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landscape_as_list() method for
PackedSpatRasterget_centroids() related to the patch
idshow_patches()spatialze_lsm() with directions
argumentcalculate_lsm (all metrics: more than 5 times faster with
70% less memory allocation for augusta_nlcd; larger
increases were found for smaller data) and window_lsm (a
single metric: more than 6 times faster for augusta_nlcd;
larger increases were found for smaller data)calculate_lsmextras_df object that lists which
extras are needed by each metrictibble::tibble() with
tibble::new_tibble(list()) in most functions. This change
is partially responsible for improvements of the window_lsm
speedraster_to_points with get_points
in several places. The get_points function is based on the
column and row numbers multiplied by the resolution, not actual
coordinates.table with (faster) tabulate in
lsm_p_coreprepare_extras, get_area_patches,
get_class_patches, get_complexity,
get_enn_patch, get_points, and
get_perimeter_patchwindow_lsm behaviour for situations with NAs
values and non-square windowsterra and sf instead of
raster and sp as underlying frameworksshow_* functions to avoid
ggplot2 warningshow_correlationpoints_as_mat() helper functionextract_lsm returned an no-needed warning messagergeos dependencyget_patches returns a unique patch id for all
classeswindow_lsm()get_boundaries() for matrix input and
return_raster = TRUErel_mut_inf to list_lsm()ggplot2 versionlsm_l_ai if class with only one cell existslsm_c_lsi, lsm_c_nlsi,
lsm_l_lsi not using cell surfaceslsm_l_relmutinf to calculate relative mutual
informationto_disk = TRUE for
spatialize_lsm and matrix_to_rasterget_circumscribingcircle()lsm_p_gyrate has an argument to force the cell centroid
to be within patchget_nearestneighbour() can now return ID of
neighbouring patchget_boundaries() allows now to specify edge depthget_boundaries() can return the patch id for edge
cellsget_centroid() returns the coordinates of each patch
centroidsample_lsm() that adds NA if class is
not present in sample plotlsm_p_circle() when whole landscape contains
only one patchextract_lsm() that directions argument was not
passed onunpad_raster to remove padding around rasterget_boundaries to consider landscape
boundarysample_lsm()sample_lsm()sample_lsm() can use
SpatialPolygonsDataFramecalculate_correlation() returns a tibble with all
correlations between metricsscale_sample() allows to sample landscape metrics in
buffer with increasing sizescale_window() allows calculate selected metrics in
moving windows over the provided landscape.show_correlation() can take result from
calculate_correlation()sample_lsm() returns a warning if
percentage_inside < 90%sample_lsm() and extract_lsm() can now be
used with sample_ids (rather than just 1…n)lsm_c_ai() if only one class and NA values
were presentshow_correlation() that first col was
lostsample_lsm() and extract_lsm()
to forward arguments to calculate_lsm()sample_lsm() is now comparable between
squares and circleswindow_lsm() that some arguments were not
passed on (resolution and points)extract_lsm() and window_lsm()
that allowed metric subset was wrongshow_correlation()list_lsm() allows to return all BUT the selected
metricssample_lsm() can now use SpatialPolygons to sample
metricssample_lsm() can now handle SpatialLines to sample
metricssample_lsm() automatically detects provided data
typeextract_lsm() can now handle SpatialLines to extract
metricslsm_l_ent() and thus
lsm_l_condent() and lsm_l_mutinf().calculate_lsm()/extract_lsm()/sample_lsm()/spatialize_lsm()/window_lsm()
can print progresscat() with message()calculate_lsm() returns an error message if selected
metrics do not existconstruct_buffer() can now return a matrix with coords
instead of polygonscalculate_lsm() checks the input data before
calculating metricsget_lsm() is now called
spatialize_lsm()moving_window() to calculate metrics
within a moving windowget_lsm() to raster in which each cell has
patch metric valuecheck_landscape() if NA values were
presentpad_raster() that pad_raster_cells > 1 did
not workcalculate_lsm() calculating class area where
resolution was lostdplyrcheck_landscape()check_landscape()pad_raster() is now typestable and always returns a
listpad_raster() can now return also a RasterLayer (and not
just a matrix as)sample_lsm() that occured when metrics
where selected using what argumentlsm_p_core() if only one patch is
presentlsm_p_circle() if only one cell is present in
classlsm_p_hyrate() if only one cell is present in
classget_adjacencies() that checks if
neighbourhood was specified correctly did not work
properlysample_lsm() now returns a tibble including an extra
column if return_raster = TRUE (and not a nested tibble as
before)list_lsm(), calculate_lsm() and
`sample_lsm()return_plots to
return_raster in sample_lsm()check_landscape to make sure your
landscapes are feasible for landscapemetricsraster_to_points() to get also NA cells
(not possible with raster::rasterToPoints)get_boundaries() to get only boundary
cellsget_unique_values() that shows all uniques
labels in a classlist_lsm() function to print available
metricsshow_lsm() function to vizualize patch
level metricslsm_l_rpr: Typo in internal function, used
landscapemetrics::landscape instead of user inputshow_() * functions that na.value color
is identicalget_-functions can now take matrix as input and
also return a matrixcalculate_lsm() now uses list_lsm(). This
allows more options to specify metrics to calculatelsm_abbreviations_namesshow_()-functions don’t throw warningsshow_() functionsextract_lsm() now uses list_lsm(). This
allows more options to specify metrics to calculatercpp_get_coocurrence_matrix() can now handle large
rasters and is fasterlsm_p_circle() and
get_circumscribingcircle() now consideres different x-
& y-resolutionswhat arguments of all show_()-functions
now are named class for consistency (so all
what arguments deal with metrics)what arguments of get_patches() is now
named class for consistency (so all what
arguments deal with metrics)calculate_metrics is now
calculate_lsmshow_cores, a function to plot the core
area of patchesshow_patches now also shows labelled class facets
(option what)sample_lsm, a function to sample metrics
around buffered pointsextract_lsm, a function to extract
landscape metrics for spatial coordinatespurrr package and
replaced them by lapplycalculate_lsm has the option progressconsider_boundary is available for all core
metricsedge_depth can be specified for all core
metricsThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.