• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.2
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• pp.101-108
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• 2011

Climate change could have a pronounced impact on natural and agricultural ecosystems. To assess the impact of climate change, projected climate data have been used as inputs to models. Because such studies are conducted occasionally, it would be useful to employ Cloud computing, which provides multiple instances of operating systems in a virtual environment to do processing on demand without building or maintaining physical computing resources. Furthermore, it would be advantageous to use open source geospatial applications in order to avoid the limitations of proprietary software when Cloud computing is used. As a pilot study, Amazon Web Service ? Elastic Compute Cloud (EC2) was used to calculate the number of days with rain in a given month. Daily sets of climate projection data, which were about 70 gigabytes in total, were processed using virtual machines with a customized database transaction application. The application was linked against open source libraries for the climate data and database access. In this approach, it took about 32 hours to process 17 billion rows of record in order to calculate the rain day on a global scale over the next 100 years using ten clients and one server instances. Here I demonstrate that Cloud computing could provide the high level of performance for impact assessment studies of climate change that require considerable amount of data.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.4 s.27
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• pp.35-43
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• 2003

Currently, the government has been driving numerous projects to build the e-government which can enable limitless access and utilization of the information through the accomplishment of the real time based various administrative services. In water resource field, a project to generate digital river thematic maps has been undergoing as a part of the computerization projects. As a partial results, the RIMGIS project has been completed and generation of the various river thematic maps has been required to fully utilize the DB built from RIMGIS project. For the effective generation of the thematic maps, a data model needs to be developed. A data model has been developed in this study to provide more efficient method to generate the thematic maps utilizing existing DB. The data model proposed from this study has defined the relationships between core feature data and framework Data along with relationships among data elements to represent the rivers in the real world more accurately. The core feature data and framework layers have been defined based on the survey of the domestic and foreign case studies along with requirement analysis of the users in the water resource field. The proposed core feature data has been defined based on the minimum unit of 'class', and the relationship between classes has been established based on the ArcGIS Hydro Data Model for the integrated processing of the river information. The proposed spatial data model can be judged to contribute establishing more efficient generation methodology of the river thematic maps.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.1 s.28
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• pp.11-20
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• 2004

The purpose of this paper is to evaluate the applicability of GPS data for real-time traffic information collection especially after SA removal. Two major results have been reported. One is the GPS data availability and/or useful data point density for travel time estimation using Circle-X algorithm. 87.23% of data points can be mobilized after SA whereas only 29.94% of data was useful in calculating travel time. The other is the possible reduction of the buffer size that is used for screening the points of all GPS into useful and useless data, respectively. With these outcomes, it is safely expected that the regular GPS alone can provide the data points for real-time travel time estimation instead of the more expensive DGPS system.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.1 s.28
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• pp.69-77
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• 2004

Since there are a lot of changes in climate on domestic and natural disasters owing to the disturbance-development of the land, damages of properties and human life frequently occur due to the coastal floodings. Accordingly, it is necessary to find the area where the danger of flooding coasts is relatively high and to inform resident the characteristics of the area As a part of preventive land management to minimize the flooding damages of the coastal area, this study suggested the generation of the coastal flood hazard map that provides detailed information such as refuge path, a place of refuge, and the location of medical supplies, food, and main rescue equipment, etc. This study selected the southern region of Daebu-do as an exemplary area, conducted a document study to establish GIS data, secured pre-structured data, and suggested the method of establishing GIS data fit to the study area. In particular, it emphasized the efficient construction of the geographical spatial data that were accurate, economic, objective, and realistic in supporting the modeling to predict the flooding zone. The specific type of established database was divided into flooding risk area, flooding warning area, and flooding-volume area. The prototype of coastal flood hazard map can be widely used for efficient disaster management. Furthermore, it is considered that the map could be applied for arousing residents' attentions to the flooding, prior education, and local governments' management actions against the danger of flooding.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.4 s.27
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• pp.21-27
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• 2003

The rational polynomial coefficients(RPC) model is a generalized sensor model that is used as an alternative for the physical sensor model for IKONOS-2 and QuickBird. As the number of sensors increases along with greater complexity, and as the need for standard sensor model has become important, the applicability of the RPC model is also increasing. The RPC model can be substituted for all sensor models, such as the projective camera the linear pushbroom sensor and the SAR This paper is aimed at generating a RPC model from the physical sensor model of the KOMPSAT-1(Korean Multi-Purpose Satellite) and aerial photography. The KOMPSAT-1 collects $510{\sim}730nm$ panchromatic images with a ground sample distance (GSD) of 6.6m and a swath width of 17 km by pushbroom scanning. We generated the RPC from a physical sensor model of KOMPSAT-1 and aerial photography. The iterative least square solution based on Levenberg-Marquardt algorithm is used to estimate the RPC. In addition, data normalization and regularization are applied to improve the accuracy and minimize noise. And the accuracy of the test was evaluated based on the 2-D image coordinates. From this test, we were able to find that the RPC model is suitable for both KOMPSAT-1 and aerial photography.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.99-107
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• 2016

Korea has been known as volcanic disaster free area. However, recent surveying result shows that Baekdu mountain located in northernmost in the Korean peninsula is not a dormant volcano anymore. When Baekdu mountain is erupting, various damages due to the volcanic ash are expected in South Korea area. Especially, volcanic ash in the air may cause big aviation accident because it can hurt engine or gauges in the airplane. Therefore, it is a crucial issue to interrupt airplane navigation, whose route is overlapped with volcanic ash, after predicting three dimensional dispersion of volcanic ash. In this paper, we deals with 3D visualization techniques for volcanic ash dispersion prediction results. First, we introduce the data acquisition of the volcanic ash dispersion prediction. Dispersion prediction data is obtained from Fall3D model, which is volcanic ash dispersion simulation program. Next, three 3D visualization techniques for volcanic ash dispersion prediction are proposed. Firstly proposed technique is so called 'Cube in the Air', which locates the semitransparent cubes having different color depends on its particle concentration. Second technique is a 'Cube in the Cube' which divide the cube in proportion to particle concentration and locates the small cubes. Last technique is 'Semitransparent Volcanic Ash Plane', which laminates the layer, whose grids present the particle concentration, and apply the semitransparent effect. Based on the proposed techniques, the user could 3D visualize the volcanic ash dispersion prediction results upon his own purposes.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.89-98
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• 2016

In this paper, we proposed an automated areal feature matching method based on geometric similarity without user intervention and is applied into areal features of many-to-many relation, for confusion of spatial data-sets of different scale and updating cycle. Firstly, areal feature(node) that a value of inclusion function is more than 0.4 was connected as an edge in adjacency matrix and candidate corresponding areal features included many-to-many relation was identified by multiplication of adjacency matrix. For geometrical matching, these multiple candidates corresponding areal features were transformed into an aggregated polygon as a convex hull generated by a curve-fitting algorithm. Secondly, we defined matching criteria to measure geometrical quality, and these criteria were changed into normalized values, similarity, by similarity function. Next, shape similarity is defined as a weighted linear combination of these similarities and weights which are calculated by Criteria Importance Through Intercriteria Correlation(CRITIC) method. Finally, in training data, we identified Equal Error Rate(EER) which is trade-off value in a plot of precision versus recall for all threshold values(PR curve) as a threshold and decided if these candidate pairs are corresponding pairs or not. To the result of applying the proposed method in a digital topographic map and a base map of address system(KAIS), we confirmed that some many-to-many areal features were mis-detected in visual evaluation and precision, recall and F-Measure was highly 0.951, 0.906, 0.928, respectively in statistical evaluation. These means that accuracy of the automated matching between different spatial data-sets by the proposed method is highly. However, we should do a research on an inclusion function and a detail matching criterion to exactly quantify many-to-many areal features in future.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.81-87
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• 2016

It is important to analyze the exact damage information for fast recovery when natural disasters cause damage on river-side facilities such as dams, bridges, embankments etc. In this study, we shows the method to effectively damage analysis plan using UAV(Unmanned aerial vehicle) images and accuracy assessment of it. The UAV images are captured on area near the river-side facilities and the core methodology for damage analysis are image matching and change detection algorithm. The result(point cloud) from image matching is to construct 3-dimensional data using by 2-dimensional images, it extracts damage areas by comparing the height values on same area with reference data. The results are tested absolute locational precision compared by post-processed aerial LiDAR data named reference data. The assessment analysis test shows our matching results 10-20 centimeter level precision if external orientation parameters are very accurate. This study shows suggested method is very useful for damage analysis in a large size structure like river-side facilities. But the complexity building can't apply this method, it need to the other method for damage analysis.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.61-68
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• 2016

Digital aerial images have been commonly used in a large scale map production owing to their excellent geometry, and high spatial and radiometric resolution in recent years. However, a quality verification process for acquired images should be preceded in order to secure the high precision and reliability of produced results. Several experimental studies to verify digital imaging systems have been vigorously researched by constructing permanent test field in abroad. On the other hand, it is urgently necessary to suggest a practical scheme for an image quality verification, because this related study and experiment are still in its early stage at home. Hence, this study aims to present an easy method to measure the spatial resolution of the image in a visual way using a portable Siemens star. The images used in the study were obtained with three different cameras, two frame array sensors of DMC, UltraCamXp and a linear array sensor of ADS80. The Siemens star target appeared in every image is extracted and then the spatial resolution of image is compared with theoretical GSD(Ground Sample Distance) by a visual method. In addition, the change of spatial resolution depending on the location of the Siemens star from image center and flight direction and cross-flight direction is also compared and analyzed. As study results, while the theoretical GSDs of images taken with each camera are about 6~9cm, the visual resolutions are 1.2~1.3 times as great as the theoretical ones.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.51-59
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• 2016

Global consumption of fossil fuels continues to increase. As developing countries use fossil fuel as much as the existing fossil fuel using countries, the total amount of fossil fuel consumed has risen. The finite fossil energy depletion insecurity have become serious. In addition, fossil energy is caused by environmental pollution, economic and social problems remain in assignments that need to be addressed. Although solar power is clean and has many benefits, there are several problems in the process of installing a solar power plant. To solve these problems, floating photovoltaic plants has emerged as an alternative. This floating photovoltaic plants location analysis has not been made yet. In this study, the conditions of the floating photovoltaic plants location is analyzed with the Analytic Hierarchy Process using the terrain and climate factors. The score is assigned to the attribute information of each factor by the classification table. After multiplied by the weight the result is analyzed by visualization of the score. As the result, the score of the northen part of Gyeongsangbuk-do province is higher than the southern part of Gyeongsangbuk-do province. Especially Andongho lake in Andong City and the reservoir in Yeongyang-Gun are extracted as the optimal location. The score of the river boundary is low not the center of the river stream. It is expected that this study would be a more accurate floating solar power plant location analysis.