• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.437-444
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• 2008

In the paper, a methodology is verified to integrate IKONOS-2 satellite imagery and ALS dataset by compensating biases of RPC models. To achieve this, conjugate features from both data should be extracted in advance. For this purpose, linear features are chosen as conjugate features because they can be accurately extracted from man-made structures in urban area and more easily extracted than point features from ALS data. Then, observation equations are established from similarity measurements of the extracted features. During the process, several kinds of transformation functions were selected and used to register them. In addition, it was also analyzed how the number of linear features used as control features affects the accuracy of registration results. Finally, the results were evaluated by using check-points obtained from DGPS surveying techniques and it was clearly demonstrated that the proposed algorithms are appropriate to integrate these data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.4
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• pp.331-338
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• 2004

This paper describes capability of utilizing ground control points(GCPs) obtained from 1:1,000 and 1:5,000 digital vector maps to correct image coordinates which have errors due to bais rational polynomial coefficient(RPC) of IKONOS Geo-level stereo images. The accuracy of the bias-corrected images was improved to approximately 4m and 2m in planimetry and height, respectively. The accuracy was also compared with results from using GCPs obtained by GPS surveying. In consequence, bias-compensated IKONOS sereo imagery was evaluated to satisfy generating topographic map 1:10,000.

• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.201-214
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• 2020

This study proposes a bias correction method of dual-pol radar rain rate in real time using the dual Kalman filter. Unlike the conventional Kalman filter, the dual Kalman filter predicts state variables with two systems (state estimation system and model estimation system) at the same time. Bias of rain rate is corrected by applying the bias correction ratio to the rain rate estimate. The bias correction ratio is predicted from the state-space model of the dual Kalman filter. This method is applied to a storm event with long duration occurred in July 2016. Most of the bias correction ratios are estimated between 1 and 2, which indicates that the radar rain rate is underestimated than the ground rain rate. The AR (1) model is found to be appropriate for explaining the time series of the bias correction ratio. The time series of the bias correction ratio predicted by the dual Kalman filter shows a similar tendency to that of observation data. As the variability of the bias correction increases, the dual Kalman filter has better prediction performance than the Kalman filter. This study shows that the dual Kalman filter can be applied to the bias correction of radar rain rate, especially for long and heavy storm events.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.4
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• pp.19-29
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• 2007

This study compares various ground-truth designs of radar rainfall using rain-gauge data sets from Korea Meteorological Administration (KMA), AWS and Ministry of Construction and Transportation (MOCT). These Rain-gauge data sets and the Mt. Gwanak radar rainfall data for the same period were compared, and then the differences between two observed rainfall were evaluated with respect to the amount of bias. Additionally this study investigated possible differences in bias due to different storm characteristics. The application results showed no distinct differences between biases from three rain-gauge data sets, but some differences in their statistical characteristics. In overall, the design bias from MOCT was estimated to be the smallest among the three rain-gauge data sets. Among three storm events considered, the jangma with the highest spatial intermittency showed the smallest bias.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.354-354
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• 2019

기후변화에 따른 이상기후의 영향으로 과거 관측되지 않은 태풍, 가뭄, 폭우, 홍수 및 해일과 같은 재해의 빈도가 증가하고 있다. 특히, 가뭄은 장기간에 걸쳐 피해를 야기하여 대책을 장기적으로 고려하지 않으면 전 지구적으로 심각한 피해가 초래될 것으로 전망되고 있다. 많은 연구에서 가뭄에 따른 재해를 평가하기 위한 분석이 수행되고 있으며, 최근 연구에서는 토양수분을 통한 가뭄재해 분석이 대두되고 있다. 토양수분은 토양에 포함된 수분의 평균값을 의미하며 물 순환 관점에서 매우 중요한 수문변량 중 하나이다. 그러나 기존 연구에서 사용되고 있는 실측 토양수분은 자료의 기간이 짧고 검증이 수행되지 않아 분석 시 결과의 신뢰성이 결여되는 문제점이 있다. 일부 토양수분 연구에서는 위성 관측 자료를 통한 분석을 수행하였지만 실측 자료와의 상관성 문제로 인하여 모의된 결과의 활용은 어려운 실정이다. 이에 본 연구에서는 Quantile mapping 기반의 편의 보정 방법을 제시하여 용담 유역 내 6개 지점와 전국에 흩어져 있는 6개 지점(철원장흥, 수원, 대곡, 전주, 오창가곡, 춘천신북)의 실측자료와 위성 자료 기반의 재해석 토양수분 (re-analysis soil moisture data)에 따른 토양수분 모의 기법을 제시하였다. 본 연구에서 개발한 모형에 따른 결과는 가뭄재해 평가 시 기초자료로써 신뢰성 있는 정보로 활용할 수 있을 것으로 판단된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5B
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• pp.431-438
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• 2011

This study investigated the problem of mean-field bias correction under the assumption that the radar and rain gauge rainfall data follow the log-normal distribution. Regression curves for the average, median and mode of the radar and rain gauge rainfall were derived and evaluated for their usefulness. Additionally, these regression curves were compared with those derived under the assumption that the radar and rain gauge data follow the normal distribution. This study investigated the regression results for the Typhoon Meami occurred in 2003 as an example. As results, three regression lines with the radar rainfall as the independent variable were found to underestimate the rainfall, while those with the rain gauge rainfall as the independent variable to overestimate. Among three types of regression curves considered, the result for the average was most appropriate. However this case was found to be inferior to the regression line passing the origin under the assumption of the normal distribution with the rain gauge rainfall as its independent variable. So it was hard to conclude that the consideration of the log-normality on the correction of radar rainfall is beneficial.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.2
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• pp.90-98
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• 2006

Signals captured from a Combo calibration standard tube paly a crucial role in the evaluation of motorized rotating pancake coil (MRPC) probe signals from steam generator (SG) tubes in nuclear power plants (NPPs). Therefore, the Combo tube signals should be consistent and accurate. However, MRPC probe signals are very easily affected by various factors around the tubes so that they can be distorted in their amplitudes and phase angles which are the values specifically used in the evaluation. To overcome this problem, in this study, we explored possibility of simulation to be used as a practical calibration tool far the evaluation of real field signals. For this purpose, we investigated the characteristics of a MRPC probe and a Combo tube. And then using commercial software (VIC-3D) we simulated a set of calibration signals and compared to the experimental signals. From this comparison, we verified the accuracy of the simulated signals. Finally, we evaluated two defects using the simulated Combo tube signals, and the results were compared with those obtained using the actual field calibration signals.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.455-455
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• 2017

최근 기후변화로 인한 도시홍수 피해가 증가하고 있다. 이에 따라 본 연구에서는 기상청에서 제공하는 HadGEM3-RA의 한반도(12.5km) 기후변화 RCP 4.5 및 RCP 8.5시나리오에 대해 편의보정 및 시간상세화를 실시하여 기후변화를 고려한 수문분석을 하였다. 기후변화 시나리오의 편의보정은 Gamma분포를 이용한 모수적 분위사상법과 관측자료의 누가확률분포를 이용하는 비모수적 분위사상법으로 수행하였으며, 관측된 분 단위 강우자료를 기반으로 기후변화 시나리오 미래기간에 대해 시간상세화를 실시하였다. 또한, 도림천유역을 중심으로 기후변화 시나리오 미래기간의 확률강우량과 설계홍수량을 산정하였다. 본 연구에 결과는 수문분석을 위한 기후변화 시나리오 시간상세화 방안에 크게 기여 할 것으로 판단된다.

• The Journal of Engineering Geology
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• v.25 no.4
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• pp.525-532
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• 2015

After comparing the effectiveness of standoff compensation between current techniques using data obtained from a series of borehole model experiments for standoff compensation in 2007, 2008, and 2009, a follow-up study was conducted to find a more effective standoff compensation algorithm, Comparing the results of the application of the conventional spine and ribs technique, and the spine and ribs technique in terms of apparent density shows that the standoff compensation error obtained from the latter method is more than twice that obtained from the former. The larger size of the compensation error from the spine and ribs plot using the radioactive decay equation indicates that there are no benefits in using this equation in standoff compensation. Based on these results, we propose a reverse transform spine and ribs technique by essentially combining the conventional spine and ribs technique and the spine and ribs technique in terms of apparent density.

• Analytical Science and Technology
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• v.36 no.6
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• pp.315-323
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• 2023

This study is to quantify α-quartz, cristobalite and kaolinite using by FTIR in respirable dust generated in the mining workplace. Various minerals in mines can interfere with peaks when quantifying respirable crystalline silica by FTIR. Therefore, for accurate quantification, it is necessary to remove interfering substances or correct the peaks that cause interference. To confirm the peaks occurring in α-quartz, cristobalite and kaolinite, each standard material was diluted with KBr and scanned in the range of 400 cm^-1 to 4000 cm^-1 using by FTIR. As a result of scanning the analytes, it was decided to use the peaks of 797.66 cm^-1 and 695.25 cm^-1 for α-quartz, 621.58 cm^-1 for cristobalite, and 3696.47 cm^-1 for kaolinite. When the above materials are mixed, interference occurs at the peak for quantification, which is corrected by the calculation formula. The analysis of the mixture of α-quartz and cristobalite shows the average bias (%) of 2.64 (corrected) at α-quartz (797.66 cm^-1), 5.61 (uncorrected) at α-quartz (695.25 cm^-1) and 1.51 (uncorrected) at cristobalite (621.58 cm^-1). The analysis of the mixture of α-quartz and kaolinite shows the average bias(%) of 1.79(corrected) at α-quartz (797.66 cm^-1), 3.92 (corrected) at α-quartz (695.25 cm^-1) and 2.58 (uncorrected) at kaolinite (3696.47 cm^-1). The analysis of the mixture of cristobalite and kaolinite shows the average bias (%) of 2.15 (corrected) at cristobalite (621.58 cm^-1), 4.32 (uncorrected) at kaolinite (3696.47 cm^-1). The analysis of the mixture of αquartz and cristobalite and kaolinite shows the average bias (%) of 1.93(corrected) at α-quartz (797.66 cm^-1), 6.47 (corrected) at α-quartz (695.25 cm^-1) and 1.77 (corrected) at cristobalite (621.58 cm^-1) and 2.61 (uncorrected) at kaolinite (3696.47 cm^-1). The experimental results showed that the deviation caused by peak interference by two or three substances could be corrected to less than 6 % of the average deviation. This study showed the possibility of correcting and quantifying when various interfering substances that are difficult to remove are mixed.