Coefficient of variation of core area (Core area metric)
lsm_l_core_cv(landscape, directions, consider_boundary, edge_depth)# S3 method for RasterLayer
lsm_l_core_cv(
landscape,
directions = 8,
consider_boundary = FALSE,
edge_depth = 1
)
# S3 method for RasterStack
lsm_l_core_cv(
landscape,
directions = 8,
consider_boundary = FALSE,
edge_depth = 1
)
# S3 method for RasterBrick
lsm_l_core_cv(
landscape,
directions = 8,
consider_boundary = FALSE,
edge_depth = 1
)
# S3 method for stars
lsm_l_core_cv(
landscape,
directions = 8,
consider_boundary = FALSE,
edge_depth = 1
)
# S3 method for list
lsm_l_core_cv(
landscape,
directions = 8,
consider_boundary = FALSE,
edge_depth = 1
)
Raster* Layer, Stack, Brick or a list of rasterLayers.
The number of directions in which patches should be connected: 4 (rook's case) or 8 (queen's case).
Logical if cells that only neighbour the landscape boundary should be considered as core
Distance (in cells) a cell has the be away from the patch edge to be considered as core cell
tibble
$$CORE_{CV} = cv(CORE[patch_{ij}])$$ where \(CORE[patch_{ij}]\) is the core area in square meters of each patch.
CORE_CV is a 'Core area metric'. It equals the Coefficient of variation of the core area of each patch in the landscape. The core area is defined as all cells that have no neighbour with a different value than themselves (rook's case). The metric describes the differences among all patches in the landscape and is easily comparable because it is scaled to the mean.
McGarigal, K., SA Cushman, and E Ene. 2012. FRAGSTATS v4: Spatial Pattern Analysis Program for Categorical and Continuous Maps. Computer software program produced by the authors at the University of Massachusetts, Amherst. Available at the following web site: http://www.umass.edu/landeco/research/fragstats/fragstats.html
lsm_p_core
,
cv
,
lsm_c_core_mn
,
lsm_c_core_sd
,
lsm_c_core_cv
,
lsm_l_core_mn
,
lsm_l_core_sd
# NOT RUN {
lsm_l_core_cv(landscape)
# }
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