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DCAD (class level)

Source: R/lsm_c_dcad.R
lsm_c_dcad.Rd

Disjunct core area density (core area metric)

Usage

lsm_c_dcad(
  landscape,
  directions = 8,
  consider_boundary = FALSE,
  edge_depth = 1
)

Arguments

landscape

A categorical raster object: SpatRaster; Raster* Layer, Stack, Brick; stars or a list of SpatRasters.

directions

The number of directions in which patches should be connected: 4 (rook's case) or 8 (queen's case).

consider_boundary

Logical if cells that only neighbour the landscape boundary should be considered as core

edge_depth

Distance (in cells) a cell has the be away from the patch edge to be considered as core cell

Value

tibble

Details

$$DCAD = (\frac{\sum \limits_{j = 1}^{n} n_{ij}^{core}} {A}) * 10000 * 100$$ where \(n_{ij}^{core}\) is the number of disjunct core areas and \(A\) is the total landscape area in square meters.

DCAD is a 'Core area metric'. It equals the number of disjunct core areas per 100 ha relative to the total area. A disjunct core area is a 'patch within the patch' containing only core cells. A cell is defined as core area if the cell has no neighbour with a different value than itself (rook's case). The metric is relative and therefore comparable among landscapes with different total areas.

Because the metric is based on distances or areas please make sure your data is valid using check_landscape.

Units

Number per 100 hectares

Range

DCAD >= 0

Behaviour

Equals DCAD = 0 when DCORE = 0, i.e. no patch of class i contains a disjunct core area. Increases, without limit, as disjunct core areas become more present, i.e. patches becoming larger and less complex.

References

McGarigal K., SA Cushman, and E Ene. 2023. FRAGSTATS v4: Spatial Pattern Analysis Program for Categorical Maps. Computer software program produced by the authors; available at the following web site: https://www.fragstats.org

See also

lsm_c_ndca, lsm_l_ta,
lsm_l_dcad

Examples

landscape <- terra::rast(landscapemetrics::landscape)
lsm_c_dcad(landscape)
#> # A tibble: 3 × 6
#>   layer level class    id metric value
#>   <int> <chr> <int> <int> <chr>  <dbl>
#> 1     1 class     1    NA dcad   5556.
#> 2     1 class     2    NA dcad   6667.
#> 3     1 class     3    NA dcad   8889.