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Checks that only matter for distance sampling

Source: R/validate.R
distsamp_checks.Rd

The checks in this package, for use alongside the handbook-general set that narwcr::narwc_checks() provides.

Usage

distsamp_checks()

Value

A named list of functions, in the shape narwcr::narwc_checks() uses.

Why these are separate

Everything here is a problem only if you are computing a right-angle distance. A declination angle above the horizon and an exact sighting position 200 km from the aircraft that logged it are both perfectly ordinary columns to carry around; they become defects at the point where a detection function is fitted to them. So they live with the package that fits one, rather than in the reader that every analysis shares.

exact_position_far_from_event

An exact sighting position more than 20 km from the event position that recorded it. A sighting is made from the aircraft, so this is a coordinate problem — usually a dropped minus sign, or degrees and decimal minutes read as decimal degrees — rather than a distant animal.

angle_out_of_range

ANGLEL or ANGLER outside (0, 90]. Handbook 8.A.2 defines these as declination angles below the horizon, so a value at or below zero is at or above the horizon and one above 90 is behind the aircraft. Neither yields a perpendicular distance.

angle_both_sides

Both ANGLEL and ANGLER recorded on one record. A sighting is on one side of the track, so the side is ambiguous and no distance can be computed.

angle_without_altitude

A declination angle with no ALT. Handbook 8.A.2: the distance calculation must factor in altitude, so an angle without one is unusable.

References

Kenney, R.D. (2023) The North Atlantic Right Whale Consortium Database: A Guide for Users and Contributors, Version 8, section 8.A.2. NARWC Reference Document 2023-01.

See also

narwcr::validate_narwc(), narwcr::narwc_checks()

Examples

path <- system.file("extdata", "narwc-example.csv", package = "distsamp")
dat <- read_narwc(path, quiet = TRUE)

# The handbook rules and the distance-sampling ones together
issues <- validate_narwc(dat, checks = c(narwc_checks(), distsamp_checks()))
issues[, c("check", "severity", "n")]
#> # A tibble: 1 × 3
#>   check                    severity     n
#>   <chr>                    <chr>    <int>
#> 1 legstage_line_not_closed note         1