• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.20-20
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• 2022

최근 국내 기후변화와 산업화로 인한 오염물 배출량 증가로 인해 하천 및 호소에 남조류 과대 성장이 빈번히 발생한다. 과거에 비해 녹조현상의 빈도가 잦아졌으며, 지속기간이 증가하였다. 조류 발생 시 현장에서 채수한 샘플을 통해 검경 및 chlorophyll-a 분석을 진행하여 조류의 정성·정량적 평가를 진행한다. 이러한 분석결과는 녹조 발생에 대한 기초자료로 활용되고 있다. 하지만 현장 시료 샘플을 통한 조류 검경의 경우 단일지점에 대한 분석으로 인해 하천 및 호소의 전체적인 대표성을 나타내기엔 한계가 있고, 많은 인력과 시간이 소요된다. 또한 chlorophyll-a는 녹조류와 높은 관련성이 있어 유해남조류에 대한 집중 분석에는 한계가 발생한다. 이러한 한계점을 통해 국내·외로 조류 연구에 분광 스펙트럼을 활용한 원격탐사 기법 적용되고 있으며, 남조류 농도를 분석하기 위해 남조류의 보조 색소인 phycocyanin을 활용한 연구가 진행되고 있다. 본 연구에서는 분광스펙트럼을 활용한 phycocyanin 분석을 진행하였다. 분광 스펙트럼을 측정하기 위해 점(point) 단위의 고해상도 분광방사계를 활용하였으며, phycocyanin 측정을 위해서 형광 센서를 활용하였다. 현장에서 형광센서 및 분광방사계를 동시에 측정하여 데이터를 취득하였으며, 분광 스펙트럼 특성상 노이즈 및 이상치가 발생하기 때문에 전처리 과정을 통해 이를 보완하였다. phycocyanin 분석을 위해 다중 스펙트럼을 활용한 분광지수를 활용했으며, 이를 통해 phycocyanin 분석에 있어 최적의 분광지수를 제시하고자 한다. 본 연구 결과는 고해상도 점(point)단위 분석으로 향후 선단위, 면단위 하천 조류-스펙트럼 분석에 있어 기초자료로 활용될 것으로 판단된다.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1761-1775
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• 2022

Due to unpredictable climate change, the frequency of occurrence of water-related disasters and the scale of damage are also continuously increasing. In terms of disaster management, it is essential to identify the damaged area in a wide area and monitor for mid-term and long-term forecasting. In the field of water disasters, research on remote sensing technology using Synthetic Aperture Radar (SAR) satellite images for wide-area monitoring is being actively conducted. Time-series analysis for monitoring requires a complex preprocessing process that collects a large amount of images and considers the noisy radar characteristics, and for this, a considerable amount of time is required. With the recent development of cloud computing technology, many platforms capable of performing spatiotemporal analysis using satellite big data have been proposed. Google Earth Engine (GEE)is a representative platform that provides about 600 satellite data for free and enables semi real time space time analysis based on the analysis preparation data of satellite images. Therefore, in this study, immediate water disaster damage detection and mid to long term time series observation studies were conducted using GEE. Through the Otsu technique, which is mainly used for change detection, changes in river width and flood area due to river flooding were confirmed, centered on the torrential rains that occurred in 2020. In addition, in terms of disaster management, the change trend of the time series waterbody from 2018 to 2022 was confirmed. The short processing time through javascript based coding, and the strength of spatiotemporal analysis and result expression, are expected to enable use in the field of water disasters. In addition, it is expected that the field of application will be expanded through connection with various satellite bigdata in the future.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.623-634
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• 2022

Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.179-190
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• 2018

The purpose of this study is an analysis of the risk of soil erosion before and after the maintenance of riparian area using the Revised Universal Soil Loss Equation (RUSLE) model based on GIS and digitizing data. To analysis of soil erosion loss in the study area, land cover maps, topographical maps, soil maps, precipitation and other data were used. After digitizing the riparian area of the Geumhogang, the area is divided into administrative district units, respectively. Amount of soil loss was classified into 5 class according to the degree of loss. Totally, 1 and 5 class were decreased, and 2-4 class were increased. Daegu and Yeongcheon decreased the area of 5 class, and Gyeongsan did not have area of 5 class. The reason for this is thought to be the decrease of the 5 class area due to the park construction, expansion of artificial facilities, and reduction of agricultural land. Simplification of riverside for river dredging and park construction has increased the flow rate of the riverside and it is considered that the amount of soil erosion has increased.

• Korean Journal of Remote Sensing
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• v.21 no.4
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• pp.253-271
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• 2005

We have analyzed surface water temperature and seasonal stratification of lakes in the Han river system using time-series Landsat images and in situ measurement data. Using NASA equation, at-satellite temperature is derived from 29 Landsat-5 TM and Landsat-7 ETM+ images obtained from 1994 to 2004, and was compared with in situ surface temperature on river-type dam lakes such as Paro, Chuncheon, Euiam, Chongpyong, Paldang, and with 10m-depth temperature on lake-type dam lake Soyang. Although the in situ temperature at the time of satellite data acquisition was interpolated from monthly measurements, the number of images with standard deviation of temperature difference (at-satellite temperature - in situ interpolated temperature) less than $2^{\circ}C$ was 24 on which a novel statistical atmospheric correction could be applied. The correlation coefficient at Lake Soyang was 0.915 (0.950 after correction) and 0.951-0.980 (0.979-0.997 after correction) at other lakes. This high correlation implies that there exist a mixed layer in the shallow river-like dam lakes due to physical mixing from continuous influx and efflux, and the daily and hourly temperature change is not fluctuating. At Lake Soyang, an anomalous temperature difference was observed from April to July where at-satellite temperature is $3-5^{\circ}C$ higher than in situ interpolated temperature. Located in the uppermost part of the Han river system and its influx is governed only by natural precipitation, Lake Soyang develops stratification during this time with rising sun elevation and no physical mixture from influx in this relatively dry season of the year.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.1
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• pp.84-93
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• 2011

Levee line mapping is critical to the protection of environments in river zones, the prevention of river flood and the development of river zones. Use of the remote sensing data such as LiDAR and aerial orthoimage is efficient for river mapping due to their accessibility and higher accuracy in horizontal and vertical direction. Airborne laser scanning (LiDAR) has been used for river zone mapping due to its ability to penetrate shallow water and its high vertical accuracy. Use of image source is also efficient for extraction of features by analysis of its image source. Therefore, aerial orthoimage also have been used for river zone mapping tasks due to its image source and its higher accuracy in horizontal direction. Due to these advantages, in this paper, research on three dimensional levee line mapping is implemented using LiDAR and aerial orthoimage separately. Accuracy measurement is implemented for both extracted lines generated by each data using the ground truths and statistical comparison is implemented between two measurement results. Statistical results show that the generated 3D levee line using LiDAR data has higher accuracy than the generated 3D levee line using aerial orthoimage in horizontal direction and vertical direction.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.444-444
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• 2023

하천 및 저수지와 같은 공간의 수체 탐지는 수자원 관리에서 매우 중요하며, 유역의 수문학적 과정을 이해하는데 도움을 준다. 수문학적 데이터 수집은 우량계, 수위계와 같은 물리적 인프라의 배치가 필요하다. 그러나 상대적으로 저개발된 국가는 수문학적 측정을 위한 인프라가 매우 미흡한 것이 현실이며, 북한과 같은 비접근 지역에 대한 수문학적 과정을 분석하는데는 한계가 있다. 인공위성 원격탐사 센서 중 SAR영상은 지표면에 직접 전파를 방사하고 산란되어 돌아오는 신호를 수신하여 영상을 만들기 때문에 일반적인 광학영상과는 달리 햇빛의 유무와 강우, 구름여부 등의 기상 조건의 영향을 거의 받지 않는 장점이 있다. 또한 국내와 같이 계절적인 요인과 인간활동에 의해 변화되는 물 순환을 SAR 영상은 지표수의 계절적 및 연간 변동성을 모니터링하는데 매우 유용한 자료로 평가되고 있다. 본 연구는 SAR영상을 이용하여 국내의 검증 가능한 지역의 저수지 수면적 변화를 모니터링하고 저수지 수면적과 저수량 분석을 수행하는 것을 목적으로 하였다. 분석자료인 SAR영상은 ESA의 Sentinel-1영상을 2022년 4월부터 2022년 11월의 자료를 수집하여 소양강댐 저수지 수면적과 저수량과의 관계식을 도출하였다. 수체 추출을 위한 SAR 영상은 특히 수로의 일부 가장자리와 홍수터의 식물 존재로 인한 제외지의 매핑에 부정확성을 포함하여 처리에 몇 가지 단점을 갖는 한계도 존재하지만 악천후의 기상 조건에서도 작동할 수 있는 SAR 영상의 능력 덕분에 규칙적인 시간 간격으로 수체면적의 변화에 대한 정보를 제공할 수 있다. 향후 북한 지역의 주요 댐 저수지 수면적에 대한 연간변화와 장기간의 추세를 분석하는 연구를 진행할 계획이다.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.607-616
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• 2014

This research is to observe the shoreline changes in Jinha beach over the 50 years with aerial photographs and satellite images. The shoreline image feature was retrieved from the corrected images using wet and dry techniques and analyzed by DSAS from the statistical point of view. From 1967 to 1992, the mouth of Hoeya River was severely blocked and the northern shoreline off Jinha beach was eroded. The blockade of river mouth seemed to have been eased along with the completion of the dike, but soil continued to be deposited along the high sea away from the river month. Compared to the past, a layer of sediment has been formed off the northern coastline while the southern coastline has eroded. At least in the region subject to this research, the construction of a training dike is to blame. On top of that, a mere combination of dredges and artificial nourishment is not enough to take under control the changing shorelines properly. Thus, it is necessary to devise a more fundamental solution by taking into account reasons behind sediment from the river area that could change the shorelines besides the costal environment.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.294-294
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• 2015

하천과 해양에서 발생한 수질오염은 특성상 유속의 흐름에 따라 광범위하며 급속도로 퍼져나가기 때문에 이를 효율적으로 유지, 관리하기 위해서는 오염인자들에 대한 모니터링이 수행되어야 한다. 원격탐사 기술을 이용한 하천의 수질측정은 대규모지역으로 분포해있는 수질농도의 변화양상을 시 공간적으로 모니터링 하는 것이 가능하게 할 뿐 아니라, 사람이 접근하기 어려운 지역에는 직접취수를 하지 않음으로써 기존의 수질측정방법들에 비해 편의성을 높여 시간적, 경제적 측면에서 효율적이다. 이에 본 연구에서는 최근 수질오염이 심화되고 있는 낙동강유역을 대상으로 인공위성 이미지영상을 이용하여 수질인자들의 농도측정을 수행하였다. 연구를 위해 사용된 인공위성은 NASA와 USGS가 공동으로 운용중인 Landsat 8 인공위성이다. Landsat 8의 11개 band 중 band2(Blue), band3(Green), band4(Red), band5(Near Infrared)를 사용하여 실제로 측정된 지점자료와 인공위성자료간의 상관관계를 규명하였다. 사용된 인공위성자료는 지점자료 날짜를 포함하는 총 4개의 연구날짜(2013/10/27, 2013/11/12, 2014/04/14, 2014/05/16)에 해당하는 위성이미지영상이다. Pearson상관계수를 통한 밴드와 수질인자간의 상관 결과, 본 연구지역에서는 $0.85-0.88{\mu}m$(band5)의 파장영역에서 클로로필-a와 부유물질이 가장 민감하게 반응함을 알 수 있었다. 두 수질인자들은 band2, band3, band4에서도 비교적 높은 상관성을 보였으며, 이를 근거로 band combination, band ratio를 통해 클로로필-a와 부유물질의 회귀모델식을 유도하였다. 각각의 회귀모델식은 실제 측정된 데이터들과 비교 검증을 통해 4개의 연구기간 중 2013년 10월 27일, 2014년 5월 16일에 대해서 클로로필-a와 부유물질의 공간적인 분포양상을 시각적으로 도시화하였다.

• Ecology and Resilient Infrastructure
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• v.10 no.4
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• pp.135-142
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• 2023

A various technology of remote sensing and image analysis are applied to study landscape changes and their influencing factors in stream corridors. We developed a method to detect landscape changes over time by calculating the optical index using multispectral images taken from satellites at various time points, calculating the threshold to delineate the boundaries of water bodies, and creating binarized maps into land and water areas. This method was applied to the upstream reach of the weirs in the Geumgang River to track changes in the sandbar formed by the opening of the weir gate. First, we collected multispectral images with a resolution of 10 m × 10 m taken from the Sentinel-2 satellite at various times before and after the opening of the dam in the Geumgang River. The normalized difference water index (NDWI) was calculated using the green light and near-infrared bands from the collected images. The Otsu's threshold of NDWI calculated to delineate the boundary of the water body ranged from -0.0573 to 0.1367. The boundary of the water area determined by remote sensing matched the boundary in the actual image. A map binarized into water and land areas was created using NDWI and the Otsu's threshold. According to these results of the developed method, it was estimated that a total of 379.7 ha of new sandbar was formed by opening the three weir floodgates from 2017 to 2021 in the longitudinal range from Baekje Weir to Daecheong Dam on the Geumgang River. The landscape detection method developed in this study is evaluated as a useful method that can obtain objective results with few resources over a wide spatial and temporal range.