Skip to contents

Calculate daily camera trap captures

Source: R/ct_camera_day.R
ct_camera_day.Rd

Aggregates camera trap data into daily capture summaries.

Usage

ct_camera_day(
  data,
  deployment_data = NULL,
  deployment_column,
  datetime_column,
  species_column,
  size_column,
  format,
  start_column = NULL,
  end_column = NULL,
  deployment_format = format,
  time_zone = ""
)

Arguments

data

A data frame containing camera trap observation data.

deployment_data

A data frame containing camera trap deployment records.

deployment_column

The column name (unquoted or as a string) that uniquely identifies the deployment (e.g., camera ID).

datetime_column

Column in data containing observation timestamps. Can be supplied as a bare name, quoted string, or column position.

species_column

The column in the data frame representing species identifiers. Can be specified as a string or unquoted column name.

size_column

(Optional) The column representing the size or abundance of the species at each site. If not provided, counts of species occurrences are calculated.

format

Character string specifying the datetime format for parsing datetime_column.

start_column

The column name (unquoted or as a string) indicating deployment start datetime.

end_column

The column name (unquoted or as a string) indicating deployment end datetime.

deployment_format

Character string specifying the datetime format for parsing start_column and end_column. Defaults to the same format as format.

time_zone

The time zone used to parse the datetime columns. Default is "" (i.e., system time zone).

Value

A tibble with the following columns:

  • deployment_column (camera/location identifier)

  • date (Date of observation)

  • species_column (species name)

  • size_column (daily count, 0 if no observations)

  • sampling_unit (unique identifier for location × date combination)

See also

ct_inext(), ct_get_effort()

Examples

# Example observation data
obs <- data.frame(
  species = c("Deer", "Deer", "Fox", "Deer"),
  count = c(2, 1, 1, 3),
  datetime = c("2023-06-01 08:12:00", "2023-06-01 15:30:00",
               "2023-06-01 21:10:00", "2023-06-02 06:45:00"),
  location_id = c("Cam1", "Cam1", "Cam1", "Cam1"),
  stringsAsFactors = FALSE
)

# Example deployment data
dep <- data.frame(
  location_id = c("Cam1"),
  deploy_start = "2023-06-01 00:00:00",
  deploy_end = "2023-06-03 23:59:59",
  stringsAsFactors = FALSE
)

ct_camera_day(
  data = obs,
  deployment_data = dep,
  datetime_column = "datetime",
  species_column = "species",
  size_column = "count",
  deployment_column = "location_id",
  format = "%Y-%m-%d %H:%M:%S",
  start_column = "deploy_start",
  end_column = "deploy_end"
)
#> # A tibble: 6 × 5
#>   location_id date       species count sampling_unit
#>   <chr>       <date>     <chr>   <dbl> <chr>        
#> 1 Cam1        2023-06-01 Deer        3 Cam120230601 
#> 2 Cam1        2023-06-01 Fox         1 Cam120230601 
#> 3 Cam1        2023-06-02 Deer        3 Cam120230602 
#> 4 Cam1        2023-06-02 Fox         0 Cam120230602 
#> 5 Cam1        2023-06-03 Deer        0 Cam120230603 
#> 6 Cam1        2023-06-03 Fox         0 Cam120230603