• Journal of the Korean association of regional geographers
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• v.7 no.1
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• pp.35-50
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• 2001

Since remotely sensed images of coastal wetlands are very sensitive to spatial resolution, it is very important to select an optimum resolution for particular geographic phenomena needed to be represented. Scale is one of the most important factors in spatial analysis techniques, which is defined as a spatial and temporal interval for a measurement or observation and is determined by the spatial extent of study area or the measurement unit. In order to acquire the optimum scale for a particular subject (i.e., coastal wetlands), measuring and representing the characteristics of attribute information extracted from the remotely sensed images are required. This study aims to explore and analyze the scale effects of attribute information extracted from remotely sensed coastal wetlands images. Specifically, it is focused on identifying the effects of scale in response to spatial resolution changes and suggesting a methodology for exploring the optimum spatial resolution. The LANDSAT TM image of Sunchon Bay was classified by a supervised classification method, Six land cover types were classified and the Kappa index for this classification was 84.6%. In order to explore the effects of scale in the classification procedure, a set of images that have different spatial resolutions were created by a aggregation method. Coarser images were created with the original image by averaging the DN values of neighboring pixels. Sixteen images whose resolution range from 30 m to 480 m were generated and classified to obtain land cover information using the same training set applied to the initial classification. The values of Kappa index show a distinctive pattern according to the spatial resolution change. Up to 120m, the values of Kappa index changed little, but Kappa index decreased dramatically at the 150m. However, at the resolution of 240 m and 270m, the classification accuracy was increased. From this observation, the optimum resolution for the study area would be either at 240m or 270m with respect to the classification accuracy and the best quality of attribute information can be obtained from these resolutions. Procedures and methodologies developed from this study would be applied to similar kinds and be used as a methodology of identifying and defining an optimum spatial resolution for a given problem.

• Journal of the Korean Geographical Society
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• v.50 no.6
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• pp.607-619
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• 2015

It is important to detect trails accurately for finding a proper management. We examined the applicability of KOMPSAT imagery to detect trails and found that it could be an efficient alternative to track trails correctly. We selected K2 and K3 imagery with different spatial resolution. Then, we processed each imagery to get NDVI, SAVI, and SC data. And then, we identified trails by object-based analysis and network analysis. Finally, we evaluated the potential trails with F-measurement and Jaccard coefficient which are based on correctness and completeness. The results show that the applicability is quite different in each case. Among them, especially the SC data with K3 shows the most highest value; correctness of detecting legal trails is 0.44 and completeness of that is 0.54. F-measurement and Jaccard coefficient are 0.49 and 0.32. In general, although there is a limit in detecting trails by using only KOMPSAT imagery, the usefulness of KOMPSAT imagery can be a higher considering its cost efficiency and availability of acquiring periodic data.

• Journal of the Korean earth science society
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• v.39 no.6
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• pp.533-544
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• 2018

Rainfall is one of the most important meteorological variables in meteorology, agriculture, hydrology, natural disaster, construction, and architecture. Recently, satellite remote sensing is essential to the accurate detection, estimation, and prediction of rainfall. In this study, the accuracy of Integrated Multi-satellite Retrievals for GPM (IMERG) product, a composite rainfall information based on Global Precipitation Measurement (GPM) satellite was evaluated with ground observation data in the inland of Korea. The Automatic Weather Station (AWS)-based rainfall measurement data were used for validation. The IMERG and AWS rainfall data were collocated and compared during one year from January 1, 2016 to December 31, 2016. The coastal regions and islands were also evaluated irrespective of the well-known uncertainty of satellite-based rainfall data. Consequently, the IMERG data showed a high correlation (0.95) and low error statistics of Bias (15.08 mm/mon) and RMSE (30.32 mm/mon) in comparison to AWS observations. In coastal regions and islands, the IMERG data have a high correlation more than 0.7 as well as inland regions, and the reliability of IMERG data was verified as rainfall data.

• Journal of the Korean earth science society
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• v.40 no.5
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• pp.518-537
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• 2019

This study examined the implications of a place-based earth science program integrated with Mathematics. 11 pre-service earth science teachers and 22 middle school students participated in the service education activities of earth science for 30 hours focusing on the measurement of the earth's size through earth science experiments as part of the middle school curriculum. In order to minimize errors that may occur during the earth's size measurement experiments using Eratosthenes's shadows length method of the ancient Greek era, the actual data were collected after triangulation ratios were conducted in the locations of two middle schools: one in remote metropolitan and the other in rural area. The two schools' students shared the final estimate result. Through this process, they learned the mathematical method to express the actual data effectively. Participants, experienced the importance and difficulty of the repetitive and accurate data acquisition process, and also discussed the causes of errors included in the final results. It implies that a Place-Based Earth Science Program activity can contribute to students' increased-understanding of the characteristics of earth science inquiry and to developing their problem solving skills, thinking ability, and communication skills as well, which are commonly emphasized in science and mathematics in the 2015 reunion curriculum. It is expected that a place-based science program can provide a foundation for developing an integrated curriculum of mathematics and science.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.2
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• pp.96-109
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• 2021

Since terrestrial input plays a major role in coastal primary production, an understanding of land-ocean coupling (LOC) is key to understand coastal ecological changes. In this study, the LOC has been classified into three stages (i.e., the baseflow, plume event and residual flow). In order to characterize its pattern in Nakdong River estuary, multi-platform data were obtained from remote sensing (geostationary ocean color image (GOCI)), in-situ measurement (marine environment information system (MEIS)), on-site measurement (discharge data and meteorological data). The MEIS data were grouped into three stages of LOC using principal component analysis (PCA), and the LOC (2013 ~ 2018) was examined at each stage using multi-platform data. In the Nakdong River estuary, the maximum value of chlorophyll-a (chl-a) was unexpectedly appeared during the plume event. It is assumed that there was no significant increase in turbidity, expected during the typical plume event, together with the weak flushing effect, caused the enhanced phytoplankton growth. Compared with other estuaries, LOC is common in estuaries affected by freshwater inflow, but LOC has different pattern depending on the size of the plume. While estuaries that form small plumes of about 10 km (low freshwater discharge and weak flushing effect) observed high chl-a in the plume event because the phytoplankton can response to the increased nutrient more rapidly. estuaries that form large plumes of more than 100 km est (high freshwater discharge and strong flushing effect) follow the typical LOC pattern conceptualized in this study (high chl-a in the residual flow).

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.77-84
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• 2022

In this paper, we propose a system for monitoring air pollutants such as fine dust using an unmanned aerial vehicle capable of autonomous navigation. The existing air quality management system used a method of collecting information through a fixed sensor box or through a measurement sensor of a drone using a control device. This has disadvantages in that additional procedures for data collection and transmission must be performed in a limited space and for monitoring. In this paper, to overcome this problem, a GPS module for location information and a PMS7003 module for fine dust measurement are embedded in an unmanned aerial vehicle capable of autonomous navigation through flight information designation, and the collected information is stored in the SD module, and after the flight is completed, press the transmit button. It configures a system of one-stop structure that is stored in a remote database through a smartphone app connected via Bluetooth. In addition, an HTML5-based web monitoring page for real-time monitoring is configured and provided to interested users. The results of this study can be utilized in an environmental monitoring system through an unmanned aerial vehicle, and in the future, various pollutants measuring sensors such as sulfur dioxide and carbon dioxide will be added to develop it into a total environmental control system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.519-525
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• 2023

The human brain constantly emits electrical impulses, which is called brain waves, and brain waves can be defined as the electrical activity of the brain generated by the flow of ions generated by the biochemical interaction of brain cells. There is a study that emotion is one of the factors that can cause stress. Brain waves are the most used in the study of emotions. This paper is a study on whether emotions affect stress, and showed two images of fear and joy to four experimenters and divided them into three stages before, during, and after watching. As a measurement tool, brain waves at the positions of Fp1 and Fp2 were measured using the NeuroBrain System, a system that can automate brain wave measurement, analysis, brain wave reinforcement, and suppression training with remote control. After obtaining the brain wave data for each emotion, the average value was calculated and the study was conducted. As for the frequency related to stress, the values of Alpha and SMR, Low Beta, and High Beta were analyzed. Brainwave analysis affects stress depending on the emotional state, and "fear" emotions cause anxiety by raising Beta levels, resulting in higher Mind Stress levels, while "joy" emotions lower Beta levels, resulting in a significant drop in Mind Stress.

• Journal of Korea Water Resources Association
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• v.57 no.9
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• pp.615-626
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• 2024

To accurately and efficiently monitor soil moisture (SM) across South Korea, this study developed a SM estimation model that integrates the cloud computing platform Google Earth Engine (GEE) and Automated Machine Learning (AutoML). Various spatial information was utilized based on Terra MODIS (Moderate Resolution Imaging Spectroradiometer) and the global precipitation observation satellite GPM (Global Precipitation Measurement) to test optimal input data combinations. The results indicated that GPM-based accumulated dry-days, 5-day antecedent average precipitation, NDVI (Normalized Difference Vegetation Index), the sum of LST (Land Surface Temperature) acquired during nighttime and daytime, soil properties (sand and clay content, bulk density), terrain data (elevation and slope), and seasonal classification had high feature importance. After setting the objective function (Determination of coefficient, R² ; Root Mean Square Error, RMSE; Mean Absolute Percent Error, MAPE) using AutoML for the combination of the aforementioned data, a comparative evaluation of machine learning techniques was conducted. The results revealed that tree-based models exhibited high performance, with Random Forest demonstrating the best performance (R² : 0.72, RMSE: 2.70 vol%, MAPE: 0.14).

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.629-637
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• 2016

In this present study, we identified the $SO_2$ effect on $O_3$ retrieval from the Ozone Monitoring Instrument (OMI) measurement over Chinese Industrial region from 2005 through 2007. The Planetary boundary layer (PBL) $SO_2$ data measured by OMI sensor is used in this present study. OMI-Total Ozone Mapping Spectrometer (TOMS) total $O_3$ is compared with OMI-Differential Optical Absorption Spectrometer (DOAS) total $O_3$ in various $SO_2$ condition in PBL. The difference between OMI-TOMS and OMI-DOAS total $O_3$ (T-D) shows dependency on $SO_2$ (R (Correlation coefficient) = 0.36). Since aerosol has been reported to cause uncertainty of both OMI-TOMS and OMI-DOAS total $O_3$ retrieval, the aerosol effect on relationship between PBL $SO_2$ and T-D is investigated with changing Aerosol Optical Depth (AOD). There is negligible aerosol effect on the relationship showing similar slope ($1.83{\leq}slope{\leq}2.36$) between PBL $SO_2$ and T-D in various AOD conditions. We also found that the rate of change in T-D per 1.0 DU change in PBL, middle troposphere (TRM), and upper troposphere and stratosphere (STL) are 1.6 DU, 3.9 DU and 4.9 DU, respectively. It shows that the altitude where $SO_2$ exist can affect the value of T-D, which could be due to reduced absolute radiance sensitivity in the boundary layer at 317.5 nm which is used to retrieve OMI-TOMS ozone in boundary layer.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.2035-2046
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• 2021

Glacier movement speed is the most basic measurement for glacial dynamics research and is a very important indicator in predicting sea level rise due to climate change. In this study, the two-dimensional velocity measurements of Campbell Glacier located in Terra Nova Bay in East Antarctica were observed through the SAR offset tracking technique. For this purpose, domestic KOMPSAT-5 SAR satellite images taken on July 9, 2021 and August 6, 2021 were acquired. The Multi-kernel SAR offset tracking proposed through previous studies is a technique to obtain the optimal result that satisfies both resolution and precision. However, since offset tracking is repeatedly performed according to the size of the kernel, intensive computational power and time are required. Therefore, in this study, we strategically proposed a coarse-to-fine offset tracking approach. Through coarse-to-fine SAR offset tracking, it is possible to obtain a result with improved observation precision (especially, about 4 times in azimuth direction) while maintaining resolution compared to general offset tracking results. Using this proposed technique, a two-dimensional velocity measurements of Campbell Glacier were generated. As a result of analyzing the two-dimensional movement velocity image, it was observed that the grounding line of Campbell Glacier exists at approximately latitude -74.56N. The flow velocity of Campbell Glacier Tongue analyzed in this study (185-237 m/yr) increased compared to that of 1988-1989 (140-240 m/yr). And compared to the flow velocity (181-268 m/yr) in 2010-2012, the movement speed near the ground line was similar, but it was confirmed that the movement speed at the end of the Campbell Glacier Tongue decreased. However, there is a possibility that this is an error that occurs because the study result of this study is an annual rate of glacier movement that occurred for 28 days. For accurate comparison, it will be necessary to expand the data in time series and accurately calculate the annual rate. Through this study, the two-dimensional velocity measurements of the glacier were observed for the first time using the KOMPSAT-5 satellite image, a domestic X-band SAR satellite. It was confirmed that the coarse-to-fine SAR offset tracking approach of the KOMPSAT-5 SAR image is very useful for observing the two-dimensional velocity of glacier movements.