autonomy rate and the number of forestry officer was prepared. All indicators were standardized, and then calculated using the vulnerability assessment equation. The period of vulnerability assessment was divided into the past(1971-2000) and the future(2021-2050). To understand what policy has a priority to climate change, distribution maps of each indicators was depicted and the vulnerability results were compared among administrative districts. Evident differences could be found in entire study area. These differences were mostly derived from regionalspecific adaptive capacity. The result and methodology of this study would be helpful for the development of decision-making supporting system and policy making in forest management with respect to climate change.

• Journal of Korean Society of Forest Science
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• v.88 no.2
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• pp.157-168
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• 1999

This paper analyzed vegetation and land use classification, slope and permanent preservation and legal reserves on the farm Jangada and Jamaica-Mato Grosso do Sul, Brazil, using satellite image for assisting the planning of planting Eucalyptus spp. This part of the State of Mato Grosso do Sul represents an important geopolitcal area, since it is located on the borders of Bolivia and Paraguay. Also exportation of goods can be achieved through hydrovias extending to Buenos Aires, Argentina-through the Paraguay River. Also there are road and railroad connection which link the soutreastern part of Brazil to the Andean countries. The vegetation map from sheet SF 21-Campo Grande of the RADAMBRASIL Project was used as the basis for the preliminary interpretation of coverage, and complemented by a visit of the field. After the initial interpretation of the image, definition of classes of use and land occupation were made, and files of spectral signatures were created. On the farms Jamaica and Jangada Open Arboreal Savanna and Grass Savanna are the predominant physiognomies occupying 68% of total area. In spite of the results being satisfactory at the present moment, the development of this project should be revised and adjusted based on the evaluations already made, including a greater detailing of environmental components, principally with respect to soil and topography.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.120-134
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• 2000

In this paper we present a Distributed Object oriented Virtual computing Environment, called DOVE which consists of autonomous distributed objects interacting with one another via method invocations based on a distributed object model. DOVE appears to a user logically as a single virtual computer for a set of heterogeneous hosts connected by a network as if objects in remote site reside in one virtual computer. By supporting efficient parallelism, heterogeneity, group communication, single global name service and fault-tolerance, it provides a transparent and easy-to-use programming environment for parallel applications. Efficient parallelism is supported by diverse remote method invocation, multiple method invocation for object group, multi-threaded architecture and synchronization schemes. Heterogeneity is achieved by automatic data arshalling and unmarshalling, and an easy-to-use and transparent programming environment is provided by stub and skeleton objects generated by DOVE IDL compiler, object life control and naming service of object manager. Autonomy of distributed objects, multi-layered architecture and decentralized approaches in hierarchical naming service and object management make DOVE more extensible and scalable. Also,fault tolerance is provided by fault detection in object using a timeout mechanism, and fault notification using asynchronous exception handling methods

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.879-888
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• 2017

This study is a preliminary research conducted in Buhansan mountain National Park to develop a management system to predict and control oak wilt disease by indicating spatial factors which affect diffusion of the disease. After analysing altitude factor during the estimation of spatial analysis of damaged area, it is indicated that damaged trees are mainly distributed at altitude of 200-500 m and number decreased drastically over the altitude of 500 m. The result showed that 92% of total damaged trees are on slope between 20~40 degrees and the number decreased drastically on slope steeper than 40 degrees. It is indicated that damaged area is mainly distributed on southern aspect. It is estimated by using CART that slope factor affected the diffusion of disease mostly but aspect factor did not. Surface temperature and altitude showed similar effect.By simulating possible diffusion scenario, it is estimated that the disease could spread to DO-BONG Mt., northeast of Bukhansan mountain.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.461-471
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• 2015

In this study, we generated orthoimages and Digital Elevation Model (DEM) from Unmanned Aerial Vehicle (UAV) to confirm the accuracy of possibility of geospatial information system generation, then compared the DEM with the topographic height values measured from Real Time Kinematic-GPS (RTK-GPS). The DEMs were generated from aerial triangulation method using fixed-wing UAV and rotary-wing UAV, and DEM based on the waterline method also generated. For the accurate generation of mosaic images and DEM, the distorted images occurred by interior and exterior orientation were corrected using camera calibration. In addition, we set up the 30 Ground Control Points (GPCs) in order to correct of the UAVs position error. Therefore, the mosaic images and DEM were obtained with geometric error less than 30 cm. The height of generated DEMs by UAVs were compared with the levelled elevation by RTK-GPS. The value of R-square is closely 1. From this study, we could confirm that accurate DEM of the tidal flat can be generated using UAVs and these detailed spatial information about tidal flat will be widely used for tidal flat management.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.351-375
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• 2018

This paper aims to i) introduce the characteristics of HF ocean radar and the major results and information produced by the radar networks in the Korean coasts to the readers, ii) make an up-to-date inventory of the existing radar systems, and iii) share the information related to the radar operating skill and the ocean current data application. The number of ocean radars has been showing a significant growth over the past 20 years, currently deploying more than 44 radars in the Korean coasts. Most of radars are in operation at the present time for the purposes related to the marine safety, tidal current forecast and understanding of ocean current dynamics, mainly depending on the mission of each organization operating radar network. We hope this overview paper may help expand the applicability of the ocean radar to fisheries, leisure activity on the sea, ocean resource management, oil spill response, coastal environment restoration, search and rescue, and vessel detection etc., beyond the level of understanding of tidal and ocean current dynamics. Additionally we hope this paper contributes further to the surveillance activity on our ocean territory by founding a national ocean radar network frame and to the domestic development of ocean radar system including signal processing technology.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1881-1890
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• 2021

Particulate matter (PM) affects the human, ecosystems, and weather. Motorized vehicles and combustion generate fine particulate matter (PM_2.5), which can contain toxic substances and, therefore, requires systematic management. Consequently, it is important to monitor and predict PM_2.5 concentrations, especially in large cities with dense populations and infrastructures. This study aimed to predict PM_2.5 concentrations in large cities using meteorological and chemical variables as well as satellite-based aerosol optical depth. For PM_2.5 concentrations prediction, a random forest (RF) model showing excellent performance in PM concentrations prediction among machine learning models was selected. Based on the performance indicators R², RMSE, MAE, and MAPE with training accuracies of 0.97, 3.09, 2.18, and 13.31 and testing accuracies of 0.82, 6.03, 4.36, and 25.79 for R², RMSE, MAE, and MAPE, respectively. The variables used in this study showed high correlation to PM_2.5 concentrations. Therefore, we conclude that these variables can be used in a random forest model to generate reliable PM_2.5 concentrations predictions, which can then be used to assess the vulnerability of schools to PM_2.5.