• Journal of Environmental Science International
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• v.22 no.5
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• pp.581-589
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• 2013

Surface Image Velocimetry(SIV) is an instrument to measure water surface velocity by using image processing techniques. Since SIV is a non-contact type measurement method, it is very effective and useful to measure water surface velocity for steep mountainous streams, such as streams in Jeju island. In the present study, a surface imaging velocimetry system was used to calculate the flow rate for flood event due to a typhoon. At the same time, two types of electromagnetic surface velocimetries (electromagnetic surface current meter and Kalesto) were used to observe flow velocities and compare the accuracies of each instrument. The comparison showed that for velocity distributions root mean square error(RMSE) was 0.33 and R-squared was 0.72. For discharge measurements, root mean square error(RMSE) reached 6.04 and R-squared did 0.92. It means that surface image velocimetry could be used as an alternative method for electromagnetic surface velocimetries in measuring flood discharge.

• Journal of Environmental Science International
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• v.24 no.4
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• pp.359-369
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• 2015

This study analyzed the velocimetry of runoff and measured the flood discharge by applying the SIV (Surface Image Velocimetrer) to the daytime and nighttime flow image data with special reference to Seong-eup Bridge at Cheonmi stream of Jeju during the flow by the severe rainstorm on May 27, 2013. A 1000W lighting apparatus with more than 150 lux was installed in order to collect proper nighttime flow image applied to the SIV. Its value was compared and analyzed with the velocity value of the fixed electromagnetic wave surface velocimetry (Kalesto) at the same point to check the accuracy and applicability of the measured velocity of flow. As a result, determination coefficient $R^2$ values were 0.891 and 0.848 respectively in line with the velocity distribution of the daytime and nighttime image and the flow volume measured with Kalesto was approximately 18.2% larger than the value measured with the SIV.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.739-742
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• 2008

Surface Image Velocity (SIV) is a technique which measures the surface velocity of river by using the principle of Paticle Image Velocimetry (PIV). The technique is economical and efficient way to measure velocity in rivers. The present paper aims to apply the technique to three rivers in Korea. It uses pairs of river surface images taken with two digital-cameras and reference points and cross section data which were acquired through plane survey. The performance of SIV was verified with automatic cart on an experimental flume. The test revealed that average error was less than 10 %, which assures that SIV can be used to measure velocity accurately. When it was applied to rivers with low water levels or rough weather condition, however, it showed the error about 20 %. If the problems of SIV technique are settled down, it can be one of the most convenient and economical ways to measure water discharge anytime and anywhere. And then it would be helpful to river management as developing a real-time river information system.

• Journal of Environmental Science International
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• v.23 no.4
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• pp.571-584
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• 2014

The present study aims to apply a surface image velocimetry(SIV) system to video images captured with CCTV and estimate the flood discharge. The CCTV was installed at the Hancheon Bridge of the Han Cheon in Jeju Island for disaster surveillance, and seven flood events occurred in 2012 were used. During the image analyses, input parameters, interrogation areas and searching areas were determined with proper calibration procedures. To check for accuracy and applicability of SIV, the velocities and flood discharges estimated by SIV were compared with the measured ones by an electromagnetic surface velocimeter, Kalisto. The comparison results showed fairly good agreements. The RMSE(Root Mean Square Error) values between two instruments showed a range of 4.13 and 14.2, and the determination coefficients reached 0.75 through 0.85. It means that the SIV could be used as a good alternative method for other traditional velocity measuring instruments in measuring flood discharges.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1926-1930
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• 2010

표면영상유속계(SIV, Surface Image Velcimetry)는 수표면의 영상분석을 통해 유속을 측정하는 도구이다. SIV는 하천의 유속을 매우 간편하게 측정할 수 있기 때문에, 야외 실험이나 하천의 유속 측정에 매우 유용한 장비이다. 그러나, SIV를 이용하여 유량을 산정하고자 할 경우, 하천 표면의 평면 측량 자료와 하천의 단면 측량 자료가 반드시 필요하다. 그러나, 측량 작업 특히 강우 중의 측량 작업은 매우 번거롭기 때문에, SIV의 간편성과 유용성에도 불구하고, 이용자들로 하여금 SIV를 쉽게 이용하기 어렵다는 그릇된 인식을 줄 수 있다. 만일 번거로운 측량을 거치지 않고도 효율적이고 간편하게 하천의 평면을 추정할 수 있다면, SIV를 마치 일반적인 프로펠러 유속계처럼 쉽게 이용할 수 있을 것이며, 그 적용성도 크게 증진될 것이다. 본 연구는 카메라 영상 모형을 유도하는 것이다. 이 카메라 모형을 이용하여 번거로운 측량 작업이 없이 평면의 좌표점을 추정할 수 있게 되며, 유속장 측정을 자동화할 수 있을 것이다. 이를 위하여 평면 좌표와 참조점을 관련짓는 사영 변환과 회전 변환 등 사진 측정 기법을 도입하였다.

• Journal of Environmental Science International
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• v.24 no.4
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• pp.403-414
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• 2015

This study is daytime and nighttime runoff image data caused by heavy rain on May 27, 2013 at Oedo Water Treatment Plant of Oedo-Stream, Jeju to compute runoff by applying Surface image velocimeter (SIV) and analyzing correlation according to current. At the same time, current was comparatively analyzed using ADCP observation data and fixed electromagnetic surface current meter (Kalesto) observed at the runoff site. As a result of comparison on resolutions of daytime and nighttime runoff images collected, correlation coefficient corresponding to the range of 0.6~0.7 was 6.8% higher for nighttime runoff image compared to daytime runoff image. On the contrary, correlation coefficient corresponding to the range of 0.9~1.0 was 17% lower. This result implies that nighttime runoff image has lower image quality than daytime runoff image. In the process of computing current using SIV, a rational filtering process for correlation coefficient is needed according to images obtained.

• Journal of Korea Water Resources Association
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• v.41 no.8
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• pp.855-862
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• 2008

Surface Image Velocimetry (SIV) is an instrument to measure water surface velocity by using image processing techniques. To improve its measuring accuracy, it is essential to get high quality images with low skewness. A truck-mounted SIV system would be a good way to get images, since its crane gives high altitude to the images. However, the images taken with a truck-mounted SIV would be swayed due to the movement of crane and the camera by winds. In that case, to analyze the images, it is necessary to compensate the side sway in the images. The present study is to develop an algorithm to analyze the swayed images by combining common image processing techniques and coordinate transform techniques. The system follows the traces of some selected fixed points and calculates the displacements of the video camera. By subtracting the average velocity of the fixed points from that of grid points, the velocity fields of the flow can be corrected. To evaluate the system's performance, two image sets were used, one image set without side sway and another set with side sway. The comparison of their results showed very close with the error of around 6 %.

• Journal of Korea Water Resources Association
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• v.44 no.5
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• pp.377-388
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• 2011

Surface Image Velocimetry (SIV) is a recently-developed discharge measurement instrument. It uses image processing techniques to measure the water surface velocity and estimate water discharge with given cross section. The present study aims to implement a FSIV (Fixed-type Surface Image Velocimetry) at Soojeon Bridge in the Dalcheon. The hardware system consists of two digital cameras, a computer, and a pressure-type water stage gauge. The images taken with the hardware system are sent to a server computer via a wireless internet, and analyzed with a image processing software (SIV software). The estimated discharges were compared with the observed discharges through Goesan dam spillway and index velocity method using ADVM. The computed results showed a good agreement with the observed one, except for the night time. The results compared with discharges through Goesan dam spillway reached around 5~10% in the case of discharge over 30 m3/s, and the results compared with discharges through index velocity method using ADVM reached around 5% in the case of discharge over 200 $m^3/s$. Considering the low cost of the system and the visual inspection of the site situation with the images, the SIV would be fairly good way to measure water discharge in real time.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.340-340
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• 2012

하천의 정밀한 유량관측은 수자원의 확보 및 효율적인 관리에 가장 기본적으로 수행되어야 하며 하천유량측정에 사용되는 기존의 방법으로는 유속계를 이용하여 평수기 때의 유속을 관측하는 방법과 홍수기시에 봉부자를 이용한 관측방법이 널리 이용되어 왔다. 하지만 기존의 관측방법은 경제성 및 효율성면에서 뒤떨어지기 때문에 새로운 측정방법을 개발하기 위한 연구가 활발히 진행되고 있다. 최근에는 한국수자원공사에서 개발된 전자파표면유속계를 이용하여 홍수유량을 관측하는 방법과 영상처리기술을 이용하여 관측하는 방법들이 다양하게 이용되고 있으며 본 연구에서는 표면영상유속계(SIV, Surface Image Velocimertry)를 이용하여 유량을 관측하였으며 동시에 전자파표면 유속계를 이용하여 관측된 값과 비교 분석하였다. 표면영상유속계(SIV, Surface Image Velocimertry)는 동영상 카메라를 이용하여 강이나 하천의 표면 유동을 촬영하고, 영상을 초당 30프레임으로 분석하여 변위를 구한다음 영상들의 시간 간격을 이용하여 최종적으로 표면 유속을 구하는 방법이다. 여기에 표면 유속과 평균 유속의 관계(노영신, 2005)를 이용하고, 하천 횡단면을 적용하여 유량을 산정하는 기법이다. SIV 기법을 이용하여 제주도 한천유역에 적용하여 전자파표면유속계의 관측 값과 비교한 결과 2~3m/s의 유속 분포를 보이고 있으며 통상적으로 관측된 홍수 유출시의 유속과 근사한 값을 보이고 있다. 향후 다양한 유출 사상에 대하여 SIV 기법을 적용하여 검증하고 동시에 다양한 유량 관측 기법과 비교 검토한다면 제주도의 체계적인 유량 관측 기술을 확립할 수 있을 것으로 판단된다.

• Ecology and Resilient Infrastructure
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• v.8 no.1
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• pp.22-31
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• 2021

Surface image velocimetry (SIV) is a noncontact velocimetry technique based on images. Recently, studies have been conducted on surface velocity measurements using drones to measure a wide range of velocities and discharges. However, when measuring the surface velocity using a drone, reference points must be included in the image for image correction and the calculation of the ground sample distance, which limits the flight altitude and shooting area of the drone. A technique for calculating the surface velocity that does not require reference points must be developed to maximize spatial freedom, which is the advantage of velocity measurements using drone images. In this study, a technique for calculating the surface velocity that uses only the drone position and the specifications of the drone-mounted camera, without reference points, was developed. To verify the developed surface velocity calculation technique, surface velocities were calculated at the Andong River Experiment Center and then measured with a FlowTracker. The surface velocities measured by conventional SIV using reference points and those calculated by the developed SIV method without reference points were compared. The results confirmed an average difference of approximately 4.70% from the velocity obtained by the conventional SIV and approximately 4.60% from the velocity measured by FlowTracker. The proposed technique can accurately measure the surface velocity using a drone regardless of the flight altitude, shooting area, and analysis area.