• Journal of Space Technology and Applications
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• v.4 no.2
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• pp.87-104
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• 2024

CubeSats are being utilized in various fields such as Earth observation, space exploration, and verification of space science and technology due to their low cost, short development period, enhanced mission-oriented performance, and ability to perform various missions through constellation and formation flights. Recently, as the availability of CubeSats has increased and their application areas have expanded, the demand for high-speed transmission of large amounts of data obtained by CubeSats has increased unprecedentedly. Laser-based free space optical communication technology is capable of transmitting large amounts of data at high speeds compared to the existing radio communication methods, and provides various advantages such as use of unlicensed spectrum, low cost, low power, high security characteristics, and of use a small communication platform. For this reason, it is suitable as a high-performance communication technology to support CubeSat missions. In this paper, we will present the core components and characteristics of CubeSat-based space laser communication system, and recent research trends, as well as representative technology development results.

• Journal of the Korean GEO-environmental Society
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• v.18 no.2
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• pp.47-51
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• 2017

In this study, the optimization algorithm by inverse analysis that is the core of the adaptive management technique was adopted to update the soil engineering properties based on the ground response during the construction. Adaptive management technique is the framework wherein construction and design procedures are adjusted based on observations and measurements made as construction proceeds. To evaluate the performance of the adaptive management technique, the numerical simulation for the triaxial tests and the synthetic deep excavation were conducted with the Hardening Soil model. To effectively conduct the analysis, the effective parameters among the parameters employed in the model were selected based on the composite scaled sensitivity analysis. The results from the undrained triaxial tests performed with soft Chicago clays were used for the parameter calibration. The simulation for the synthetic deep excavation were conducted assuming that the soil engineering parameters obtained from the triaxial simulation represent the actual field condition. These values were used as the reference values. The observation for the synthetic deep excavation simulations was the horizontal displacement of the support wall that has the highest composite scaled sensitivity among the other possible observations. It was found that the horizontal displacement of the support wall with the various initial soil properties were converged to the reference displacement by using the adaptive management technique.

• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1259-1268
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• 2004

To organize training in limited training area for an actuai combat, realistic training simulation plugged in by various battle conditions is essential. In this paper, we propose a virtual target overlay technique which does not use a virtual image, but Projects a virtual target on ground-based CCD image by appointed scenario for a realistic training simulation. In the proposed method, we create a realistic 3D model (for an instructor) by using high resolution Geographic Tag Image File Format(GeoTIFF) satellite image and Digital Terrain Elevation Data (DTED), and extract the road area from a given CCD image (for both an instructor and a trainee). Satellite images and ground-based sensor images have many differences in observation position, resolution, and scale, thus yielding many difficulties in feature-based matching. Hence, we propose a moving synchronization technique that projects the target on the sensor image according to the marked moving path on 3D satellite image by applying Thin-Plate Spline(TPS) interpolation function, which is an image warping function, on the two given sets of corresponding control point pair. To show the experimental result of the proposed method, we employed two Pentium4 1.8MHz personal computer systems equipped with 512MBs of RAM, and the satellite and sensor images of Daejoen area are also been utilized. The experimental result revealed the effective-ness of proposed algorithm.

• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.189-211
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• 2005

This paper makes an effort to compare the recently evolved soft classification method based on Linear Spectral Mixture Modeling (LSMM) with the traditional hard classification methods based on Iterative Self-Organizing Data Analysis (ISODATA) and Maximum Likelihood Classification (MLC) algorithms in order to achieve appropriate results for mapping, monitoring and preserving valuable coastal wetland ecosystems of southern India using Indian Remote Sensing Satellite (IRS) 1C/1D LISS-III and Landsat-5 Thematic Mapper image data. ISODATA and MLC methods were attempted on these satellite image data to produce maps of 5, 10, 15 and 20 wetland classes for each of three contrast coastal wetland sites, Pitchavaram, Vedaranniyam and Rameswaram. The accuracy of the derived classes was assessed with the simplest descriptive statistic technique called overall accuracy and a discrete multivariate technique called KAPPA accuracy. ISODATA classification resulted in maps with poor accuracy compared to MLC classification that produced maps with improved accuracy. However, there was a systematic decrease in overall accuracy and KAPPA accuracy, when more number of classes was derived from IRS-1C/1D and Landsat-5 TM imagery by ISODATA and MLC. There were two principal factors for the decreased classification accuracy, namely spectral overlapping/confusion and inadequate spatial resolution of the sensors. Compared to the former, the limited instantaneous field of view (IFOV) of these sensors caused occurrence of number of mixture pixels (mixels) in the image and its effect on the classification process was a major problem to deriving accurate wetland cover types, in spite of the increasing spatial resolution of new generation Earth Observation Sensors (EOS). In order to improve the classification accuracy, a soft classification method based on Linear Spectral Mixture Modeling (LSMM) was described to calculate the spectral mixture and classify IRS-1C/1D LISS-III and Landsat-5 TM Imagery. This method considered number of reflectance end-members that form the scene spectra, followed by the determination of their nature and finally the decomposition of the spectra into their endmembers. To evaluate the LSMM areal estimates, resulted fractional end-members were compared with normalized difference vegetation index (NDVI), ground truth data, as well as those estimates derived from the traditional hard classifier (MLC). The findings revealed that NDVI values and vegetation fractions were positively correlated ($r^2$= 0.96, 0.95 and 0.92 for Rameswaram, Vedaranniyam and Pitchavaram respectively) and NDVI and soil fraction values were negatively correlated ($r^2$ =0.53, 0.39 and 0.13), indicating the reliability of the sub-pixel classification. Comparing with ground truth data, the precision of LSMM for deriving moisture fraction was 92% and 96% for soil fraction. The LSMM in general would seem well suited to locating small wetland habitats which occurred as sub-pixel inclusions, and to representing continuous gradations between different habitat types.

• Journal of Conservation Science
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• v.37 no.3
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• pp.191-208
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• 2021

In this study, the status of damage by subterranean termites and their management according to the region and type of domestic wooden cultural properties were identified. This was based on the survey reports of agencies conducting regular nationwide and regional monitoring of subterranean termites. In addition, using geographical information system (GIS) based on the survey contents, a map was constructed of termite infestation and its progress on 2,805 wooden cultural properties that were surveyed nationwide. Based on the map produced, a total of 486 cases of termite infestation were confirmed in wooden cultural properties during 2018-2019, of which 143 cases (approximately 29.4%) were confirmed to be owing to the invasion of termites in the ground and infestation of wood materials. A web platform and an application using a mapping application program interface were created to increase accessibility to the investigated damage status data. The methods employed by each institution for investigating and monitoring the invasion of termites in the ground included the use of detection dogs, visual observation, installation of wood specimens made of pine, and microwave equipment. However, it was confirmed that monitoring and survey methods were not applied to determine the territorial range of the subterranean termite colonies. Accordingly, the use of dyeing and mark-release-recapture methods were deemed necessary to understand the current status, such as calculating the scope of the target wooden cultural property, when monitoring subterranean termite colonies.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.903-911
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• 2022

Groundwater, one of the resources for supplying water, fluctuates in water level due to various natural factors. Recently, research has been conducted to predict fluctuations in groundwater levels using Artificial Neural Network (ANN). Previously, among operators in ANN, Gradient Descent (GD)-based Optimizers were used as Optimizer that affect learning. GD-based Optimizers have disadvantages of initial correlation dependence and absence of solution comparison and storage structure. This study developed Gradient Descent combined with Harmony Search (GDHS), a new Optimizer that combined GD and Harmony Search (HS) to improve the shortcomings of GD-based Optimizers. To evaluate the performance of GDHS, groundwater level at Icheon Yullhyeon observation station were learned and predicted using Multi Layer Perceptron (MLP). Mean Squared Error (MSE) and Mean Absolute Error (MAE) were used to compare the performance of MLP using GD and GDHS. Comparing the learning results, GDHS had lower maximum, minimum, average and Standard Deviation (SD) of MSE than GD. Comparing the prediction results, GDHS was evaluated to have a lower error in all of the evaluation index than GD.

• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.471-479
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• 2024

Flood damage is becoming more serious due to the heavy rainfall caused by climate change. Physically based hydrological models have been utilized to predict stream water level variability and provide flood forecasting. Recently, hydrological simulations using machine learning and deep learning algorithms based on nonlinear relationships between hydrological data have been getting attention. In this study, the Long Short-Term Memory (LSTM) algorithm is used to predict the water level of the Seomjin River watershed. In addition, Climate Prediction Center morphing method (CMORPH)-based gridded precipitation data is applied as input data for the algorithm to overcome for the limitations of ground data. The water level prediction results of the LSTM algorithm coupling with the CMORPH data showed that the mean CC was 0.98, RMSE was 0.07 m, and NSE was 0.97. It is expected that deep learning and remote data can be used together to overcome for the shortcomings of ground observation data and to obtain reliable prediction results.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.377-385
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• 2024

We investigated the effect of spectral fitting wavelength interval variations and selection of absorption cross-section on the sulfur dioxide slant column density (SCD) retrievals from the scattered sunlight observation using a UV-Vis hyperspectral instrument. The sulfur dioxide slant column densities were retrieved from the combinations of multiple spectral fitting intervals and absorption cross-sections. The observation was carried out at the site 0.53 km away from a combustion site located in Gimhae from December 1, 2023, to January 23, 2024. The radiances were obtained on the line of measurement sight toward the stack of the combustion facility. The best spectral fitting intervals were found to be from 305.7 to 321.1 nm. In terms of the absorption cross-section dependency, the SO₂ (293 K), O₃ (223 K, 243 K) show the best spectral fitting for the observed radiances with both the smallest fitting residual and SCD error. The effects of the fitting interval and cross sections found in this study can be useful information for improving SO₂ retrievals based on UV hyperspectral measurements.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.56.3-57
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• 2015

As of early 2015, more than 12,000 Near-Earth Objects (NEOs) have been catalogued by the Minor Planet Center, however their observational properties such as broadband colors and rotational periods are known only for a small fraction of the population. Thanks to time series observations with the KMTNet, orbits, optical sizes (and albedo), spin states and three dimensional shapes of asteroids and comets including NEOs will be systematically investigated and archived for the first time. Based on SDSS and BVRI colors, their approximate surface mineralogy will also be characterized. This so-called DEEP-South (Deep Ecliptic Patrol of the Southern Sky) project will provide a prompt solution to the demand from the scientific community to bridge the gaps in global sky coverage with a coordinated use of the network of ground-based telescopes in the southern hemisphere. We will soon finish implementing dedicated software subsystem consisted of automated observation scheduler and data pipeline for the sake of increased discovery rate, rapid follow-up, timely phase coverage, and efficient data analysis. We will give a brief introduction to test runs conducted at CTIO with the first KMTNet telescope in February and March 2015 and experimental data processing. Preliminary scientific results will also be presented.

• Journal of Astronomy and Space Sciences
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• v.20 no.4
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• pp.327-338
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• 2003

The aim of this paper is to describe the results of the study on the extreme-ultra-violet (EUV) solar telescope, which is designed to. a possible satellite mission. Since the EUV band can not be observed on the ground, the observation in EUV should be performed in space using a satellite or a rocket. Design of the Extreme-Ultra-Violet solar Telescope (BUVT) in this study is based on "Designing a small-sized engineering model of solar EUV telescope for a Korean satellite" (Han et al. 2001). Our EUVT design is satisfied with the requirements for a satellite in size and input voltage. The major goal of the study is to confirm if we can detect the specific wavelength (58.4nm to 62.9nm) with the EUVT. We describe re-designing of the EUVT to decrease a shelter ratio. Also we describe the technics in the optic system and the detector, which were used to manufacture the EUVT. We explain the detective program, which is to calculate the amount of the solar radiation, and the image data processing system.ng system.