• Journal of the Korean earth science society
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• v.23 no.1
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• pp.87-96
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• 2002

Aeromagnetic and gravity data were analyzed to delineate the subsurface structure of the Yeongdong basin and its related fault movement in the Okcheon fold belt. The aeromagnetic data of the total intensity (KIGAM, 1983) were reduced to the pole and three dimensional inverse modeling, which considers topography of the survey area in the modeling process, were carried out. The apparent susceptibility map obtained by three dimensional magnetic inversion, as well as the observed aeromagnetic anomaly itself, show clearly the gross structural trend of the Yeongdong basin in the direction on between $N30^{\circ}E$ and $N45^{\circ}E$. Gravity survey was carried out along the profile, of which the length is about 18.2 km across the basin. Maximum relative Bouguer anomaly is about 7 mgals. Both forward and inverse modeling were also carried out for gravity analysis. The magnetic and gravity results show that the Yeongdong basin is developed by the force which had created the NE-SW trending the magnetic anomalies. The susceptibility contrast around Yeongdong fault is apparent, and the southeastern boundary of the basin is clearly defined. The basement depth of the basin appears to be about 1.1 km beneath the sea level, and the width of the basin is estimated to be 7 km based on the simultaneous analysis of gravity and magnetic profiles. There exists an unconformity between the sedimentary rocks and the gneiss at the southeastern boundary, which is the Yeongdong fault, and granodiorite is intruded at the northwestern boundary of the basin. Our results of gravity and magnetic data analysis support that the Yeongdong basin is a pull-apart basin formed by the left-stepping sinistral strike-slip fault, which formed the Okcheon fold belt.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.673-679
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• 2016

This study propose a new method to detect Cochlodinium polykrikoides red tide occurring in South Sea of Korea using Water-leaving Radiance data and Absorption Coefficients data of Geostationary Ocean Color Imager (GOCI). C. polykrikoides were analyzed and the irradiance and light emission characteristics of the wavelength range from 412 nm to 555 nm were confirmed. The detection technique proposed in this study detects the red tide occurring in the optically complex South Sea. Based on these results, it can be used for future red tide prevention.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.573-586
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• 2020

PM (particulate matter) is of interest to everyone because it can have adverse effects on human health by the infiltration from respiratory to internal organs. To date, many studies have made efforts for the prediction of PM10 and PM2.5 concentrations. Unlike previous studies, we conducted the prediction of tomorrow's PM10 concentration for the Air Korea stations using Chinese PM10 data in addition to the satellite AOD and weather variables. We constructed 230,639 matchups from the raw data over 3 million and built an RF (random forest) model from the matchups to cope with the complexity and nonlinearity. The validation statistics from the blind test showed excellent accuracy with the RMSE (root mean square error) of 9.905 ㎍/㎥ and the CC (correlation coefficient) of 0.918. Moreover, our prediction model showed a stable performance without the dependency on seasons or the degree of PM10 concentration. However, part of coastal areas had a relatively low accuracy, which implies that a dedicated model for coastal areas will be necessary. Additional input variables such as wind direction, precipitation, and air stability should also be incorporated into the prediction model as future work.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.379-379
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• 2020

The influence of drought has increased due to global warming. In addition, forest fires have occurred more frequently due to droughts and resulted in property losses and casualty. In this study, the effects of drought on Goseong-Sokcho Forest Fire in 2019 were analyzed using high-resolution synthetic precipitation data. In order to determine the severity of drought, the average, 20%tile and 80%ile values were calculated using the synthetic precipitation data of the past 30 years and compared with the current climatology. We have investigated the multi-year accumulated precipitation data to determine the persistence of drought. In Goseong-Sokcho forest fire case, the two-year cumulative synthetic precipitation data shows a similar value to the climate, but the three-year cumulative synthetic precipitation data was close to the 20%ile lines of the climate value. It may expose that the shortage of precipitation in 2017 had persisted until 2019, despite abundant precipitation during the summer in 2018. Therefore, Goseong-Sokcho forest fire might be spread more rapidly by drought which has been persisted since 2017.

• Proceedings of the KSRS Conference
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• v.1
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• pp.398-401
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• 2006

Dual channel Radiometer for Earth and Atmospheric Monitoring (DREAM) is the main payload on Science and Technology SATellite-2 (STSAT-2) of Korea. DREAM is two-channel microwave radiometer with linear polarization, and operating at center frequencies of 23.8 GHz and 37 GHz. An equation for DREAM calibration is derived which accounts for losses and re-radiation in the microwave components of the radiometer due to physical temperature. This paper describes the radiometric calibration equation to get antenna temperature ($T_A$) from the measured output data. At lower altitude, the measured deep space temperature is contaminated by middle atmosphere and earth radiation. In this paper, we presented the detail mathematical formulation to find the altitude up to which cold source brightness temperature is not affected by earth and middle atmosphere radiation. The DREAMPFM data is used to calculate the performance parameters (linearity, sensitivity, dynamic range, and etc.) of the system.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1767-1772
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• 2021

Global satellite observation surface albedo data over a long period of time are actively used to monitor changes in the global climate and environment, and their utilization and importance are great. Through the generational shift of geostationary satellites COMS (Communication, Ocean and Meteorological Satellite)/MI (Meteorological Imager sensor) and GK-2A (GEO-KOMPSAT-2A)/AMI (Advanced Meteorological Imager sensor), it is possible to continuously secure surface albedo outputs. However, the surface albedo outputs of COMS/MI and GK-2A/AMI differ between outputs due to Differences in retrieval algorithms. Therefore, in order to expand the retrieval period of the surface albedo of COMS/MI and GK-2A/AMI to secure continuous climate change monitoring linkage, the analysis of the two satellite outputs and errors should be preceded. In this study, error characteristics were analyzed by performing comparative analysis with ground observation data AERONET (Aerosol Robotic Network) and other satellite data GLASS (Global Land Surface Satellite) for the overlapping period of COMS/MI and GK-2A/AMI surface albedo data. As a result of error analysis, it was confirmed that the RMSE of COMS/MI was 0.043, higher than the RMSE of GK-2A/AMI, 0.015. In addition, compared to other satellite (GLASS) data, the RMSE of COMS/MI was 0.029, slightly lower than that of GK-2A/AMI 0.038. When understanding these error characteristics and using COMS/MI and GK-2A/AMI's surface albedo data, it will be possible to actively utilize them for long-term climate change monitoring.

• Smart Structures and Systems
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• v.33 no.2
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• pp.93-103
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• 2024

Despite the rapid development of sensors, structural health monitoring (SHM) still faces challenges in monitoring due to the degradation of devices and harsh environmental loads. These challenges can lead to measurement errors, missing data, or outliers, which can affect the accuracy and reliability of SHM systems. To address this problem, this study proposes a classification method that detects anomaly patterns in sensor data. The proposed classification method involves several steps. First, data scaling is conducted to adjust the scale of the raw data, which may have different magnitudes and ranges. This step ensures that the data is on the same scale, facilitating the comparison of data across different sensors. Next, informative features in the time and frequency domains are extracted and used as input for a deep neural network model. The model can effectively detect the most probable anomaly pattern, allowing for the timely identification of potential issues. To demonstrate the effectiveness of the proposed method, it was applied to actual data obtained from a long-span cable-stayed bridge in China. The results of the study have successfully verified the proposed method's applicability to practical SHM systems for civil infrastructures. The method has the potential to significantly enhance the safety and reliability of civil infrastructures by detecting potential issues and anomalies at an early stage.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.28 no.4
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• pp.133-142
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• 2023

In this paper, we built a data-driven artificial intelligence model using RNN-LSTM (Recurrent Neural Networks-Long Short-Term Memory) to predict the Lorenz system, and examined the possibility of whether this model can replace chaotic dynamic models. We confirmed that the data-driven model reflects the chaotic nature of the Lorenz system, where a small error in the initial conditions produces fundamentally different results, and the system moves around two stable poles, repeating the transition process, the characteristic of "deterministic non-periodic flow", and simulates the bifurcation phenomenon. We also demonstrated the advantage of adjusting integration time intervals to reduce computational resources in data-driven models. Thus, we anticipate expanding the applicability of data-driven artificial intelligence models through future research on refining data-driven models and data assimilation techniques for data-driven models.

• Journal of The Korean Association For Science Education
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• v.25 no.5
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• pp.610-623
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• 2005

This was a theoretical study of which the goal was to provide a foundation for developing and implementing earth science inquiry activities based on abduction as a scientific inquiry method. Through a review of relevant literature, the study examined the nature of earth science in terms of the goals of earth science inquiry and the characteristics of what is investigated in earth science. It also explored the forms and meanings of abduction, thinking strategies used in the abductive inference, and the abductive inquiry model. Abduction is the process of inferring certain rules (e.g., scientific facts, principles, laws) and providing explanatory statements or hypotheses in order to explain some phenomena. This method was found to be well-suited to the earth science inquiry which studies the causes and processes of natural phenomena in the earth and space environment. Abduction has the nature of ampliative, selective, evaluative, and creative inference, and several thinking strategies, including reconstruction of data, heuristic generalization, analogy, existential, conceptual combination, and elimination strategies, are employed for inferring rules and suggesting hypotheses. This study found the abductive inquiry model to be adaptable to earth science classrooms, and it is therefore suggested that earth science instructions should be based on the abductive method and that research work concerning the abductive inquiry in the classroom should follow.

• Journal of Korean Society of Rural Planning
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• v.15 no.4
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• pp.199-211
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• 2009

The aim of this paper is to investigate the applicability of high spatial resolution remote sensing images for conducting the rural amenity resources survey. There are a large number of rural amenity resources and field reconnaissance without a sufficient preliminary survey involves a big amount of cost and time even if the data quality cannot always be satisfied with the advanced study. Therefore, a new approach should be considered like the state-of-the-art remote sensing technology to support field survey of rural amenity resources as well as to identify the spatial attributes including the geographical location, pathway, area, and shape. Generally high-resolution satellite or aerial photo images are too expensive to cover a large area and not free of meteorological conditions, but recently rapidly-advanced internet-based image services, such as Google Earth, Microsoft Bing maps, Bluebirds, Daum maps, and so on, are expected to overcome the handicaps. The review of the different services shows that Google Earth would be the most feasible alternative for the survey of rural amenity resources in that it provides powerful tools to build spatial features and the attributes and the data format is completely compatible with other GIS(Geographic information system) software. Hence, this study tried to apply the Google Earth service to interpret the amenity resources and proposed the reformed work process conjugating the internet-based high-resolution images like satellite and aerial photo data.