Skip to contents

Correct camera trap datetime records

mm_correct_datetime.Rd

This function corrects datetime stamps in camera trap data using a reference correction table. It applies time adjustments based on known timing errors for each camera deployment.

Usage

mm_correct_datetime(data, datetime, deployment, corrector, format = NULL)

Arguments

data

A data.frame or tibble containing camera trap records with datetime information that needs correction.

datetime

Column name (unquoted) in data containing the datetime values to be corrected. Can be character or POSIXct format.

deployment

Column name (unquoted) in both data and corrector that identifies unique camera deployments (e.g., camera ID, site name, or deployment identifier).

corrector

A data.frame containing correction information with columns:

  • deployment column matching the deployment parameter

  • sign - character indicating correction direction ("+" or "-")

  • datetimes - reference datetime showing the correct time

format

Optional datetime format specification. Can be:

  • NULL (default) - attempts multiple common formats

  • Single format string - used for both data and corrector datetimes

  • Vector of 2 format strings - first for data, second for corrector

Value

A data.frame with the original data plus additional columns:

  • corrected_datetime - corrected datetime as POSIXct

  • correction_applied - sign of correction applied

  • time_offset_seconds - magnitude of correction in seconds

  • corrector_reference - reference datetime used for correction

Examples

# Load camera trap data
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union

camtrap_data <- read.csv(maimer:::table_files()[1]) %>%
  dplyr::filter(project == "Last")

# Create correction table
# CAMERA 1 was running slow (+), CAMERA 2 was running fast (-)
crtor <- data.frame(
  camera = c("CAMERA 1", "CAMERA 2"),
  sign = c("+", "-"),
  datetimes = c("2025-03-14 8:17:00", "2024-11-14 10:02:03")
)

# Apply datetime corrections
mm_correct_datetime(
  data = camtrap_data,
  datetime = datetimes,
  deployment = camera,
  corrector = crtor
) %>%
  dplyr::select(datetimes,
                corrected_datetime,
                time_offset_seconds) %>%
  dplyr::slice_head(n = 10)
#>              datetimes  corrected_datetime time_offset_seconds
#> 1   2024-03-24 8:03:07 2025-03-14 08:17:00            30672833
#> 2   2024-03-24 8:03:07 2025-03-14 08:17:00            30672833
#> 3   2024-03-24 8:03:08 2025-03-14 08:17:01            30672833
#> 4  2024-03-24 20:19:35 2025-03-14 20:33:28            30672833
#> 5  2024-03-24 20:19:35 2025-03-14 20:33:28            30672833
#> 6  2024-03-24 20:19:35 2025-03-14 20:33:28            30672833
#> 7  2024-03-24 20:20:02 2025-03-14 20:33:55            30672833
#> 8  2024-03-24 20:20:02 2025-03-14 20:33:55            30672833
#> 9  2024-03-24 20:20:03 2025-03-14 20:33:56            30672833
#> 10 2024-03-24 20:20:24 2025-03-14 20:34:17            30672833