• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.1
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• pp.34-39
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• 2015

KCG, responsible Agency of maritime SAR operation has been known to address the marine casualties well, however, it was criticized because KCG failed to take prompt and effective response to the recent Ferry disaster at the very early stage. In this regards, the authors analyze the characteristics of marine incident with historical data, and also review and examine the national SAR system focusing on SAR coordination and human resources to make recommendation and suggestion in order to minimize the loss of lives to future marine incidents. As a result, KCG shall augment its capabilities, inter alia, fast libeboats and rescue helicopters for prompt response to marine incidents at the coastal waters, and KCG shall re-adjust the establishment of Rescue Coordination Center to improve operational problems of current system in accordance with IMO guidance, KCG is required to introduce mandatory training, qualification and certificate system to enhance the professionalism of SAR personnel.

• Journal of Korean Society of societal Security
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• v.2 no.2
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• pp.85-90
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• 2009

In recent days, climatic change cause abnormal weather all over the world and we have a great loss of life and property every year. In Korea, we suffer from landslide problem because large regions of Korea Peninsula are composed of mountain. In order to detect rapidly and to take follow-up measures of disaster, the remote sensing is being used actively as conventional field survey has many restrictions in accessibility because of more time and man power requirement. In additions interferometric SAR is one of the techniques that have our attention because it can provide many kinds of accurate surface information without restriction of atmospheric and ground conditions by using L-band. In this study, we aimed to monitor the displacement of mountain area in Kangwondo and this results will be used for detecting landslide. Also we build the web system for detecting and analyzing the landslide.

• Journal of the Korean earth science society
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• v.31 no.5
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• pp.475-487
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• 2010

Sea surface wind field was retrieved from high-resolution SIR-C SAR data by using CMOD algorithms off the east coast of Korea. In order to extract wind direction information from SAR data, a two-dimensional spectral analysis method was applied to the normalized radar cross section of the image. An $180^{\circ}$-ambiguity problem in the determination of wind direction was solved by selecting a direction nearest to the wind vector of the ECMWF reanalysis data. Comparison of the wind retrieval patterns with the ECMWF and NCEP/NCAR dataset showed RMS errors in the range of 1.30 to $1.72\;ms^{-1}$. In contrast, comparison of wind directions revealed large errors of greater than $60^{\circ}$, which is enormously higher than the permitted limit of about $20^{\circ}$ for satellite scatterometer winds. Compared with wind speed results from different algorithms, wind vectors based on commonly-used CMOD4 algorithm showed good agreement with those derived by other algorithms such as CMOD_IFR2 and CMOD5, particularly at medium winds from 4 to $8\;ms^{-1}$. However, apparent discrepancy appeared at low winds (< $4\;ms^{-1}$). This study also addressed an importance of accurate wind direction data to improve the accuracy of wind speed retrieval and discussed potential causes of wind retrieval errors from SAR data.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.33-41
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• 2003

Every year, several typhoons hit the Korean peninsula and cause severe damage. For the prevention and accurate estimation of these damages, real time or almost real time flood information is essential. Because of weather conditions, images taken by optic sensors or LIDAR are sometimes not appropriate for an accurate estimation of water areas during typhoon. In this case SAR (Synthetic Aperture Radar) images which are independent of weather condition can be useful for the estimation of flood areas. To get detailed information about floods from satellite imagery, accurate classification of water areas is the most important step. A commonly- and widely-used classification methods is the ML(Maximum Likelihood) method which assumes that the distribution of brightness values of the images follows a Gaussian distribution. The distribution of brightness values of the SAR image, however, usually does not follow a Gaussian distribution. For this reason, in this study the ANN (Artificial Neural Networks) method independent of the statistical characteristics of images is applied to the SAR imagery. RADARS A TSAR images are primarily used for extraction of water areas, and DEM (Digital Elevation Model) is used as supplementary data to evaluate the ground undulation effect. Water areas are also extracted from KOMPSAT image achieved by optic sensors for comparison purpose. Both ANN and ML methods are applied to flat and mountainous areas to extract water areas. The estimated areas from satellite imagery are compared with those of manually extracted results. As a result, the ANN classifier performs better than the ML method when only the SAR image was used as input data, except for mountainous areas. When DEM was used as supplementary data for classification of SAR images, there was a 5.64% accuracy improvement for mountainous area, and a similar result of 0.24% accuracy improvement for flat areas using artificial neural networks.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.39-47
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• 2017

The SAR payload of the KOMPSAT-5 is equipped with an X-band (9.66GHz) microwave-based sensor. Especially, since it has a fixed antenna that can be electronically steered with respect to the azimuth and elevation planes, various applications are expected. This study evaluates the production performance and the accuracy of the DEM by producing DEM using the HR and UH mode images of KOMPSAT-5. To evaluate the production performance of the DEM, the sensitivity of DEM was assessed through a baseline analysis and $2{\pi}$ ambiguity; it was found to have good production performance. In addition, to evaluate the accuracy of the produced DEM, 30 check points were compared with SRTM data. As a result, STDEV ${\pm}15-20m$ accuracy was obtained. If the accuracy of the DEM is improved by adjusting the parameters of the filtering method or phase unwrapping method in the future, it will be possible to widely use the KOMPSAT-5 image for environmental and disaster monitoring.

• Journal of electromagnetic engineering and science
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• v.16 no.2
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• pp.87-99
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• 2016

This paper describes an implementation method and the results of numerical mobile phone models representing real phone models that have been released on the Korean market since 2002. The aim is to estimate the electromagnetic absorption in the human brain for case-control studies to investigate health risks related to mobile phone use. Specific absorption rate (SAR) compliance test reports about commercial phone models were collected and classified in terms of elements such as the external body shape, the antenna, and the frequency band. The design criteria of a numerical phone model representing each type of phone group are as follows. The outer dimensions of the phone body are equal to the average dimensions of all commercial models with the same shape. The distance and direction of the maximum SAR from the earpiece and the area above -3 dB of the maximum SAR are fitted to achieve the average obtained by measuring the SAR distributions of the corresponding commercial models in a flat phantom. Spatial peak 1-g SAR values in the cheek and tilt positions against the specific anthropomorphic mannequin phantom agree with average data on all of the same type of commercial models. Second criterion was applied to only a few types of models because not many commercial models were available. The results show that, with the exception of one model, the implemented numerical phone models meet criteria within 30%.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.152-152
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• 2019

This study demonstrates a novel approach of remotely sensed estimates of stream flow at fifteen hydrological station in the Han River Basin, Korea. Multi-temporal data of the European Space Agency's Sentinel-1 SAR satellite from 19 January, 2015 to 25 August, 2018 is used to develop and validate the flow estimation model for each station. The flow estimation model is based on a power law relationship established between the remotely sensed surface area of water at a selected reach of the stream and the observed discharge. The satellite images were pre-processed for thermal noise, radiometric, speckle and terrain correction. The difference in SAR image brightness caused by the differences in SAR satellite look angle and atmospheric condition are corrected using the histogram matching technique. Selective area filtering is applied to identify the extent of the selected stream reach where the change in water surface area is highly sensitive to the change in stream discharge. Following this, an iterative procedure called the Optimum Threshold Classification Algorithm (OTC) is applied to the multi-temporal selective areas to extract a series of water surface areas. It is observed that the extracted water surface area and the stream discharge are related by the power law equation. A strong correlation coefficient ranging from 0.68 to 0.98 (mean=0.89) was observed for thirteen hydrological stations, while at two stations the relationship was highly affected by the hydraulic structures such as dam. It is further identified that the availability of remotely sensed data for a range of discharge conditions and the geometric properties of the selected stream reach such as the stream width and side slope influence the accuracy of the flow estimation model.

• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.617-623
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• 2019

Numerous water disasters have recently occurred all over the world, including South Korea, due to global climate change in recent years. As water-related disasters occur extensively and their sites are difficult for people to access, it is necessary to monitor them using satellites. The Ministry of Environment and K-water plan to launch the next-generation medium satellite No. 5 (water resource/water disaster satellite) equipped with C-band synthetic aperture radar (SAR) in 2025. C-band SAR has the advantage of being able to observe water resources twice a day at a high resolution both day and night, regardless of weather conditions. Currently, RADARSAT-2 and Sentinel-1 equipped with C-band SAR achieve the purpose of their launch and are used in various environmental fields such as forest structure detection and coastline change monitoring, as well as for unique purposes including the detection of flooding, drought and soil moisture change, utilizing the advantages of SAR. As such, this study aimed to analyze the characteristics of the next-generation medium satellite No. 5 and its application in environmental fields. Our findings showed that it can be used to improve the degree of precision of existing environmental spatial information such as the classification accuracy of land cover map in environmental field works. It also enables us to observe forests and water resources in North Korea that are difficult to access geographically. It is ultimately expected that this will enable the monitoring of the whole Korean Peninsula in various environmental fields, and help in relevant responses and policy supports.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.5
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• pp.89-99
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• 2019

In this study, we estimated the spatially-distributed soil moisture at the high resolution ($10m{\times}10m$) using the satellite-based Sentinel-1A/B SAR (Synthetic Aperture Radar) sensor images. The Sentinel-1A/B raw data were pre-processed using the SNAP (Sentinel Application Platform) tool provided from ESA (European Space Agency), and then the pre-processed data were converted to the backscatter coefficients. The regression equations were derived based on the relationships between the TDR (Time Domain Reflectometry)-based soil moisture measurements and the converted backscatter coefficients. The TDR measurements from the 51 RDA (Rural Development Administration) monitoring sites were used to derive the regression equations. Then, the soil moisture values were estimated using the derived regression equations with the input data of Sentinel-1A/B based backscatter coefficients. Overall, the soil moisture estimates showed the linear trends compared to the TDR measurements with the high Pearson's correlations (more than 0.7). The Sentinel-1A/B based soil moisture values matched well with the TDR measurements with various land surface conditions (bare soil, crop, forest, and urban), especially for bare soil (R: 0.885~0.910 and RMSE: 3.162~4.609). However, the Mandae-ri (forest) and Taean-eup (urban) sites showed the negative correlations with the TDR measurements. These uncertainties might be due to limitations of soil surface penetration depths of SAR sensors and complicated land surface conditions (artificial constructions near the TDR site) at urban regions. These results may infer that qualities of Sentinel-1A/B based soil moisture products are dependent on land surface conditions. Although uncertainties exist, the Sentinel-1A/B based high-resolution soil moisture products could be useful in various areas (hydrology, agriculture, drought, flood, wild fire, etc.).

• Journal of Aerospace System Engineering
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• v.16 no.5
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• pp.49-56
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• 2022

S-STEP is a small SAR satellite mission that monitors time-limited emergency targets and military anomalies in areas of interest, achieving the average revisit in less than 30 minutes by deploying a constellation of 32 satellites in low orbit at an altitude of 510 km. The mission operation mode of S-STEP is divided into normal mode, observation mode, communication mode, and orbit maintenance mode. Further,, the attitude control mode is subdivides into initial detumbling, sun pointing, target pointing, ground station pointing, and thrust direction maintenance. Based on the preliminary mission operational scenario and the satellite's characteristics, this study analyzed the attitude control performance during initial detumbling and observation modes. It verifies that each mode's attitude control accuracy requirements within the time allotted by the scenario of the S-STEP achieved.