• Convergence Security Journal
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• v.18 no.1
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• pp.85-91
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• 2018

In this study, we design a marine environmental information service system with satellite images based on satellite images to reduce the damage caused by changes in the marine environment. The system provides satellite oceanographic information such as water temperature, chlorophyll, float, etc. as hierarchical texts, which is implemented as a unit module Web service so that it can be expanded in OpenAPI environment. And stability of system plug-in portability, service hours, data extraction precision and speed are used as a basis for diagnosing service stability. By securing the function and performance of the service system implemented in this study, it can be expanded to a complex technology that can customize the users by group by adding not only general services of existing systems operated by location but also information about a specific interested areas. Especially, various other items of interest including marine environment information are developed in modules, so we expect to be able to expand and service the system by plugging into the system and to spread it in technical linkage with the related institution information system.

• Korean journal of communication and information
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• v.36
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• pp.374-398
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• 2006

This paper attempts to identify motivations of the satellite DMB use and to examine the relationship between user motivations and structure of genre consumption. Firstly, this paper identified motivational dimensions for satellite DMB usage. The results of the factor analysis revealed three dimensions: information-seeking, entertainment-oriented and social communication. It accounts for 69.9% of the variances found within this data. Secondly, the results of the regression analyses suggested that both information seeking and entertainment-oriented motivations were closely related to genre preferences of satellite DMB contents. In addition, these two motivations predicted genre repertoires and similarity in genre consumption. In conclusion, motivations of the satellite DMB use were the best predictors for explaining the structure of genre consumption.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.151-157
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• 2019

In geostationary satellite communications, which are widely used for broadcasting and communication, there is a path loss where the signal power on the path is largely reduced. It is important to consider rain attenuation when calculating link budget because the Ka band frequency is vulnerable to rain attenuation. In this study, rainfall trends were analyzed by using rainfall data from the year 2000 in four regions of Korea (Seoul, Incheon, Busan, Jeju) and the rainfall attenuation was calculated. This was used to analyse the satellite link budget and receiving performance for the down-link of the korea satellite COMS. In this study, the calculated G/T for the rainfall intensity of 0.5% per year using the rainfall data for 18 years increased by approximately $8.5dBK^{-1}$ compared to the ITU's zone-K rain model, and decreased by approximately $1dBK^{-1}$ compared to the precipitation data for 13 years from the TTA(Korea Telecommunications Technology Association). The results of this study can be used for the design of G/T in domestic-installed satellite ground station.

• Journal of Korea Water Resources Association
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• v.47 no.4
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• pp.371-384
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• 2014

This study developed a new algorithm of extreme rainfall extraction based on the Communication, Ocean and Meteorological Satellite (COMS) and the Tropical Rainfall Measurement Mission (TRMM) Satellite image data and evaluated its applicability for the heavy rainfall event in July-2011 in Seoul, South Korea. The power-series-regression-based Z-R relationship was employed for taking into account for empirical relationships between TRMM/PR, TRMM/VIRS, COMS, and Automatic Weather System(AWS) at each elevation. The estimated Z-R relationship ($Z=303R^{0.72}$) agreed well with observation from AWS (correlation coefficient=0.57). The estimated 10-minute rainfall intensities from the COMS satellite using the Z-R relationship generated underestimated rainfall intensities. For a small rainfall event the Z-R relationship tended to overestimated rainfall intensities. However, the overall patterns of estimated rainfall were very comparable with the observed data. The correlation coefficients and the Root Mean Square Error (RMSE) of 10-minute rainfall series from COMS and AWS gave 0.517, and 3.146, respectively. In addition, the averaged error value of the spatial correlation matrix ranged from -0.530 to -0.228, indicating negative correlation. To reduce the error by extreme rainfall estimation using satellite datasets it is required to take into more extreme factors and improve the algorithm through further study. This study showed the potential utility of multi-geostationary satellite data for building up sub-daily rainfall and establishing the real-time flood alert system in ungauged watersheds.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.73-82
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• 2021

Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.80-89
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• 2008

Mapping applications using satellite imagery have been possible to quantitative analysis since SPOT satellite with stereo image was launched. Especially, high resolution satellite imagery was efficiently used in the field of digital mapping for the areas which are difficult to produce large-scale maps by aerial photogrammetry or carry out ground control point surveying due to unaccessibility. This study extracted the geospatial information out of consideration for topographic characteristic from ortho imagery of the National Geospatial-intelligence Agency(NGA) in the United States of America and analyzed the accuracy of plane coordinate for ortho imagery. For this purpose, the accuracy according to topographic character by comparison between both extraction data from ortho imagery and the digital topographic maps of 1:5000 scale which were produced by Korea National Geographic Information Institute(NGI) was evaluated. It is expected that the results of this study will be fully used as basic information for ground control point acquisition or digital mapping in unaccessible area.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.31-42
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• 2015

The objective of this study is to estimate the flood flow of inaccessible regions using satellite-derived rainfall and global geographic data. This study focuses on Dongsingun, an area located upstream of the Cheongcheon River in North Korea. The IFAS model was used to estimate flood flow. The model was calibrated in the Gap Stream watershed in South Korea and verified for the Byeongsung Stream watershed in the Nakdong River basin. Satellite-derived rainfalls for North Korea was revised using ground gauge data. Analysis results using CMORPH and GSMaP_NRT showed $4,886m^3/s$ and $5,718m^3/s$ respectively. In future studies, hydrological analysis in unmeasured and inaccessible regions will be carried out by applying more rainfall events.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.1
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• pp.107-117
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• 2011

This study aimed to inquire into possibilities of the web-based representation of thematic maps by geo-information mashup in the geoweb platform. In the Web2.0, Google platform leads the geoweb by offering effective mashup functions for geo-information. Geo-information mashup is opening a new horizon of map applications in fusion with a great of data in the Internet. Geo-information mashup by the available data method can be classified as two type; one is linkage of sources of platform itself(satellite images) and external data, the other is linkage of platform itself and user created contents. This study made heatmap, proportional map, and choropleth map based on Google satellite images by the linkage of platform itself and external data. As a result, thematic map of Google mashup expected to give us to a flexibility for difference interpretations of geographical distribution by representing overlap with satellite images.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.2
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• pp.11-23
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• 2000

The subjects of this study are to examine and to apply the methods of making 1 : 10,000 scale digital maps using Russian's 2 m resolution satellite images of Alternative and 8 m resolution stereo satellite images of MK-4 for the Kyoha area of Paju-city where aerial-photo surveying is not possible. A digital elevation model (DEM) was calculated from MK-4 images. With this DEM, the Alternative images were orthorectified. Ground control points (GCP) were acquired from GPS surveyings and were used to perform geometric corrections on Alternative images. From field investigation, thematic attributes are digitized on the monitor. RMS errors of the planar and vertical positions are estimated to ${\pm}0.4$ m and ${\pm}15$ m, respectively. The planar accuracy is better than an accuracy required by NGIS (national GIS) programs. Local information from field investigation was added and the resulting maps should be good as base maps for, such as, regional and urban plannings.

• Journal of Korea Water Resources Association
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• v.36 no.6
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• pp.999-1012
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• 2003

The objective of this study is to test the applicability of CN values suggested using land cover and treatment classification of satellite image. Applicability test is based on the comparison of observed effective rainfall and computed one. The 3 case study areas, where are the upstream of Gyeongan stage station, the upstream of Baekokpo stage station Pyungchang River basin, and the upstream of Koesan Dam, are selected to test the proposed CN values and the hydrologic and meteorologic data, Landsat-7 ETM of 2000, soil map of 1:50,000 are collected for the selected areas. The results show that the computed CN values for three study cases are 71, 63, 66, respectively, and the errors between observed and computed effective rainfall are within about 30%. It can be concluded that the proposed CN values from this study for land cover and treatment classification of satellite image not only provides more accurate results for the computation of effective rainfall, but also suggest the objective CN values and effective rainfall.