lsm_l_cai_sd: CAI_SD (landscape level)

In landscapemetrics: Landscape Metrics for Categorical Map Patterns

CAI_SD (landscape level)

Description

Standard deviation of core area index (Core area metric)

Usage

lsm_l_cai_sd(
  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

Details

CAI_{SD} = sd(CAI[patch_{ij}]

where CAI[patch_{ij}] is the core area index of each patch.

CAI_SD is a 'Core area metric'. The metric summarises the landscape as the standard deviation of the core area index of all patches in the landscape. 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 all patches 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_SD >= 0

Behaviour

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

Value

tibble

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, sd
lsm_c_cai_mn, lsm_c_cai_sd, lsm_c_cai_cv,
lsm_l_cai_mn, lsm_l_cai_cv

Examples

landscape <- terra::rast(landscapemetrics::landscape)
lsm_l_cai_sd(landscape)

landscapemetrics documentation built on Sept. 12, 2024, 7:42 a.m.