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Partition mixtures of animals using assumptions on airspeeds.

Source: R/clean_mixture.R
clean_mixture.Rd

Partition mixtures of birds and insects using assumptions on their respective airspeeds, following the approach by Shi et al. (2025).

Usage

clean_mixture(x, ...)

# Default S3 method
clean_mixture(
  x,
  slow = 1,
  fast = 8,
  drop_slow_component = TRUE,
  drop_missing = FALSE,
  keep_mixture = FALSE,
  u_wind,
  v_wind,
  u,
  v,
  ...
)

# S3 method for class 'vpts'
clean_mixture(
  x,
  slow = 1,
  fast = 8,
  drop_slow_component = TRUE,
  drop_missing = FALSE,
  keep_mixture = FALSE,
  u_wind = "u_wind",
  v_wind = "v_wind",
  ...
)

# S3 method for class 'vp'
clean_mixture(
  x,
  ...,
  slow = 1,
  fast = 8,
  drop_slow_component = TRUE,
  drop_missing = FALSE,
  keep_mixture = FALSE,
  u_wind = "u_wind",
  v_wind = "v_wind"
)

Arguments

x

a vp or vpts object, or a mixture animal density or linear reflectivity eta in cm\(^2\)/km\(^3\).

...

eta, u, v, u_wind, v_wind arguments, taken from object for vp or vpts class.

slow

the slow component's airspeed in m/s, typically the airspeed of birds. Either a single number, or (optionally for vpts) a numeric vector equal in length to the number of profiles, or a data column name (see Details).

fast

the fast component's airspeed in m/s, typically the airspeed of insects. Either a single number, or (optionally for vpts) a numeric vector equal in length to the number of profiles, or a data column name (see Details).

drop_slow_component

when TRUE (default) output density, ground speed and heading for fast component, when FALSE for slow component.

drop_missing

Values eta without an associated ground speed and wind speed are set to NA when TRUE, or returned unaltered when FALSE (default).

keep_mixture

When TRUE store original mixture reflectivity and speeds as renamed quantities with mixture_ prefix

u_wind

the west to east wind component in m/s. In the case of vp and vpts objects the quantity name for the U-component of the wind.

v_wind

the south to north wind component in m/s. In the case of vp and vpts objects the quantity name for the V-component of the wind.

u

the mixture's ground speed u component (west to east) in m/s.

v

the mixture's ground speed v component (south to north) in m/s.

Value

a named list with cleaned densities and speeds. Output differs depending on whether the fast component is retained (drop_slow_component=TRUE, default) or the slow component (drop_slow_component=FALSE, default). Output quantities include:

  • eta: cleaned reflectivity in cm^2/km^3. only the fast component (default) or the slow component (when drop_slow_component is TRUE).

  • u: cleaned ground speed component west to east in m/s.

  • v: cleaned ground speed component south to north in m/s.

  • airspeed: the airspeed of the selected component in m/s.

  • airspeed_u: the u-component (west to east) of the airspeed of the retained component in m/s.

  • airspeed_v: the v-component (south to north) of the airspeed of the retained component in m/s.

  • heading: the heading of the selected component in degrees clockwise from north.

  • f: the reflectivity proportion of the slow component (0-1 range), typically the proportion of insects.

For vp and vpts objects the quantities eta,u,v will be updated, and other quantities listed above will be added.

Details

For a detail description of the methodology see Shi et al. (2025). Most commonly the fast component refers to migrating birds, while the slow component refers to insects. The slow component is always oriented in the direction of the wind by definition. Note that for mixture airspeeds exceeding the airspeed of the fast component, all reflectivity is assigned to the fast component. Similarly, for mixture airspeeds below the airspeed of the slow component, all reflectivity will be assigned to the slow component.

How to use this function?

  1. To apply this function to vp or vpts data altitudinal wind data needs to be added to the vertical profile data first. This is most easily accomplished by first converting the objects to a data.frame with as.vp() or as.vpts(). Wind data can then be added as a new columns to the data.frame. By default the wind data is expected to be named u_wind for the U component and v_wind for the V component of the wind. Alternatively, arguments u_wind and v_wind can be used to specify different names.

  2. Realistic assumptions for the expected airspeed for the slow (insect) and fast (bird) components need to be provided, using arguments slow and fast. See Shi et al. 2025 for recommendations in choosing these values. The parameter values for fast and slow can be specified as follows:

    • as single values applied to all heights and timestamps

    • as a numeric vector of equal length as the number of profiles in the vpts, allowing the user to specify changes in the parameter over time

    • as the name of a profile data quantity, allowing the user to specify changes in the parameter over time and/or altitude. Profile quantities are most easily added by first converting the vpts object to a data.frame with as.data.frame.vpts(), adding the values, and back-converting with as.vpts

  3. Use drop_slow_component to toggle between retaining the slow or fast component. When TRUE the fast (bird) component is retained. When FALSE the slow (insect) component is retained. Note that in this case the corrected ground speed direction will be identical to the wind direction, and the magnitude of the ground speed will be equal to the wind speed plus the value of slow, due to the underlying assumption of wind following by the slow component.

References

  • Shi X, Drucker J, Chapman JW, Sanchez Herrera M, Dokter AM Analysis of mixtures of birds and insects in weather radar data. Ornithological Applications. 2025 (in press) doi:10.1093/ornithapp/duaf020 .

  • Nussbaumer R, Schmid B, Bauer S, Liechti F. A Gaussian mixture model to separate birds and insects in single-polarization weather radar data. Remote Sensing. 2021 May 19;13(10):1989 doi:10.3390/rs13101989 .

Examples

# convert profile object to data.frame
df <- as.data.frame(example_vp, suntime=FALSE)
# add wind u and v component wind data
# (here a NW wind identical at all altitudes)
df$u_wind=3
df$v_wind=-3
# convert back to vp object
my_vp <- as.vp(df)
#> Warning: Extra fields found: u_wind, v_wind
# partition the mixture:
my_vp_clean <- clean_mixture(my_vp)

# drop the slow component (typically insects)
clean_mixture(100,u=-13,v=13,u_wind=-7,v_wind=6, fast=8, slow=1)
#> $eta
#> [1] 100
#> 
#> $u
#> [1] -13
#> 
#> $v
#> [1] 13
#> 
#> $airspeed
#> [1] 9.219544
#> 
#> $heading
#> [1] -40.60129
#> 
#> $airspeed_u
#> [1] -6
#> 
#> $airspeed_v
#> [1] 7
#> 
#> $f
#> [1] 0
#> 
# drop the fast component (typically birds)
clean_mixture(100,u=-13,v=13,u_wind=-7,v_wind=6, fast=8, slow=1, drop_slow_component=FALSE)
#> $eta
#> [1] 100
#> 
#> $u
#> [1] -13
#> 
#> $v
#> [1] 13
#> 
#> $airspeed
#> [1] 9.219544
#> 
#> $heading
#> [1] -40.60129
#> 
#> $airspeed_u
#> [1] -6
#> 
#> $airspeed_v
#> [1] 7
#> 
#> $f
#> [1] 0
#> 
# keep the original mixture reflectivity and speed components
clean_mixture(100,u=-13,v=13,u_wind=-7,v_wind=6, fast=8, slow=1, keep_mixture=TRUE)
#> $eta
#> [1] 100
#> 
#> $u
#> [1] -13
#> 
#> $v
#> [1] 13
#> 
#> $airspeed
#> [1] 9.219544
#> 
#> $heading
#> [1] -40.60129
#> 
#> $airspeed_u
#> [1] -6
#> 
#> $airspeed_v
#> [1] 7
#> 
#> $f
#> [1] 0
#> 
#> $mixture_eta
#> [1] 100
#> 
#> $mixture_u
#> [1] -13
#> 
#> $mixture_v
#> [1] 13
#> 
#> $mixture_airspeed
#> [1] 9.219544
#> 
#> $mixture_heading
#> [1] 319.3987
#> 
# keep reflectivity unaltered when one of the speed components is not a number:
clean_mixture(100,u=-13,v=13,u_wind=NaN,v_wind=6, fast=8, slow=1)["eta"]
#> Warning: U component of wind contains non finite values
#> $eta
#> [1] 100
#> 
# set reflectivity to NaN when one of the speed components is not a number:
clean_mixture(100,u=-13,v=13,u_wind=NaN,v_wind=6, fast=8, slow=1, drop_missing=TRUE)["eta"]
#> Warning: U component of wind contains non finite values
#> $eta
#> [1] NaN
#>