• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.384-390
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• 2018

This paper introduces a MATLAB graphical user interface (GUI) based software for analysis of korea augmentation satellite system (KASS) availability performance. This software uses minimum variance (MV) estimator and Kriging algorithm to generate integrity information such as user differential range error (UDRE) and grid ionospheric vertical error (GIVE). The information is offered to ground and aviation users in Korean region. The software also gives accuracy data, protection level data and availability map about each user position by using the integrity information. In particular the software calculates the protection level along a path of aircraft. We verified the result of protection level of aviation user by comparing them with the results of SBASimulator#2, which is a simulation tool of european geostationary navigation overlay service (EGNOS). As a result, the protection level error between the result of our software and the SBASimulator#2 was about 2% which means that the result of our software is accurate.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.557-563
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• 2004

Korean cadastral system keeps graphical maps made by the plane table method from 1910's. The fact is that the graphical maps grafted on paper cover about 95% of the whole land (MOGAHA, 1999). The needs are arising to transform the graphical cadastre to a digital one in compliance with modem technologies. Korean government has already digitise the old maps until last year. A nation-wide land information system, Parcel-based Land Information System, was established upon the digitised map database. However, the accuracy of the digitised coordinates hardly meet the citizens' needs because it cannot exceed that of the paper maps. The definite solution will be surveying all the parcels again and making new digital maps. However, commencing a project for resurveying 34 million parcels will require enormous amount of time and manpower. The strategy should be dividing the country into county-wise or grid-wise pieces and surveying one piece by one piece. Municipal governments of counties, cities or urban districts will be the propelling bodies of the project but the costs will hardly be affordable at a time. For the purpose of resolving the financial problem, each municipality can split its own project into smaller pieces by year base. There is accordingly a great possibility to create inconsistency over the divided project areas caused by different techniques applied, different equipments used and/or mismatches between the project borders. It provides some merits at the same time. The people in project completion areas will be satisfied with the enhanced accuracy and feel safe in land transaction and, in turn, soundly improves overall nation-wide economic situation. Therefore, the main issue of the thesis shows how to make the cadastral re-survey project scalable. Guidelines for how to perform the projects will be derived from a experienced case.

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.110-117
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• 2023

Reconstructing underwater geometry in real time with forward-looking sonar is critical for applications such as localization, mapping, and path planning. Geometrical data must be repeatedly calculated and overwritten in real time because the reliability of the acoustic data is affected by various factors. Moreover, scattering of signal data during the coordinate conversion process may lead to geometrical errors, which lowers the accuracy of the information obtained by the sensor system. In this study, we propose a three-step data processing method with low computational cost for real-time operation. First, the number of data points to be interpolated is determined with respect to the distance between each point and the size of the data grid in a Cartesian coordinate system. Then, the data are processed with a nonlinear interpolation so that they exhibit linear properties in the coordinate system. Finally, the data are transformed based on variations in the position and orientation of the sonar over time. The results of an evaluation of our proposed approach in a simulation show that the nonlinear interpolation operation constructed a continuous underwater geometry dataset with low geometrical error.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.64-80
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• 2018

In Korea, citizens can only know general information about crime. Thus it is difficult to know how much they are exposed to crime. If the police can predict the crime risky area, it will be possible to cope with the crime efficiently even though insufficient police and enforcement resources. However, there is no prediction system in Korea and the related researches are very much poor. From these backgrounds, the final goal of this study is to develop an automated crime prediction system. However, for the first step, we build a big data set which consists of local real crime information and urban physical or non-physical data. Then, we developed a crime prediction model through machine learning method. Finally, we assumed several possible scenarios and calculated the probability of crime and visualized the results in a map so as to increase the people's understanding. Among the factors affecting the crime occurrence revealed in previous and case studies, data was processed in the form of a big data for machine learning: real crime information, weather information (temperature, rainfall, wind speed, humidity, sunshine, insolation, snowfall, cloud cover) and local information (average building coverage, average floor area ratio, average building height, number of buildings, average appraised land value, average area of residential building, average number of ground floor). Among the supervised machine learning algorithms, the decision tree model, the random forest model, and the SVM model, which are known to be powerful and accurate in various fields were utilized to construct crime prevention model. As a result, decision tree model with the lowest RMSE was selected as an optimal prediction model. Based on this model, several scenarios were set for theft and violence cases which are the most frequent in the case city J, and the probability of crime was estimated by $250{\times}250m$ grid. As a result, we could find that the high crime risky area is occurring in three patterns in case city J. The probability of crime was divided into three classes and visualized in map by $250{\times}250m$ grid. Finally, we could develop a crime prediction model using machine learning algorithm and visualized the crime risky areas in a map which can recalculate the model and visualize the result simultaneously as time and urban conditions change.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.2
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• pp.72-78
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• 2009

The demand for rainfall data in gridded digital formats has increased in recent years due to the close linkage between hydrological models and decision support systems using the geographic information system. One of the most widely used tools for digital rainfall mapping is the PRISM (parameter-elevation regressions on independent slopes model) which uses point data (rain gauge stations), a digital elevation model (DEM), and other spatial datasets to generate repeatable estimates of monthly and annual precipitation. In the PRISM, rain gauge stations are assigned with weights that account for other climatically important factors besides elevation, and aspects and the topographic exposure are simulated by dividing the terrain into topographic facets. The size of facet or grid cell resolution is determined by the density of rain gauge stations and a $5{\times}5km$ grid cell is considered as the lowest limit under the situation in Korea. The PRISM algorithms using a 270m DEM for South Korea were implemented in a script language environment (Python) and relevant weights for each 270m grid cell were derived from the monthly data from 432 official rain gauge stations. Weighted monthly precipitation data from at least 5 nearby stations for each grid cell were regressed to the elevation and the selected linear regression equations with the 270m DEM were used to generate a digital precipitation map of South Korea at 270m resolution. Among 1.25 million grid cells, precipitation estimates at 166 cells, where the measurements were made by the Korea Water Corporation rain gauge network, were extracted and the monthly estimation errors were evaluated. An average of 10% reduction in the root mean square error (RMSE) was found for any months with more than 100mm monthly precipitation compared to the RMSE associated with the original 5km PRISM estimates. This modified PRISM may be used for rainfall mapping in rainy season (May to September) at much higher spatial resolution than the original PRISM without losing the data accuracy.

• Journal of Ocean Engineering and Technology
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• v.23 no.5
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• pp.25-31
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• 2009

The most important component of wind turbine is rotor blades. The developing method of wind turbine was focused on design of rotor blade. By the way, the design of a rotating body is more decisive process in order to adjust the performance of wind turbine. For instance, the design allows the designer to specify the wind characteristics derived by topographical map. The iterative solver is then used to adjust one of the selected inputs so that the desired rotating performance which is directly related to power generating capacity and efficiency is achieved. Furthermore, in order to save the money for manufacturing the rotor blades and to decrease the maintenance fee of wind power generation plant, while decelerating the cut-in speed of rotor. Therefore, the design and manufacturing of rotating body is understood as a substantial technology of wind power generation plant development. The aiming of this study is building-up the profitable approach to designing of rotating body as a system for the wind power generation plant. The process was conducted in two steps. Firstly, general designing and it’s serial testing of rotating body for voltage measurement. Secondly, the serial test results above were examined with the CFD code. Then, the analysis is made on the basis of amount of electricity generated by rotor-blades and of cut-in speed of generator.

• Proceedings of the Korea Contents Association Conference
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• 2010.05a
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• pp.277-280
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• 2010

The prevention of disasters is important to prepare in advance through analysis and an estimate. But for all the efforts of the government to stave off disasters, the damage out of a guerilla localized heavy rain caused the global warming, a landslide and inundation is growing. To prevent these damages, the basic data and system through systematic research and analysis should be set up. But it is true that collecting of the basic data and the system for preventing disasters are either constructing or insufficient so far. In this research, by using topography spatial data including LiDAR data including the aerial photo and digital maps, and etc. the factor of a disaster, the disaster risk element was extracted. Moreover, the disaster region about the disaster generation available region was evaluated in advance using the easy disaster analysis of current situation photo map which made with the grid analysis method and weighted value estimate technique.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.149-157
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• 2009

Tracking technologies which provide real-time and customized information through various information collecting and processing for pedestrians who use traffic connective and transferring center have been being examined. However some problems are caused due to the wide-range positioning error for some services as device installation and service place. It is also difficult to be applied to traffic linkage and transfer services because many situations can be barren. In the testbed, Gwangmyoung Station, we got some results in bad conditions such as a lot of steel construction and another communication device. Practically, conditions of the place which will be built can be worse than Gwangmyoung station. Therefore, we researched suitable Location correction algorithm as a method for accuracy to traffic connective and transferring system. And its algorithm is designed through grid coordinates, map-matching, modeling coordinates and Kalman filtering and is being implemented continuously. Also preparing for optimization of various transferring center model, we designed for simulator type algorithm what is available for deciding algorithm factor.

• Journal of the Korean Institute of Landscape Architecture
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• v.13 no.1
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• pp.43-66
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• 1985

Korea needs proper and rational public policies on conservation and use of forest land and other natural resources because of the accelerating expansion of national land developments in recent years. Unfortunately, there is no systematic planning system to support the needs. Generally, forest land use planning needs suitability analysis based on efficient land classification system. The goal of this study was to classify a forest land using multivariate satistical methods. A case study was carried out in winter of 1983 on a mountainous area higher than 100m above sea level located at Mt. Kwanak in Anyang -city, Kyung-gi-do (province). The study area was 19.80 km$^2$wide and was divided into 1, 383 Operational Taxonomic Units (OTU's) by a 120m$\times$120m grid. Fourteen descriptors were identified and quantified for each OTU from existing national land data : elevation, slope, aspect, terrain form, geologic material, surface soil permeability, topsoil type, depth of the solum, soil acidity, forest cover type, stand size class, stand age class, stand density class, and simple forest soil capability class. For this study, a FORTRAN IV program was written for input and output map data, and the computer statistics packages, SPSS and BMD, were used to perform the multivariate statistical analysis. Fourteen variables were analyzed to investigate the characteristics of their fire quench distribution and to estimate the correlation coefficients among them. Principal component analysis was executed to find the dimensions of forest land characteristics, and factor scores were used for proper samples of OTU throughout the study area. In order to develop the classes of forest land classification based on 102 surrogates, cluster and discriminant analyses of principal descriptor variable matrix were undertaken. Results obtained through a series of multivariate statistical analyses were as follows ; 1) Principal component analysis was proved to be a useful tool for data selection and identification of principal descriptor variables which represented the characteristics of forest land and facilitated the selection of samples.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.3
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• pp.171-177
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• 2013

The purpose of this study is to find a scheme to scale down the KMA (Korea Meteorological Administration) digital precipitation maps to the grid cell resolution comparable to the rural landscape scale in Korea. As a result, we suggest two steps procedure called RATER (Radar Assisted Topography and Elevation Revision) based on both radar echo data and a mountain precipitation model. In this scheme, the radar reflection intensity at the constant altitude of 1.5 km is applied first to the KMA local analysis and prediction system (KLAPS) 5 km grid cell to obtain 1 km resolution. For the second step the elevation and topography effect on the basis of 270 m digital elevation model (DEM) which represented by the Parameter-elevation Regressions on Independent Slopes Model (PRISM) is applied to the 1 km resolution data to produce the 270 m precipitation map. An experimental watershed with about $50km^2$ catchment area was selected for evaluating this scheme and automated rain gauges were deployed to 13 locations with the various elevations and slope aspects. 19 cases with 1 mm or more precipitation per day were collected from January to May in 2013 and the corresponding KLAPS daily precipitation data were treated with the second step procedure. For the first step, the 24-hour integrated radar echo data were applied to the KLAPS daily precipitation to produce the 1 km resolution data across the watershed. Estimated precipitation at each 1 km grid cell was then regarded as the real world precipitation observed at the center location of the grid cell in order to derive the elevation regressions in the PRISM step. We produced the digital precipitation maps for all the 19 cases by using RATER and extracted the grid cell values corresponding to 13 points from the maps to compare with the observed data. For the cases of 10 mm or more observed precipitation, significant improvement was found in the estimated precipitation at all 13 sites with RATER, compared with the untreated KLAPS 5 km data. Especially, reduction in RMSE was 35% on 30 mm or more observed precipitation.