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Convert STRIP codes to distance intervals

Source: R/strip.R
strip_distance.Rd

Resolves each STRIP code to the right-angle distance interval it stands for, and the side of the track it was on.

Usage

strip_distance(
  strip,
  platform = c("skymaster", "at-11"),
  scheme = c("auto", "cetap", "nlpsc"),
  date = NULL,
  units = c("m", "km", "nmi"),
  left_truncation = FALSE
)

Arguments

strip

Integer vector of STRIP codes.

platform

"skymaster" (default) or "at-11".

scheme

"auto", "cetap", or "nlpsc".

date

Vector of survey dates, used when scheme = "auto".

units

"m" (default), "km", or "nmi".

left_truncation

Apply the Skymaster blind-spot offset? Default FALSE.

Value

A tibble with one row per input: distbegin, distend, side, scheme.

Choosing the scheme

With scheme = "auto" (the default) the scheme is chosen from date: the NLPSC / Mass CEC breakpoints for October 2011 onwards, the CETAP ones before. That is a reasonable default but not a guarantee — a survey flown after 2011 under the older protocol would be misread — so pass scheme explicitly when you know which applies. With no date and no scheme, this errors rather than guess.

The Skymaster blind spot

Handbook 8.A.31 notes that the Skymaster's restricted downward visibility means CETAP-era distances from that aircraft "are actually measured from about 1/8 mile to either side of the survey line". The strip boundaries do not record this, so distances near zero are not what they appear: the region under the aircraft was never searched. Set left_truncation = TRUE to shift the innermost bins accordingly, and see detection_data() (not yet implemented) for fitting with a left truncation, which is the statistically correct treatment.

See also

narwc_strip_bins(), sighting_distances()

Examples

strip_distance(c(5, 6, 13), scheme = "nlpsc")
#> # A tibble: 3 × 4
#>   distbegin distend side  scheme
#>       <dbl>   <dbl> <chr> <chr> 
#> 1       463     926 left  nlpsc 
#> 2       463     926 right nlpsc 
#> 3      7408     Inf left  nlpsc 

# Same codes, different era, different distances
strip_distance(c(5, 6, 13), scheme = "cetap")
#> # A tibble: 3 × 4
#>   distbegin distend side  scheme
#>       <dbl>   <dbl> <chr> <chr> 
#> 1      232.     463 left  cetap 
#> 2      232.     463 right cetap 
#> 3     1852     3704 left  cetap