Summarize environmental layers within corridors

For every pair of sites, summarizes each environmental layer inside the pair's corridor. With least cost corridors (acc and q), each cell counts in proportion to its corridor weight, so likely routes matter more than marginal ones. With path buffers, cells are weighted by the share of the cell inside the buffer.

Usage

corridor_extract(
  env,
  pairs,
  acc = NULL,
  q = 0.05,
  buffers = NULL,
  stat = "mean",
  progress = interactive()
)

Arguments

env

A SpatRaster of environmental layers. Layers are resampled to the corridor grid as needed (bilinear for continuous layers).

pairs

Data.frame with columns from and to.

acc, q

Accumulated cost surfaces from accumulated_cost() and the corridor threshold for lcc_weights(). Use these for least cost corridors.

buffers

Alternatively, an sf layer of buffered paths from path_buffers() with columns from and to.

stat

How to summarize each layer: "mean" (weighted mean, the default) or "sum" (weighted sum, for counts such as stream or trail crossings). A named vector sets the statistic per layer.

progress

Show a progress bar.

Value

A data.frame with from, to and one column per layer of env.

Examples

# \donttest{
ex <- corridor_example()
tr <- make_transition(ex$resistance)
pr <- data.frame(from = c("M01", "M02"), to = c("M12", "M05"))
acc <- accumulated_cost(tr, ex$sites[ex$sites$site %in% unlist(pr), ])
corridor_extract(ex$env, pr, acc = acc, q = 0.05)
#>   from  to snowpack   runoff moisture summer_temp    slope    forest
#> 1  M01 M12 702.5725 474.9524 7.035619    22.80098 3.897698 0.9004108
#> 2  M02 M05 720.7984 483.6719 7.086381    22.82677 3.646871 0.9465355
# }