• Journal of the Korean earth science society
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• v.30 no.1
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• pp.49-57
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• 2009

We studied a structure of the Kunsan basin in the Yellow Sea using ship-borne magnetic data and altimetry satellite-derived gravity data provided from the Scripps institution of oceanography in 2006. The gravity data was analyzed via power spectrum analysis and gravity inversion, and the magnetic data via analytic signal technique, pseudo-gravity transformation, and its inversion. The results showed that the depth of bedrock tended to increase as we approached the center of the South Central Sag in Kunsan basin and that the maximum and minimum of its depth were estimated to be about 6-8 km and 2 km, respectively. Inaddition, the observed high anomaly of gravity and magnetism was attributed to the intrusion of igneous rock of higher density than the surrounding basement rock in the center of South Central Sag, which was consistent with the interpretation of seismic data obtained in the same region.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.1-16
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• 2008

Steam and advection fogs are frequently observed in the Yellow Sea from March to July except for May. This study uses remote sensing (RS) data for the monitoring of sea fog. Meteorological data obtained from the Ieodo Ocean Research Station provided a valuable information for the occurrence of steam and advection fogs as a ground truth. The RS data used in this study were GOES-9, MTSAT-1R images and QuikSCAT wind data. A dual channel difference (DCD) approach using IR and shortwave IR channel of GOES-9 and MTSAT-1R satellites was applied to detect sea fog. The results showed that DCD, texture-related measurement and the weak wind condition are required to separate the sea fog from the low cloud. The QuikSCAT wind data was used to provide the wind speed criteria for a fog event. The laplacian computation was designed for a measurement of the homogeneity. A new combined method, which includes DCD, QuikSCAT wind speed and laplacian computation, was applied to the twelve cases with GOES-9 and MTSAT-1R. The threshold values for DCD, QuikSCAT wind speed and laplacian are -2.0 K, $8m\;s^{-1}$ and 0.1, respectively. The validation results showed that the new combined method slightly improves the detection of sea fog compared to DCD method: improvements of the new combined method are $5{\sim}6%$ increases in the Heidke skill score, 10% decreases in the probability of false detection, and $30{\sim}40%$ increases in the odd ratio.

• Journal of the Korean earth science society
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• v.38 no.3
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• pp.222-238
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• 2017

The purpose of this study is to explore a learning progression for integrated process skills in Earth science inquiry. For the purpose, a hypothetical learning progression (HLP) that capture how students' integrated process skills of science become sophisticated over time is developed through the literature review. This learning progression contains four components of the integrated process skills of science: designing inquiry, collecting data, analyzing data, and forming conclusion. Three hypothetico-deductive inquiry tasks of Earth science that start from recognition of the given problem to the forming conclusion are developed in order to document students' integrated process skills. A total of 126 students from middle, high, college level students participated in this study. After conducting the Earth science inquiry tasks, the integrated process skills of individual students are assessed by element based on HLP. In addition, the validation process for HLP was administered by applying the Rasch model using the students' assessment data. Finally, based on the analyzed data, the empirical learning progression (ELP) is developed by revising and supplementing the HLP. This study can help to find scaffolding methods to effectively improve the students' integrated process skills in Earth science inquiry class by identifying the factors that affect students' development of integrated process skills. It also provide implications for improving teachers' PCK of Earth science inquiry instruction.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.434-436
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• 2005

Analysis method using remote sensing data is one of the effective ways to research a spatial and temporal variability of the mesoscale oceanic motions. During past several decades, many researchers have been getting comprehensive results using remote sensing data with application of data fusion methods in many parts of geo-science. For this study, we took the integration and fusion of several remote sensing data, which are different data resolution, timescale and characteristics, for improving accurate analysis of variation of the Kuroshio Extension. Furthermore, we might get advanced ways to understand the variability of the Kuroshio Extension, has close relation to the spatial and temporal variation of the Kuroshio and Oyashio Current.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.777-788
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• 2021

Since aerosol has a relatively short duration and significant spatial variation, satellite observations become more important for the spatially and temporally continuous quantification of aerosol. However, optical remote sensing has the disadvantage that it cannot detect AOD (Aerosol Optical Depth) for the regions covered by clouds or the regions with extremely high concentrations. Such missing values can increase the data uncertainty in the analyses of the Earth's environment. This paper presents a spatial gap-filling framework using a univariate statistical method such as DCT-PLS (Discrete Cosine Transform-based Penalized Least Square Regression) and FMM (Fast Matching Method) inpainting. We conducted a feasibility test for the hourly AOD product from AHI (Advanced Himawari Imager) between January 1 and December 31, 2019, and compared the accuracy statistics of the two spatial gap-filling methods. When the null-pixel area is not very large (null-pixel ratio < 0.6), the validation statistics of DCT-PLS and FMM techniques showed high accuracy of CC=0.988 (MAE=0.020) and CC=0.980 (MAE=0.028), respectively. Together with the AI-based gap-filling method using extra explanatory variables, the DCT-PLS and FMM techniques can be tested for the low-resolution images from the AMI (Advanced Meteorological Imager) of GK2A (Geostationary Korea Multi-purpose Satellite 2A), GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI2 (Geostationary Ocean Color Imager) of GK2B (Geostationary Korea Multi-purpose Satellite 2B) and the high-resolution images from the CAS500 (Compact Advanced Satellite) series soon.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2004.09a
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• pp.113-114
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• 2004

In order to classify the groundwater recharge characteristics in an urban area, a time series analysis of groundwater level data was performed. For this study, the daily groundwater level data from 35 monitoring wells were collected for 3 years (Fig. 1). The use of the cross-correlation function (CCF), one of the time series analysis, showed both the close relationship between rainfall and groundwater level change and the lag time (delay time) of groundwater level fluctuation after a rainfall event. Based on the result of CCF, monitored wells were classified into two major groups. Group I wells (n=10) showed a fast response of groundwater level change to rainfall event, with a delay time of maximum correlation between rainfall and groundwater level near 1 to 7 days. On the other hand, the delay time of 17-68 days was observed from Group II wells (n=25) (Fig. 1). The fast response in Group I wells is possibly caused by the change of hydraulic pressure of bedrock aquifer due to the rainfall recharge, rather than the direct response to rainfall recharge.

• Journal of the Korean earth science society
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• v.34 no.1
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• pp.69-80
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• 2013

Terrain data is one of important basic data in various areas of Earth science. Recently, finer DEM data is available, which necessary to develop a method that deals with such huge data efficiently. This study was conducted on the lossless compression of DEM data and efficient partial reconstruction of terrain information from compressed data. In this study, we compressed the wavelet coefficients of DEM, obtained from integer wavelet transform (IWT) by entropy encoding. CDF (Cohen-Daubechies-Feauveau) 3.5 wavelet showed the best compression ratio of about 45.4% and the optimum decomposition level was 3. Results also showed that a small region of terrain could be restored from the inverse wavelet transform with a part of the wavelet coefficients that are related to such region instead of whole reconstruction. We discussed the potential applications of the terrain data compression for precise gravity terrain correction.

• Journal of Environmental Science International
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• v.31 no.7
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• pp.617-635
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• 2022

The effect of coupled data assimilation (DA) on the meteorological prediction in the west coastal region of Korea was evaluated using a coupled atmosphere-ocean model (e.g., COAWST) in the spring (March 17-26) of 2019. We performed two sets of simulation experiments: (1) with the coupled DA (i.e., COAWST_DA) and (2) without the coupled DA (i.e., COAWST_BASE). Overall, compared with the COAWST_BASE simulation, the COAWST_DA simulation showed good agreement in the spatial and temporal variations of meteorological variables (sea surface temperature, air temperature, wind speed, and relative humidity) with those of the observations. In particular, the effect of the coupled DA on wind speed was greatly improved. This might be primarily due to the prediction improvement of the sea surface temperature resulting from the coupled DA in the study area. In addition, the improvement of meteorological prediction in COAWST_DA simulation was also confirmed by the comparative analysis between SST and other meteorological variables (sea surface wind speed and pressure variation).

• Journal of the Korean earth science society
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• v.23 no.2
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• pp.180-187
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• 2002

The aim of this study was to investigate the factors affecting earth science problem-solving performances of elementary school pre-service teachers. The participants of the study were 81 students attending an elementary school teacher education university. The instruments of the study were paper-and-pencil tests, questionnaires, and interviews. The tests mainly measured the participants' problem solving abilities in the motions of the moon and the planets. Correlation and multiple regression techniques were used for data analysis. The results demonstrated that the pre-service teachers' problem solving abilities were low. Problem-solving performances were affected by the procedural knowledge, the participants' perception of the past earth science performance, self-efficacy, and the prerequisite declarative knowledge. Contrary to our expectation, the spatial visualization ability was not found to be related to the problem-solving performances. Implications of the study are drawn, and suggestions are made for further research.

• Journal of the Korean earth science society
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• v.28 no.7
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• pp.825-837
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• 2007

The researchers compiled two sets of digital terrain data released by NORI (National Oceanographic Research Institute, Korea) and NIMA (National Imagery and Mapping Agency, USA) respectively and analyzed a new set of $3"{\times}3"$ gridded terrain data in order to calculate terrain correction value in gravity in and around the Korean Peninsula. Using this new set of terrain data, the researchers developed an effective algorithm to calculate precise terrain correction value in gravity considering Earth's curvature and coded a fortran program to evaluate terrain correction value covering the surface of which the radius reaches up to 166.735 km. The researchers also calculated terrain correction value over the southern part of Korea. According to the statistics of terrain correction value calculated in and around the Korean Peninsula up to 166.735 km of surface radius, the maximum value soars to 56.508 mGal and the mean value is 4.539 mGal.