discretize: Rasterize Area Search or Transect Data

Description

It is sometimes useful to re-cast area search (polygon) data as if it was from a set of closely spaced point detectors, i.e. to rasterize the detection locations. This function makes that conversion. Each polygon detector in the input is replaced by a number of point detectors, each representing a square pixel. Detections are mapped to the new detectors on the basis of their x-y coordinates. If object contains transect data the problem is passed to snip and reduce.capthist.

Usage

discretize(object, spacing = 5, outputdetector = c("proximity", "count", "multi"), 
    tol = 0.001, ...)

Arguments

object

secr capthist or traps object

spacing

numeric spacing between point detectors in metres

outputdetector

character output detector type

tol

numeric fractional inflation of perimeter (see Details)

...

other arguments passed to snip if object is transect

Value

A capthist or traps object of the requested detector type, but otherwise carrying forward all attributes of the input. The embedded traps object has a factor covariate `polyID' recording the polygon to which each point detector relates.

Details

The input should have detector type `polygon' or `polygonX'. Centres of a new array of equally spaced detectors are placed within each polygon of the input, inflated radially by 1 + tol to avoid some inclusion problems. The origin of the superimposed grid is fixed automatically. `tol' may be negative, in which case the array(s) will be shrunk relative to the polygon(s).

Examples

Run this code

## generate some polygon data
pol <- make.poly()
CH <- sim.capthist(pol, popn=list(D=30), detectpar=list(g0 = 0.3))
plot(CH, border = 10, gridl = FALSE, varycol = FALSE)

## discretize and plot
CH1 <- discretize(CH, spacing = 10, output = 'count')
plot(CH1, add = TRUE, cappar = list(col = 'orange'), varycol =
    FALSE, rad = 0)
plot(traps(CH1), add = TRUE)

## show how detections are snapped to new detectors
newxy <- traps(CH1)[nearesttrap(xy(CH),traps(CH1)),]
segments(xy(CH)[,1], xy(CH)[,2], newxy[,1], newxy[,2])