scholarly journals Measuring River Surface Velocity with Doppler Radar and Particle Image Velocimetry (PIV) Using Unmanned Aerial Systems (UASs)

2021 ◽  
Author(s):  
Filippo Bandini ◽  
Monica Coppo Frias ◽  
Jun Liu ◽  
Kasparas Simkus ◽  
Sofia Karagkiolidou ◽  
...  
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Doppler Radar ◽  
Low Cost ◽  
High Water ◽  
Surface Velocity ◽  
Unmanned Aerial Systems ◽  
Image Velocimetry ◽  
Remote Sensing Techniques ◽  
Aerial Systems

Surface velocity is traditionally measured with invasive techniques such as velocity probes (in shallow rivers) or Acoustic Doppler Current Profilers (in deeper water). In the last years, researchers have developed remote sensing techniques, both optical (e.g. image-based velocimetry techniques) and microwave (e.g. Doppler radar). These techniques can be deployed from Unmanned Aerial Systems (UAS), which ensure fast and low-cost surveys also in remote locations. We compare the results obtained with a UAS-borne Doppler radar and UAS-borne Particle Image Velocimetry (PIV) in different rivers, which presented different hydraulic conditions (width, slope, surface roughness and sediment material). The Doppler radar was a commercial 24 GHz instrument, developed for static deployment, adapted for UAS integration. PIV was applied with natural seeding (e.g. foam, debris) when possible or, with artificial seeding (woodchips) in the stream where the density of natural particles was insufficient. PIV reconstructed the velocity profile with high accuracy typically in the order of a few cm/s in all investigated rivers, whilst UAS-borne radar was only successful in locations with high water roughness. However, UAS integration of Doppler radar is complex because of vibrations, large instrument sampling footprint, large required sampling time and difficult-to-interpret quality indicators.

scholarly journals sUAS-Based Remote Sensing of River Discharge Using Thermal Particle Image Velocimetry and Bathymetric Lidar

2019 ◽  
Vol 11 (19) ◽  
pp. 2317 ◽  
Author(s):  
Paul Kinzel ◽  
Carl Legleiter
Keyword(s):  
Particle Image Velocimetry ◽  
River Discharge ◽  
Water Surface ◽  
Large Scale ◽  
Particle Image ◽  
Field Evaluation ◽  
Remotely Sensed ◽  
Surface Velocity ◽  
Unmanned Aerial Systems ◽  
Image Velocimetry

This paper describes a non-contact methodology for computing river discharge based on data collected from small Unmanned Aerial Systems (sUAS). The approach is complete in that both surface velocity and channel geometry are measured directly under field conditions. The technique does not require introducing artificial tracer particles for computing surface velocity, nor does it rely upon the presence of naturally occurring floating material. Moreover, no prior knowledge of river bathymetry is necessary. Due to the weight of the sensors and limited payload capacities of the commercially available sUAS used in the study, two sUAS were required. The first sUAS included mid-wave thermal infrared and visible cameras. For the field evaluation described herein, a thermal image time series was acquired and a particle image velocimetry (PIV) algorithm used to track the motion of structures expressed at the water surface as small differences in temperature. The ability to detect these thermal features was significant because the water surface lacked floating material (e.g., foam, debris) that could have been detected with a visible camera and used to perform conventional Large-Scale Particle Image Velocimetry (LSPIV). The second sUAS was devoted to measuring bathymetry with a novel scanning polarizing lidar. We collected field measurements along two channel transects to assess the accuracy of the remotely sensed velocities, depths, and discharges. Thermal PIV provided velocities that agreed closely ( R 2 = 0.82 and 0.64) with in situ velocity measurements from an acoustic Doppler current profiler (ADCP). Depths inferred from the lidar closely matched those surveyed by wading in the shallower of the two cross sections ( R 2 = 0.95), but the agreement was not as strong for the transect with greater depths ( R 2 = 0.61). Incremental discharges computed with the remotely sensed velocities and depths were greater than corresponding ADCP measurements by 22% at the first cross section and <1% at the second.

scholarly journals EVALUATION OF AIRBORNE IMAGE VELOCIMETRY APPROACHES USING LOW-COST UAVS IN RIVERINE ENVIRONMENTS

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 597-604
Author(s):  
F. Ioli ◽  
L. Pinto ◽  
D. Passoni ◽  
V. Nova ◽  
M. Detert
Keyword(s):  
Particle Image Velocimetry ◽  
Velocity Field ◽  
Flow Velocity ◽  
Particle Image ◽  
Low Cost ◽  
Time Lag ◽  
Surface Velocity ◽  
Low Flow ◽  
Graphical Interface ◽  
Image Velocimetry

Abstract. Traditional flow velocity measurements in natural environments require contact with the fluid and are usually costly, time-consuming and, sometimes, even dangerous. Particle Image Velocimetry allows the flow velocity field to be remotely characterized from the shift of intensity patterns of sub-image areas in at least two video frames with a known time lag. Recently, Airborne Image Velocimetry has enabled the surface velocity field of large-scale water bodies to be determined by applying Particle Image Velocimetry on videos recorded by cameras mounted on unmanned aerial vehicles. This work presents a comparison of three Airborne Image Velocimetry approaches: BASESURV, Fudaa-LSPIV and RIVeR. For the evaluation, two nadiral videos were acquired with a low-cost quadcopter. The first was recorded under low flow and seeded conditions, the second during a flood event. According to the results obtained, BASESURV is an accurate and complete research oriented approach but it is time-consuming and neither a graphical interface nor documentation are yet provided. Fudaa-LSPIV is a well-developed software package, with a user-friendly graphical interface and good documentation. However it lacks some features and the source code is closed. RIVeR may be suitable for real time monitoring thanks to the rectification of velocity vectors only. Overall, all the codes are found to be effective in performing Airborne Image Velocimetry in riverine environments.

Development and Testing of an Unmanned Aerial Vehicle for Large Scale Particle Image Velocimetry

2014 ◽  
Author(s):  
Christopher Pagano ◽  
Flavia Tauro ◽  
Salvatore Grimaldi ◽  
Maurizio Porfiri
Keyword(s):  
Particle Image Velocimetry ◽  
Large Scale ◽  
Field Experiments ◽  
Particle Image ◽  
Low Cost ◽  
Surface Flow ◽  
Natural Environments ◽  
Natural Stream ◽  
Image Velocimetry ◽  
Scale Particle

Large scale particle image velocimetry (LSPIV) is a nonintrusive environmental monitoring methodology that allows for continuous characterization of surface flows in natural catchments. Despite its promise, the implementation of LSPIV in natural environments is limited to areas accessible to human operators. In this work, we propose a novel experimental configuration that allows for unsupervised LSPIV over large water bodies. Specifically, we design, develop, and characterize a lightweight, low cost, and stable quadricopter hosting a digital acquisition system. An active gimbal maintains the camera lens orthogonal to the water surface, thus preventing severe image distortions. Field experiments are performed to characterize the vehicle and assess the feasibility of the approach. We demonstrate that the quadricopter can hover above an area of 1×1m2 for 4–5 minutes with a payload of 500g. Further, LSPIV measurements on a natural stream confirm that the methodology can be reliably used for surface flow studies.

An Experimental Review on Microbubble Generation to be Used in Echo-Particle Image Velocimetry Method to Determine the Pipe Flow Velocity

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
Alinaghi Salari ◽  
M. B. Shafii ◽  
Shapour Shirani
Keyword(s):  
Particle Image Velocimetry ◽  
Contrast Agents ◽  
Particle Image ◽  
Low Cost ◽  
Ultrasound Contrast Agents ◽  
Surface Active Agents ◽  
Image Velocimetry ◽  
Particle Image Velocimetry Method ◽  
Microbubble Contrast Agents

Microbubbles are broadly used as ultrasound contrast agents. In this paper we use a low-cost flow focusing microchannel fabrication method for preparing microbubble contrast agents by using some surface active agents and a viscosity enhancing material to obtain appropriate microbubbles with desired lifetime and stability for any in vitro infusion for velocity measurement. All the five parameters that govern the bubble size extract and some efforts are done to achieve the smallest bubbles by adding suitable surfactant concentrations. By using these microbubbles for the echo-particle image velocimetry method, we experimentally determine the velocity field of steady state and pulsatile pipe flows.

Large scale particle image velocimetry measurement of river surface velocity based on images captured by a camera of the mobile phone

2020 ◽  
Author(s):  
Wen-Cheng Liu ◽  
Wei-Che Huang
Keyword(s):  
Particle Image Velocimetry ◽  
Mobile Phone ◽  
Large Scale ◽  
Particle Image ◽  
Digital Camera ◽  
Real Space ◽  
Surface Velocity ◽  
Image Velocimetry ◽  
Scale Particle ◽  
Perspective Center

&lt;p&gt;In this research, we conducted LSPIV (Large Scale Particle Image Velocimetry) measurements to measure river surface velocity based on images recorded by mobile phone. The realization of this research is based on the developments of two products. The first one is the digital camera, which has been combined with the mobile phone after several years of development. The second one is the three-axis accelerometer, which can measure the attitude of the object. A three-axis accelerometer is one of the necessary parts of the mobile phone nowadays, as many functions of the mobile phone, such as step counting, Do Not Disturb mode, games, require the detection of attitude.&lt;/p&gt;&lt;p&gt;In LSPIV, there are nine parameters of the collinear equation. Three of parameters are the coordinates of the perspective center in the image space (focus distance d and image center position (u, v)), which can be determined in advance in the laboratory; the other three parameters are the coordinates (x, y, z) of the perspective center in real space, which can be set to (0, 0, 0); the last three parameters are the attitude of the camera (i.e., the mobile phone), which is determined by the depression angle, the horizontal angle, and the left-right rotation angle and can be measured by three-axis accelerometer. Therefore, river surface velocity could be analyzed by LSPIV with not only continuous images captured by a camera of the mobile phone but also the acceleration values obtained by the three-axis accelerometer when each image was captured.&lt;/p&gt;&lt;p&gt;In the present study, Yufeng gauging station, which is in the upstream catchment of the Shihmen Reservoir in Taiwan, is selected as the study site. Two other measurement methods were used to measure the river surface velocity and the comparison was conducted. One is using a handheld digital flow meter and another is using LSPIV with control points to calculate the parameters for measuring the river surface velocity.&lt;/p&gt;

Comparison of the surface velocity of a debris flow at the Gadria creek using pulse compression radar and digital particle image velocimetry (DPIV).

2020 ◽  
Author(s):  
Tobias Schöffl ◽  
Georg Nagl ◽  
Johannes Hübl
Keyword(s):  
Particle Image Velocimetry ◽  
Debris Flow ◽  
Debris Flows ◽  
Pulse Compression ◽  
Particle Image ◽  
Video Camera ◽  
Digital Particle Image Velocimetry ◽  
Surface Velocity ◽  
Image Velocimetry ◽  
Pulse Compression Radar

&lt;p&gt;&lt;strong&gt;Comparison of the surface velocity of a debris flow at the Gadria creek using pulse compression radar and digital particle image velocimetry (DPIV).&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&amp;#160;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Tobias Sch&amp;#246;ffl, Georg Nagl, Johannes H&amp;#252;bl&lt;/p&gt;&lt;p&gt;Institute of Mountain Risk Engineering, University of Natural Resources and Life Sciences, Vienna, Austria&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;A central aspect of protection against debris flows is the understanding of the process. The flow velocity is an important parameter which is used, for example, in the dimensioning of protective structures, for technical building protection and for early warning systems. The measurement of the surface velocity which is regarded as the maximum velocity occurring within a debris flow, is therefore an essential link in the chain of fundamental process research and applied protection against natural hazards.&lt;/p&gt;&lt;p&gt;Due to the further development of various technologies such as video technology and high-frequency radar technology, the non-contact measurement of the surface speed of a debris flow has improved significantly in recent years. Radar technology provides a wide aspect of applications in alpine mass movements such as debris flows, avalanches and rockfall and is able to detect such processes up to a range of 2500 meters in distance. An additional beneficial feature is the possibility of non-contact measurement of the surface velocity. In the catchment area of the Gadria basin (South Tyrol, Italy), the measuring station, which has been in operation since 2016, has been extended by a pulse compression radar and a new HD video camera. On July 26, 2019 a debris flow consisting of several surges was recorded with both the radar and the HD video camera. To obtain surface velocity data from the video material, the material was analyzed and evaluated using digital particle image velocimetry by making use of the MATLAB software and its freely accessible ADD-On &quot;PIVlab&quot;.&lt;/p&gt;&lt;p&gt;The results of the compared surface velocity data showed a value of up to 0.74 according to the statistical mean of the coefficient of determination. The results demonstrate the high effectiveness of the pulse compression radar and the DPIV analysis in a wide range of the assessment of surface velocity of natural debris flows. There is great potential in both measuring systems and the chosen comparative analysis provides a blueprint for future recorded debris flows.&lt;/p&gt;

scholarly journals Efficiency of a Digital Particle Image Velocimetry (DPIV) Method for Monitoring the Surface Velocity of Hyper-Concentrated Flows

Geosciences ◽  
2018 ◽  
Vol 8 (10) ◽  
pp. 383 ◽  
Author(s):  
Donatella Termini ◽  
Alice Di Leonardo
Keyword(s):  
Particle Image Velocimetry ◽  
Digital Image ◽  
Particle Image ◽  
Estimation Error ◽  
Digital Particle Image Velocimetry ◽  
Velocity Estimation ◽  
Surface Velocity ◽  
Image Velocimetry ◽  
Image Technique ◽  
Interrogation Area

Digital particle image velocimetry records high resolution images and allows the identification of the position of points in different time instants. This paper explores the efficiency of the digital image-technique for remote monitoring of surface velocity and discharge measurement in hyper-concentrated flow by the way of laboratory experiment. One of the challenges in the application of the image-technique is the evaluation of the error in estimating surface velocity. The error quantification is complex because it depends on many factors characterizing either the experimental conditions or/and the processing algorithm. In the present work, attention is devoted to the estimation error due either to the acquisition time or to the size of the sub-images (interrogation areas) to be correlated. The analysis is conducted with the aid of data collected in a scale laboratory flume constructed at the Hydraulic laboratory of the Department of Civil, Environmental, Aerospace and of Materials Engineering (DICAM)—University of Palermo (Italy) and the image processing is carried out by the help of the PivLab algorithm in Matlab. The obtained results confirm that the number of frames used in processing procedure strongly affects the values of surface velocity; the estimation error decreases as the number of frames increases. The size of the interrogation area also exerts an important role in the flow velocity estimation. For the examined case, a reduction of the size of the interrogation area of one half compared to its original size has allowed us to obtain low values of the velocity estimation error. Results also demonstrate the ability of the digital image-technique to estimate the discharge at given cross-sections. The values of the discharge estimated by applying the digital image-technique downstream of the inflow sections by using the aforementioned size of the interrogation area compares well with those measured.

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