Summarise a burn without materialising it

Compute a compact description of a burn() result in time proportional to the number of records in its sparse tables, never to the number of grid cells, so it is cheap even for a national grid of billions of cells.

Usage

# S3 method for class 'controlledburn'
summary(object, tiles = 256L, ...)

# S3 method for class 'summary.controlledburn'
print(x, ascii = FALSE, ...)

Arguments

object

A controlledburn object returned by burn().

tiles

Target number of tiles along the longer grid axis for the overview, passed to overview_burn().

...

Ignored.

x

A summary.controlledburn object.

ascii

Also print the overview as text.

Value

A list of class summary.controlledburn.

Details

The pieces are:

overview

a coarse matrix of mean coverage per tile, see overview_burn(). When the grid is small enough that one tile is one cell, this is the exact coverage.

row_marginal, col_marginal

exact covered-cell totals per grid row and per grid column, at full resolution.

content

the extent and 1-based row/col range of touched cells, or NULL for an empty burn.

area

per-geometry totals in cells: interior (run cells), boundary (summed edge fractions), lines (summed length, in extent units), points (count).

fractions

quantiles of the edge coverage fractions.

records

row counts of the sparse tables.

Coverage here means: run cells 1 each, edge cells their fraction, line and point cells 1 each (presence).

The number of geometries is taken as the largest id present, so geometries after the last one that touched the grid are not counted.

Examples

if (requireNamespace("geos", quietly = TRUE)) {
  poly <- geos::as_geos_geometry(c("POLYGON ((1 1, 9 1, 9 9, 1 9, 1 1))",
                                   "POLYGON ((2 2, 4 3, 3 5, 2 2))"))
  r <- burn(poly, extent = c(0, 10, 0, 10), dimension = c(100L, 100L))
  s <- summary(r)
  s
  s$area
}
#>   id interior boundary lines points
#> 1  1     6400        0     0      0
#> 2  2      216       34     0      0