• Journal of Korean Society for Geospatial Information Science
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• v.7 no.2 s.14
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• pp.123-132
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• 1999

With the rapid increases of the amount of data and computing, the parallelization of the computing algorithm becomes necessary more than ever. However the parallelization had been conducted mostly in a super-computer until the rod 1990s, it was not for the general users due to the high price, the complexity of usage, and etc. A new concept for the parallel processing has been emerged in the form of K-clustering form the late 1990s, it becomes an excellent alternative for the applications need high computer power with a relative low cost although the installation and the usage are still difficult to the general users. The mapping algorithms (cut, join, resizing, warping, conversion from raster to vector and vice versa, etc) in GIS are well suited for the parallelization due to the characteristics of the data structure. If those algorithms are manipulated using PC-clustering, the result will be satisfiable in terms of cost and performance since they are processed in real flu with a low cos4 In this paper the tools and the libraries for the parallel processing and PC-clustering we introduced and how those tools and libraries are applied to mapping algorithms in GIS are showed. Parallel programs are developed for the mapping algorithms and the result of the experiments shows that the performance in most algorithms increases almost linearly according to the number of node.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.63-71
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• 2012

Recently, web portals have been offering georeferenced SLI(Street-Level Imagery) services, such as Google Streetview. The SLI has a distinctive strength over aerial images or vector maps because it gives us the same view as we see the real world on the street. Based on the characteristic, applicability of the SLI can be increased substantially through conflation with other spatial datasets. However, spatial inconsistency between different datasets is the main reason to decrease the quality of conflation when conflating them. Therefore, this research aims to remove the spatial inconsistency to conflate an SLI with a widely used 2D vector map. The removal of the spatial inconsistency is conducted through three sub-processes of (1) road intersection matching between the SLI trace and the road layer of the vector map for detecting CPPs(Control Point Pairs), (2) inaccurate CPPs filtering by analyzing the trend of the CPPs, and (3) local alignment using accurate CPPs. In addition, we propose an evaluation method suitable for conflation result including an SLI, and verify the effect of the removal of the spatial inconsistency.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.15-22
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• 2012

The variation in the wind speed with height above ground is called the wind shear profile. In the field of wind resource assessment, analysts typically use one of two mathematical relations to characterize the measured wind shear profile: the logarithmic profile (log law) and the power law profile (power law). The logarithmic law uses the surface roughness as a parameter, and the power law uses the power law exponent as a parameter. The shape of the wind shear profile typically depends on several factors, most notably the roughness of the surrounding terrain and the stability of the atmosphere. Since the atmospheric stability changes with season, time of day, and meteorological conditions, the surface roughness and the power law exponent also tends to change in time. For this study, Using the observed data from Met-mast, located in Pyeongdae, Handong in Jeju. we used the matlab and windograper to calculate roughness length and the law exponents. These calculations are similar to reference the data, but they have different ranges. In the ocean case, each reference data and calculated data was the same, but the crop area is higher than the earlier studies. In addition, the agricultural village is lower than the earlier studies.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.3-13
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• 2012

This study evaluated the feasibility of the location for PM-10 Monitoring Stations utilizing through GIS analysis. In addition, optimal sites were investigated to properly manage PM-10 which are closely related with public health. There are 11 PM-10 monitoring stations in Daegu area and the PM-10 data monitored at these stations are utilized to understand the overall status of PM-10 pollution. However, there are contrastive issues on the locations of current monitoring stations. Thus, this study prepared the map of PM-10 concentrations in Daegu area using IDW and Kriging techniques. Furthermore, average PM-10 concentrations were calculated using zonal statistical methods according to legal divisions and then, the current monitoring stations were evaluated whether their location is appropriate or not for PM-10 pollution distribution. It was found that, on the basis of yearly, seasonal and daily concentration analysis, the location of current PM-10 monitoring stations were not appropriate, particularly as they could not represent regional PM-10 pollution characteristics. In order to supplement this deficiency, seven sites(Namsandong, Namildong, Dongildong, Buksungro 1, Jongro 1, Hyangchondong and Haejeondong) commonly selected from each analytical step are suggested as additional PM-10 monitoring sites. It is further suggested that this kind of scientific evaluation for the location of PM-10 monitoring stations are needed in order to properly manage public heath in other cities as well as Daegu area.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.4
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• pp.59-64
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• 2008

We need to use the strength of each Species Distribution Model(SDM) because presence location data were only collected due to time and economic limitations in Korea. This study investigated and compared GAM(Generalized Additive Model) which is one of presence-absence models with Maxent(Maximum Entropy Model) which is one of presence only models according to location data(presence/absence data). The target species was Fisher(Martes pennanti) which is an endangered species in California, USA. We implemented environmental data such as topography, climate and vegetation, and applied models to sub-regions and study area. The results of this study were as follows. Firstly, GAM which used real presence and absence data was better than GAM which used pseudo-absence data and Maxent which used presence-only data. Secondly, Maxent was better than GAM when presence-only data were used. Lastly, each model which applied to different regions didn't predict other area well due to the difference of habitat environment and over-predicted outside of study area. We need to select an optimal model to predict a suitable habitat according to the type and distribution of location data.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.47-54
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• 2017

Recently, there are many studies related aerial mapping project and 3 dimensional shape and model reconstruction using UAV(unmanned aerial vehicle) system and images. In this study, we create 3D reconstruction point data using image matching technology of the UAV overlap images, detect shape change of structure and perform accuracy assessment of area($m^2$) and volume($m^3$) value. First, we build the test structure model data and capturing its images of shape change Before and After. Second, for post-processing the Before dataset is convert the form of raster format image to ensure the compare with all 3D point clouds of the After dataset. The result shows high accuracy in the shape change of more than 30 centimeters, but less is still it becomes difficult to apply because of image matching technology has its own limits. But proposed methodology seems very useful to detect illegal any structures and the quantitative analysis of the structure's a certain amount of damage and management.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.37-46
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• 2017

Recently, disaster caused by social factors is frequently occurring in Korea. Prediction about what crisis could happen is difficult, raising the citizen's concern. In this study, we developed a program to acquire tweet data by applying Python language based Tweepy plug-in, regarding social disasters such as 'Nonspecific motive crimes' and 'Oxy' products. These data were used to evaluate psychological trauma and anxiety of citizens through the text clustering analysis and the opinion mining analysis of the R Studio program after natural language processing. In the analysis of the 'Oxy' case, the accident of Sewol ferry, the continual sale of Oxy products of the Oxy had the highest similarity and 'Nonspecific motive crimes', the coping measures of the government against unexpected incidents such as the 'incident' of the screen door, the accident of Sewol ferry and 'Nonspecific motive crime' due to misogyny in Busan, had the highest similarity. In addition, the average index of the Citizens sentiment score in Nonspecific motive crimes was more negative than that in the Oxy case by 11.61%p. Therefore, it is expected that the findings will be utilized to predict the mental health of citizens to prevent future accidents.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.71-78
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• 2017

Many studies have been implemented to manage solar plant being supplied widely in recent years. This study analyzed heat emission of solar cell using unmanned aerial vehicle(UAV)-based thermal infrared sensor, and major conclusions are as belows. Firstly, orthomosaic image and digital surface model(DSM) data were acquired using UAV-based RGB sensor, and solar light module layer necessary to analyze the heat emission of solar cell was constructed by these data. Also as a result of horizontal error into validation points using virtual reference service(VRS) survey for evaluating the location accuracy of solar light module layer, higher location accuracy could be acquired like standard error of $dx={\pm}2.4cm$ and $dy={\pm}3.2cm$. And this study installed rubber patch to test the heat emission of solar cell and could analyzed efficiently the location of rubber patch being emitted heat using UAV-based thermal infrared sensor. Also standard error showd as ${\pm}3.5%$ in analysis between calculated cell ratio by rubber patch and analyzed cell ratio by UAV-based thermal infrared sensor. Therefore, it could be efficiently analyzed to heat emission of solar cell using UAV-based thermal infrared sensor. Also efficient maintenance of solar plant could be possible through extracting the code of solar light module being emitted of heat automatically.

• Journal of Korean Society for Geospatial Information Science
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• v.5 no.2 s.10
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• pp.131-144
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• 1997

Traffic jam densified day by day is phenomenon to occur lack of the road capacity in comparison with traffic density, but lack of the road cannot be concluded by main cause of traffic ism. Because the central function of a city would be concentrated upon the downtown and traffic demand would not be evenly distributed by the classification of an hour. Therefore, this study based on the fact that each driver will select the route generating traffic delay very low when path choice from origin to destination in travel plan estimating the quality of passage could be maintained the speed he want will approach to a characteristic grasp of a road, traffic, driver changing every moment by traffic-demand of road increased as a geometrical series with analysis a classification of a street, a intersection along the path on traffic density and highway capacity analysis the path using GIS techniques about complex street network, also will get the path of actual optimum for traffic delay trend creating under various condition the classification per a hour, a day of week and an incident through network such as analysis for traffic generation zone adjacent about street, intersection, afterward will expect the result increasing efficiency of the road-use through a good distribution of traffic by optimum-path choice, accordingly will prepare the scientific, objective, appropriate basis to decide the reasonable time of a road-widen and expansion through section analysis along a rate of traffic volume vs. road capacity.

• Journal of Korean Society for Geospatial Information Science
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• v.6 no.2 s.12
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• pp.69-79
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• 1998

It is one of the most crutial thing to secure efficient infrastructure of social infrastructure Including rna drinking water, sewer, gas, and electricity, etc. in modern society. Among them, the sourer system need to be properly maintained so as to sustain water quality over the large watershed thereby to provide reasonable level of living environment A few municipalities and private firms have so in been using sewer management system for assessing existing sewer network and auxiliary facilities. Such existing system can only provide functions to manage the sewer pipe itself and they can not fully estimate the amount of sewage water over the pipe through 4he network analysis due to the deficiency of the system Such a limited sewer network analysis function can only analyze the whole network under the assumption of uniformity. The results from such a process can not be fully implemented in the field. Therefore, this study emphasized the development of a sewer management system which can provide practical values from network analysts considering areal peculiarities using a zoning map utilizing a GIS. The system can support analyzing scenarios due to the changes of sewer amounts from the changes of population densities and rainfall amounts not to mention of calculating sewer amount for individual sewer pipes. furthermore, the system can support the decision making for better designing sewer facilities from the expansion of metropolitan areas and constructing satellite cities. Eventually, it will contribute to enhance the effectiveness of sewer-related works and services for residents as well as supporting a decision making for minor and major trouble-shootings.