• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.2
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• pp.46-64
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• 2003

The vector shaped object is generally very long (hundreds or thousands of kilometers) and very narrow (10-100 meters). Image mapping techniques and tools for these objects should be totally different from the traditional area-based targets. Acknowledging these unique characteristics of the vector shaped object, a motion picture mapping system has been developed by combining internet GIS technology with airborne video. In particular, integration between airborne video and digital maps took advantage of each component, and enabled the landscape structure to be visualized, interacted with and deployed all on the Web. The motion picture maps provided a completely new means for disseminating information for area-wide landscape in a visual and interactive manner to the general public while digital map with location information revealed successfully the major parameters that influence an area-wide spatial structure in the study area. The remote video approach breaks down the usual concept of image mapping in a conventional cartography. As a result, the research findings have established the new concept of 'internet airborne video mapping for vector shaped object', proposed as an initial aim of this paper. It would playa crucial role in improving the quality of public information service if the mapping system is operationally introduced into the Government since the highly user-friendly moving picture provides a completely new means for disseminating spatia) information for vector shaped object.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3086-3103
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• 2017

Video images captured by vehicle cameras often contain blurry or dithering frames due to inadvertent motion from bumps in the road or by insufficient illumination during the morning or evening, which greatly reduces the perception of objects expression and recognition from the records. Therefore, a real-time electronic stabilization method to correct fuzzy video from driving recorders has been proposed. In the first stage of feature detection, a coarse-to-fine inspection policy and a scale nonlinear diffusion filter are proposed to provide more accurate keypoints. Second, a new antiblurry binary descriptor and a feature point selection strategy for unintentional estimation are proposed, which brought more discriminative power. In addition, a new evaluation criterion for affine region detectors is presented based on the percentage interval of repeatability. The experiments show that the proposed method exhibits improvement in detecting blurry corner points. Moreover, it improves the performance of the algorithm and guarantees high processing speed at the same time.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.19 no.2
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• pp.37-44
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• 2011

This paper summarizes the HVO concept and procedures, presents a summary of the research and results, and outlines areas where future HVO is required. This concept enables people to get their destinations through shortest paths with advanced air traffic control system and equipments. The concept's key feature is that pilots maintain their own separation from other aircraft using air-to-air datalink and on-board software which are needed for supporting flight information present on the high Way in the sky display and airborne internet. By assigning Self-Controlled Area which assume pilot have separation responsibility, controllers evaluated SATS HVO concept as a successful method on the view of reduced workload and increased traffic level on high volume operation.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.216-224
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• 2021

Aim of this research was to classify forest types at Wando in Jeonnam Province and develop warm temperate forest management system with application of Remote Sensing and GIS. Another emphasis was given to the analysis of satellite images to compare forest type changes over 10 year periods from 2009 to 2019. We have accomplished this study by using ArcGIS Pro and ENVI. For this research, Landsat satellite images were obtained by means of terrestrial, airborne and satellite imagery. Based on the field survey data, all land uses and forest types were divided into 5 forest classes; Evergreen broad-leaved forest, Evergreen Coniferous forest, Deciduous broad-leaved forest, Mixed fores, and others. Supervised classification was carried out with a random forest classifier based on manually collected training polygons in ROI. Accuracy assessment of the different forest types and land-cover classifications was calculated based on the reference polygons. Comparison of forest changes over 10 year periods resulted in different vegetation biomass volumes, producing the loss of deciduous forests in 2019 probably due to the expansion of residential areas and rapid deforestation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3295-3311
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• 2020

With the wide application of hyperspectral images, it becomes more and more important to compress hyperspectral images. Conventional recursive least squares (CRLS) algorithm has great potentiality in lossless compression for hyperspectral images. The prediction accuracy of CRLS is closely related to the correlations between the reference bands and the current band, and the similarity between pixels in prediction context. According to this characteristic, we present an improved CRLS with adaptive band selection and adaptive predictor selection (CRLS-ABS-APS). Firstly, a spectral vector correlation coefficient-based k-means clustering algorithm is employed to generate clustering map. Afterwards, an adaptive band selection strategy based on inter-spectral correlation coefficient is adopted to select the reference bands for each band. Then, an adaptive predictor selection strategy based on clustering map is adopted to select the optimal CRLS predictor for each pixel. In addition, a double snake scan mode is used to further improve the similarity of prediction context, and a recursive average estimation method is used to accelerate the local average calculation. Finally, the prediction residuals are entropy encoded by arithmetic encoder. Experiments on the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) 2006 data set show that the CRLS-ABS-APS achieves average bit rates of 3.28 bpp, 5.55 bpp and 2.39 bpp on the three subsets, respectively. The results indicate that the CRLS-ABS-APS effectively improves the compression effect with lower computation complexity, and outperforms to the current state-of-the-art methods.

• Electronics and Telecommunications Trends
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• v.34 no.6
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• pp.51-60
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• 2019

As a way to further expand and enable the 5G ecosystem, the $3^{rd}$ Generation Partnership Project (3GPP) is considering the development of a 5G new radio (NR)-based non-terrestrial network (NTN). These NTNs are expected to provide ubiquitous 5G services to user's equipment (especially, in Internet of Things/machine-type communications (IoT/MTC) public safety, and critical communications) by extending service coverage to areas not covered by 5G terrestrial networks. To this end, this NTN is developing scenarios to provide 5G services using spaceborne vehicles, such as geosynchronous and low-Earth orbit satellites, and airborne vehicles, such as unmanned aircraft systems, including high-altitude pseudo-satellites. In addition, various technologies are being studied to satisfy new requirements not considered in 5G NR, such as long propagation delay time, large cell coverage, large Doppler effect, and base station movement. In this paper, we present the scenarios, requirements, technical issues and solutions, and standardization planning for NR-based NTN in 3GPP.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.6
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• pp.561-569
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• 2008

Currently, satellite image, aerial image and airborne laser scanning data are mostly used to build 3D image models. However, we are in need of quality 3D image models as current models cannot express topographic and features most elaborately and realistically. When making 3D image models, the model is first built and textures from terrestrial photos are applied to add realistic features to the model. This study analyzed techniques to use photogrammetry and laser scanning data to create a 3D image models with topography, building and statue that emphasize spatial accuracy, delicate depiction and photo-realistic imaging. 3D image models with spatial accuracy and photographic texture were built to be served via 3D image map services systems on the internet. The 3D image models can be used for various purposes, such as daylight and view right analysis, landscape analysis, facility management system.

• Journal of Internet of Things and Convergence
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• v.6 no.2
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• pp.19-24
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• 2020

In the present study, using biological information of bacteria and biochemical information of chlorine dioxide gas, Gram-positive bacteria, e.g., Alloiococcus otitis, Erysipelothrix rhusiopathiae, Staphylococcus caprae, Staphylococcus lentus, and gram-negative bacteria, e.g., Acinetobacter baumannii complex, Aeromonas salmonicida, Brucella melitensis, Oligella ureolytica were used whether a plastic kit to release ClO₂ gas could inhibit their growth. Overall, chlorine dioxide gas showed about 99% inhibition of bacterial growth, with less than 10 CFU. However, it was found that Gram positive Alloiococcus otitis and Gram negative Aeromonas salmonicida had more than about 50 CFU. When comparing the results of experiments with several bacteria, it suggested that the concentration of chlorine dioxide gas would be at least 10 ppm to 400 ppm for the bacterial inhibition. The results of this study could be used as basic data to evaluate the clinical usefulness of chlorine dioxide gas. If this study helps with prior knowledge to help clinicians to recognize and prevent the presence of micro-organisms that cause infections in hospitals, it would be helpful for activities such as patient care as a convergence field. In the future, it is considered that the research results will be the basis for rapidly inhibiting the microbes infected with patients by utilizing data of the information of the microbes that are inhibited for chlorine dioxide gas.

• Korean Journal of Remote Sensing
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• v.21 no.4
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• pp.341-369
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• 2005

Hyperspectral images have emerged as a new and promising remote sensing data that can overcome the limitations of existing optical image data. This study was designed to provide a comprehensive review on definition, data processing methods, and applications of hyperspectral data. Various types of airborne, spaceborne, and field hyperspectral image sensors were surveyed from the available literatures and internet search. To understand the current status of hyperspectral remote sensing technology and research development, we collected several hundreds research papers from international journals (IEEE Transactions on Geoscience and Remote Sensing, International Journal of Remote Sensing, Remote Sensing of Environment and AVIRIS Workshop Proceedings), and categorized them by sensor types, data processing techniques, and applications. Although several hyperspectral sensors have been developing, AVIRIS has been a primary data source that the most hyperspectral remote sensing researches were relied on. Since hyperspectral data have very large data volume with many spectral bands, several data processing techniques that are particularly oriented to hyperspectral data have been developed. Although atmospheric correction, spectral mixture analysis, and spectral feature extraction are among those processing techniques, they are still in experimental stage and need further refinement until the fully operational adaptation. Geology and mineral exploration were major application in early stage of hyperspectral sensing because of the distinct spectral features of rock and minerals that could be easily observed with hyperspectral data. The applications of hyperspectral sensing have been expanding to vegetation, water resources, and military areas where the multispectral sensing was not very effective to extract necessary information.