• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.520-523
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• 2022

일본 우주항공연구개발기구(Japan Aerospace Exploration Agency, JAXA)는 2007년부터 2017년까지 달 탐사선 셀레네(Selenological and Engineering Explorer, SelEnE)가 관측한 데이터를 수집하고, 연구했다. JAXA는 지구 상층 대기에 존재하는 산소가 자기장의 꼬리 부분에 실려 달로 이동한다는 사실을 발견했다. 하지만 이 연구는 아직 진행 중이며 달의 산화 과정 규명에 추가 연구가 필요하다. 본 논문에서는 생성적 적대 신경망(Generative Adversarial Networks, GAN)으로 달 분화구의 영구 그림자 영역을 제거하고, 물과 얼음을 발견하여 선행 연구의 완성도를 향상하고자 한다. 실험에 사용할 모델은 CIPS(Conditionally Independent Pixel Synthesis)다. CIPS는 실제 같은 영상을 고해상도로 합성한다. 합성할 데이터의 최적인 가중치 초기화 및 파라미터 갱신 방법, 활성 함수 조합은 실험을 통해 확인한다. 필요에 따라 앙상블 학습을 할 수도 있다. 성능평가는 FID(Frechet Inception Distance), 정밀도, 재현율을 사용한다. 제안한 방법은 진행 중인 연구의 시간과 비용을 절약하고, 인과관계를 더욱 명확히 밝히는 데 도움 될 수 있다고 사료된다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.104-105
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• 2023

해양 관측과 위성 원격탐사를 이용하여 시공간적으로 다양하게 변하는 생태 어장 환경 및 선박 관련 자료를 획득할 수 있다. 이번 연구의 주요 목적은 야간 불빛 위성 자료를 이용하여 광범위한 해역에 대한 어선의 위치 분포를 파악하는 딥러닝 기반 모델을 제안하는 것이다. 제안한 모델의 정확성을 평가하기 위해 야간 조업 어선의 위치를 포함하고 있는 AIS(Automatic Identification System) 정보와 상호 비교 평가 하였다. 이를 위해, 먼저 AIS 자료를 획득 및 분석하는 방법을 소개한다. 해양안전종합시스템(General Information Center on Maritime Safety & Security, GICOMS)으로부터 제공받은 AIS 자료는 동적정보와 정적정보로 나뉜다. 동적 정보는 일별 자료로 구분되어있으며, 이 정보에는 해상이동업무식별번호(Maritime Mobile Service Identity, MMSI), 선박의 시간, 위도, 경도, 속력(Speed over Ground, SOG), 실침로(Course over Ground, COG), 선수방향(Heading) 등이 포함되어 있다. 정적정보는 1개의 파일로 구성되어 있으며, 선박명, 선종 코드, IMO Number, 호출부호, 제원(DimA, DimB, DimC, Dim D), 홀수, 추정 톤수 등이 포함되어 있다. 이번 연구에서는 선박의 정보에서 어선의 정보를 추출하여 비교 자료로 사용하였으며, 위성 자료는 구름의 영향이 없는 깨끗한 날짜의 영상 자료를 선별하여 사용하였다. 야간 불빛 위성 자료, 구름 정보 등을 이용하여 야간 조업 어선의 불빛을 감지하는 심층신경망(Deep Neural Network; DNN) 기반 모델을 제안하였다. 본 연구의결과는 야간 어선의 분포를 감시하고 한반도 인근 어장을 보호하는데 기여할 것으로 기대된다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1089-1095
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• 2023

Windows are essential and important architectural elements for the organization of architectural spaces, and they give character to the space and have a great impact on the reaction of users. Virtual windows are installed to activate architectural spaces such as underground spaces where windows cannot be installed, and to provide a sense of psychological security to users in hospital clinics, etc. In this study, we reviewed the literature and collected and analyzed the precedents of virtual windows to discuss the factors necessary to improve the realism of virtual windows. The factors that affect the realism of virtual windows are further grouped into five categories: 1. Use of reproduced images or videos for views, 2. Representation of temporality, 3. Responsiveness to changes in the observer's perspective, 4. Realistic reproduction of sunlight, and 5. Provision of non-visual sensory elements. Virtual windows are not just a replacement for traditional windows, but a way to realize a virtual environment using digital media, and it is necessary to expand the discussion to the realization of the virtual environment and the relationship with architectural elements.

• Journal of the Korean Society for Marine Environment & Energy
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• v.18 no.3
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• pp.166-178
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• 2015

We investigated marine environmental characteristics of Goheung coastal areas in August where is known to be the first outbreak site of Cochlodinium polykrikoides (hereafter C. polykrikoides) blooms, based on the oceanographic data observed from 1993 to 2013 around the Korean southern coastal waters including Eastern China Sea by National Fisheries Research and Development Institute (NFRDI). The data of NOAA/NGSST satellite images as well as numerical simulation results by Seo et al. [2013] were also used for analysis. Water temperatures at the surface and bottom layers in Goheung coast, i.e. Narodo, were $25.0^{\circ}C$ and $23.7^{\circ}C$ so that they were higher than $23.8^{\circ}C$ and $19.4^{\circ}C$ in Geoje coast where is a reference site, respectively. In addition, salinities at the surface and bottom layers in Goheung coast were 31.78 psu and 31.98 psu so that they were a little higher than 31.54 psu at the surface but a little lower than 32.79 psu at the bottom in Geoje coast, respectively. That is, the differences in water temperature or salinity between the surface and bottom layers in Goheung coast in August were not large compared to Geoje coast. This suggests that stratification in Goheung coast in August is fairly weak or may not be established. In addition, the concentrations of DIN and DIP at the surface layer were 0.068 mg/L ($4.86{\mu}M$) and 0.015 mg/L ($5.14{\mu}M$) in Goheung coast while 0.072 mg/L ($5.14{\mu}M$) and 0.01 mg/L ($0.32{\mu}M$) in Geoje coast, so they did not indicate a meaningful difference. On the other hand, when C. polykrikoides blooms, water temperature and salinity in August at the station 317-22 ($31.5^{\circ}N$, $124^{\circ}E$) of the East China Sea, where is near the mouth of Yangtze River, were $27.8^{\circ}C$ and 31.61 psu, respectively. Thus, water temperature was much higher whereas salinity was almost similar compared to Goheung coast. Furthermore, concentrations of $NO_3-N$ and $PO_4-P$ in the East China Sea in August were remarkably high compared to Goheung coast. When C. polykrikoides blooms, according to not only the image data of satellites NOAA/NGSST but also numerical experiment results by Seo et al.[2013], the freshwater out of Yangtze River was judged to clearly affect the Korean southern coastal waters. Therefore, the supply of nutrients in terms of Yangtze River may greatly contribute to the outbreak of C. polykrikoides blooms in Goheung coast in summer.

• Journal of the Korean earth science society
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• v.40 no.5
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• pp.447-463
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• 2019

Sea surface wind is a fundamental element for understanding the oceanic phenomena and for analyzing changes of the Earth environment caused by global warming. Global research institutes have developed and operated scatterometers to accurately and continuously observe the sea surface wind, with the accuracy of approximately ${\pm}20^{\circ}$ for wind direction and ${\pm}2m\;s^{-1}$ for wind speed. Given that the spatial resolution of the scatterometer is 12.5-25.0 km, the applicability of the data to the coastal area is limited due to complicated coastal lines and many islands around the Korean Peninsula. In contrast, Synthetic Aperture Radar (SAR), one of microwave sensors, is an all-weather instrument, which enables us to retrieve sea surface wind with high resolution (<1 km) and compensate the sparse resolution of the scatterometer. In this study, we investigated the Geophysical Model Functions (GMF), which are the algorithms for retrieval of sea surface wind speed from the SAR data depending on each band such as C-, L-, or X-band radar. We reviewed in the simulation of the backscattering coefficients for relative wind direction, incidence angle, and wind speed by applying LMOD, CMOD, and XMOD model functions, and analyzed the characteristics of each GMF. We investigated previous studies about the validation of wind speed from the SAR data using these GMFs. The accuracy of sea surface wind from SAR data changed with respect to observation mode, GMF type, reference data for validation, preprocessing method, and the method for calculation of relative wind direction. It is expected that this study contributes to the potential users of SAR images who retrieve wind speeds from SAR data at the coastal region around the Korean Peninsula.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1449-1463
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• 2020

As recent global warming and climate changes become more serious, the importance of CO2 absorption by forests is increasing to cope with the greenhouse gas issues. According to the UN Framework Convention on Climate Change, it is required to calculate national CO2 absorptions at the local level in a more scientific and rigorous manner. This paper presents the gridded expansion of forest flux observations and mapping of daily CO2 absorption by the forests in Korea using numerical weather prediction data and satellite images. To consider the sensitive daily changes of plant photosynthesis, we built a machine learning model to retrieve the daily RACA (reference amount of CO2 absorption) by referring to the climax forest in Gwangneung and adopted the NIFoS (National Institute of Forest Science) lookup table for the CO2 absorption by forest type and age to produce the daily AACA (actual amount of CO2 absorption) raster data with the spatial variation of the forests in Korea. In the experiment for the 1,095 days between Jan 1, 2013 and Dec 31, 2015, our RACA retrieval model showed high accuracy with a correlation coefficient of 0.948. To achieve the tier 3 daily statistics for AACA, long-term and detailed forest surveying should be combined with the model in the future.

• 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.

• 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.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.

• Korean Journal of Soil Science and Fertilizer
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• v.19 no.4
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• pp.339-344
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• 1986

Frost damage which can reduce yields, impair fruit quality and cause loss of trees is closely related to the occurrence of daily minimum temperature. Horizontal distribution of air temperature minima can be characterized by conditions of radiational cooling and gravitational movement of cold air, which are influenced by the regional topographic features. Observations were made on the air temperature minima over Yangpyeong area, to delineate potential effects of topography on the temperature pattern during spring season. Two routes were selected for the observation. Liquid glass minimum thermometers were installed at 17 sites through the old peach orchards which had been closed due to the frequent freeze-frost hazards during the recent years. This route was 8.5km long and the highest point was 350m above mean sea level. The other route, which was 2.5km in distance, was run with a digital resistance thermometer during the hour just before sunrise. Observations were made both on a calm-clear day (April 30, 1986) and a windy-overcast day (May 1, 1986). The temperature on April 30 was in increasing trend with elevation but this was modified at near the riverside and the downtown area. An orchard lying on a hilltop showed the temperature $1^{\circ}C$ higher than near by lowland of which elevation was about 30m lower. The minimum temperature on the overcast day was little affected by terrestrial conditions but by the atmospheric lapse condition. The peach orchards severely damaged by cold air were found in the area where the lowest minimum temperature was observed. The results may be useful for selection of the proper orchard location to be developed in an area.