taxa_conc_n: A binned data frame of concentration data per category
In vprr: Processing and Visualization of Video Plankton Recorder Data
taxa_conc_n R Documentation
A binned data frame of concentration data per category
Description
A 'binned' dataframe from sample VPR data, including concentrations
of each category, where each data point represents a 5 metre bin of
averaged VPR data. Produced using vpr_roi_concentration
Usage
taxa_conc_n
Format
A dataframe with 21 variables
- depth
Depth calculated from pressure in metres
- min_depth
The minimum depth of the bin in metres
- max_depth
The maximum depth of the bin in metres
- depth_diff
The difference between minimum and maximum bin depth in metres
- min_time_s
The minimum time in seconds of the bin
- max_time_s
The maximum time in seconds of the bin
- time_diff_s
The difference between minimum and maximum time in a bin, in seconds
- n_roi_bin
The number of ROI observations in a bin
- conc_m3
The concentration of ROIs in a bin, calculated based on image volume and number of frames per bin
- temperature
Temperature measured from the VPR CTD in celsius (averaged within the bin)
- salinity
Salinity measured from the VPR CTD (averaged within the bin)
- density
sigma T density calculated from temperature, salinity and pressure (averaged within the bin)
- fluorescence
Fluorescence measured by the VPR CTD in millivolts
(uncalibrated) (averaged within the bin)
- turbidity
Turbidity measured by the VPR CTD in
millivolts (uncalibrated) (averaged within the bin)
- avg_hr
The mean time in which bin data was collected, in hours
- n_frames
The number of frames captured within a bin
- vol_sampled_bin_m3
The volume of the bin sampled in metres cubed
- toyo
Identifier of the tow-yo section which bin is a part of, either ascending or descending, appended by a number
- max_cast_depth
The maximum depth of the entire VPR cast
- taxa
The category in which ROIs in bin have been classified by Visual Plankton
- station
Station identifier provided during processing
vprr documentation built on July 12, 2022, 5:07 p.m.
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| taxa_conc_n | R Documentation |
A binned data frame of concentration data per category
Description
A 'binned' dataframe from sample VPR data, including concentrations
of each category, where each data point represents a 5 metre bin of
averaged VPR data. Produced using vpr_roi_concentration
Usage
taxa_conc_n
Format
A dataframe with 21 variables
- depth
Depth calculated from pressure in metres
- min_depth
The minimum depth of the bin in metres
- max_depth
The maximum depth of the bin in metres
- depth_diff
The difference between minimum and maximum bin depth in metres
- min_time_s
The minimum time in seconds of the bin
- max_time_s
The maximum time in seconds of the bin
- time_diff_s
The difference between minimum and maximum time in a bin, in seconds
- n_roi_bin
The number of ROI observations in a bin
- conc_m3
The concentration of ROIs in a bin, calculated based on image volume and number of frames per bin
- temperature
Temperature measured from the VPR CTD in celsius (averaged within the bin)
- salinity
Salinity measured from the VPR CTD (averaged within the bin)
- density
sigma T density calculated from temperature, salinity and pressure (averaged within the bin)
- fluorescence
Fluorescence measured by the VPR CTD in millivolts (uncalibrated) (averaged within the bin)
- turbidity
Turbidity measured by the VPR CTD in millivolts (uncalibrated) (averaged within the bin)
- avg_hr
The mean time in which bin data was collected, in hours
- n_frames
The number of frames captured within a bin
- vol_sampled_bin_m3
The volume of the bin sampled in metres cubed
- toyo
Identifier of the tow-yo section which bin is a part of, either ascending or descending, appended by a number
- max_cast_depth
The maximum depth of the entire VPR cast
- taxa
The category in which ROIs in bin have been classified by Visual Plankton
- station
Station identifier provided during processing
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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