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CAI_CV (class level)

Source: R/lsm_c_cai_cv.R
lsm_c_cai_cv.Rd

Coefficient of variation of core area index (Core area metric)

Usage

lsm_c_cai_cv(
  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

$$CAI_{CV} = cv(CAI[patch_{ij}]$$ where \(CAI[patch_{ij}]\) is the core area index of each patch.

CAI_CV is a 'Core area metric'. The metric summarises each class as the Coefficient of variation of the core area index of all patches belonging to class i. The core area index is the percentage of core area in relation to patch area. A cell is defined as core area if the cell has no neighbour with a different value than itself (rook's case). The metric describes the differences among patches of the same class i in the landscape.

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

Units

Percent

Range

CAI_CV >= 0

Behaviour

Equals CAI_CV = 0 if the core area index is identical for all patches. Increases, without limit, as the variation of the core area indices increases.

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_p_cai,
lsm_c_cai_mn, lsm_c_cai_sd,
lsm_l_cai_mn, lsm_l_cai_sd, lsm_l_cai_cv

Examples

landscape <- terra::rast(landscapemetrics::landscape)
lsm_c_cai_cv(landscape)
#> # A tibble: 3 × 6
#>   layer level class    id metric value
#>   <int> <chr> <int> <int> <chr>  <dbl>
#> 1     1 class     1    NA cai_cv 164. 
#> 2     1 class     2    NA cai_cv 143. 
#> 3     1 class     3    NA cai_cv  72.1