scholarly journals USING THERMAL AND RGB UAV IMAGERY TO MEASURE SURFACE FLOW VELOCITIES OF RIVERS

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 717-722
Author(s):  
A. Eltner ◽  
D. Mader ◽  
N. Szopos ◽  
B. Nagy ◽  
J. Grundmann ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Water Area ◽  
Image Sequences ◽  
Surface Flow ◽  
Frame Rate ◽  
Regulated River ◽  
Flying Height ◽  
Average Deviation ◽  
Target Field ◽  
Flow Velocities

Abstract. This study assesses the suitability to use RGB and thermal infrared imagery acquired from an UAV to measure surface flow velocities of rivers. The reach of a medium-scale river in Hungary is investigated. Image sequences with a frame rate of 2 Hz were captured with two sensors, a RGB and an uncooled thermal camera, at a flying height that ensures the visibility of both shores. The interior geometry of both cameras were calibrated with an in-house designed target field. The image sequences were automatically co-registered to account for UAV movements during the image acquisition. The TIR data was processed to keep loss-free image information solely in the water area and to enhance the signal to noise ratio. Image velocimetry with PIV applied to the TIR data and PTV applied to the RGB data was utilised to retrieve surface flow velocities. Comparison between RGB and TIR data reveal an average deviation of about 0.01 m/s. Future studies are needed to evaluate the transferability to other non-regulated river reaches.

scholarly journals Inferring Surface Flow Velocities in Sediment-Laden Alaskan Rivers from Optical Image Sequences Acquired from a Helicopter

2020 ◽  
Vol 12 (8) ◽  
pp. 1282 ◽  
Author(s):  
Carl J. Legleiter ◽  
Paul J. Kinzel
Keyword(s):  
Remote Sensing ◽  
Field Measurements ◽  
Video Camera ◽  
Image Sequences ◽  
Surface Flow ◽  
Optical Image ◽  
Frame Rate ◽  
Digital Mapping ◽  
Lower Frame ◽  
Flow Velocities

The remote, inaccessible location of many rivers in Alaska creates a compelling need for remote sensing approaches to streamflow monitoring. Motivated by this objective, we evaluated the potential to infer flow velocities from optical image sequences acquired from a helicopter deployed above two large, sediment-laden rivers. Rather than artificial seeding, we used an ensemble correlation particle image velocimetry (PIV) algorithm to track the movement of boil vortices that upwell suspended sediment and produce a visible contrast at the water surface. This study introduced a general, modular workflow for image preparation (stabilization and geo-referencing), preprocessing (filtering and contrast enhancement), analysis (PIV), and postprocessing (scaling PIV output and assessing accuracy via comparison to field measurements). Applying this method to images acquired with a digital mapping camera and an inexpensive video camera highlighted the importance of image enhancement and the need to resample the data to an appropriate, coarser pixel size and a lower frame rate. We also developed a Parameter Optimization for PIV (POP) framework to guide selection of the interrogation area (IA) and frame rate for a particular application. POP results indicated that the performance of the PIV algorithm was highly robust and that relatively large IAs (64–320 pixels) and modest frame rates (0.5–2 Hz) yielded strong agreement ( R 2 > 0.9 ) between remotely sensed velocities and field measurements. Similarly, analysis of the sensitivity of PIV accuracy to image sequence duration showed that dwell times as short as 16 s would be sufficient at a frame rate of 1 Hz and could be cut in half if the frame rate were doubled. The results of this investigation indicate that helicopter-based remote sensing of velocities in sediment-laden rivers could contribute to noncontact streamgaging programs and enable reach-scale mapping of flow fields.

FlowVeloTool: Measuring flow velocities in terrestrial and UAV image sequences automatically with PIV and PTV

2020 ◽  
Author(s):  
Anette Eltner ◽  
Jens Grundmann
Keyword(s):  
Flow Direction ◽  
Control Point ◽  
Region Of Interest ◽  
Software Tool ◽  
Image Sequences ◽  
Surface Flow ◽  
Area Of Interest ◽  
Image Velocimetry ◽  
Uav Image ◽  
Flow Velocities

<p>We introduce a Python based software tool to measure surface flow velocities and to estimate discharge eventually. Minimum needed input are image sequences, some camera parameters and object space information to scale the image measurements. Reference information can be provided either indirectly via ground control point measurements or directly providing camera pose parameters. To improve the reliability and density of velocity measurements the area of interest has to be masked for image velocimetry. This can either be performed with a binary mask file or considering a 3D point cloud, for instance retrieved with Structure from Motion (SfM) photogrammetry, describing the region of interest. The tracking task can be done with particle image velocimetry (PIV) considering small interrogation regions or using particle tracking velocimetry (PTV) and thus detecting and tracking features at the water surface. To improve the robustness of the tracking results, filtering can be applied that implements statistical information about the flow direction, flow steadiness and average velocities.</p><p>The FlowVeloTool has been tested with two different datasets; one at a gauging station and one at a natural river reach. Thereby, UAV and terrestrial data were acquired and processed. Velocities can be estimated with an accuracy of 0.01 m/s. If information about the river topography and bathymetry are available, as in our demonstration, discharge can be estimated with an error ranging from 5 to 31 % (Eltner et al. 2019). Besides these results we demonstrate further developments of the FlowVeloTool regarding filtering of tracking results, discharge estimation, and processing of time series. Furthermore, we illustrate that thermal data can be used, as well, with our tool to retrieve river surface velocities.</p><p> </p><p>Eltner, A., Sardemann, H., and Grundmann, J.: Flow velocity and discharge measurement in rivers using terrestrial and UAV imagery, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-289, 2019.</p>

scholarly journals A Convolutional Neural Network-Based Method for Corn Stand Counting in the Field

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 507
Author(s):  
Le Wang ◽  
Lirong Xiang ◽  
Lie Tang ◽  
Huanyu Jiang
Keyword(s):  
Frame Rate ◽  
Flying Height ◽  
Battery Life ◽  
Growth Stages ◽  
Camera Motion ◽  
Long Duration ◽  
Manual Counting ◽  
Detection And Counting ◽  
Plant Image ◽  
Early Seedling

Accurate corn stand count in the field at early season is of great interest to corn breeders and plant geneticists. However, the commonly used manual counting method is time consuming, laborious, and prone to error. Nowadays, unmanned aerial vehicles (UAV) tend to be a popular base for plant-image-collecting platforms. However, detecting corn stands in the field is a challenging task, primarily because of camera motion, leaf fluttering caused by wind, shadows of plants caused by direct sunlight, and the complex soil background. As for the UAV system, there are mainly two limitations for early seedling detection and counting. First, flying height cannot ensure a high resolution for small objects. It is especially difficult to detect early corn seedlings at around one week after planting, because the plants are small and difficult to differentiate from the background. Second, the battery life and payload of UAV systems cannot support long-duration online counting work. In this research project, we developed an automated, robust, and high-throughput method for corn stand counting based on color images extracted from video clips. A pipeline developed based on the YoloV3 network and Kalman filter was used to count corn seedlings online. The results demonstrate that our method is accurate and reliable for stand counting, achieving an accuracy of over 98% at growth stages V2 and V3 (vegetative stages with two and three visible collars) with an average frame rate of 47 frames per second (FPS). This pipeline can also be mounted easily on manned cart, tractor, or field robotic systems for online corn counting.

scholarly journals Research on Key Technology of Real-time Video Transmission Based on Mobile Terminal

1970 ◽  
Vol 1 (2) ◽  
Author(s):  
Cao Pengfei
Keyword(s):  
Video Coding ◽  
Real Time ◽  
Video Transmission ◽  
Loss Rate ◽  
Signal To Noise Ratio ◽  
Mobile Terminal ◽  
Frame Rate ◽  
Minimum Requirement ◽  
Encapsulation Method ◽  
Real Time Transmission

In order to solve the problems existing in real-time video transmission of mobile terminals, this paper proposes the encapsulation method which is suitable for H.263 and H.264 video coding, and re- duces the extra waste of real-time transmission proto- col packets and to improve the transmission efficien- cy of the video. Experimental results show that the peak signal to noise ratio (PSNR) in H.263 and H.264 video coding mode is above 30 dB at the lowest frame rate and resolution, and the minimum requirement of video transmission has been satisfied. Rate of 24 Hz, the two encoding PSNR are more than 40 dB, videotransmission quality ideal. In addition, the two packet loss rate of about10%maximum, themaximumdelay of 400 ms or less, have reached the requirements of real-time videotransmission.

scholarly journals Patch based reconstruction of undersampled data (PROUD) for high signal-to-noise ratio and high frame rate contrast enhanced liver imaging

2014 ◽  
Vol 74 (6) ◽  
pp. 1587-1597 ◽  
Author(s):  
Mitchell A. Cooper ◽  
Thanh D. Nguyen ◽  
Bo Xu ◽  
Martin R. Prince ◽  
Michael Elad ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Frame Rate ◽  
High Signal ◽  
Liver Imaging ◽  
Signal To Noise ◽  
High Frame Rate ◽  
Contrast Enhanced ◽  
Noise Ratio ◽  
Undersampled Data

scholarly journals A Perception-Driven Transcale Display Scheme for Space Image Sequences

2018 ◽  
Vol 2018 ◽  
pp. 1-14
Author(s):  
Lingling Zi ◽  
Xin Cong ◽  
Yanfei Peng ◽  
Pei Yang
Keyword(s):  
Rapid Development ◽  
Visual Saliency ◽  
Image Sequences ◽  
Image Resolution ◽  
Frame Rate ◽  
Multimedia Technology ◽  
High Quality ◽  
Target Trajectory ◽  
Rate Conversion ◽  
Space Image

With the rapid development of multimedia technology, the way of obtaining high-quality motion reproduction for space targets has attracted much attention in recent years. This paper proposes a Perception-driven Transcale Display Scheme, which significantly improves the awareness of multimedia processing. This new scheme contains two important modules, transcale description based on visual saliency and perception-driven display of space image sequences. The former concentrates on describing the transcle feature of space targets, including three algorithms, attention region computing, frame rate conversion, and image resolution resizing. On this basis, the latter focuses on high-quality display of space movements under different scales, including three algorithms, namely, target trajectory computing, space transcale display, and space movement display. Extensive quantitative and qualitative experimental evaluations demonstrate the effectiveness of the proposed scheme.

Effect of Western the Fourth Phase Project on Hydrodynamic Condition for Shijiu Port in Rizhao

2012 ◽  
Vol 204-208 ◽  
pp. 2369-2373
Author(s):  
Jia Rui Li ◽  
Die Shuang Yu
Keyword(s):  
Channel Flow ◽  
Water Area ◽  
Main Channel ◽  
Hydrodynamic Condition ◽  
Port Area ◽  
Before And After ◽  
Project Construction ◽  
Sheltering Effect ◽  
Sea Area ◽  
Flow Velocities

A hydrodynamic model of Shijiu port and its adjacent sea area was built to discuss the effect of western the fourth phase project on the flow condition for Shijiu port area. The results show that with the sheltering effect of breakwaters, flow velocity values are small inside the breakwaters. The water area near the project is affected more by the project construction. The flow velocities there are faster after the project construction than before it. In the main channel, flow velocities outside the breakwaters almost have no difference before and after the project. The project construction doesn’t have significant effect on it.

scholarly journals Experimental Investigation of Helical Cross-Flow Axis Hydrokinetic Turbines, Including Effects of Waves and Turbulence

2011 ◽  
Author(s):  
Peter Bachant ◽  
Martin Wosnik
Keyword(s):  
Cross Flow ◽  
Surface Flow ◽  
Frame Rate ◽  
Power Coefficient ◽  
Speed Ratio ◽  
Grid Turbulence ◽  
Flow Axis ◽  
Power Extraction ◽  
Tip Speed Ratio ◽  
Hydrokinetic Turbines

The performance characteristics of two cross-flow axis hydrokinetic turbines were evaluated in UNH’s tow and wave tank. A 1m diameter, 1.25m (nominal) height three-bladed Gorlov Helical Turbine (GHT) and a 1m diameter, four-bladed spherical-helical turbine (LST), both manufactured by Lucid Energy Technologies, LLP were tested at tow speeds up to 1.5 m/s. Relationships between tip speed ratio, solidity, power coefficient (Cp), kinetic exergy efficiency, and overall streamwise drag coefficient (Cd) are explored. As expected, the spherical-helical turbine is less effective at converting available kinetic energy in a relatively low blockage, free-surface flow. The GHT was then towed in waves to investigate the effects of a periodically unsteady inflow, and an increase in performance was observed along with an increase in minimum tip speed ratio at which power can be extracted. Regarding effects of turbulence, it was previously documented that an increase in free-stream homogenous isotropic turbulence increased static stall angles for airfoils. This phenomenon was first qualitatively investigated on a smaller scale with a NACA0012 hydrofoil in a UNH water tunnel, using an upstream grid turbulence generator and using high frame-rate PIV to measure the flow field. Since the angle of attack for a cross-flow axis turbine blade oscillates with higher amplitude as tip speed ratio decreases, any delay of stall should allow power extraction at lower tip speed ratios. This hypothesis was tested experimentally on a larger scale in the tow tank by creating grid turbulence upstream of the turbine. It is shown that the range of operable tip speed ratios is slightly expanded, with a possible improvement of power coefficient at lower tip speed ratios. Drag coefficients at higher tip speed ratios seem to increase more rapidly than in the non-turbulent case.

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