• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1341-1352
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• 2023

The normalized difference vegetation index (NDVI) derived from satellite images is a crucial tool to monitor forests and agriculture for broad areas because the periodic acquisition of the data is ensured. However, optical sensor-based vegetation indices(VI) are not accessible in some areas covered by clouds. This paper presented a synthetic aperture radar (SAR) based approach to retrieval of the optical sensor-based NDVI using machine learning. SAR system can observe the land surface day and night in all weather conditions. Radar vegetation indices (RVI) from the Sentinel-1 vertical-vertical (VV) and vertical-horizontal (VH) polarizations, surface elevation, and air temperature are used as the input features for an automated machine learning (AutoML) model to conduct the gap-filling of the Sentinel-2 NDVI. The mean bias error (MAE) was 7.214E-05, and the correlation coefficient (CC) was 0.878, demonstrating the feasibility of the proposed method. This approach can be applied to gap-free nationwide NDVI construction using Sentinel-1 and Sentinel-2 images for environmental monitoring and resource management.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1643-1652
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• 2022

Deposited Marine Debris(DMD) can negatively affect marine ecosystems, fishery resources, and maritime safety and is mainly detected by sonar sensors, lifting frames, and divers. Considering the limitation of cost and time, recent efforts are being made by integrating underwater images and artificial intelligence (AI). We conducted a comparative study of You Only Look Once Version 5 (YOLOv5) and You Only Look Once Version 7 (YOLOv7) models to detect DMD from underwater images for more accurate and efficient management of DMD. For the detection of the DMD objects such as glass, metal, fish traps, tires, wood, and plastic, the two models showed a performance of over 0.85 in terms of Mean Average Precision (mAP@0.5). A more objective evaluation and an improvement of the models are expected with the construction of an extensive image database.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.953-966
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• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

• Journal of the Korean earth science society
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• v.26 no.7
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• pp.640-651
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• 2005

This study was to analyze the subject objectives of Middle school 7th grade Science textbooks based on the Korean 7th curriculum by using Klopfer’s taxonomic system and find out how much compatible they were with the requiring objectives of the curriculum. Particularly, this study makes educational objectives for textbooks coherent wit the requiring objectives of the curriculum, through the analysing the problems. The results are follows. The Middle school science educational objective of the 7th curriculum sets up almost of the objectives through all of the domains of the Klopfer’s taxonomy system, except the operational function (Category G.0), and emphasizes on emotionable domain (Category $H.0\~I.0$) more. However, comparing with an encouragement objective rate of NSTA, Middle school Science textbooks based on the 7th curriculum were published putting more importance in a cognitive domain, and the intention objective (Category I.0) was not mentioned.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1407-1419
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• 2020

Long time-series gridded data is crucial for the analyses of Earth environmental changes. Climate reanalysis and satellite images are now used as global-scale periodical and quantitative information for the atmosphere and land surface. This paper examines the feasibility of DCT-PLS (penalized least square regression based on discrete cosine transform) for the spatial gap filling of gridded data through the experiments for multiple variables. Because gap-free data is required for an objective comparison of original with gap-filled data, we used LDAPS (Local Data Assimilation and Prediction System) daily data and MODIS (Moderate Resolution Imaging Spectroradiometer) monthly products. In the experiments for relative humidity, wind speed, LST (land surface temperature), and NDVI (normalized difference vegetation index), we made sure that randomly generated gaps were retrieved very similar to the original data. The correlation coefficients were over 0.95 for the four variables. Because the DCT-PLS method does not require ancillary data and can refer to both spatial and temporal information with a fast computation, it can be applied to operative systems for satellite data processing.

• Journal of Environmental Science International
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• v.17 no.2
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• pp.257-267
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• 2008

Groundwater recharge characteristics in a fractured granite area, Mt. Geumjeong, Korea. was interpreted using bedrock groundwater and wet-land water data. Time series analysis using autocorreclation, cross-correlation and spectral density was conducted for characterizing water level variation and recharge rate in low water and high water seasons. Autocorrelation analysis using water levels resulted in short delay time with weak linearity and memory. Cross-correlation function from cross-correlation analysis was lower in the low water season than the high water season for the bedrock groundwater. The result of water level decline analysis identified groundwater recharge rate of about 11% in the study area.

• Biomedical Engineering Letters
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• v.8 no.4
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• pp.373-382
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• 2018

Since epileptic seizure is unpredictable and paroxysmal, an automatic system for seizure detecting could be of great significance and assistance to patients and medical staff. In this paper, a novel method is proposed for multichannel patient-specific seizure detection applying the earth mover's distance (EMD) in scalp EEG. Firstly, the wavelet decomposition is executed to the original EEGs with five scales, the scale 3, 4 and 5 are selected and transformed into histograms and afterwards the distances between histograms in pairs are computed applying the earth mover's distance as effective features. Then, the EMD features are sent to the classifier based on the Bayesian linear discriminant analysis (BLDA) for classification, and an efficient postprocessing procedure is applied to improve the detection system precision, finally. To evaluate the performance of the proposed method, the CHB-MIT scalp EEG database with 958 h EEG recordings from 23 epileptic patients is used and a relatively satisfactory detection rate is achieved with the average sensitivity of 95.65% and false detection rate of 0.68/h. The good performance of this algorithm indicates the potential application for seizure monitoring in clinical practice.

• Journal of the Korean earth science society
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• v.36 no.6
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• pp.591-608
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• 2015

The purpose of this study was to analyze system thinking revealed in science teachers' teaching practices of middle school astronomy classes. Astronomy lessons were video-taped from four eighth grade science teachers. The video recordings were all transcribed and analyzed by employing a framework for systems thinking analysis after modifying an existing frame of hierarchial structure used in relevant previous studies. In addition, four participants were interviewed in order to uncover their orientation toward teaching using video stimulated recall method. Findings are as follows: All participating teachers were not able to employ the four levels of system thinking appropriately and only utilized the low level of systems thinking. They also demonstrated teacher-centered practices for employing system thinking despite their student-centered orientation toward teaching. The main reason for these results may be that teachers focused more on spatial thinking, than on system thinking as well as the lack of teacher's knowledge about the content and formative assessment of non-earth science teachers. Implications on how to effectively employ the system thinking in astronomy class are discussed in this paper.

• Journal of Environmental Science International
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• v.31 no.12
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• pp.1051-1059
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• 2022

This study investigated microbial communities and their diversity in a full-scale mesophilic anaerobic digester treating sewage sludge. Influent sewage sludge and anaerobic digester samples collected from a wastewater treatment plant in Busan were analyzed using high-throughput sequencing. It was found that the microbial community structure and diversity in the anaerobic digester could be affected by inoculation effect with influent sewage sludge. Nevertheless, distinct microbial communities were identified as the dominant microbial communities in the anaerobic digester. Twelve genera were identified as abundant bacterial communities, which included several groups of syntrophic bacteria communities, such as Candidatus Cloacimonas, Cloacimonadaceae W5, Smithella, which are (potential) syntrophic-propionate-oxidizing bacteria and Mesotoga and Thermovigra, which are (potential) syntrophic-acetate-oxidizing bacteria. Lentimicrobium, the most abundant genus in the anaerobic digester, may contribute to the decomposition of carbohydrates and the production of volatile fatty acids during the anaerobic digestion of sewage sludge. Of the methanogens identified, Methanollinea, Candidatus Methanofastidiosum, Methanospirillum, and Methanoculleus were the dominant hydrogenotrophic methanogens, and Methanosaeta was the dominant aceticlastic methanogens. The findings may be used as a reference for developing microbial indicators to evaluate the process stability and process efficiency of the anaerobic digestion of sewage sludge.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.715-727
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• 2023

To provide detailed and appropriate meteorological information in mountainous areas, the Korea Forest Service has established an Automatic Mountain Meteorology Observation Station (AMOS) network in major mountainous regions since 2012, and 464 stations are currently operated. In this study, we proposed an optimal kriging technique with lapse rate correction to produce gridded temperature data suitable for Korean forests using AMOS point observations. First, the outliers of the AMOS temperature data were removed through statistical processing. Then, an optimized theoretical variogram, which best approximates the empirical variogram, was derived to perform the optimal kriging with lapse rate correction. A 500-meter resolution Kriging map for temperature was created to reflect the elevation variations in Korean mountainous terrain. A blind evaluation of the method using a spatially unbiased validation sample showed a correlation coefficient of 0.899 to 0.953 and an error of 0.933 to 1.230℃, indicating a slight accuracy improvement compared to regular kriging without lapse rate correction. However, the critical advantage of the proposed method is that it can appropriately represent the complex terrain of Korean forests, such as local variations in mountainous areas and coastal forests in Gangwon province and topographical differences in Jirisan and Naejangsan and their surrounding forests.