• Geophysics and Geophysical Exploration
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• v.25 no.1
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• pp.26-37
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• 2022

Recently, multiple methods using small aircraft for geophysical exploration have been suggested as a result of the development of information and communication technology. In this study, we introduce the hybrid unmanned aircraft electromagnetic system of the Korea Institute of Geosciences and Mineral resources, which is under development. Additionally, data processing and interpretation methods are suggested via the analysis of datasets obtained using the system under development to verify the system. Because the system uses a three-component receiver hanging from a drone, the effects of rotation on the obtained data are significant and were therefore corrected using a rotation matrix. During the survey, the heights of the source and the receiver and their offsets vary in real time and the measured data are contaminated with noise. The noise makes it difficult to interpret the data using the conventional method. Therefore, we developed a recurrent neural network (RNN) model to enable rapid predictions of the apparent resistivity using magnetic field data. Field data noise is included in the training datasets of the RNN model to improve its performance on noise-contaminated field data. Compared with the results of the electrical resistivity survey, the trained RNN model predicted similar apparent resistivities for the test field dataset.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.39 no.5
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• pp.489-494
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• 1994

Near Infrared Reflectance Spectroscopy(NIRS) has been used as a tool for the rapid, accurate, protein assay of malting barley. NIRS used in this study was filter type instruments, Neotec 102. The objective of this study was to obtain the best calibration equation, for the rapid, ease and accurate protein content analysis of malting barley using NIRS system. The optimum wavelength for protein content analysis used NIRS were 2095nm, 2095/1941nm, 2095/1941/2282nm, 2905/1941/2282/2086nm, respectively. Mean protein content with this calibration equation in NIRS analysis was 10.59%, while 10.60% in Micro-Kjeldahl one. The range of protein content in Micro-Kjeldahl was 8.66~12.66% and that in NIRS was 8.80~12.35%. When 18 other varieties produced in 1992 were analysed with 2095nm, 2095/1941nm, 2095/1941/2282nm, 2095/1941/2282/2086nm equation, standard deviation of difference (SDD)and standard error of performence(SEP) and $R^2$ values were 0.47, 0.43, 0.95, respectively. Both the mean protein content by Micro-Kjeldahl and by NIRS was 10.25%. With this equation, analysied 31 varities produced in 1993, SDD and SEP and r values were 0.69, 0.67, 0.91, respectively, and that bias value was 0.65. In this analysis, mean protein content by Micro-Kjeldahl was 10.17% and by NIRS was 10.81%. The range of protein content in Micro-Kjeldahl was 7.58~14.29%, What that in NIRS was 8.63~13.93%. After adjusted bias in the best calibration equation, mean protein content of Micro-Kjeldahl was 10.17% and that of NIRS was 10.09%, without variance of SDD, SEP and r values.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.148-148
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• 2023

산업 고도화로 인하여 복잡하고 다양한 유기물의 사용량이 증가하였으며, 공공수역 내 새로운 오염물질이 유입됨에 따라 생화학적 산소요구량(BOD) 중심의 수질평가에 한계를 나타내었다. 이후 난분해성 물질을 고려한 유기물관리 정책과 총량관리의 필요성이 제기되었고 국내 하천과 호소에서는 총 유기탄소(TOC)를 유기물 관리지표로 설정하였다. 그러나 부영양 하천과 호소에서 TOC는 외부 부하뿐만아니라 식물플랑크톤의 과잉성장에 의해 증가할 수 있는 항목이므로 TOC 관리정책 추진을 위해서는 유기물의 기원에 대한 파악이 필요하다. 한편, 우리나라와 같이 몬순 기후대에 속한 댐 저수지의 경우 강우시 유입하는 탁수에 의해 다량의 유기물과 인이 유입되기도 하지만 식물플랑크톤의 제한요인 중 광량에 많은 영향을 미친다. 식물플랑크톤의 광합성은 수체 내 유기탄소 내부생성에 매우 중요한 요소이나 점 단위의 실험적 방법을 활용한 유기탄소 순환 해석은 저수지의 시·공간적인 변동성을 고려하기에 한계가 있다. 본 연구의 목적은 금강 수계 최대 상수원인 대청호를 대상으로 3차원 수리-수질 모델을 적용하여 유기탄소 성분 별 유입과 유출, 내부생성 및 소멸량을 평가하고 탁수가 저수지에서의 유기탄소 순환에 미치는 영향을 분석하는데 있다. 유기탄소 물질수지 해석을 위해 AEM3D 모델을 사용하였으며 2018년을 대상으로 입력자료를 구축한 후 보정 및 검정을 수행하였다. 모델은 유기탄소를 입자성, 용존성, 그리고 난분해성과 생분해성으로 구분하여 모의하며 유기물질 성상별 실험결과를 이용하여 입력자료를 구축하였으며 유기탄소순환 해석을 위해 4가지의 탄소성분과 조류 세포 내 탄소의 질량 변화율을 계산하였다. 이를 위해 외부 유입·유출부하율, 수체 내 생성(일차생산, 재부상, 퇴적물과 수체 간 확산) 및 소멸률(POC 및 조류 침강, DOC 무기화, 탈질)을 고려하였으며 탁수의 영향을 분석하기 위해 탁수 포함여부 시나리오를 구성하고 유기탄소 생성 및 소멸기작별 변동성을 비교 분석하였다. 모델은 2018년의 물수지를 적절히 재현하였으며 저수지의 수온 및 탁도 성층구조를 잘 재현해내면서 전반적인 수질을 적절하게 모의하였다. 탁수를 고려하였을 시 연간 TOC 부하량 중 내부기원 부하량은 56% 수준이였으나 탁수를 배제한 경우 내부기원 부하량은 82%로 나타났다. 특히, 연평균 Chl-a 농도가 44~48% 차이가 발생하면서 1차생산량이 약 4배가량 증가하였다. 몬순지역에서의 탁수는 체류시간이 긴 성층 저수지에서 식물플랑크톤 성장제어에 큰 영향을 미쳤으며 전반적인 유기탄소 순환을 해석하는데 있어 매우 중요한 인자로 작용하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.62-62
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• 2021

산업 고도화로 인하여 복잡하고 다양한 유기물의 사용량이 증가하였으며, 공공수역 내 새로운 오염물질이 유입됨에 따라 생화학적 산소요구량(BOD) 중심의 수질평가에 한계를 나타내었다. 이후 난분해성 물질을 고려한 유기물관리 정책과 총량관리의 필요성이 제기되었고 국내 하천과 호소에서는 총 유기탄소(TOC)를 유기물 관리지표로 설정하였다. 그러나 부영양 하천과 호소에서 TOC는 외부 부하뿐만아니라 식물플랑크톤의 과잉성장에 의해 증가할 수 있는 항목이므로 TOC 관리정책 추진을 위해서는 유기물의 기원에 대한 파악이 필요하다. 특히, 국내 하천에서 나타나고 있는 난분해성 유기물 오염도의 증가 추세에 대응한 실효성 있는 유기물 오염관리 정책을 수립하기 위해서는 다양한 유기물의 근원을 정확하게 파악하는 것이 매우 중요하다. 본 연구의 목적은 금강 수계 최대 상수원인 대청호를 대상으로 3차원 수리-수질 모델을 적용하여 유기탄소 성분 별 유입과 유출, 내부생성 및 소멸량을 평가하고 저수지시스템에서의 유기탄소 물질수지를 해석하는 데 있다. 유기탄소 물질수지 해석을 위해 AEM3D 모델을 사용하였으며 2017년을 대상으로 입력자료를 구축한 후 보정을 수행하였고 2018년을 대상으로 모델을 검정하였다. 모델은 유기탄소를 입자성, 용존성, 그리고 난분해성과 생분해성으로 구분하여 모의하며 유기물질 성상별 실험결과를 이용하여 입력자료를 구축하였다. 유기탄소 물질수지 해석을 위해 4가지의 탄소성분과 조류 세포 내 탄소의 질량 변화율을 계산하였다. 이를 위해 외부 유입·유출부하율, 수체 내 생성(일차생산, 재부상, 퇴적물과 수체 간 확산) 및 소멸률(POC 및 조류 침강, DOC 무기화, 탈질)을 고려하였다. 모델은 2017년과 2018년의 물수지를 적절히 재현하였으며 저수지의 성층구조를 잘 재현해내면서 전반적인 수온, 수질을 적절하게 모의하였다. 연간 TOC 부하량 중 내부기원 부하량은 2017년 68.4 %, 2018년은 높은 강우량의 영향으로 55.0%로 산정되었다. 내부 소멸 기작 중 침전으로 인한 손실이 가장 높은 것으로 나타났으며, 2017년과 2018년 각각 31.3%, 29.0%로 나타났다. TOC의 공간분포는 Chl-a 농도 분포와 유사하게 나타났으며, 댐 설치로 형성된 정체수역은 유역의 유기물 순환에 많은 영향을 미치는 것으로 평가되었다. TOC 관리 정책 기초자료 확보를 위해서는 향후 유역-저수지 시스템을 연계한 유기물 물질순환 심층 연구가 필요하다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.107-120
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• 2010

The effect of potential future climate change on the inflow of agricultural reservoir and its impact to downstream streamflow by reservoir operation for paddy irrigation water was assessed using the SLURP (semi-distributed land use-based runoff process), a physically based hydrological model. The fundamental input data (elevation, meteorological data, land use, soil, vegetation) was collected to calibrate and validate of the SLURP model for a 366.5 $km^2$ watershed including two agricultural reservoirs (Geumgwang and Gosam) located in Anseongcheon watershed. Then, the CCCma CGCM2 data by SRES (special report on emissions scenarios) A2 and B2 scenarios of the IPCC (intergovernmental panel on climate change) was used to assess the future potential climate change. The future weather data for the year, m ms, m5ms and 2amms was downscaled by Change Factor method through bias-correction using 3m years (1977-2006) weather data of 3 meteorological stations of the watershed. In addition, the future land uses were predicted by modified CA (cellular automata)-Markov technique using the time series land use data fromFactosat images. Also the future vegetation cover information was predicted and considered by the linear regression between monthly NDVI (normalized difference vegetation index) from NOAA AVHRR images and monthly mean temperature using eight years (1998-2006) data.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.75-85
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• 2017

A method to estimate hourly temperature profiles on calm and clear nights was developed based on temporal changes of inversion height and strength. A meteorological temperature profiler (Model MTP5H, Kipp and Zonen) was installed on the rooftop of the Highland Agriculture Research Institute, located in Daegwallyeong-myeon, Pyeongchang-gun, Gangwon-do. The hourly vertical distribution of air temperature was measured up to 600 m at intervals of 50 m from May 2007 to March 2008. Temperature and relative humidity data loggers (HOBO U23 Pro v2, Onset Computer Corporation, USA) were installed in the Jungdae-ri Valley, located between Gurye-gun, Jeollanam-do and Gwangyang-si, Jeollanam-do. These loggers were used to archive measurements of weather data 1.5 m above the surface from October 3, 2014, to November 23, 2015. The inversion strength was determined using the difference between the temperature at the inversion height, which is the highest temperature in the profile, and the temperature at 100 m from the surface. Empirical equations for the changes of inversion height and strength were derived to express the development of temperature inversion on calm and clear nights. To estimate air temperature near the ground on a slope exposed to crops, the equation's parameters were modified using temperature distribution of the mountain slope obtained from the data loggers. Estimated hourly temperatures using the method were compared with observed temperatures at 19 weather sites located within three watersheds in the southern Jiri-mountain in 2015. The mean error (ME) and root mean square error (RMSE) of the hourly temperatures were $-0.69^{\circ}C$ and $1.61^{\circ}C$, respectively. Hourly temperatures were often underestimated from 2000 to 0100 LST the next day. When temperatures were estimated at 0600 LST using the existing model, ME and RMSE were $-0.86^{\circ}C$ and $1.72^{\circ}C$, respectively. The method proposed in this study resulted in a smaller error, e.g., ME of $-0.12^{\circ}C$ and RMSE of $1.34^{\circ}C$. The method could be improved further taking into account various weather conditions, which could reduce the estimation error.

• 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.

• Korean Journal of Soil Science and Fertilizer
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• v.9 no.1
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• pp.47-55
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• 1976

This study is conducted to find out potential evapotranspiration values computed by a reasonable formula which is well suited among the existing ones for Suweon area. Each formula based on the data from Suweon Agricultural Meteorological Station during 1964 to 1973. Five formulas which are Blanney-Criddle, Thornthwaite, Penman, Jensen-Haise and Truc have been applied for calculation of potential evapotanspiration. Results obtained are summarized as follows. 1. Potential evapotranspiration of Suweon area shows uni-modal distribution which maximum value occurs in summer and minimum value occurs in winter. Annual potential evapotranspiration computed by Blanney-Criddle formula is 1,377 mm and that computed by others ranges from 714mm to 896mm. 2. Potential evapotranspiration computed by Blanney-Criddle formula is higher value than that computed by others, and among the other formulas it's values show little differences. However, relationships between the former and the mean of four others is highly correlated. 3. In comparison with potential evapotranspiration computed by formulas and actual evapotranspiration for rice paddy which is already reported, value for crop coefficient may be 0.8 in local varities, 1.0 in Tongil varity on Blanney-Criddle formula, and 1.2 in local varities and 1.5 in Tongil varity on the mean of four other fomulas. 4. Five formulas may applied for calculation of potential evapotranspiration because of relatively good correlation among them. However Blanney-Criddle formula is one of recommendable ones, because it is easy to compute and requires less data in compare with other formulas.

• Journal of Animal Science and Technology
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• v.46 no.3
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• pp.335-346
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• 2004

Factors associated with milk urea nitrogen on milk yield and milk composition were investigated in this study regarding feeding management and Physiological status of lactating cows. The data for 3 years between 1999 and 2002 for this study were collected from 129,645 cows by Korean Agricultural Cooperatives Federation. The objectives of this study were to describe the relationships between milk urea concentrations and seasonal factors, cow factors and production of milk, milk fat, protein and somatic cell score(SCS). Milk urea was highest in summer and it also showed a nonlinear association with milk yield. Milk yield was higher at milk urea concentrations of 21 ${\sim}$ 24mg/dl, however it decreased at higher level of milk urea concentrations than 24mg/dl. Milk urea was higher with increased parities of cows and in particular, at 3 to 4 parities. There was a negative association between milk urea and SCS in milk. SCS in milk was lowest at milk urea concentrations of 2l${\sim}$24mg/dl. Milk fat and milk protein were greatly affected by days in milk(DIM), year of birth, season and milk urea concentrations, respectively. While milk urea increased in summer, milk fat and protein were decreased. Milk protein decreased according to longer days in milk. With regard to the influences of parity, milk protein in overall was negatively correlated to milk urea in all lactations, however the extent of decrease of milk protein at high concentrations of milk urea was bigger at third lactation. The balanced supply of energy and protein to the animals might have greatly affected the urea concentrations and protein content of milk.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.847-860
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• 2020

The 2-pass DInSAR (Differential Interferometric SAR) processing steps for DEM generation consist of the co-registration of SAR image pair, interferogram generation, phase unwrapping, calculation of DEM errors, and geocoding, etc. It requires complicated steps, and the accuracy of data processing at each step affects the performance of the finally generated DEM. In this study, we developed an improved method for enhancing the performance of the DEM generation method based on the 2-pass DInSAR technique of TanDEM-X bistatic SAR images was developed. The developed DEM generation method is a method that can significantly reduce both the DEM error in the unwrapped phase image and that may occur during geocoding step. The performance analysis of the developed algorithm was performed by comparing the vertical accuracy (Root Mean Square Error, RMSE) between the existing method and the newly proposed method using the ground control point (GCP) generated from GPS survey. The vertical accuracy of the DInSAR-based DEM generated without correction for the unwrapped phase error and geocoding error is 39.617 m. However, the vertical accuracy of the DEM generated through the proposed method is 2.346 m. It was confirmed that the DEM accuracy was improved through the proposed correction method. Through the proposed 2-pass DInSAR-based DEM generation method, the SRTM DEM error observed by DInSAR was compensated for the SRTM 30 m DEM (vertical accuracy 5.567 m) used as a reference. Through this, it was possible to finally create a DEM with improved spatial resolution of about 5 times and vertical accuracy of about 2.4 times. In addition, the spatial resolution of the DEM generated through the proposed method was matched with the SRTM 30 m DEM and the TanDEM-X 90m DEM, and the vertical accuracy was compared. As a result, it was confirmed that the vertical accuracy was improved by about 1.7 and 1.6 times, respectively, and more accurate DEM generation was possible with the proposed method. If the method derived in this study is used to continuously update the DEM for regions with frequent morphological changes, it will be possible to update the DEM effectively in a short time at low cost.