View source: R/metrics_gradient.R
metrics_gradient | R Documentation |
Selects a set of points whose associated landscapes comprise an optimized gradient for a given landscape metric.
metrics_gradient(
x,
rasterlayer = NULL,
class = NULL,
radius = NULL,
metric = NULL,
n,
cutpoints = NULL,
breaks = NULL,
random = FALSE,
output = "MLM"
)
x |
An object of class 'MultiLandMetrics' generated with |
rasterlayer |
The raster layer to be considered. If an extra raster layer must be specified, the string "ext" must precede the raster layer number (e.g. "ext1", "ext2") |
class |
The class to be considered, as a number or as a string with the name of the class. |
radius |
The radius to be considered. |
metric |
The metric to be considered. Metrics as extra calculations for extra raster layers must be provided as "fun_" + the name of the function. |
n |
The number of points that will comprise the gradient. See Details. |
cutpoints |
A sequence of numbers that will serve as numeric approximations to select the points that will comprise the gradient. See Details. |
breaks |
A unique number with the number of breaks that will generate the cutpoints for the specified metric values. Default is 10. See Details. |
random |
Logical. If TRUE, random points will be selected. |
output |
One of the following: "MLM" to return an updated version of the 'MultiLandMetrics' object provided in |
Selects a subset of landscapes that overall will
generate an optimized gradient of values for a given landscape metric of a specified raster layer,
class and radius. One can define a gradient as optimized if
its values fulfill to cover a good range of values between a minimum and a maximum value. The
final gradient will comprise the number of points specified in argument n
. Note that
only one landscape metric can be specified at a time.
The algorithm will select those points whose associated landscapes present values for the specified landscape metric that are
the most close to the specified cutpoints
. Alternatively, the user can provide a number of
breaks
from which the sequence of cutpoints will be generated. If both arguments are specified,
the function will consider the values inputted in cutpoints
. If both arguments are NULL, the
algorithm will simply select n
random points.
A 'MultiLandMetrics' if output = "MLM"
, a 'SpatVector' if output = "spatial"
,
a data.frame if output = "data"
or a data.frame with geographical information of the points if output = "coords"
.
metrics_filter()
# Generates an optimized gradient for the landscape metric "pland", for the class "Forest".
pland_gradient <- metrics_gradient(otf_metrics, rasterlayer = 1, class = "Forest",
radius = 2000, metric = "pland", n = 15, breaks = 10)
# Note that, in this case, specifications for the rasterlayer and the radius are
# redundant, and could be simply ignored and left as default, asthe object otf_metrics
# only comprises a unique rasterlayer and radius.
# By default, the output is an updated version of the object otf_metrics. In order to
# inspect the returned values, let's select only the dataframe containing the
# metric's values.
foo <- subset(pland_gradient@data, metric == "pland" & classname == "Forest",
select = value)
# Next, we output the range of values we have obtained, note there are 15 points, as
# previously specified in the function definition in the argument 'n'
round(sort(foo$value), digits = 2)
# 1.15 1.57 8.17 8.19 15.24 22.32 29.27 36.32 43.17 43.20 49.79 50.25 55.44 57.62 64.53
# Alternatively, we can define specific cutpoints around the landscapes will be selected
# in termsof its numeric closeness.
pland_gradient <- metrics_gradient(otf_metrics, rasterlayer = 1, class = "Forest",
radius = 2000,metric = "pland", n = 15,
cutpoints = seq(1, 60, 5))
# Again, we inspect the dataframe with the metric values to see our results.
foo <- subset(pland_gradient@data, metric == "pland" & classname == "Forest",
select = value)
round(sort(foo$value), digits = 2)
# 1.15 6.02 6.03 10.99 15.97 20.99 26.01 31.02 35.95 41.14 41.34 45.93 51.41 54.56 55.44
# Both alternatives generated a wide-ranged gradient of values for the forest metric "pland"
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