landscapemetrics (version 1.1)

window_lsm: window_lsm

Description

Moving window

Usage

window_lsm(landscape, window, metric, name, type, what, progress, ...)
# S3 method for RasterLayer
window_lsm(landscape, window, metric = NULL,
  name = NULL, type = NULL, what = NULL, progress = FALSE, ...)
# S3 method for RasterStack
window_lsm(landscape, window, metric = NULL,
  name = NULL, type = NULL, what = NULL, progress = FALSE, ...)
# S3 method for RasterBrick
window_lsm(landscape, window, metric = NULL,
  name = NULL, type = NULL, what = NULL, progress = FALSE, ...)
# S3 method for stars
window_lsm(landscape, window, metric = NULL,
  name = NULL, type = NULL, what = NULL, progress = FALSE, ...)
# S3 method for list
window_lsm(landscape, window, metric = NULL,
  name = NULL, type = NULL, what = NULL, progress = FALSE, ...)

Arguments

landscape

Raster* Layer, Stack, Brick or a list of rasterLayers.

window

matrix

metric

Abbreviation of metrics (e.g. 'area').

name

Full name of metrics (e.g. 'core area')

type

Type according to FRAGSTATS grouping (e.g. 'aggregation metrics').

what

Selected level of metrics: either "patch", "class" or "landscape". It is also possible to specify functions as a vector of strings, e.g. what = c("lsm_c_ca", "lsm_l_ta").

progress

Print progress report.

...

Arguments passed on to calculate_lsm().

Value

list

Details

The function calculates for each focal cell the selected landscape metrics (currently only landscape level metrics are allowed) for a local neighbourhood. The neighbourhood can be specified using a matrix. For more details, see ?raster::focal(). The result will be a RasterLayer in which each focal cell includes the value of its neighbourhood and thereby allows to show gradients and variability in the landscape (Hagen-Zanker 2016). To be type stable, the acutally result is always a nested list (first level for RasterStack layers, second level for selected landscape metrics).

References

Fletcher, R., Fortin, M.-J. 2018. Spatial Ecology and Conservation Modeling: Applications with R. Springer International Publishing. 523 pages

Hagen-Zanker, A. (2016). A computational framework for generalized moving windows and its application to landscape pattern analysis. International journal of applied earth observation and geoinformation, 44, 205-216.

McGarigal, K., Cushman, S.A., and Ene E. 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 website: http://www.umass.edu/landeco/research/fragstats/fragstats.html

See Also

list_lsm calculate_lsm focal

Examples

# NOT RUN {
window <- matrix(1, nrow = 5,ncol = 5)
window_lsm(landscape, window = window, what = c("lsm_l_pr", "lsm_l_joinent"))
window_lsm(landscape_stack, window = window, what = c("lsm_l_pr", "lsm_l_joinent"))
# }
# NOT RUN {
# }