<div><p><strong>Video particle profiler (VPP)</strong>: (from Bochdansky,et al (2017) JMS)</p>
<p>The VPP was similar to that published in Bochdansky et al. (2010). However, instead of 45° angle lighting from both sides, side lighting with two white high-intensity LED lights was used ~7 cm in front of the lens. Some backscatter from transparent exopolymers (TEP), or from small particles embedded in that matrix, was possible using high-intensity light. The light beams were restricted using a slit width of 1 cm; however, as the light intensity dropped exponentially in the front and back of the image beam, only the brightest lit image plane was used for analysis. This method reduced bias caused by overlapping particles, removed motion blur streaks, and provided more accurate particle size estimates. At the focal plane, the field of view was 3.5 cm tall and 4.7 cm wide. The analysis program for the VPP was expanded from that in Bochdansky et al. (2010) to include more variables for particle characterization (including perimeter, volume and porosity). The VPP can record 30 images per second, with image analysis by a Linux-based image analysis program (an adapted Avidemux video editing software) at high speeds (approximately in real time after retrieval). The images were later aligned with depth from the CTD using time as the common variable and by filming a clock displaying UTC at the beginning and the end of each video sequence. In Matlab, CTD data were matched at one-second resolution with the particle data. The raw data consisted of millions of particles with associated CTD data. These raw data allow us to resample particle metrics at all scales. Particle volumes were calculated as shown in Fig. 2. Instead of assuming a specific geometric shape, the projected area of the particle on the screen (sum of white and black pixels within the perimeter of the particle) was converted into a circle that was then converted to volume. This method reduces error in volume calculations greatly because 2-dimensional information rather than 1-dimensional information is used to reconstruct volumes, thus avoiding the bias of assigning disproportionally large volumes to elongated objects. This approach is widely used in image analysis of ocean particles (e.g., Iversen et al., 2010). Total particle volume (pixel3 frame-1) was approximated by multiplying the mean volume of particles with the mean particle number.</p></div>
ODV and CTD
ODV and CTD
<div><p>A moving average with an unweighted 100 m window served as a low-pass filter for the particle data before they were matched with depths.</p>
<p>The degree of overdispersion (i.e., patchiness) in the system was assessed using two indices. One, the Lloyd index of patchiness (Lloyd, 1967), is domain-dependent (i.e., zero values affect the estimates); the other one, the index of aggregation (Bez, 2000), is domain-independent.</p>
<p>The Lloyd index (Lloyd, 1967) was calculated as:</p>
<p>(equation 1) <img src="https://datadocs.bco-dmo.org/d3/data_docs/TRACERS/ODV_equation_1.png" style="height:30px; width:172px" />,</p>
<p>where <em>Lp</em> is the Lloyd index of patchiness, <em>m</em> the mean particle abundance (number of particles per frame in 1 m bins), and <em>s<sup>2</sup></em> the variance of the particle abundance.</p>
<p> </p>
<p>The index of aggregation (Bez, 2000) was calculated as:</p>
<p>(equation 2) <img src="https://datadocs.bco-dmo.org/d3/data_docs/TRACERS/ODV_equation_2.png" style="height:20px; width:177px" />,</p>
<p>where <em>ia</em> is the index of aggregation, <em>z<sub>i</sub></em> the particle density, and <em>S</em> the sample scale (set to 1 for this analysis).</p>
<p><strong>BCO-DMO Processing notes:</strong><br />
- added conventional header with dataset name, PI name, version date<br />
- modified parameter names to conform with BCO-DMO naming conventions<br />
- reduced number of digits to right of decimal due to sampling precision methods</p></div>
683064
ODV and CTD
2017-02-24T15:14:51-05:00
2017-02-24T15:14:51-05:00
2023-07-07T16:10:26-04:00
urn:bcodmo:dataset:683064
Particle abundances and characteristics from the video plankton profiler with matching CTD data, from casts on RVIB Nathaniel B. Palmer NBP1302, Feb/Mar 2013 (TRACERS project)
Ocean Data View (ODV) and conductivity, temperature and depth (CTD) casts from NBP13-2 in the Ross Sea in February and March 2013. Data include temperature, salinity, density, fluorescence, light transmission, oxygen concentration, particle number, size, roundness, roughness, calculations of patchiness and index of aggregation.
false
Bochdansky, A. B. (2021) Particle abundances and characteristics from the video plankton profiler with matching CTD data, from casts on RVIB Nathaniel B. Palmer NBP1302, Feb/Mar 2013 (TRACERS project). Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2017-02-28 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.683064.1 [access date]
false
1
10.26008/1912/bco-dmo.683064.1
false
2017-02-28
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ISO 19115-2 (NOAA Profile)
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