• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.75-82
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• 2011

In this study, author analyzed the overview and the convergence time of Fixed solutions (<15cm) of OmniSTAR, one of SBAS(Satellite Based Augmentation System) as WADGPS (Wide Area Differential GPS), which can compensate the drawbacks of the existed GNSS (Global Navigation Satellite System) that require the expensive receiver and is impossible to position in case of the radio interference in urban sometimes. As a result, the test shows that the less than 15cm 3D standard deviation converges in 39 minutes at Dynamic mode and 28 minutes at Static mode. It is expected that we can apply OmniSTAR to a variety of fields such as LBS(Location Based Service), mobile positioning, and the geo-spatial information industry that does not necessarily guarantee the high position accuracy.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.3
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• pp.483-497
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• 2023

This study aims to provide strategic recommendations for promoting the development of the global satellite data services industry by analyzing the startup landscape. Based on the analysis of startup data, such as number of startups, market segment, and funding amount, we examined the paradigm shift in the global satellite data services market, particularly its convergence with other market segments. To this end, we derived the cumulative funding-convergence dynamics matrix, which classifies the converging areas into four quadrants by considering the growth rate of converging segments and the cumulative funding amount. In this way, we can specify converging areas in the satellite data services market that bear potential importance for the creation of new markets. The findings of this study are expected to contribute to the advancement of the satellite data services industry and facilitate the exploration of new market opportunities. Furthermore, they can serve as a valuable reference for policy makers, industry stakeholders, government officials, and researchers involved in the satellite data services industry in capitalizing on the emerging space economy.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.945-957
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• 2019

In this study, we propose a coarse to fine image registration method for eliminating geometric error between images over agricultural areas acquired using Unmanned Aerial Vehicle (UAV). First, images of agricultural area were acquired using UAV, and then orthophotos were generated. In order to reduce the probability of extracting outliers that cause errors during image registration, the region of interest is selected by using the metadata of the generated orthophotos to minimize the search area. The coarse image registration was performed based on the extracted tie-points using the Speeded-Up Robust Features (SURF) method to eliminate geometric error between orthophotos. Subsequently, the fine image registration was performed using tie-points extracted through the Mutual Information (MI) method, which can extract the tie-points effectively even if there is no outstanding spatial properties or structure in the image. To verify the effectiveness and superiority of the proposed method, a comparison analysis using 8 orthophotos was performed with the results of image registration using the SURF method and the MI method individually. As a result, we confirmed that the proposed method can effectively eliminated the geometric errors between the orthophotos.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.5
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• pp.785-792
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• 2023

Because hyperspectral imaging provides detailed spectral information across a broad range of wavelengths, it can be utilized in numerous applications, including environmental monitoring, food quality inspection, medical diagnosis, material identification, art authentication, and crime scene analysis. However, hyperspectral images often contain various types of distortions due to the environmental conditions during image acquisition, which necessitates the proper removal of these distortions through a data preprocessing process. In this study, a preprocessing method was investigated to effectively correct the distortion caused by artificial light sources used in indoor hyperspectral imaging. For this purpose, a halogen-tungsten artificial light source was installed indoors, and hyperspectral images were acquired. The acquired images were then corrected for distortion using a preprocessing that does not require complex auxiliary equipment. After the corrections were made, the results were analyzed. According to the analysis, a statistical transformation technique using mean and standard deviation with reference to a reference signal was found to be the most effective in correcting distortions caused by artificial light sources.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.225-230
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• 2016

Dam is built to supply water necessary for life stably and reduce the damage caused by heavy rains. Recently there has been required the analysis and utilization of spatial information on the area around the dam because construction of the dam gives a great impact on the environment of the surrounding area. In this study, we build spatial information about the submerged district due to dam construction using drone and propose the effective method for analysis of the spatial information. As a result, orthoimage and DSM of study area were constructed effectively. Change of submerged district of this area was calculated according to the analysis of spatial information. Building and analyzing spatial information carried out in this study are expected to be utilized as the basis in related fields.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.669-676
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• 2018

As the Moon's scientific, technological, and economic value has increased, major space agencies around the world are leading lunar exploration projects by establishing a road map to develop lunar resources and to construct a lunar base. In addition, as the lunar base construction requires huge amounts of resources from the Earth, lunar in-situ construction technology is being developed to produce construction materials from local lunar resources. On the other hand, the characteristics of lunar topography and resources vary spatially due to the crustal and volcanic activities inside the Moon as well as the solar wind and meteorites from outside the Moon. Therefore, in this paper, the geospatial analysis of lunar resource distribution was conducted to suggest regional consideration factors to apply the lunar in situ construction technologies. In addition, the lunar topographic condition to select construction sites was suggested to ensure the safe landing of a lunar lander and the easy maneuvering of a rover. The lunar topographic and resource information mainly from lunar orbiters were limited to the lunar surface with a low spatial resolution. Rover-based lunar exploration in the near future is expected to provide valuable information to develop lunar in situ construction technology and select candidate sites for lunar base construction.

• Journal of Construction Engineering and Project Management
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• v.1 no.3
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• pp.45-51
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• 2011

During disaster response, prioritization of limited resources is one of the most important but challenging tasks. At the same time, it is imperative to timely provide to the rescuers with the adequate heavy equipment to facilitate lifesaving operations. However, supply of high demand equipment is usually insufficient during the initial phase of disaster response, challenging lifesaving operations. At the same time, resources outside of the disaster affected zone converge into the area to assist the response efforts, which is the effect of convergence that often made resource coordination challenging in large scale disasters. Meanwhile, the initial condition of the disaster is usually best known by civilians already at the area before and during impact of the disaster. The knowledge of the civilians is not always received and considered by the responding organizations. With the help of these civilians, critical information such as victim location, infrastructure damage, and risk condition could be better know before any response actions are taken. To efficiently collect information and utilize the converging resources, this paper proposes a geospatial information repository for initial condition reporting and update to guide search and rescue operations and deployment of equipment with safety considerations for the rescuers in large scale disaster response scenarios.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.6
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• pp.345-354
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• 2018

It is conservative to say that lots of research is performed as measures to use UAV for application to the rapid spatial information and its application is faced with settlement stage to some extent. In addition, Korea Land and Geospatial Informatix Corporation autonomously produces work regulation which is applied to every kind of orders and National Geographic Information Institute (2018) has notified public surveying work instructions about unmanned aerial device for the rapid spatial information construction. The results acquired by UAV are comprised of contents about accuracy improvements for the orthophoto when reviewing pertinent regulations. The results acquired by UAV are comprised of contents about accuracy improvements for the orthophoto when reviewing pertinent regulations. As a result, it is known that error amount has been sharply increased from 400m separation distance, and this study proposes that cross flight is able to reduce irregular error occurrence as measures to acquire stable results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.187-196
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• 2020

In this study, collapsed building detection using UAV (Unmanned Aerial Vehicle) and PlanetScope satellite images was carried out, suggesting the possibility of utilization of heterogeneous sensors in object detection located on the surface. To this end, the area where about 20 buildings collapsed due to forest fire damage was selected as study site. First of all, the feature information of objects such as ExG (Excess Green), GLCM (Gray-Level Co-Occurrence Matrix), and DSM (Digital Surface Model) were generated using high-resolution UAV images performed object-based segmentation to detect collapsed buildings. The features were then used to detect candidates for collapsed buildings. In this process, a result of the change detection using PlanetScope were used together to improve detection accuracy. More specifically, the changed pixels acquired by the bitemporal PlanetScope images were used as seed pixels to correct the misdetected and overdetected areas in the candidate group of collapsed buildings. The accuracy of the detection results of collapse buildings using only UAV image and the accuracy of collapse building detection result when UAV and PlanetScope images were used together were analyzed through the manually dizitized reference image. As a result, the results using only UAV image had 0.4867 F1-score, and the results using UAV and PlanetScope images together showed that the value improved to 0.8064 F1-score. Moreover, the Kappa coefficiant value was also dramatically improved from 0.3674 to 0.8225.

• Journal of information and communication convergence engineering
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• v.9 no.1
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• pp.69-73
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• 2011

Twitter is a microblogging service that allows its user to share short messages called tweets with each other. All the tweets are visible on a public timeline. These tweets have the valuable geospatial component and particularly time critical events. In this paper, our interest is in the rapid detection of disaster events such as tsunami, tornadoes, forest fires, and earthquakes. We describe the detection system of disaster events and show the way to detect a target event from Twitter data. This research examines the three disasters during the same time period and compares Twitter activity and Internet news on Google. A significant result from this research is that emergency detection could begin using microblogging service.