• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2001년도 추계학술발표회
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• pp.155-159
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• 2001

A study on multivariate statistical classification of ground water hydrographs was conducted. The vast data of national ground water monitoring network (78 sites of alluvium) were used. 6 factors were selected to classify the ground water level change. Factor analysis was proved to be useful tool for classifying vast hydrogeological data.

• 한국지하수토양환경학회지:지하수토양환경
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• 제7권3호
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• pp.45-59
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• 2002

본 연구의 목적은 국가 지하수 관측망 자료를 활용하여 우리나라 지하수위 변동 곡선의 유형을 구분하고, 각 유형별 함양률을 평가하여 지하수 함양률의 공간적 변동성을 규명하는 데 있다. 전국 지하수의 수위 변동 곡선을 구분하기 위하여 요인 분석 방법을 사용했으며 그 결과 총 5 개의 유형으로 구분하였다. 유형별 함양률은 95.44%의 신뢰도 수준에서 6.2 %(유형 I), 4.1 %(유형 II), 9.2 %(유형 III), 5.8 %(유형 IV), 15.3 %(유형 V)로 추정되었으며 한 유형에서도 관측 지점별로 약 6 %의 변화폭을 보였다. 지하수위 변동 곡선법을 이용하여 유역별로 지하수 함양률을 평가한 결과 한강과 금강 유역에서는 각각 강수량 대비 10.0 %, 8.3 %의 함양률을 보였고, 낙동강 및 영산강·섬진강 유역에서는 각각 6.1 %, 6.6 %의 함양률을 보였으며 기저유출법에 의해서 유역별로 함양률을 추정한 연구의 결과와 유사하게 나타났다 따라서 본 연구를 통하여 지하수 함양률이 수위 변동 곡선의 유형별 혹은 유역별로 변동성을 가짐을 규명할 수 있었다.

• 한국측량학회지
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• 제36권5호
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• pp.423-432
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• 2018

Surface water mapping has been widely used in various remote sensing applications. Water indices have been commonly used to distinguish water bodies from land; however, determining the optimal threshold and discriminating water bodies from similar objects such as shadows and snow is difficult. Deep learning algorithms have greatly advanced image segmentation and classification. In particular, FCN (Fully Convolutional Network) is state-of-the-art in per-pixel image segmentation and are used in most benchmarks such as PASCAL VOC2012 and Microsoft COCO (Common Objects in Context). However, these data sets are designed for daily scenarios and a few studies have conducted on applications of FCN using large scale remotely sensed data set. This paper aims to fine-tune the pre-trained FCN network using the CRMS (Coastwide Reference Monitoring System) data set for surface water mapping. The CRMS provides color infrared aerial photos and ground truth maps for the monitoring and restoration of wetlands in Louisiana, USA. To effectively learn the characteristics of surface water, we used pre-trained the DeepWaterMap network, which classifies water, land, snow, ice, clouds, and shadows using Landsat satellite images. Furthermore, the DeepWaterMap network was fine-tuned for the CRMS data set using two classes: water and land. The fine-tuned network finally classifies surface water without any additional learning process. The experimental results show that the proposed method enables high-quality surface mapping from CRMS data set and show the suitability of pre-trained FCN networks using remote sensing data for surface water mapping.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• 제2권4호
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• pp.298-304
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• 2021

This study aimed to determine the applicability of drones and air quality sensors in environmental monitoring of air pollutant emissions by developing and testing two new methods. The first method used orthoimagery for precise monitoring of pollutant-emitting facilities. The second method used atmospheric sensors for monitoring air pollutants in emissions. Results showed that ground sample distance could be established within 5 cm during the creation of orthoimagery for monitoring emissions, which allowed for detailed examination of facilities with naked eyes. For air quality monitoring, drones were flown on a fixed course and measured the air quality in point units, thus enabling mapping of air quality through spatial analysis. Sensors that could measure various substances were used during this process. Data on particulate matter were compared with data from the National Air Pollution Measurement Network to determine its future potential to leverage. However, technical development and applications for environmental monitoring of pollution-emitting facilities are still in their early stages. They could be limited by meteorological conditions and sensitivity of the sensor technology. This research is expected to provide guidelines for environmental monitoring of pollutant-emitting facilities using drones.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2002년도 총회 및 춘계학술발표회
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• pp.237-242
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• 2002

This study is objected to assess the recharges of phreatic aquifers in the south Korea. The water level data of the national ground-water monitoring network were analysed by PCA(Principal Component Analysis), and classified to 8 types. The recharge were estimated by ‘water-level change method’ on basis of the classified types and compared with the previous methods(hydrograph separation methods) on basis of 4 river basins. The recharge were various type by type and site by site. But the recharge estimated by this study were consistent with that of the other studies.

• 지질공학
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• 제27권3호
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• pp.305-312
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• 2017

The most effective way to distinguish subsurface interfaces that produce various geophysical responses is through the integration of multiple geophysical methods, with each method detecting both a complementary and unique set of distinct physical properties relating to the subsurface. In this study, shallow seismic reflection (SSR) and ground penetrating radar (GPR) surveys were conducted at the Cheongju-Gadeok site of the Korea National Groundwater Monitoring Network to map the water table, which was measured at 12 m depth during the geophysical surveys. The water table proved to be a good target reflector in both datasets, as the abrupt transition from the overlying unsaturated weathered rock to the underlying saturated weathered rock yielded large acoustic impedance and dielectric constant contrasts. The two datasets were depth converted and integrated into a single section, with the SSR and GPR surveys conducted to ensure subsurface imaging at approximately the same wavelength. The GPR data provided detailed information on the upper ~15 m of the section, whereas the SSR data imaged structures at depths of 10-45 m. The integrated section thus captured the full depth coverage of the sandy clay, water table, weathered rock, soft rock, and hard rock structures, which correlated well with local drillcore and water table observations. Incorporation of these two geophysical datasets yielded a synthetic section that resembled a simplified aquifer model, with the best-fitting seismic velocity, dielectric constant, and porosity of the saturated weathered layer being $v_{seismic}=1000m/s$, ${\varepsilon}_r=16$, and ${\phi}=0.32$, respectively.

• 농업과학연구
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• 제38권4호
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• pp.747-752
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• 2011

Wireless technology has enabled farmers monitor and control protected production environment more efficiently. Utilization of USN (Ubiquitous Sensor Network) devices also brought benefits due to reduced wiring and central data handling requirements. However, wireless communication loses signal under unfavorable conditions (e.g., blocked signal path, low signal intensity). In this paper, performance of commercial wireless communication devices were evaluated for application to protected crop production. Two different models of wireless communication devices were tested. Sensors used in the study were weather units installed outside and top of a greenhouse (wind velocity and direction, precipitation, temperature and humidity), inside ambient condition units (temperature, humidity, $CO_2$, and light intensity), and irrigation status units (irrigation flow and pressure, and soil water content). Performance of wireless communication was evaluated with and without crop. For a 2.4 GHz device, communication distance was decreased by about 10% when crops were present between the transmitting and receiving antennas installed on the ground, and the best performance was obtained when the antennas were installed 2 m above the crop canopy. When tested in a greenhouse, center of a greenhouse was chosen as the location of receiving antenna. The results would provide information useful for implementation of wireless environment monitoring system for protected crop production using USN devices.

• 대한원격탐사학회지
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• 제38권1호
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• pp.111-126
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• 2022

Land use and land cover (LULC) mapping is an important factor in geospatial analysis. Although highly precise ground-based LULC monitoring is possible, it is time consuming and costly. Conversely, because the synthetic aperture radar (SAR) sensor is an all-weather sensor with high resolution, it could replace field-based LULC monitoring systems with low cost and less time requirement. Thus, LULC is one of the major areas in SAR applications. We developed a LULC model using only KOMPSAT-5 single co-polarized data and digital elevation model (DEM) data. Twelve HH-polarized images and 18 VV-polarized images were collected, and two HH-polarized images and four VV-polarized images were selected for the model testing. To train the LULC model, we applied the conditional generative adversarial network (cGAN) method. We used U-Net combined with the residual unit (ResUNet) model to generate the cGAN method. When analyzing the training history at 1732 epochs, the ResUNet model showed a maximum overall accuracy (OA) of 93.89 and a Kappa coefficient of 0.91. The model exhibited high performance in the test datasets with an OA greater than 90. The model accurately distinguished water body areas and showed lower accuracy in wetlands than in the other LULC types. The effect of the DEM on the accuracy of LULC was analyzed. When assessing the accuracy with respect to the incidence angle, owing to the radar shadow caused by the side-looking system of the SAR sensor, the OA tended to decrease as the incidence angle increased. This study is the first to use only KOMPSAT-5 single co-polarized data and deep learning methods to demonstrate the possibility of high-performance LULC monitoring. This study contributes to Earth surface monitoring and the development of deep learning approaches using the KOMPSAT-5 data.

• 한국농공학회논문집
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• 제60권6호
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• pp.33-42
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• 2018

This study evaluated the vulnerability of irrigation water supplied to the crops. The target areas were selected as Dangjin-si, Yesan-gun, and Cheongyang-gun. The survey items of the climate exposure were annual precipitation and rainless days. The sensitivity survey items were cultivation area, groundwater level, evapotranspiration and groundwater consumption. The survey items of the adaptability were Number of groundwater well and Water supply ratio. The survey methods for these items were investigated in a variety of ways, including "National Climate Data Service System", "Korean Statistical Information Service", "National ground water monitoring network in korea annual report" and "Chungcheongnam-do Statistical Yearbook", "HOMWRS". Vulnerability assessment results were rated within the range of 0~100 points. The first grade was rated 0-25, the second grade 26-50, the third grade 51-75, and the fourth grade 76-100. And the lower the score, the lower the vulnerability. As a result, Cheongyang-gun showed a high vulnerability of over 50 points, Dangjin-si showed a low vulnerability rating of 31.20 points and a Yesan-gun of 36.00 points.

• 한국지리정보학회지
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• 제14권4호
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• pp.1-12
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• 2011

도시 팽창과 신도시 개발로 도로, 전기, 상하수도 등의 7대 지하시설물의 안전에 대한 관심이 대두되고 있다. 특히 상하수도, 가스관 등을 수용하고 있는 공동구 설치 및 관리 방법이 대안으로 제시되고 있으나, 기존 공동구 시설은 국가 보안지역으로 묶여 관련 관리 기술에 대한 연구가 많이 이루어지지 못하였다. 특히 기존 인력에 의존하여 운영하는 현 방식은 실시간으로 긴박하게 발생하는 사건 사고에 적절히 대처하기 어려울 뿐만 아니라, 공동구내부에 화재 발생이나 가스유출 사고 발생 시 접근조차 불가능하며 사고에 대한 상황파악이나 대처가 어렵다. 그러므로 본 연구에서는 한국건설기술연구원내 설치되어 있는 실증실험장(TestLab)내에 설치되어 있는 공동구에서 무인 모니터링 장치를 설치하는 방법과 상수도관을 중심으로 시설물 관리 방법과 전체 모니터링을 위한 CCTV 영상 자료 처리 방법을 제안하고자 한다. 본 기술의 적용은 공동구내부에 실시간 모니터링이 가능하며, 사건 사고 발생 시 신속한 접근 및 대처가 가능하다.