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Perform a series of QA checks on the Timelapse Image data

Source: R/qa-images.R
qa_image_data.Rd

  • Check for blanks in key fields (study area, station label, deployment date, surveyor, trigger mode, temperature, episode)

  • Species detected with no count data

  • Count data with no species

  • Sum of subcount fields equals Total Count

  • Multiple entries under same Episode number (indicating possible double entry)

  • Ensure dates for timelapse images are continuous and in order.

  • Ensure daily timelapse photos are at the expected time

  • Snow data

    • No blanks unless lens obscured is TRUE

    • Look for snow depth outliers (e.g., 10, 10, 110, 10, 15, 20)

Usage

qa_image_data(
  image_data,
  exclude_human_use = TRUE,
  check_snow = TRUE,
  tl_time = "12:00:00"
)

Arguments

image_data

data.frame of class image_data, as read in by read_image_data().

exclude_human_use

should images where human_use_type indicates a motion detection event from humans be excluded from the count/species checks? Default TRUE.

check_snow

show QA be performed on snow measurements? Default TRUE

tl_time

the time of day timelapse images should be set at. Default "12:00:00"

Value

input data frame with additional QA_* columns appended, and subset only to rows where a QA issue was flagged.