focal_metrics | R Documentation |
Calculates the various texture metrics over windows centered
on individual pixels. This creates a continuous surface of the
texture metric.
This function is a modified version of the window_lsm
function from the
landscapemetrics package (Hesselbarth et al. 2019).
focal_metrics(x, window, metrics, progress, ...)
x |
A raster or matrix. Image over which to apply focal window calculations. |
window |
Matrix. The focal window used to create the image. |
metrics |
List. List of metrics to apply. Function names must be strings. |
progress |
Logical. Display progress through metrics list? |
... |
Additional arguments for the metric functions. All applicable arguments will be applied to the entire list of metrics. |
Metrics available from geodiv package:
'sa'
: average surface roughness
'sq'
: root mean square roughness
's10z'
: ten-point height
'sdq'
: root mean square slope of surface, 2-point method
'sdq6'
: root mean square slope of surface, 7-point method
'sdr'
: surface area ratio
'sbi'
: surface bearing index
'sci'
: core fluid retention index
'ssk'
: skewness
'sku'
: kurtosis
'sds'
: summit density
'sfd'
: 3d fractal dimension
'srw'
: dominant radial wavelength, radial wavelength index, mean half wavelength
'std'
: angle of dominating texture, texture direction index
'svi'
: valley fluid retention index
'stxr'
: texture aspect ratio
'ssc'
: mean summit curvature
'sv'
: maximum valley depth
'sph'
: maximum peak height
'sk'
: core roughness depth
'smean'
: mean peak height
'svk'
: reduced valley depth
'spk'
: reduced peak height
'scl'
: correlation length
'sdc'
: bearing area curve height interval
A raster of the metric calculated in windows over the raster or matrix. If the input was a matrix, the function will return a raster with an extent of [0, 1, 0, 1].
Hesselbarth, M.H.K., Sciaini, M., With, K.A., Wiegand, K., Nowosad, J. 2019. landscapemetrics: an open-source R tool to calculate landscape metrics. - Ecography 42:1648-1657(ver. 0).
# import raster image
data(normforest)
normforest <- terra::unwrap(normforest)
# crop raster to smaller area
x <- terra::crop(normforest, terra::ext(normforest[1:100, 1:100, drop = FALSE]))
# get a surface of root mean square roughness
sa_img <- focal_metrics(x = x, window = matrix(1, 5, 5),
metrics = list('sa'), progress = TRUE)
# plot the result
terra::plot(sa_img$sa)
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