http://lod.bco-dmo.org/id/dataset/683064
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2017-02-24
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
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)
2017-02-28
publication
2017-02-28
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2021-02-18
publication
https://doi.org/10.26008/1912/bco-dmo.683064.1
Alexander Boris Bochdansky
Old Dominion University
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: 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]
ODV and CTD Dataset Description: Methods and Sampling: <p><strong>Video particle profiler (VPP)</strong>: (from&nbsp;Bochdansky,et&nbsp;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>
Funding provided by NSF Division of Polar Programs (NSF PLR) Award Number: PLR-1142097 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1142097
completed
Alexander Boris Bochdansky
Old Dominion University
757-683-4933
Ocean, Earth and Atmospheric Sciences 4600 Elkhorn Ave.
Norfolk
VA
23529
USA
abochdan@odu.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
cast
depth
lat
lon
julianday
temp
sal
density
sigmatheta
max_sigmatheta_change
fluor
beamtrans
O2
partnum_mean
partnum_variance
length_mean
esd_mean
esd_median
elongation
roundness
roughness
volume_mean
volume_sum
vmr
lloyd_patchiness
ia
Black and white charge-coupled device video camera (Sentec)
CTD
theme
None, User defined
cast
depth
latitude
longitude
Julian day as a decimal (time elapsed in days from 00:00 on January 1st 4713 BC)
water temperature at measurement depth
salinity
density
sigma-t
fluorescence
transmission
dissolved Oxygen
count
length
No BCO-DMO term
volume
featureType
BCO-DMO Standard Parameters
Camera
CTD - profiler
instrument
BCO-DMO Standard Instruments
NBP1302
service
Deployment Activity
Ross Sea
place
Locations
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
TRacing the fate of Algal Carbon Export in the Ross Sea
https://osprey.bco-dmo.org/project/547771
TRacing the fate of Algal Carbon Export in the Ross Sea
<p>Sinking particles are a major element of the biological pump and they are commonly assigned to two fates: mineralization in the water column and accumulation at the seafloor. However, there is another fate of export hidden within the vertical decline of carbon, the transformation of sinking organic matter to fine suspended and/or dissolved organic fractions. This process has been suggested but has rarely been observed or quantified. As a result, it is presumed that the solubilized fraction is largely mineralized over short time scales. However, global ocean surveys of dissolved organic carbon are demonstrating a significant water column accumulation of organic matter under high productivity environments. This proposal will investigate the transformation of organic particles from sinking to solubilized phases of the export flux in the Ross Sea. The Ross Sea experiences high export particle production, low dissolved organic carbon export with overturning circulation, and the area has a predictable succession of production and export events. In addition, the basin is shallow (< 1000 m) so the products the PIs will target are relatively concentrated. To address the proposed hypothesis, the PIs will use both well-established and novel biochemical and optical measures of export production and its fate. The outcomes of this work will help researchers close the carbon budget in the Ross Sea.</p>
TRACERS
largerWorkCitation
project
eng; USA
oceans
Ross Sea
178
-135
-79
-66
2013-02-14
2013-02-14
Ross Sea
0
BCO-DMO catalogue of parameters from 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)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/683193.rdf
Name: cast
Units: unitless
Description: <p>cast number</p>
http://lod.bco-dmo.org/id/dataset-parameter/683194.rdf
Name: depth
Units: meters
Description: <p>depth; calculated from CTD pressure</p>
http://lod.bco-dmo.org/id/dataset-parameter/683195.rdf
Name: lat
Units: decimal degrees
Description: <p>latitude; north is positive</p>
http://lod.bco-dmo.org/id/dataset-parameter/683196.rdf
Name: lon
Units: decimal degrees
Description: <p>longitude; east is positive</p>
http://lod.bco-dmo.org/id/dataset-parameter/683197.rdf
Name: julianday
Units: unitless
Description: <p>Julian Day in 2013</p>
http://lod.bco-dmo.org/id/dataset-parameter/683198.rdf
Name: temp
Units: degrees Celsius
Description: <p>temperature</p>
http://lod.bco-dmo.org/id/dataset-parameter/683199.rdf
Name: sal
Units: PSU
Description: <p>salinity</p>
http://lod.bco-dmo.org/id/dataset-parameter/683200.rdf
Name: density
Units: kg/m^3
Description: <p>density</p>
http://lod.bco-dmo.org/id/dataset-parameter/683201.rdf
Name: sigmatheta
Units: kg/m^3
Description: <p>sigma theta: potential density as density minus 1000 (without the effect of pressure)</p>
http://lod.bco-dmo.org/id/dataset-parameter/683202.rdf
Name: max_sigmatheta_change
Units: kg/m^3
Description: <p>maximum change in sigma theta</p>
http://lod.bco-dmo.org/id/dataset-parameter/683203.rdf
Name: fluor
Units: relative fluorescence units
Description: <p>fluorescence</p>
http://lod.bco-dmo.org/id/dataset-parameter/683204.rdf
Name: beamtrans
Units: dimensionless
Description: <p>light transmission as percent</p>
http://lod.bco-dmo.org/id/dataset-parameter/683205.rdf
Name: O2
Units: micromol/kilogram
Description: <p>oxygen; dissolved; from CTD</p>
http://lod.bco-dmo.org/id/dataset-parameter/683206.rdf
Name: partnum_mean
Units: particles/meter
Description: <p>Mean of particle numbers per video frame (averaged over 1 meter)</p>
http://lod.bco-dmo.org/id/dataset-parameter/683207.rdf
Name: partnum_variance
Units: particles/meter
Description: <p>Variance particle number per video frame (averaged over 1 meter)</p>
http://lod.bco-dmo.org/id/dataset-parameter/683208.rdf
Name: length_mean
Units: pixels
Description: <p>Mean of the maximum dimension of the particle per meter</p>
http://lod.bco-dmo.org/id/dataset-parameter/683209.rdf
Name: esd_mean
Units: pixels
Description: <p>Mean equivalent spherical diameter of particles per meter</p>
http://lod.bco-dmo.org/id/dataset-parameter/683210.rdf
Name: esd_median
Units: pixels
Description: <p>Median equivalent spherical diameter of particles per meter (pixels)</p>
http://lod.bco-dmo.org/id/dataset-parameter/683211.rdf
Name: elongation
Units: particles/meter
Description: <p>Mean elongation of particles</p>
http://lod.bco-dmo.org/id/dataset-parameter/683212.rdf
Name: roundness
Units: particles/meter
Description: <p>Mean roundness of particles</p>
http://lod.bco-dmo.org/id/dataset-parameter/683213.rdf
Name: roughness
Units: particles/meter
Description: <p>Mean roughness of particles</p>
http://lod.bco-dmo.org/id/dataset-parameter/683214.rdf
Name: volume_mean
Units: cubic pixels
Description: <p>Mean volume of particles per meter</p>
http://lod.bco-dmo.org/id/dataset-parameter/683215.rdf
Name: volume_sum
Units: cubic pixels
Description: <p>Sum of volumes of particles per meter</p>
http://lod.bco-dmo.org/id/dataset-parameter/683216.rdf
Name: vmr
Units: dimensionless
Description: <p>Variance to mean ratios of particle numbers per frame</p>
http://lod.bco-dmo.org/id/dataset-parameter/683217.rdf
Name: lloyd_patchiness
Units: unitless
Description: <p>Lloyd index of patchiness</p>
http://lod.bco-dmo.org/id/dataset-parameter/683218.rdf
Name: ia
Units: unitless
Description: <p>Index of aggregation</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
8548332
https://darchive.mblwhoilibrary.org/bitstream/1912/26699/1/dataset-683064_odv-and-ctd__v1.tsv
download
https://doi.org/10.26008/1912/bco-dmo.683064.1
download
onLine
dataset
<p><strong>Video particle profiler (VPP)</strong>: (from&nbsp;Bochdansky,et&nbsp;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>
Specified by the Principal Investigator(s)
<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)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <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>&nbsp;</p>
<p>The index of aggregation (Bez, 2000) was calculated as:</p>
<p>(equation 2) &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<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&nbsp;number of digits to right of decimal due to sampling precision methods</p>
Specified by the Principal Investigator(s)
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
Black and white charge-coupled device video camera (Sentec)
Black and white charge-coupled device video camera (Sentec)
PI Supplied Instrument Name: Black and white charge-coupled device video camera (Sentec) Instrument Name: Camera Instrument Short Name:camera Instrument Description: All types of photographic equipment including stills, video, film and digital systems. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/311/
CTD
CTD
PI Supplied Instrument Name: CTD PI Supplied Instrument Description:The rosette frame also held a video camera, Niskin sample bottles, conductivity, temperature and oxygen probes, and an optical backscatter sensor (Seapoint turbidity meter). The CTD with instruments was lowered at 0.5 m s−1 for the first 100 m, and then accelerated to 1 m s−1 for the remainder of each cast. Instrument Name: CTD - profiler Instrument Short Name: Instrument Description: The Conductivity, Temperature, Depth (CTD) unit is an integrated instrument package designed to measure the conductivity, temperature, and pressure (depth) of the water column. The instrument is lowered via cable through the water column. It permits scientists to observe the physical properties in real-time via a conducting cable, which is typically connected to a CTD to a deck unit and computer on a ship. The CTD is often configured with additional optional sensors including fluorometers, transmissometers and/or radiometers. It is often combined with a Rosette of water sampling bottles (e.g. Niskin, GO-FLO) for collecting discrete water samples during the cast.
This term applies to profiling CTDs. For fixed CTDs, see https://www.bco-dmo.org/instrument/869934. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/130/
Cruise: NBP1302
NBP1302
Community Standard Description
International Council for the Exploration of the Sea
RVIB Nathaniel B. Palmer
vessel
NBP1302
Dennis Hansell
University of Miami Rosenstiel School of Marine and Atmospheric Science
http://dmoserv3.whoi.edu/data_docs/TRACERS/NBP1302_data_report.pdf
Report describing NBP1302
Community Standard Description
International Council for the Exploration of the Sea
RVIB Nathaniel B. Palmer
vessel