| Title |
Exploring the optimal experimental setup for surface flow velocity measurements using PTV
|
|---|---|
| Published in |
Environmental Monitoring and Assessment, July 2018
|
| DOI | 10.1007/s10661-018-6848-3 |
| Pubmed ID | |
| Authors |
S. F. Dal Sasso, A. Pizarro, C. Samela, L. Mita, S. Manfreda |
| Abstract |
Advances in flow monitoring are crucial to increase our knowledge on basin hydrology and to understand the interactions between flow dynamics and infrastructures. In this context, image processing offers great potential for hydraulic monitoring, allowing acquisition of a wide range of measurements with high spatial resolution at relatively low costs. In particular, the particle tracking velocimetry (PTV) algorithm can be used to describe the dynamics of surface flow velocity in both space and time using fixed cameras or unmanned aerial systems (UASs). In this study, analyses allowed exploration of the optimal particle seeding density and frame rate in different configurations. Numerical results provided useful indications for two field experiments that have been carried out with a low-cost quadrocopter equipped with an optical camera to record RGB videos of floating tracers manually distributed over the water surface. Field measurements have been carried out using different natural tracers under diverse hydraulic and morphological conditions; PTV's processed velocities have been subsequently benchmarked with current meter measurements. The numerical results allowed rapid identification of the experimental configuration (e.g., required particle seeding density, image resolution, particle size, and frame frequency) producing flow velocity fields with high resolution in time and space with good agreement with the benchmark velocity values measured with conventional instruments. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 1 | 25% |
| Chile | 1 | 25% |
| Italy | 1 | 25% |
| United States | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 43 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 9 | 21% |
| Student > Ph. D. Student | 6 | 14% |
| Researcher | 4 | 9% |
| Student > Bachelor | 3 | 7% |
| Student > Doctoral Student | 3 | 7% |
| Other | 6 | 14% |
| Unknown | 12 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 15 | 35% |
| Earth and Planetary Sciences | 6 | 14% |
| Environmental Science | 3 | 7% |
| Computer Science | 1 | 2% |
| Arts and Humanities | 1 | 2% |
| Other | 2 | 5% |
| Unknown | 15 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 August 2018.
All research outputs
#3,045,691
of 23,854,458 outputs
Outputs from Environmental Monitoring and Assessment
#127
of 2,748 outputs
Outputs of similar age
#61,012
of 329,673 outputs
Outputs of similar age from Environmental Monitoring and Assessment
#1
of 40 outputs
Altmetric has tracked 23,854,458 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,748 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,673 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.