• Journal of the Korean earth science society
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• v.28 no.1
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• pp.123-135
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• 2007

Five episodes of the large-scale transport of air pollutants in East Asia and its inflow into the Korean Peninsula have been analyzed through satellite and ground observations. These episodes include regionally polluted continental airmass, which is created by the pollutants produced in the cities and the industrial regions in China, to land on or pass through the Korean Peninsula by way of the Yellow Sea. The analysis of the NOAA satellite observation data made it possible to create images by combining 3 channels of visible and infrared ray ranges and also to identify the distribution and the transport of the air pollution mass over the Yellow Sea. The ground observation data of the air pollutants gathered in Chongwon were found highly valuable in verifying the information in comparison with ones from the satellite. Especially, regarding the episodes of large-scale transport of the air pollutants, the difference of concentration between $PM_{10}\;and\;PM_{2.5}$ was found small with the increase of $PM_{2.5}$ value. The concentration of $PM_{10}$ in the episode of yellows and, however, was found much higher than that of $PM_{2.5}$. In the episode of 27 January 2006, the inflow of the regionally polluted continental air mass into the central and southwestern region of the Korean Peninsula was observed sequentially in the various ground observatories as well as by the satellite. The north-northwest airflow dissipated the clouds over from Mt. Halla in Jeju Island up to far downwind, reduced air pollution, and created von $K\acute{a}rm\acute{a}n$ vortex.

• Journal of the Korean Society of Marine Environment & Safety
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• v.14 no.2
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• pp.163-168
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• 2008

Ship detection from satellite remote sensing is a crucial application for global monitoring for the purpose of protecting the marine environment and ensuring marine security. It permits to monitor sea traffic including fisheries, and to associate ships with oil discharge. An automatic ship detection approach for RADARSAT Fine Synthetic Aperture Radar (SAR) image is described and assessed using in situ ship validation information collected during field experiments conducted on August 6, 2004. Ship detection algorithms developed here consist of five stages: calibration, land masking, prescreening, point positioning, and discrimination. The fine image was acquired of Ulsan Port, located in southeast Korea, and during the acquisition, wind speeds between 0 m/s and 0.4 m/s were reported. The detection approach is applied to anchoring ships in the anchorage area of the port and its results are compared with validation data based on Vessel Traffic Service (VTS) radar. Our analysis for anchoring ships, above 68 m in length (LOA), indicates a 100% ship detection rate for the RADARSAT single beam mode. It is shown that the ship detection performance of SAR for smaller ships like barge could be higher than the land-based radar. The proposed method is also applied to estimate the ship's dimensions of length and breadth from SAR radar cross section(RCS), but those values were comparatively higher than the actual sizes because of layover and shadow effects of SAR.

• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.121-133
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• 2005

Texture imaging, which means texture image creation by co-occurrence relation, has been known as one of the useful image analysis methodologies. For this purpose, most commercial remote sensing software provides texture analysis function named GLCM (Grey Level Co-occurrence Matrix). In this study, texture-imaging program based on GLCM algorithm is newly implemented. As well, texture imaging modules for GLDV (Grey Level Difference Vector) are contained in this program. As for GLCM/GLDV Texture imaging parameters, it composed of six types of second order texture functions such as Homogeneity, Dissimilarity, Energy, Entropy, Angular Second Moment, and Contrast. As for co-occurrence directionality in GLCM/GLDV, two direction modes such as Omni-mode and Circular mode newly implemented in this program are provided with basic eight-direction mode. Omni-mode is to compute all direction to avoid directionality complexity in the practical level, and circular direction is to compute texture parameters by circular direction surrounding a target pixel in a kernel. At the second phase of this study, some case studies with artificial image and actual satellite imagery are carried out to analyze texture images in different parameters and modes by correlation matrix analysis. It is concluded that selection of texture parameters and modes is the critical issues in an application based on texture image fusion.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1255-1272
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• 2023

Satellite-based chlorophyll-a concentration, produced as a long-term time series, is crucial for global climate change research. The production of data without gaps through the merging of time-synthesized or multi-satellite data is essential. However, studies related to satellite-based chlorophyll-a concentration in the waters around the Korean Peninsula have mainly focused on evaluating seasonal characteristics or proposing algorithms suitable for research areas using a single ocean color sensor. In this study, a merging dataset of remote sensing reflectance from the geostationary sensor GOCI-II and polar-orbiting sensors (MODIS, VIIRS, OLCI) was utilized to achieve high spatial coverage of chlorophyll-a concentration in the waters around the Korean Peninsula. The spatial coverage in the results of this study increased by approximately 30% compared to polar-orbiting sensor data, effectively compensating for gaps caused by clouds. Additionally, we aimed to quantitatively assess accuracy through comparison with global chlorophyll-a composite data provided by Ocean Colour Climate Change Initiative (OC-CCI) and GlobColour, along with in-situ observation data. However, due to the limited number of in-situ observation data, we could not provide statistically significant results. Nevertheless, we observed a tendency for underestimation compared to global data. Furthermore, for the evaluation of practical applications in response to marine disasters such as red tides, we qualitatively compared our results with a case of a red tide in the East Sea in 2013. The results showed similarities to OC-CCI rather than standalone geostationary sensor results. Through this study, we plan to use the generated data for future research in artificial intelligence models for prediction and anomaly utilization. It is anticipated that the results will be beneficial for monitoring chlorophyll-a events in the coastal waters around Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.151-161
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• 2003

The spatiotemporal distribution of resuspended solid on the shelf of the southern Yellow Sea and the northern East China Sea was studied. The sea surface reflectance imageries obtained by remote sensing using satellite at channels of red (620~670nm), green(545~565nm) and blue(459~479nm) from Terra MODIS were used to explain the front of the high concentration suspended solid(SS) on the shelf in the East China Sea. The horizontal distribution of the resuspended solid was depended on the wind force, tidal current and stratification of water. The horizontal distribution areas of the resuspended solid in winter season during January~April, 2002 were three times wider than those in summer season during June~September, 2001.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.145-157
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• 2015

In 2015, drought was at the worst stage of devastation in Soyanggang Dam watershed. The purpose of this study is to trace the drought area around Soyanggang dam watershed by using Terra MODIS image because it has the ability of spatio-temporal dynamics. The MODIS indices, which included the enhanced vegetation index (NDVI), were extracted from MODIS product MOD13 16-day composite datasets with a spatial resolution of 250m from 2010.01.01 to 2015.06.30. We found that application of Vegetation Condition Index (VCI) and Standardized Vegetation Index (SVI) was suitable for monitoring the drought area. The result can be used to acquire the drought data scattered and demonstrate the potential for the use of MODIS data for temporal and spatial detection of drought effects.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.246-246
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• 2021

본 연구는 강우 발생시 유량을 추정하는 것에 목적이 있다. 이를 위해 본 연구는 선행연구의 모형 개발방법론에서 벗어나 딥러닝 알고리즘 중 하나인 합성곱 신경망 (convolution neural network)과 수문학적 이미지 (hydrological image)를 이용하여 강우 발생시 유량을 추정하였다. 합성곱 신경망은 일반적으로 분류 문제 (classification)을 해결하기 위한 목적으로 개발되었기 때문에 불특정 연속변수인 유량을 모의하기에는 적합하지 않다. 이를 위해 본 연구에서는 합성곱 신경망의 완전 연결층 (Fully connected layer)를 개선하여 연속변수를 모의할 수 있도록 개선하였다. 대부분 합성곱 신경망은 RGB (red, green, blue) 사진 (photograph)을 이용하여 해당 사진이 나타내는 것을 예측하는 목적으로 사용하지만, 본 연구의 경우 일반 RGB 사진을 이용하여 유출량을 예측하는 것은 경험적 모형의 전제(독립변수와 종속변수의 관계)를 무너뜨리는 결과를 초래할 수 있다. 이를 위해 본 연구에서는 임의의 유역에 대해 2차원 공간에서 무차원의 수문학적 속성을 갖는 grid의 집합으로 정의되는 수문학적 이미지는 입력자료로 활용했다. 합성곱 신경망의 구조는 Convolution Layer와 Pulling Layer가 5회 반복하는 구조로 설정하고, 이후 Flatten Layer, 2개의 Dense Layer, 1개의 Batch Normalization Layer를 배열하고, 다시 1개의 Dense Layer가 이어지는 구조로 설계하였다. 마지막 Dense Layer의 활성화 함수는 분류모형에 이용되는 softmax 또는 sigmoid 함수를 대신하여 회귀모형에서 자주 사용되는 Linear 함수로 설정하였다. 이와 함께 각 층의 활성화 함수는 정규화 선형함수 (ReLu)를 이용하였으며, 모형의 학습 평가 및 검정을 판단하기 위해 MSE 및 MAE를 사용했다. 또한, 모형평가는 NSE와 RMSE를 이용하였다. 그 결과, 모형의 학습 평가에 대한 MSE는 11.629.8 m3/s에서 118.6 m3/s로, MAE는 25.4 m3/s에서 4.7 m3/s로 감소하였으며, 모형의 검정에 대한 MSE는 1,997.9 m3/s에서 527.9 m3/s로, MAE는 21.5 m3/s에서 9.4 m3/s로 감소한 것으로 나타났다. 또한, 모형평가를 위한 NSE는 0.7, RMSE는 27.0 m3/s로 나타나, 본 연구의 모형은 양호(moderate)한 것으로 판단하였다. 이에, 본 연구를 통해 제시된 방법론에 기반을 두어 CNN 모형 구조의 확장과 수문학적 이미지의 개선 또는 새로운 이미지 개발 등을 추진할 경우 모형의 예측 성능이 향상될 수 있는 여지가 있으며, 원격탐사 분야나, 위성 영상을 이용한 전 지구적 또는 광역 단위의 실시간 유량 모의 분야 등으로의 응용이 가능할 것으로 기대된다.

• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.205-208
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• 2006

Based on SAR signatures for bars, bar transformation is investigated from 2000 to 2005, and monitoring of suspended-silt transportations from terrestrial runoff is tried to understand the morphology during the events of severe rain storm. SAR data did not reveal clearly the bar locations because of most of data acquisitions during high tides form 6.8 m to 9.0 m. Even though the problem, it could be said that in the estuary vegetated area and natural levees are developed well, but bars are shifted after an event like a flood. It is also showed that suspended solids such as silt transported through the estuary could contributed highly to a sedimentation environment around Incheon. A navigational route could be designed with a minimum width of about 200m.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.1 s.31
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• pp.63-69
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• 2005

Interferometric Synthetic Aperture Radar(InSAR) is a rapidly evolving technique. Spectacular results obtained in various fields such as the monitoring of earthquakes, volcanoes, land subsidence and glacier dynamics, as well as in the construction of Digital Elevation Models(DEMs) of the Earth's surface and the classification of different land types have demonstrated its strength. As InSAR is a remote sensing technique, it has various sources of errors due to the satellite positions and attitude, atmosphere, and others. Therefore, it is important to validate its accuracy, especially for the DEM derived from Satellite SAR images. In this study, Real Time Kinematic(RTK) GPS and Kinematic GPS positioning were chosen as tools for the validation of InSAR derived DEM. The results showed that Kinematic GPS positioning had greater coverage of test area in terms of the number of measurements than RTK GPS. But tracking the satellites near and/or under trees md transmitting data between reference and rover receivers are still pending tasks in GPS techniques.

• 한국지구과학회:학술대회논문집
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• 2010.04a
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• pp.37-37
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• 2010

2008년 동아시아 대륙에서 발생기원이 다른 황사와 인위적 오염입자의 광역적 이동 사례를 NOAA위성 RGB 합성영상과 지상 TSP, PM10, PM2.5 질량농도 관측으로 구별하였다. 또한 Terra/Aqua 위성MODIS (MODerate Imaging Spectroradiometer) 센서의AOD (Aerosol Optical Depth)와 FW (Fine aerosol Weighting)를 통해 동아시아 지역에서 발생기원이 다른 대기 에어로졸의 분포와 입자 크기 특성을 분석하였다. 중국 북부와 몽골, 그리고 중국 황토고원에서 모래폭풍이 발생하여 광역적으로 이동하여 청원에 먼지입자(황사)로 영향을 주는 6 사례를 분석했다. 질량농도 TSP중 PM10 은 70%, PM2.5 는 16% 로 조대입자 (> $2.5{\mu}m$)의 비율이 큰 것은 사막과 반사막의 자연적 발생원에서 생성되었기 때문이다. 그러나, 모래 폭풍이 이동 과정에서 중국 동부의 산업 지역을 거쳐 유입 되는 사례에서는 TSP 중 PM2.5 가 23% 까지 증가하기도 했다. 중국 동부로부터 황해를 거쳐 한반도로 유입하고 있는 다른5사례는 TSP 중 PM10, PM2.5가 각각 82%, 65% 로 PM2.5 의 비율이 높았는데 인위적 오염입자의 영향 때문이다. 동아시아 지역에서 인위적 오염입자의 광역적 이동 사례에 대한 평균 AOD는 $0.42{\pm}0.17$로 황사에 의한 AOD ($0.36{\pm}0.13$)와 비교하여 대기 에어로졸에 대한 비율이 높게 나타났다. 특히, 중국 동부에서 황해, 한반도, 동해에 이르는 광역적 지역에 높은 AOD값이 분포했다. 인위적 오염입자의 사례는 FW가 평균 $0.63{\pm}0.16$로 모래폭풍의 이동 사례의 $0.52{\pm}0.13$ 보다 높은 값을 보이고 있어, 대기 에어로졸에 대한 인위적 미세 오염입자의 기여가 크게 나타나고 있었다.