Space-time Image Velocimetry Research Articles

Evaluation of the Applicability of STIV to Wave Characteristic Measurement in the Swash Zone

The swash zone is an area that causes a change in the shape of a beach by generating sediment transport under the influence of intermittent waves, where wave run-up and run-down are infinitely repeated in the final stage of the shoaling process. However, the ability to predict the sediment transport is extremely poor despite the swash zone being an extremely important area in terms of offshore disaster prevention. In particular, many researchers are conducting studies on the development of various types of observation equipment and analysis techniques because the turbulent flow of active fluid dominates the sediment transport and is an extremely important parameter for the analysis of the transport mechanism. However, in flow velocity measurement, it is difficult to measure a quantitative representative flow velocity over time because the swash zone has a shallow water depth and an active turbulent flow. Expensive equipment and short-time measurement are also limitations. Therefore, the purpose of this study was to evaluate the applicability of nonintrusive space-time image velocimetry(STIV) to analyze the flow characteristics of fluid in the swash zone, such as the movement velocity and period of intermittent waves in the shoaling process. The prediction accuracy was improved by removing various noises included in the images with the introduction of artificial intelligence for immediate and accurate calculation of the representative flow velocity using images that can be obtained easily. Consequently, it was discovered that the spatial representative flow velocity occurring in the swash zone, change in the wave period according to the shoaling effect, rip current and surface velocity can be measured.

Two-Dimensional Space-Time Image Velocimetry for Surface Flow Field of Mountain Rivers Based on UAV Video

Space-time image velocimetry (STIV) is a promising technique for river surface flow field measurement with the development of unmanned aerial vehicles (UAVs). STIV can give the magnitude of the velocity along the search line set manually thus the application of the STIV needs to determine the flow direction in advance. However, it is impossible to judge the velocity direction at any points before measurement in most mountainous rivers due to their complex terrain. A two-dimensional STIV is proposed in this study to obtain the magnitude and direction of the velocity automatically. The direction of river flow is independently determined by rotating the search line to find the space-time image which has the most prominent oblique stripes. The performance of the two-dimensional STIV is examined in the simulated images and the field measurements including the Xiasi River measurements and the Kuye River measurements, which prove it is a reliable method for the surface flow field measurement of mountain rivers.

An improvement of the Space-Time Image Velocimetry combined with a new denoising method for estimating river discharge

The Space-Time Image Velocimetry (STIV) is a time-averaged velocity measurement method, which takes river surface images as the analysis object, and detects the Main Orientation of Texture (MOT) in a generated Space-Time Image (STI) to obtain one-dimensional velocities on the water surface. The STIV has great potential in real-time monitoring of river flow owing to its high spatial resolution and low time complexity. However, the generated STI contains a lot of noise and interference texture, which is inevitable in practical applications. The practicality of the STIV is severely limited by the low-quality STI. To solve this problem, a denoising method based on the filtering technology is proposed and combined with different texture detection algorithms in this paper. The accuracy of this method is verified through a comparative field experiment with an impellor-style current meter. The experimental results show: (1) By using this new denoising method, the robustness and accuracy of the STIV are significantly improved no matter what kind of texture detection algorithm is adopted; (2) Among all the texture detection algorithms, the FFT-based STIV combined with the new denoising method performs best. The relative errors of the surface velocities are controlled within 6%, and the relative errors of the discharges are controlled within ±4%.

Application of masked two-dimensional Fourier spectra for improving the accuracy of STIV-based river surface flow velocity measurements

Space-time image velocimetry (STIV) is a well-established image-based technique for measuring river surface flow from videos or image time series. Because the fundamental measurement mechanism is relatively simple, STIV has been used widely in research and for practical purposes in Japan and other countries. The advantage of STIV over other imaging techniques such as large-scale particle image velocimetry (LSPIV) is its robustness. More specifically, the streamwise velocity component can be efficiently estimated by simply measuring the slope appearing in a space-time image (STI) that represents the advection of surface textures. However, in the course of practical applications cases occur in which STIV yields erroneous results when the measurement conditions at the river site are not satisfactory for accurate measurements, such as when the water surface includes textures other than those directly related to turbulent advection. In this research, surface textures are classified into ten types and image filters based on wavenumber–frequency spectra are developed to improve the quality of the STI so that the texture contains only those features that represents the advection of surface turbulence. The quality of the STI can be improved with the filters and thus further increase the robustness of the measurement technique.

Real-Time Measurement of Flash-Flood in a Wadi Area by LSPIV and STIV

Flash floods in wadi systems discharge large volumes of water to either the sea or the desert areas after high-intensity rainfall events. Recently, wadi flash floods have frequently occurred in arid regions and caused damage to roads, houses, and properties. Therefore, monitoring and quantifying these events by accurately measuring wadi discharge has become important for the installation of mitigation structures and early warning systems. In this study, image-based methods were used to measure surface flow velocities during a wadi flash flood in 2018 to test the usefulness of large-scale particle image velocimetry (LSPIV) and space–time image velocimetry (STIV) techniques for the estimation of wadi discharge. The results, which indicated the positive performance of the image-based methods, strengthened our hypothesis that the application of LSPIV and STIV techniques is appropriate for the analysis of wadi flash flood velocities. STIV is suitable for unidirectional flow velocity and LSPIV is reliable and stable for two-dimensional measurement along the wadi channel, the direction of flow pattern which varies with time.

Development of Aerial Space Time Volume Velocimetry for Measuring Surface Velocity Vector Distribution from UAV

Due to the remarkable development of unmanned aerial vehicle (UAV) in recent years, its application in river engineering increases widely mainly for the measurement of ground topography such as by the technique Structure from Motion (SfM) using a series of high-resolution static images. However, although UAV usually installed a high density video camera, the use of the movie is limited just for watching and observing the geometrical feature of the ground. In the light of such a present status, the authors have developed an aerial space-time image velocimetry (STIV) technique to measure streamwise river surface velocity distributions. However, as STIV is insensitive to the change of flow direction, the aerial space-time volume velocimetry (STVV) technique, which is an extension of STIV, was developed in this research. STVV examines the change of volumetric texture within a space-time volume (STV) instead of examining the change of image intensity on a line segment as in STIV. The performance of STVV was investigated during the measurement of snowmelt flood of the Shinano River by comparing it with those obtained by the other techniques such as STIV, LSPIV and ADCP. It was made clear the aerial STVV has a great advantage over the existing image-based techniques.

MEASUREMENT OF INUNDATING FLOW FROM A BROKEN ENBANKMENT BY USING VIDEO IMAGES SHOOT FROM A MEDIA HELICOPTER

The heavy rain disaster in the Kinugawa River basin that occurred along with the passage of the Typhoon 18 caused the embankment destruction in the middle reach of the river on September 10, 2015. Due to the overflow, the houses in the vicinity of the embankment collapsed, causing a flood inundation spreading over a wide area. Because the embankment breakwater occurred during the daytime, the state of the inundating flow was recorded from various angles by media helicopters or drones. In this study, we developed a method to extract quantitative flow information from a helicopter video image in which the shooting position and angles are changed one after another, because it was taken in emergency. In the analysis, the images were orthorectified after stabilizing the images, from which surface velocity distributions were measured by image-based technique such as the large-scale particle image velocimetry (LSPIV) or the space-time image velocimetry (STIV). As a result, the time change of water entering from the broken embankment and the total inundated water volume during the disaster were estimated. In addition, two-dimensional surface velocity distributions were analysed to show the spreading of inundated flow.

Wavenumber-frequency analysis of river surface texture to improve accuracy of image-based velocimetry

In the unseeded image-based techniques for river surface flow measurements, advection speed of surface textures composed of surface ripples or floating objects is measured by image analysis. However, the methods would yield erroneous information when the surface texture is affected by gravity waves propagating in all directions. In order to improve the measurement accuracy, such wave effects have to be subtracted in the image analysis. For that purpose, a wavenumber-frequency analysis was applied to a space-time image (STI) generated in the space-time image velocimetry (STIV) analysis and succeeded in eliminating the wavegenerated pattern contained in the texture in STI. It was made clear that turbulence-generated texture propagates at the speed of surface flow.

On the Texture Angle Detection Used in Space‐Time Image Velocimetry (STIV)

AbstractThe space‐time image velocimetry (STIV) method evaluates the velocity of a water surface by analyzing a texture angle within a space‐time image (STI) obtained from an image sequence of the flowing water's surface. The brightness gradient tensor (BGT) has been utilized for calculating the texture angle of the STI within the original STIV. The BGT is sensitive to image quality, especially high‐frequency noise, and this fact limits the capability and accuracy of the velocity estimation. The objectives of this study were to understand why the BGT is sensitive to high‐frequency noise and how to resolve this defect. In the manuscript, derivation of the BGT is first reviewed and then a geometric representation of the BGT is discussed. The reason the BGT is sensitive to high‐frequency noise is also discussed, and, then, based on geometric representations of the BGT, a measure to improve this defect is proposed. To demonstrate differences between the two methods, texture angles from artificial and field image sets were also analyzed using the BGT and the improved BGT.

Discharge Measurements of Snowmelt Flood by Space-Time Image Velocimetry during the Night Using Far-Infrared Camera

The space time image velocimetry (STIV) technique is presented and shown to be a useful tool for extracting river flow information non-intrusively simply by taking surface video images. This technique is applied to measure surface velocity distributions on the Uono River on Honshu Island, Japan. At the site, various measurement methods such as a radio-wave velocity meter, an acoustic Doppler current profiler (ADCP) or imaging techniques were implemented. The performance of STIV was examined in various aspects such as a night measurement using a far-infrared-ray (FIR) camera and a comparison to ADCP data for checking measurement accuracy. All the results showed that STIV is capable of providing reliable data for surface velocity and water discharge that agree fairly well with ADCP data. In particular, it was demonstrated that measurements during the night can be conducted without any difficulty using an FIR camera and the STIV technique. In particular, using the FIR camera, the STIV technique can capture water surface features better than conventional cameras even at low resolution. Furthermore, it was demonstrated that measurements during the night can be conducted without any difficulty.

洪水時のADCPデータに基づく更正係数の分布特性と流量推定の高度化に関する研究

In estimating river flow discharges from water surface velocity distributions measured by non-contact methods such as radio wave velocity meters or image-based techniques, it is important to use an appropriate value of surface velocity coefficient that yields a depth-averaged velocity from a surface velocity. Conventionally, a value of 0.85 has been widely used in practical purposes but its distribution feature under various conditions has not been clarified yet. In order to investigate a fundamental aspect of the coefficient, measurement data by a tethered ADCP, a remote-controlled ADCP and surface velocities obtained by space-time image velocimetry(STIV) as well as a three-dimensional numerical simulation data were compared for the floods of the Uono River and the Niyodo River. It was made clear from measured and numerical data that the variance of the coefficient distribution tends to increase with decrease of the relative water depth and vice versa.

Image Analysis and Reconstruction of the 2008 Toga River Flash Flood in an Urbanised Area

In the afternoon of 28 July 2008, a flash flood occurred in the water-friendly reach of the Toga River in Kobe City, tragically drowning five people that included three children. They were among about 50 people enjoying the river environment. The flash flood was caused by sudden localised torrential rain in urbanised area of the small river basin. The onset of the flash flood was captured by a river monitoring camera as consecutive still images, while the surface flow just after the peak flow was videotaped by a TV cameraman without using a tripod. In order to estimate the peak discharge of the flash flood, the space-time image velocimetry technique developed by the authors was applied to the video images after applying image stabilisation. The estimated discharge was used as an input hydraulic parameter of the 2D numerical simulation, with a success of reproducing the transient flow pattern observed by the monitoring camera. In addition, the distribution of hydrodynamic force the people in the river were exposed to was calculated to reveal the diff culty of evacuation in flash flood condition, even when the depth of water is less than knee high.

Measurement of the flood discharge of a small-sized river using an existing digital video recording system

In this study, a closed-circuit television (CCTV) system, installed for surveillance purposes, is utilized to measure the flow rate during a flood. The procedure to determine both the angle and scale-factor of the camera is described. Then, image analysis techniques, namely the direct visual measurement method, Large-Scale PIV (LSPIV) and Space-Time Image Velocimetry (STIV), are applied to the video images recorded by the CCTV camera. The results of these methods and the conventional float measurement are compared. In addition, the accuracy of the respective methods is discussed. A set of low-quality video images of a flood during a thunderstorm that occurred under the dark ambient conditions (midnight) is analyzed using three image-based methods. The transition of the flow rate during the event is successfully estimated.

MEASUREMENT ACCURACY OF NON-CONTACT DISCHARGE MEASUREMENT METHOD USING RIVER MONITORING MOVIE AND DEVELOPMENT OF QUASI REAL TIME MEASUREMENT SYSTEM

Monitoring of river is significant both in flow management and river usage. Although river monitoring systems have been installed in many rivers in Japan, most of the existing system do not record images and utilize them for quantitative measurement of the flow. Already proposed methods for quantitative measurement include image analysis techniques such as large scale particle image velocimetry (LSPIV) or space-time image velocimetry (STIV) proposed by the authors. However, there still resides skepticism about the accuracy of the methods. Therefore, we conducted concurrent measurements with ADCP to verify the performance of the image analysis techniques. At the same time, we established a quasi-real time system of discharge measurement by introducing a novel image collection system with high image compressibility.

Development of a non‐intrusive and efficient flow monitoring technique: The space‐time image velocimetry (STIV)

A novel image analysis technique for measuring river surface flow is proposed. When we assume that the brightness distribution of river surface image is convected with the surface velocity, a space‐time image for a searching line set parallel to the main flow would indicate velocity information as its image orientation. The new technique, the space‐time image velocimetry (STIV), is capable to measure the orientation angle of the pattern using the eigenvalue analysis of the local space‐time image. The performance of STIV is compared with the other image analysis technique, the large‐scale particle image velocimetry (LSPIV), previously proposed by the authors and it is shown that STIV is an alternative image analysis method for measuring streamwise velocity distributions efficiently.