• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.205-211
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• 2018

Remote estimation of water quality via radiometric instruments provides a convenient means for monitoring environmental changes in water bodies in wide areas. Combined with platforms such as satellite, manned/unmanned vehicles, it reduces the measurement cost and time for acquiring water quality information on the interested target areas. To develop accurate retrieval algorithms, however, acquisition of in-situ measurements from various optical environment is critical. In this study, hyperspectral radiometric measurements, the coincident water quality variables, and its optical properties were obtained to analyze the optical environment of the study area. Field data collected around the Tongyeong area showed that the area has optically complex environment, with occasional outbreak of red tide in summer seasons. Effect of water constituents on the optical variables (remote sensing reflectance and absorption coefficients) were qualitatively analyzed.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.76-76
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• 2019

최근 기후변화로 인해 퇴적 및 세굴이 심화되었고, 4대강 사업으로 인해 급격한 하천 지형 변화가 발생하였다. 특히, 4대강 사업 이후 하상변동 모니터링에 대한 지속적인 수요가 증가하고 있다. 이에 따라 개정된 하천법에 따르면 하상변동조사를 기본 10년 주기로 정기적으로 실시하되, 퇴적 및 세굴 발생 구간에 대해서는 기본 2년을 기준으로 하상변동이 큰 곳에 대해서는 1년 주기로, 하상변동이 작은 곳에 대해서는 5년 주기로 실시해야 한다. 하지만 기술 및 예산의 한계로 인해 하상변동조사의 경우 현장 유사량 및 하상토 입도 측정과 유량-총유사량 관계식을 활용하여 모델링을 통해 하상변동을 예측하고 있는 실정이다. 하상변동은 기본적으로 하천 수심을 기본으로 하고 있으며, 사람이 직접 투입하여 임의의 지점에 대한 수심 계측을 실시하고 있다. 하지만 직접 수심 계측의 경우 낮은 자료의 밀도로 인해 많은 인력과 예산, 시간이 소요되며 무엇보다도 관측 대상인 물이라는 작업환경에서는 인명피해가 발생할 수 있는 문제점을 가지고 있다. 최근에는 이러한 한계를 극복하기 위해 초음파 센서가 탑재된 이동식 보트를 활용하여 경로형 수심 계측을 실시하고 있으나, 초음파 센서가 가지는 기기적 한계로 인해 약 50cm 이하에 대한 수심은 측정이 어려운 실정이다. 특히, 국내 하천의 경우는 홍수기를 제외하면 수심이 얕기 때문에 얕은 수심에 대한 자료 확보가 어려워 공간적 정밀도 확보가 어려운 실정이다. 따라서 기존의 하천계측의 패러다임을 지점, 선형 계측이 아닌 면 측량을 실시를 통해 높은 밀도의 자료를 확보해야 한다. 이러한 측량이 가능한 기술로 하천원격탐사가 대안으로 제시되고 있다. 하천원격탐사는 직접 접촉하지 않고, 대상체의 광학적 특성을 통해 물리적 특성을 파악하는 기술로서 적은 시간에 높은 밀도의 자료의 확보와 저예산의 고효율 방법으로 알려져 있다. 본 연구에서는 기존의 하천원격탐사에서 활용한 고비용, 저해상도의 시공간 스케일에 해당하는 위성 및 유인항공기가 아닌 하천의 흐름방향으로 비행이 가능하고 상대적으로 저비용, 고해상도의 시공간 스케일의 측정이 가능한 드론을 활용하여 하천원격탐사를 수행하는 방법에 대해 논하고자 한다. 특히, 기술적 한계가 존재하는 청색, 녹색, 적색에 해당하는 RGB 영상을 활용한 하천원격탐사를 극복하기 위한 대안으로 초분광 영상을 수집하고 활용하는 방법을 제시하고자 한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.141-147
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• 2021

In this paper, in order to improve the utilization of hyperspectral large-capacity data feature information by reducing complex computations by dimension reduction of neural network inputs in embedded systems, the band selection algorithm is applied in each subset. Among feature extraction and feature selection techniques, the feature selection aim to improve the optimal number of bands suitable for datasets, regardless of wavelength range, and the time and performance, more than others algorithms. Through this experiment, although the time required was reduced by 1/3 to 1/9 times compared to the others band selection technique, meaningful results were improved by more than 4% in terms of performance through the K-neighbor classifier. Although it is difficult to utilize real-time hyperspectral data analysis now, it has confirmed the possibility of improvement.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.149-154
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• 2021

Unlike or common images, Hyperspectral images were taken by continuous electromagnetic spectral into numerous bands according to wavelengths and are high-capacity high-resolution images. It has more information than ordinary images, so it is used to explore objects and materials. To reduce the amount of information in hyper-spectral images to be processed, band selection is utilized. Existing band selection techniques are heuristic techniques based on statistics, which take a long time and often lack generality and universality. To compensate for this, this paper utilizes quantization concept to draw representative bands through Discrete Range, we use them for band selection algorithm. Experimental results showed that the proposed technique performed much faster than conventional band selection methods, and that the performance accuracy was similar to that of the original even though the number of bands was reduced by one-seventh to one-tenth.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.101-111
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• 2022

This study analyzed the relationship between water turbidity and its reflectance, as measured using hyperspectral imaging. First, samples of turbid water were generated in boxes. This was followed by drone-based hyperspectral imaging and analysis of the correlation between the samples' measured turbidity and hyperspectral reflectance. The nine boxes for turbidity measurement were made of black acrylic that absorbed all light turbidity was induced using soil collected near Changhacheon, which causes turbidity in Imha Lake. The results indicate that the reflectance of wavelengths in the near-infrared region followed a pattern of increase with increasing soil content for each box. Analysis of this correlation between the turbidity and average reflectance measured in each box yielded a very high R² value of 0.8702, indicating that reflectance is a suitable proxy for turbidity.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.27-27
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• 2022

본 연구는 본 연구에서는 내륙에 위치한 하천(백제보)과 호소(남양호)를 대상으로 수체반사도를 활용하여 유역특성에 따른 반사도의 변화를 확인하고 Chlorophyll-a(Chl-a)의 농도를 추정하고자 하였다. 각 유역별 특성분석을 위해 제원자료, 토지피복도 및 11개(수소이온농도, 용존산소, BOD, COD, 부유물질, 총질소, 총인, 수온, 전기전도도 및 Chlorophyll-a)의 수질인자 자료를 구축하였다. 백제보는 2016-2017년 유인항공기에 탑재된 초분광센서를 이용하여 반사도를 측정하였고, 남양호는 2020-2021년 초분광센서가 탑재된 Drone과 Sentinel-2 MSI영상으로부터 반사도를 측정하였으며 두 유역 모두 촬영 범위에 대하여 현장샘플링을 실시하였다. 유역특성, 수질인자간 상관성 및 밴드별 상관성 분석을 실시하였다. 수질인자 간 상관성 분석 결과 Chl-a와 광학적 특징이 있는 SS, TOC가 상관성이 높게 나타났으며, 반사도의 경우 Chl-a가 고농도일수록 Near-Infrared, Blue 파장과 상관성이 높게 나타났다. 해당 분석결과를 기반으로 각 유역에 대해 Chl-a Machine-learning 기법과 원격탐사자료를 이용하여 Chl-a의 농도를 산정하였으며 백제보, 남양호 각각 결정계수(R²) 0.80, 0.88의 성능을 보였다. 추후 고해상도 광학위성영상을 통해 유역특성을 고려한 광범위한 지역 규모의 Chl-a의 시공간적 분석이 가능할 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.46-46
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• 2022

유기물의 복잡한 혼합물인 CDOM(Colored or Chromophoric Dissolved Organic Matter)은 하천 내 BOD(Biological Oxygen Demand), COD(Chemical Oxygen Demand) 및 유기 오염물질과 상당한 관련이 있다. CDOM은 가시광선 영역에서 빛을 흡수하는 성질을 가지고 있으며, 최근 원격감지 기술로 CDOM을 모니터링하기 위한 연구가 진행되고 있다. 본 연구에서는 백제보 상류 23km 구간에서 3년(2016~2018) 중 13일의 초분광영상을 활용하여 머신러닝 기반 CDOM을 추정 알고리즘을 개발하고자 한다. 초분광영상은 400~970 nm의 범위의 4 nm 간격 127개 대역의 분광해상도와 2 m의 공간해상도를 가진 항공기 탑재 AsiaFENIX 초분광 센서를 통해 수집하였으며 CDOM은 Millipore polycarbonate filter (𝚽47, 0.2 ㎛)에서 여과된 CDOM 샘플 자료를 200~800 nm의 흡수계수 스펙트럼으로 추출하여 사용하였다. CDOM 값은 전체기간 동안 2.0~11.0 m^-1의 값 분포를 보였으며 5 m^-1이상의 고농도 구간 자료개수가 전체 153개 샘플자료 중 21개로 불균형하다. 따라서 ADASYN(Adaptive Synthesis Sampling Approach)의 oversampling 방법으로 생성된 합성 데이터를 사용하여 원본 데이터의 소수계층 데이터 불균형을 해결하고 모델 예측 성능을 개선하고자 하였다. 생성된 합성 데이터를 입력변수로 하여 ANN(Artificial Neural Netowk)을 활용한 CDOM 예측 알고리즘을 구축하였다. ADASYN 기법을 통한 합성 데이터는 관측된 데이터의 불균형을 해결하여 기계학습 모델의 CDOM 탐지 성능을 향상시킬 수 있으며, 저수지 내 유기 오염물질 관리를 위한 설계를 지원하는데 사용할 수 있을 것으로 판단된다.

• Horticultural Science & Technology
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• v.33 no.3
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• pp.403-408
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• 2015

Color is one of the quality determining factors for pepper powder. To measure the color of pepper powder, several methods including high-performance liquid chromatography (HPLC), thin layer chromatography (TLC), and ASTA-20 have been used. Among the methods, the ASTA-20 method is most widely used for color measurement of a large number of samples because of its simplicity and accuracy. However it requires time consuming preprocessing steps and generates chemical waste containing acetone. As an alternative, we developed a fast and simple method based on a visible/near infrared (Vis/NIR) hyperspectral method to measure the color of pepper powder. To evaluate correlation between the ASTA-20 and the visible/near infrared (Vis/NIR) hyperspectral methods, we first measured the color of a total of 488 pepper powder samples using the two methods. Then, a partial least squares (PLS) model was postulated using the color values of randomly selected 3 66 samples to predict ASTA values of unknown samples. When the ASTA values predicted by the PLS model were compared with those of the ASTA-20 method for 122 samples not used for model development, there was very high correlation between two methods ($R^2=0.88$) demonstrating reliability of Vis/NIR hyperspectral method. We believe that this simple and fast method is suitable for highthroughput screening of a large number of samples because this method does not require preprocessing steps required for the ASTA-20 method, and takes less than 30 min to measure the color of pepper powder.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.61-73
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• 2014

This study reviewed an application of water quality estimation using an Airborne Hyperspectral Imagery (A-HSI) and tested a part of Han River water quality (especially suspended solid) estimation with available in-situ data. The estimation of water quality was processed two methods. One is using observation data as downwelling radiance to water surface and as scattering and reflectance into water body. Other is linear regression analysis with water quality in-situ measurement and upwelling data as at-sensor radiance (or reflectance). Both methods drive meaningful results of RS estimation. However it has more effects on the auxiliary dataset as water quality in-situ measurement and water body scattering measurement. The test processed a part of Han River located Paldang-dam downstream. We applied linear regression analysis with AISA eagle hyperspectral sensor data and water quality measurement in-situ data. The result of linear regression for a meaningful band combination shows $-24.847+0.013L_{560}$ as 560 nm in radiance (L) with 0.985 R-square. To comparison with Multispectral Imagery (MSI) case, we make simulated Landsat TM by spectral resampling. The regression using MSI shows -55.932 + 33.881 (TM1/TM3) as radiance with 0.968 R-square. Suspended Solid (SS) concentration was about 3.75 mg/l at in-situ data and estimated SS concentration by A-HIS was about 3.65 mg/l, and about 5.85mg/l with MSI with same location. It shows overestimation trends case of estimating using MSI. In order to upgrade value for practical use and to estimate more precisely, it needs that minimizing sun glint effect into whole image, constructing elaborate flight plan considering solar altitude angle, and making good pre-processing and calibration system. We found some limitations and restrictions such as precise atmospheric correction, sample count of water quality measurement, retrieve spectral bands into A-HSI, adequate linear regression model selection, and quantitative calibration/validation method through the literature review and test adopted general methods.

• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.845-859
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• 2020

Climate change and recent heat waves have drawn public attention toward other environmental issues, such as water pollution in the form of algal blooms, chemical leaks, and oil spills. Water pollution by the leakage of chemicals may severely affect human health as well as contaminate the air, water, and soil and cause discoloration or death of crops that come in contact with these chemicals. Chemicals that may spill into water streams are often colorless and water-soluble, which makes it difficult to determine whether the water is polluted using the naked eye. When a chemical spill occurs, it is usually detected through a simple contact detection device by installing sensors at locations where leakage is likely to occur. The drawback with the approach using contact detection sensors is that it relies heavily on the skill of field workers. Moreover, these sensors are installed at a limited number of locations, so spill detection is not possible in areas where they are not installed. Recently hyperspectral images have been used to identify land cover and vegetation and to determine water quality by analyzing the inherent spectral characteristics of these materials. While hyperspectral sensors can potentially be used to detect chemical substances, there is currently a lack of research on the detection of chemicals in water streams using hyperspectral sensors. Therefore, this study utilized remote sensing techniques and the latest sensor technology to overcome the limitations of contact detection technology in detecting the leakage of hazardous chemical into aquatic systems. In this study, we aimed to determine whether 18 types of hazardous chemicals could be individually classified using hyperspectral image. To this end, we obtained hyperspectral images of each chemical to establish a spectral library. We expect that future studies will expand the spectral library database for hazardous chemicals and that verification of its application in water streams will be conducted so that it can be applied to real-time monitoring to facilitate rapid detection and response when a chemical spill has occurred.