Metrics on changing sample scale
scale_sample(landscape, y, shape, size, max_size, verbose, progress, ...)# S3 method for RasterLayer
scale_sample(
landscape,
y,
shape = "square",
size,
max_size,
verbose = TRUE,
progress = FALSE,
...
)
# S3 method for RasterStack
scale_sample(
landscape,
y,
shape = "square",
size,
max_size,
verbose = TRUE,
progress = FALSE,
...
)
# S3 method for RasterBrick
scale_sample(
landscape,
y,
shape = "square",
size,
max_size,
verbose = TRUE,
progress = FALSE,
...
)
# S3 method for stars
scale_sample(
landscape,
y,
shape = "square",
size,
max_size,
verbose = TRUE,
progress = FALSE,
...
)
# S3 method for list
scale_sample(
landscape,
y,
shape = "square",
size,
max_size,
verbose = TRUE,
progress = FALSE,
...
)
Raster* Layer, Stack, Brick or a list of rasterLayers.
2-column matrix with coordinates or SpatialPoints.
String specifying plot shape. Either "circle" or "square"
Approximated size of sample plot. Equals the radius for circles or half of the side-length for squares in mapunits. For lines size equals the width of the buffer.
Maximum size to which sample plot size is summed up.
Print warning messages.
Print progress report.
Arguments passed on to calculate_lsm()
.
tibble
This function calculates the selected metrics in subsequential buffers around a/multiple point(s) of interest.
The size of the actual sampled landscape can be different to the provided size
due to two reasons. Firstly, because clipping raster cells using a circle or a
sample plot not directly at a cell center lead to inaccuracies. Secondly,
sample plots can exceed the landscape boundary. Therefore, we report the actual
clipped sample plot area relative in relation to the theoretical, maximum sample
plot area e.g. a sample plot only half within the landscape will have a
percentage_inside = 50
. Please be aware that the output is sligthly different
to all other lsm
-function of landscapemetrics
.
The metrics can be specified by the arguments what
, level
, metric
, name
and/or type
(combinations of different arguments are possible (e.g.
level = "class", type = "aggregation metric"
). If an argument is not provided,
automatically all possibilities are selected. Therefore, to get all
available metrics, don't specify any of the above arguments.
# NOT RUN {
my_points = matrix(c(1265000, 1250000, 1255000, 1257000),
ncol = 2, byrow = TRUE)
scale_sample(landscape = augusta_nlcd, y = my_points,
size = 500, max_size = 5000, what = c("lsm_l_ent", "lsm_l_mutinf"))
# }
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