Name: image-based lagrangian particle tracking in bed-load experiments
Uploaded: 2017-07-20T15:00:00
Duration: 10 min 32 s
Description: Watch this Scientific Journal Video about Image-based Lagrangian Particle Tracking in Bed-load Experiments at JoVE.com

This work was supported by the Research Executive Agency, through the 7th Framework Programme of the European Union, Support for Training and Career Development of Researchers (Marie Curie - FP7-PEOPLE-2012-ITN), which funded the Initial Training Network (ITN) HYTECH &#34;Hydrodynamic Transport in Ecologically Critical Heterogeneous Interfaces&#34; (number 316546). It was also supported by the Polo Territoriale di Lecco of the Politecnico di Milano. The experiments were performed during a visit by S. S. to the Politecnico di Milano as a visiting scientist. The authors thank Tarcisio Fazzini, Stefania Gherbi, Francesco Mottini (B.Sc. students at the Politecnico di Milano) and Seyed Abbas Hosseini-Sadabadi (fellow of the HYTECH project and Ph.D. student at the Politecnico di Milano) for supporting the experimental activity and the data analysis. The authors gratefully thank Prof. Roger Nokes (University of Canterbury, Christchurch, New Zealand) for providing the Streams software and constant advice. Finally, the authors thank the JoVE managing editor and three anonymous reviewers for their thought-provoking comments and suggestions, thanks to which the manuscript could be significantly improved.

<ol>
	<li>Francis, J. R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experiments+on+the+motion+of+solitary+grains+along+the+bed+of+a+water-stream.">Experiments on the motion of solitary grains along the bed of a water-stream.</a> Proc Royal Soc London, A. 332, 443-471 (1973).</li><li>Drake, T. G., Shreve, R. L., Dietrich, W. E., Whiting, P. J., Leopold, L. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bedload+transport+of+fine+gravel+observed+by+motion-picture+photography.">Bedload transport of fine gravel observed by motion-picture photography.</a> J Fluid Mech. 192, 193-217 (1988).</li><li>Campagnol, J., Radice, A., Ballio, F., Nikora, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Particle+motion+and+diffusion+at+weak+bed+load:+accounting+for+unsteadiness+effects+of+entrainment+and+disentrainment.">Particle motion and diffusion at weak bed load: accounting for unsteadiness effects of entrainment and disentrainment.</a> J Hydraul Res. 53 (5), 633-648 (2015).</li><li>Fathel, S. L., Furbish, D. J., Schmeeckle, M. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experimental+evidence+of+statistical+ensemble+behavior+in+bed+load+sediment+transport.">Experimental evidence of statistical ensemble behavior in bed load sediment transport.</a> J Geophys Res: Earth Surf. 120 (11), 2298-2317 (2015).</li><li>Lajeunesse, E., Malverti, L., Charru, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bedload+transport+in+turbulent+flow+at+the+grain+scale:+experiments+and+modeling.">Bedload transport in turbulent flow at the grain scale: experiments and modeling.</a> J Geophys Res: Earth Surf. 115, F04001 (2010).</li><li>Tsakiris, A. G., Papanicolaou, A. N., Lauth, T. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Signature+of+bedload+particle+transport+mode+in+the+acoustic+signal+of+a+geophone.">Signature of bedload particle transport mode in the acoustic signal of a geophone.</a> J Hydraul Res. 52 (2), 185-204 (2014).</li><li>Mendes, L., Antico, F., Sanches, P., Alegria, F., Aleixo, R., Ferreira, R. M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+particle+counting+system+for+calculation+of+bedload+fluxes.">A particle counting system for calculation of bedload fluxes.</a> Meas Sci Technol. 27 (12), 125305 (2016).</li><li>Heays, K. G., Friedrich, H., Melville, B. W., Nokes, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantifying+the+dynamic+evolution+of+graded+gravel+beds+using+Particle+Tracking+Velocimetry.">Quantifying the dynamic evolution of graded gravel beds using Particle Tracking Velocimetry.</a> J Hydraul Eng. 140 (7), 04014027 (2014).</li><li>Radice, A., Malavasi, S., Ballio, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Solid+transport+measurements+through+image+processing.">Solid transport measurements through image processing.</a> Exp Fluids. 41 (5), 721-734 (2006).</li><li>Radice, A., Ballio, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Double-average+characteristics+of+sediment+motion+in+one-dimensional+bed+load.">Double-average characteristics of sediment motion in one-dimensional bed load.</a> Acta Geophys. 56 (3), 654-668 (2008).</li><li>Radice, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+the+Lorenz+curve+to+quantify+statistical+nonuniformity+of+sediment+transport+rate.">Use of the Lorenz curve to quantify statistical nonuniformity of sediment transport rate.</a> J Hydraul Eng. 135 (4), 320-326 (2009).</li><li>Radice, A., Ballio, F., Nikora, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+statistical+properties+of+bed+load+sediment+concentration.">On statistical properties of bed load sediment concentration.</a> Water Resou. Res. 45 (6), W06501 (2009).</li><li>Radice, A., Ballio, F., Nikora, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Statistics+and+characteristic+scales+for+bed+load+in+a+channel+flow+with+sidewall+effects.">Statistics and characteristic scales for bed load in a channel flow with sidewall effects.</a> Acta Geophys. 58 (6), 1072-1093 (2010).</li><li>Campagnol, J., Radice, A., Ballio, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Scale-based+statistical+analysis+of+sediment+fluxes.">Scale-based statistical analysis of sediment fluxes.</a> Acta Geophys. 60 (6), 1744-1777 (2012).</li><li>Radice, A., Nikora, V., Campagnol, J., Ballio, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Active+interactions+between+turbulence+and+bed+load:+Conceptual+picture+and+experimental+evidence.">Active interactions between turbulence and bed load: Conceptual picture and experimental evidence.</a> Water Resour Res. 49 (1), 90-99 (2013).</li><li>Campagnol, J., Radice, A., Nokes, R., Bulankina, V., Lescova, A., Ballio, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lagrangian+analysis+of+bed-load+sediment+motion:+database+contribution.">Lagrangian analysis of bed-load sediment motion: database contribution.</a> J Hydraul Res. 51 (5), 589-596 (2013).</li><li>Ballio, F., Radice, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluctuations+and+time+scales+for+bed-load+sediment+motion+over+a+smooth+bed.">Fluctuations and time scales for bed-load sediment motion over a smooth bed.</a> Int J Sediment Res. 30 (4), 321-327 (2015).</li><li>Hosseini-Sadabadi, S. A., Radice, A., Ballio, F., Rowi&#324;ski, P. M., Marion, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+analysis+of+entrainment+and+deposition+rate+fluctuations+in+weak+bed+load+transport.">An analysis of entrainment and deposition rate fluctuations in weak bed load transport.</a> Hydrodynamic and mass transport at freshwater aquatic interfaces. , 333-342 (2016).</li><li>Papanicolaou, A. N., Diplas, P., Balakrishnan, M., Dancey, C. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computer+vision+technique+for+tracking+bed+load+movement.">Computer vision technique for tracking bed load movement.</a> J Comput Civil Eng. 13 (2), 71-79 (1999).</li><li>Ramesh, B., Kothyari, U. C., Murugesan, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Near-bed+particle+motion+over+transitionally-rough+bed.">Near-bed particle motion over transitionally-rough bed.</a> J Hydraul Res. 49 (6), 757-765 (2011).</li><li>Amir, M., Nikora, V., Witz, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+novel+experimental+technique+and+its+application+to+study+the+effects+of+particle+density+and+flow+submergence+on+bed+particle+saltation.">A novel experimental technique and its application to study the effects of particle density and flow submergence on bed particle saltation.</a> J Hydraul Res. 55 (1), 101-113 (2017).</li><li>Ettema, R., Garc&#236;a, M. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ice+effects+on+sediment+transport+in+rivers.">Ice effects on sediment transport in rivers.</a> Sedimentation Engineering. , 613-648 (2008).</li><li>Knack, I., Shen, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sediment+transport+in+ice-covered+channels.">Sediment transport in ice-covered channels.</a> Int J Sediment Res. 30 (1), 63-67 (2015).</li><li>Goring, D. G., Nikora, V. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Despiking+acoustic+Doppler+velocimeter+data.">Despiking acoustic Doppler velocimeter data.</a> J Hydraul Eng. 128 (1), 117-126 (2002).</li><li>Nowak, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Wall+shear+stress+measurement+in+a+turbulent+pipe+flow+using+ultrasound+Doppler+velocimetry.">Wall shear stress measurement in a turbulent pipe flow using ultrasound Doppler velocimetry.</a> Exp Fluids. 33 (2), 249-255 (2002).</li><li>McCuen, R. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Microcomputer applications in statistical hydrology. , (1993).</li><li>Lloyd, P. M., Ball, D. J., Stansby, P. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Unsteady+surface-velocity+field+measurement+using+particle+tracking+velocimetry.">Unsteady surface-velocity field measurement using particle tracking velocimetry.</a> J. Hydraul. Res. 33 (4), 519-534 (1995).</li><li>Radice, A., Aleixo, R., Hosseini-Sadabadi, S. A., Sarkar, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+image+grabbing+and+processing+for+measurement+of+geophysical+flows.">On image grabbing and processing for measurement of geophysical flows.</a> Proc. HydroSenSoft 2017, International Symposium and Exhibition on Hydro-Environment Sensors and Software. , (2017).</li><li>Hosseini-Sadabadi, S. A., Radice, A., Ballio, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Post-processing+of+particle+tracking+data+for+phenomenological+depiction+of+weak+bed-load+sediment+transport.">Post-processing of particle tracking data for phenomenological depiction of weak bed-load sediment transport.</a> Proc. River Flow 2016. VIII Int. Conf. on Fluvial Hydraulics, St. , 780-786 (2016).</li></ol>

The authors declare that they have no competing financial interests.

Designing a bed-load transport experiment with particle visualization involves several steps, including the choice of an experimental configuration and hardware tools, flow measurement, particle seeding and visualization, and image analysis. Variations at each step have advantages and disadvantages. The key characteristics of the protocol presented in this manuscript are: (i) using a pressurized flow and a fixed rough bed, (ii) seeding a low number of bed-load particles having a contrasting color to the fixed bed color, (iii) using natural light and, (iv) using multiple cameras to obtain independent track sets to be joined to each other.
The experimental method and the data processing enable the bed-load particles to be reliably tracked for the final measurement. The covered flow guarantees an optimal vision of the moving particles. The fixed bed however, prevents observation of some processes (e.g., those linked with vertical displacements of sediment particles within the active bed-load layer), and thus limits the applicability of the technique to weak bed-loads.
The size of the data samples obtained using only 100 s of movie was relatively small. However, the sample size can easily be increased by lengthening the experimental duration of image acquisition and processing. Feeding a limited number of particles requires a longer experimental time than feeding at a substantially higher rate; but it is well worth the effort because of a relatively straightforward particle tracking due to the small concentration of particles in motion and the use of different colors, both of which reduce the probability of tracking mistakes. The use of natural light in the experiment avoids the need for lighting devices; however, a downside is that good lighting depends on the weather conditions.
The CFDs of particle hop length and duration depicted in Figure 4 show the lowest values as the most frequent ones. The largest measured values of hop length and duration were around 600 mm and 7 s, respectively. This was significantly larger compared to analogous values from the literature4,16,30, since measuring longer tracks runs the risk of long particle hops. The benefit of using two cameras is evident considering that a single camera had a focus area length of around 850 mm, which would not be much larger than hop length values to be measured. The measuring protocol using two cameras instead, ensured a satisfactory separation between the length scales of the process and those of the measuring field, thus reducing the risk of biasing the phenomenological results due to experimental limitations. Also, the focus area can be additionally lengthened by increasing the number of cameras placed along the flume.
An alternative procedure compared to the protocol described here is to create overlapped images before the particle identification and tracking. Our protocol (of performing the tracking twice and linking particle tracks) was preferred as the image merging method would have doubled the size of the data files, requiring a memory consumption that was not affordable.
With the processing algorithms described here, several particle tracks that were shorter than the length of the overlapping area were discarded because they prevented a full reconstruction of the sediment tracks. However, the threshold length of 120 mm was one order of magnitude shorter than the track lengths that could be obtained, and the loss of these data was therefore acceptable. Moreover, the track joining seen in the lower 8 cases of Figure 1 would not enable a significant increase in the track length to be obtained. On the other hand, these situations might help in retrieval of long tracks, such as the situation in Figure 5 that could be due to track interruptions. In a similar case, a long track could be reconstructed by iterative joining operations. It is however important to keep in mind that track interruptions like those in Figure 5 are clearly related to the tracking process rather than to the joining process.
This manuscript presented proof-of-concept results for a single experiment in order to demonstrate the capabilities of the adopted protocol. In future experiments, the protocol will be applied to a series of different hydro-dynamic conditions to achieve a detailed analysis of the bed-load sediment transport process.
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/55874/55874fig5.jpg" /> 
Figure 5: A Situation of Track Joining in the Presence of Interruptions. The joining of these tracks into a single track is not possible with the protocol described here. As mentioned in the caption of Figure 1 and in step 8.4 of the Protocol, the tracks shorter than the length of the overlapping region are excluded. This eliminates the short red and green tracks; therefore, the remaining long ones cannot be joined because they have no common point. <a href="//cloudflare.jove.com/files/ftp_upload/55874/55874fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Since pioneering works appeared some decades ago1,2, the use of image analysis for the study of river sediment transport has been constantly increasing. This technique indeed proved its capability to provide relatively high-resolution and low-cost data for detailed analyses of physical phenomena3,4,5. With time, significant improvements have been obtained for both hardware and software tools.
The measurement of sediment transport can be performed using a Eulerian approach that targets measurement of sediment fluxes, or a Lagrangian one that aims at measuring trajectories of individual grains as they move. Image processing offers unique possibilities for particle tracking in comparison to other Eulerian methods6,7. However, despite these potentialities, the application of image analysis to bed-load sediment transport suffers from some critical experimental limitations, in terms of spatial/temporal support scales for the measurement and size of data samples. For example, it is difficult to achieve simultaneously an appropriate combination of a large spatial area, long duration of an experiment, and high measuring frequency3,4,8, without compromising the quality and quantity of data. In addition, the particle tracking can be performed manually2,4, which requires a great human effort, or automatically3,8, with the possibility of tracking errors made by the software used for the analysis.
This paper presents a protocol for the experimental investigation of bed-load sediment transport, where long duration was achieved by the type of camera used, large field of view was ensured by simultaneous use of two cameras at different locations, and reliable automatic processing was made possible by ad hoc experimental conditions. The experimental operation was designed and the processing tools were selected based on experience acquired by the authors in several research works dealing with the detailed investigation of sediment transport by image methods3,9,10,11,12,13,14,15,16,17,18.
A sediment transport experiment is described, that was performed releasing particles over a fixed, rough bed. The particle feeding was much less than the transport capacity of the flow to maintain a low concentration of moving grains, thus avoiding the congestion of particles to be tracked. Furthermore, the transported particles were not moving continuously, but intermittent motion was observed. The use of a fixed bed rather than a movable one represents a loss of similarity to natural conditions. However, a fixed bed was frequently used in sediment transport experiments19,20,21 under the assumption that the results are more simple and explanatory than those from complicated scenarios with a variety of acting processes. The use of a fixed bed obviously prevents processes of sediment burial and reappearance from being observed. On the other hand, in the presence of a weak bed load, the transport of sediment takes place in a superficial layer of a loose bed, and in this case, the use of a fixed bed may be adequate. In fact, specific comparisons between the properties of particle motion in experiments run with the two conditions did not present any significant differences3,14. Finally, the experiment presented here was performed with a pressurized flow to ensure an optimal condition for particle visualization through a transparent cover. Sediment transport with a pressurized flow has been experimentally studied in research prototyping ice-covered rivers, showing that the interaction between the near-bed boundary layer and the sediment is analogous to that of open-channel flow22,23. In the following sections, all methods are outlined and some representative results are provided.

<table border="0" cellpadding="0" cellspacing="0" width="635">
	<tbody>
		<tr height="46">
			<td height="46" style="height:47px;width:216px;">Laser distance sensor</td>
			<td style="width:111px;">METRICA</td>
			<td style="width:119px;">PREXISOX2</td>
			<td style="width:191px;">Used to measure the flume slope</td>
		</tr>
		<tr height="46">
			<td height="46" style="height:47px;width:216px;">Two-component polyester resin</td>
			<td style="width:111px;">Gelson</td>
			<td style="width:119px;">MS 65213</td>
			<td style="width:191px;">Used to glue sediment particles onto steel plates</td>
		</tr>
		<tr height="46">
			<td height="46" style="height:47px;width:216px;">Water-resistant spray paint</td>
			<td style="width:111px;">Any</td>
			<td style="width:119px;"></td>
			<td style="width:191px;">Used to paint the fixed bed</td>
		</tr>
		<tr height="46">
			<td height="46" style="height:47px;width:216px;">Ultrasonic Velocity Profiler</td>
			<td style="width:111px;">Signal Processing</td>
			<td style="width:119px;">DOP 2000</td>
			<td style="width:191px;">Used to measure the water velocity profiles</td>
		</tr>
		<tr height="46">
			<td height="46" style="height:47px;width:216px;">Camera</td>
			<td style="width:111px;">Go-Pro</td>
			<td style="width:119px;">Hero 4 Black</td>
			<td style="width:191px;">Used to acquire movies of bed-load particle motion</td>
		</tr>
		<tr height="46">
			<td height="46" style="height:47px;width:216px;">Streams</td>
			<td style="width:111px;">University of Canterbury</td>
			<td style="width:119px;">2.01</td>
			<td style="width:191px;">Used for particle identification and tracking</td>
		</tr>
		<tr height="46">
			<td height="46" style="height:47px;width:216px;">MatLab</td>
			<td style="width:111px;">MathWorks</td>
			<td style="width:119px;">R14</td>
			<td style="width:191px;">Used to develop ad hoc codes for a variety of operations</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:216px;">Plexiglas</td>
			<td style="width:111px;"></td>
			<td style="width:119px;"></td>
			<td style="width:191px;">Transparent acrylic material</td>
		</tr>
	</tbody>
</table>

image-based lagrangian particle tracking in bed-load experiments

Image analysis has been increasingly used for the measurement of river flows due to its capabilities to furnish detailed quantitative depictions at a relatively low cost. This manuscript describes an application of particle tracking velocimetry (PTV) to a bed-load experiment with lightweight sediment. The key characteristics of the investigated sediment transport conditions were the presence of a covered flow and of a fixed rough bed above which particles were released in limited number at the flume inlet. Under the applied flow conditions, the motion of the individual bed-load particles was intermittent, with alternating movement and stillness terms. The flow pattern was preliminarily characterized by acoustic measurements of vertical profiles of the stream-wise velocity. During process visualization, a large field of view was obtained using two action-cameras placed at different locations along the flume. The experimental protocol is described in terms of channel calibration, experiment realization, image pre-processing, automatic particle tracking, and post-processing of particle track data from the two cameras. The presented proof-of-concept results include probability distributions of the particle hop length and duration. The achievements of this work are compared to those of existing literature to demonstrate the validity of the protocol.

Results presented in this section are for an experiment where the flume slope was set to zero (slope values were computed with &#177; 0.05% accuracy). The used sediment was made of PBT particles that were quasi-spherical, with a size d = 3 mm and a density &#961;p = 1,270 kg/m3. The experiment was run with a flow rate Q = 9.7 &#215; 10-3 m3/s resulting in a bulk velocity U = 0.31 m/s.
For the velocity measurements with the UVP, a 2 MHz probe was used at 81&#176; inclination. Velocity data were acquired at 20 Hz for 250 s. A representative velocity profile is depicted in Figure 2. It was taken at the channel axis and at 4.5 m from the flume inlet, where the flow was fully developed. Some values related to invalid elevations measurements were removed. An asymmetric profile resulted from the different roughness of the plastic lid and sediment bed. The plots also show the portion of the profile used for the estimation of the shear velocity, obtaining us = 25.9 &#177; 1.3 mm/s. The particle Reynolds number (Rep = us&#215;d/&#957;, with &#957; as the kinematic viscosity of water) was therefore equal to 78, indicating a transitionally rough regime.
The visualization of sediment transport was performed with two cameras placed at 3.5 m and 4.3 m from the flume inlet. The cameras operated at a frequency of 30 fps and with a resolution of 1,920 x 1,080 pixel. The factor for correction of image distortion was k = 0.6. After removal of distortion, the image calibration was 1 pixel = 0.5 mm. The length of overlap was from 760.15 to 880.11 mm (where the latter was the length of the focus area of the first camera from its upstream edge). The threshold intensity for particle identification was set to 80 and the expected blob size ranged from 0.5 to 8 mm. The search window for particle tracking was as follows: 1 mm upstream and 7 mm downstream, 4 mm laterally. The search window for reconnection of interrupted tracks was as follows: 1 mm upstream and 31 mm downstream, 16 mm laterally along 4 following frames. The threshold value of the square root of the mean squared difference of x and y values between two tracks to be joined was set to 10 mm.
The particle tracks measured using a subset of 3,000 images from each camera (corresponding to 100 s duration) are depicted in Figure 3. The database comprehended 37 and 34 tracks from the upstream and downstream camera, respectively. An overlap of the tracks obtained by the two cameras is first proposed and then the resulting full set of tracks is displayed. It is evident that the overlap in the central portion of the measuring area was satisfactory. 12 links were obtained at the end 59 tracks. The longest track spanned the entire observation window with a total length of approximately 1.6 m (more than 530 particle sizes, 15.2 flow depths or 5.3 flume widths), which is very large in comparison to other literature studies where similar analyses were performed3,4,5,8.
By taking a Lagrangian framework, the key indicators of particle kinematics are here applied in terms of properties of particle hops. Under an intermittent bed-load transport like the one in this experiment, these hops are motions separated by periods of rest. To detect hops within a full track for a single particle, the identification of particle motion and stillness is a necessary preliminary step. In this work, we applied a criterion30 that considers a particle in motion at a certain instant if its x position at that instant is larger than all the previous ones and lower than all the following ones. A total number of 98 hops was obtained from the 59 measured particle tracks. Figure 4 depicts the obtained Cumulative Frequency Distribution (CFD) for the hop length and duration.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/55874/55874fig2.jpg" /> 
Figure 2: Measured Velocity Profile. (Top) The time-averaged vertical profile of the stream-wise velocity component. (Bottom) The estimation of the shear velocity by fitting a logarithmic equation to the lower portion of the profile. Note that a vertical axis starting from the top of the channel and oriented downwards is used in the first plot, representing the result from the measurement with the UVP. An axis from the channel bottom and directed upwards is instead used in the second plot, as needed to estimate the shear velocity by equation fitting. <a href="https://cloudflare.jove.com/files/ftp_upload/55874/55874fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/55874/55874fig3.jpg" /> 
Figure 3: Plan View of Measured Particle Tracks. (Top) The tracks from the two cameras (upstream camera in red and downstream in black). (Bottom) The sample of joined tracks (changing color for clarity and some tracks highlighted by a thicker line). <a href="https://cloudflare.jove.com/files/ftp_upload/55874/55874fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/55874/55874fig4.jpg" /> 
Figure 4: Cumulative Frequency Distribution (CFD) of Hop Length (Top) and Duration (Bottom). Within each track of Figure 3, the particle was labeled at each time instant to represent if the particle was in motion or at rest at that instant. Particle hops were then extracted from the tracks as portions between particle entrainment (transition from stillness to motion) and disentrainment (transition from motion to stillness). The samples obtained for hop lengths and durations were used to create the distributions depicted here. <a href="https://cloudflare.jove.com/files/ftp_upload/55874/55874fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplemental Code Files: join_cameras.m <a href="http://cloudflare.jove.com/files/ftp_upload/55874/join_cameras.m">Please click here to download this file.</a>

Watch this Scientific Journal Video about Image-based Lagrangian Particle Tracking in Bed-load Experiments at JoVE.com

Image-based Lagrangian Particle Tracking in Bed-load Experiments

The manuscript presents a protocol for the conduction of bed-load sediment transport experiments where the moving particles are tracked by image analysis. The experimental facility, the procedures for run realization and data processing, and finally some proof-of-concept results are presented here.

Image analysis has been increasingly used for the measurement of river flows due to its capabilities to furnish detailed quantitative depictions at a ...

Research

JoVE Journal

Environment

Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations

Flue gas from power plants can promote algal cultivation and reduce greenhouse gas emissions1. Microalgae not only capture solar energy more efficiently ...

Tracking Microbial Contamination in Retail Environments Using Fluorescent Powder - A Retail Delicatessen Environment Example

Cross contamination of foodborne pathogens in the retail environment is a significant public health issue contributing to an increased risk for foodborne ...

Field Experiments of Pollination Ecology: The Case of Lycoris sanguinea var. sanguinea

Field Experiments of Pollination Ecology: The Case of Lycoris sanguinea var. sanguinea

Plant-pollinator interactions have been studied for approximately one hundred years. During that time, many field methods have been developed to clarify ...

A Lipid Extraction and Analysis Method for Characterizing Soil Microbes in Experiments with Many Samples

Microbial communities are important drivers and regulators of ecosystem processes. To understand how management of ecosystems may affect microbial ...

Video Tracking Protocol to Screen Deterrent Chemistries for Honey Bees

The European honey bee, Apis mellifera L., is an economically and agriculturally important pollinator that generates billions of dollars annually. Honey ...

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

A Ground Penetrating Radar (GPR) system based on a ground-coupled, densely populated antenna array was used to collect data during an infiltration ...

Methods for Image-based Surveys of Benthic Macroinvertebrates and Their Habitat Exemplified by the Drop Camera Survey for the Atlantic Sea Scallop

Underwater imaging has long been used in the field of marine ecology but decreasing costs of high-resolution cameras and data storage have made the ...

Experimental Study of the Relationship Between Particle Size and Methane Sorption Capacity in Shale

The amount of adsorbed shale gas is a key parameter used in shale gas resource evaluation and target area selection, and it is also an important standard ...

Isolation and Analysis of Microbial Communities in Soil, Rhizosphere, and Roots in Perennial Grass Experiments

Plant and soil microbiome studies are becoming increasingly important for understanding the roles microorganisms play in agricultural productivity. The ...

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

As individuals increasingly live in cities, methods to study their everyday movements and the data that can be collected becomes important and valuable. ...