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

• Ecology and Resilient Infrastructure
• /
• v.10 no.4
• /
• pp.208-216
• /
• 2023

The purpose of this study is to present the most appropriate hardware and software configurations to produce a practical SIV (surface image velocimeter). To make a practical SIV, we constructed the system with a CCTV, a water stage gauge, and an analysis software installed on an Android board. The camera captures continuously images for 30 seconds with 2 minute intervals. And the 11-parameter projection method was used in the software that analyzes the captured images to reconstruct the exact measurement points according to the changing water stage. In addition, a spatio-temporal image construction method was developed so that the directions of the images could be arranged in the main flow direction at each measurement point. The surface image velocimeter composed of the proposed method was produced and installed at the Insu Stream, Seoul for a test site. And a result of measurement during a heavy rainfall event showed that the proposed system can measure flow discharge in proper, rapid and continuous manner.

• Journal of Korea Water Resources Association
• /
• v.50 no.9
• /
• pp.597-607
• /
• 2017

In this study, the applicability of the surface image velocimeter using the far-infrared camera was examined in order to solve the application problem of the measurement in night time, which has been pointed out in previous studies as the limit of the surface image velocimeter. For this purpose, the accuracy evaluation of measurement of the far-infrared camera was conducted for two conditions. Accuracy was evaluated by calculating the relative error of the results of the measurements of surface image velocimeter using the normal video camera during the daytime that was already verified. As a result, the relative error of the surface velocimeter using the far infrared camera was 4.3% at maximum, the average error was about 1%, and the error of the fog condition was maximum 5.2% with an average of 2%. In conclusion, it is possible to measure with high accuracy when using far-infrared camera in a invisible environments where the water flow can not be visualized with a general camera.

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

• Journal of Korea Water Resources Association
• /
• v.49 no.6
• /
• pp.469-480
• /
• 2016

The present study aims to develop a real-time surface image velocimeter (SIV) using an Android smartphone. It can measure river surface velocity by using its built-in sensors and processors. At first the SIV system figures out the location of the site using the GPS of the phone. It also measures the angles (pitch and roll) of the device by using its orientation sensors to determine the coordinate transform from the real world coordinates to image coordinates. The only parameter to be entered is the height of the phone from the water surface. After setting, the camera of the phone takes a series of images. With the help of OpenCV, and open source computer vision library, we split the frames of the video and analyzed the image frames to get the water surface velocity field. The image processing algorithm, similar to the traditional STIV (Spatio-Temporal Image Velocimeter), was based on a correlation analysis of spatio-temporal images. The SIV system can measure instantaneous velocity field (1 second averaged velocity field) once every 11 seconds. Averaging this instantaneous velocity measurement for sufficient amount of time, we can get an average velocity field. A series of tests performed in an experimental flume showed that the measurement system developed was greatly effective and convenient. The measured results by the system showed a maximum error of 13.9 % and average error less than 10 %, when we compared with the measurements by a traditional propeller velocimeter.

• Journal of Environmental Science International
• /
• v.23 no.4
• /
• pp.571-584
• /
• 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
• /
• 2015.05a
• /
• pp.381-381
• /
• 2015

표면영상유속계측법(Surface Image Velocimeter; SIV)은 영상분석기법의 일종으로 하천 표면의 유동을 영상저장장치로 기록하고 연속되는 이미지상의 입자이동을 계산하여 유속을 산정하는 방법이다. 그러나 표면영상유속계를 활용한 유속분석과정에서 현장 상황에 따라 많은 오차 요인들이 있을 수 있기 때문에 계산한 유속 산정 결과를 그대로 사용하면 정확도가 낮아질 수 있다. 특히 야간 영상과 같은 영상의 화질이 떨어지는 경우에는 유속 산정 결과를 필터링해서 사용해야 한다. 이는 순간 유속장을 분석하는 과정에서 획득된 이미지에 따라 분석된 유속벡터가 평균 유속보다 과다하게 크거나 상관계수 값이 너무 작은 경우가 포함되기 때문이다. 이 연구에서는 제주도 외도천 외도정수장에서 2013년 5월 27일 집중호우에 의한 유출 발생 주 야간 유출영상자료를 획득하여 표면영상유속계(SIV)와 ADCP를 활용하여 유량을 분석하고, 동시에 고정식 전자파 표면유속계인 Kalesto 관측 유량과 비교 분석하였다. 비교과정에서 제주도는 댐방류량과 같은 유량의 참값이 없으므로 각각 관측기기의 상대적인 비교를 하여 경향성을 분석하였다. 분석결과 주간유출영상은 상관계수가 0.6~0.7범위에 해당하는 유속이 전체 59개의 유속벡터 중 6.8%로 나타났으며, 0.7~0.8범위가 13.6%, 0.8~0.9범위가 18.6%, 0.9~1.0범위가 61.0%의 퍼센트를 나타났다. 야간유출영상을 주간유출영상과 비교해보면 0.6~0.7범위에 해당하는 상관계수가 6.8% 높게 분석되었으며, 반대로 0.9~1.0범위에 해당하는 상관계수는 17% 낮게 분석되었다. 이와 같은 결과는 야간유출영상이 주간유출영상에 비해 영상의 질이 떨어짐을 나타내며 표면영상유속계를 적용하여 유량을 산정하는 과정에서 획득되는 영상에 따라 상관계수에 대한 합리적인 필터링 과정이 필요하다.

• Journal of Environmental Science International
• /
• v.26 no.9
• /
• pp.999-1011
• /
• 2017

In this study, the Chiu-2D velocity-flow rate distribution based on theoretical background of the entropy probability method was applied to actual ADCP measurement data of Gangjung Stream in Jeju from July 2011 to June 2015 to predict the parameter that take part in velocity distribution of the stream. In addition, surface velocity measured by SIV (Surface Image Velocimeter) was applied to the predicted parameter to calculate discharge. Calculated discharge was compared with observed discharge of ADCP observed during the same time to analyze propriety and applicability of depth of water velocity average conversion factor. To check applicability of the predicted stream parameter, surface velocity and discharge were calculated using SIV and compared with velocity and flow based on ADCP. Discharge calculated by applying velocity factor of SIV to the Chiu-2D velocity-flow rate distribution and discharge based on depth of water velocity average conversion factor of 0.85 were $0.7171m^3/sec$ and $0.5758m^3/sec$, respectively. Their error rates compared to average ADCP discharge of $0.6664m^3/sec$ were respectively 7.63% and 13.64%. Discharge based on the Chiu-2D velocity-flow distribution showed lower error rate compared to discharge based on depth of water velocity average conversion factor of 0.85.

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

A surface image velocimeter (SIV) measures the velocity of a particle group by calculating the intensity distribution of the particle group in two consecutive images of the water surface using a cross-correlation method. Therefore, to increase the accuracy of the flow velocity calculated by a SIV, it is important to accurately calculate the displacement of the particle group in the images. In other words, the change in the physical distance of the particle group in the two images to be analyzed must be accurately calculated. In the image of an actual river taken using a camera, camera lens distortion inevitably occurs, which affects the displacement calculation in the image. In this study, we analyzed the effect of camera lens distortion on the displacement calculation using a dense and uniformly spaced grid board. The results showed that the camera lens distortion gradually increased in the radial direction from the center of the image. The displacement calculation error reached 8.10% at the outer edge of the image and was within 5% at the center of the image. In the future, camera lens distortion correction can be applied to improve the accuracy of river surface flow rate measurements.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2016.05a
• /
• pp.534-538
• /
• 2016

2012년 9월 17일 제 16호 태풍 산바의 내습에 의한 유출발생 시 제주도 천미천 유역의 성읍교 부근에서 최대 수위 3.94 m를 기록한 9시 00분 유출영상에 표면영상유속계(SIV)를 적용하여 참조점 설정에 따른 오차율을 분석하였다. 참조점 설정 과정에서 원거리의 참조점 입력 오류가 발생하면 2~11 pixel의 미세한 오류값 입력에 의해 X축 방향으로 0.42 m, Y축 방향으로 0.94 m의 실거리 변화율이 발생하며, 근거리의 참조점 입력 오류가 발생하면 1~11 pixel의 미세한 오류값 입력에 의해 X축 방향으로 0.02 m, Y축 방향으로 0.28 m의 실거리 변화율을 발생시킨다. 이 같은 실거리 변화율은 원거리의 참조점 설정변수에 따라 유속 오차율은 최소 16.77%에서 최대 317.69%의 변동 폭을 나타냈으며, 유량 산정 시 최소 16.86%에서 최대 338.63%의 변동 폭을 나타냈다. 또한 근거리의 참조점 설정변수에 따라 유속 오차율은 최소 1.10%에서 최대 74.47%의 변동 폭을 나타냈으며, 유량 산정 시 최소 0.82%에서 최대 59.28%의 변동 폭을 나타냈다.