lsp_signature {motif} | R Documentation |
Creates a spatial signature
Description
Calculates selected spatial signatures based on categorical raster data. It also allows for calculations for any defined regular and irregular areas. It has several built-in signatures but also allows for any user-defined functions.
Usage
lsp_signature(
x,
type,
window = NULL,
neighbourhood = 4,
threshold = 0.9,
ordered = FALSE,
repeated = FALSE,
normalization = "pdf",
wecoma_fun = "mean",
wecoma_na_action = "replace",
classes = NULL
)
Arguments
x |
Object of class stars , stars_proxy , or terra's SpatRaster . It should have one attribute (for "coma" , "cove" ), two attributes ("cocoma" , "cocove" , "wecoma" , "wecove" ), two or more attributes ("incoma" , "incove" ), or any number of attributes suitable for user-defined functions.
|
type |
Type of the calculated signature. It can be "coma" (co-occurrence matrix), "cove" (co-occurrence vector), "cocoma" (co-located co-occurrence matrix), "cocove" (co-located co-occurrence vector), "wecoma" (weighted co-occurrence matrix), "wecove" (weighted co-occurrence vector), "incoma" (integrated co-occurrence matrix), "incove" (integrated co-occurrence vector), "composition" or any function that can summarize stars objects.
|
window |
Specifies areas for analysis. It can be either: NULL , a numeric value, or an sf object. If window=NULL calculations are performed for a whole area. If the window argument is numeric, it is a length of the side of a square-shaped block of cells. Expressed in the numbers of cells, it defines the extent of a local pattern. If an sf object is provided, each feature (row) defines the extent of a local pattern. The sf object should have one attribute (otherwise, the first attribute is used as an id).
|
neighbourhood |
The number of directions in which cell adjacencies are considered as neighbours:
4 (rook's case) or 8 (queen's case). The default is 4.
|
threshold |
The share of NA cells (0-1) to allow metrics calculation.
|
ordered |
For "cove" , "cocove" , "wecove" and "incove" only. The type of pairs considered.
Either "ordered" (TRUE) or "unordered" (FALSE).
The default is FALSE.
|
repeated |
For "incove" only. Should the repeated co-located co-occurrence matrices be used?
Either "ordered" (TRUE) or "unordered" (FALSE).
The default is FALSE.
|
normalization |
For "cove" , "cocove" , "wecove" , "incove" , "composition" , or user-provided functions only. Should the output vector be normalized?
Either "none" or "pdf".
The "pdf" option normalizes a vector to sum to one.
The default is "pdf".
|
wecoma_fun |
For "wecoma" and "wecove" only. Function to calculate values from adjacent cells to contribute to exposure matrix, "mean" - calculate average values of local population densities from adjacent cells, "geometric_mean" - calculate geometric mean values of local population densities from adjacent cells, or "focal" assign a value from the focal cell
|
wecoma_na_action |
For "wecoma" and "wecove" only. Decides on how to behave in the presence of missing values in w . Possible options are "replace" , "omit" , "keep" . The default, "replace" , replaces missing values with 0, "omit" does not use cells with missing values, and "keep" keeps missing values.
|
classes |
Which classes (categories) should be analyzed? This parameter expects a list of the same length as the number of attributes in x , where each element of the list contains integer vector. The default is NULL , which means that the classes are calculated directly from the input data and all of them are used in the calculations.
|
Value
Object of class lsp
.
It has three columns: (1) id
- an id of each window.
For irregular windows, it is the values provided in the window
argument,
(2) na_prop
- share (0-1) of NA
cells for each window,
(3) signature
- a list-column containing calculated signatures
Examples
library(stars)
landcover = read_stars(system.file("raster/landcover2015s.tif", package = "motif"))
landcover_coma = lsp_signature(landcover, type = "coma", threshold = 0.9, window = 2000)
landcover_coma
landcover_comp = lsp_signature(landcover, type = "composition", threshold = 0.9)
landcover_comp
# larger data example
library(stars)
landcover = read_stars(system.file("raster/landcover2015.tif", package = "motif"))
landcover_coma = lsp_signature(landcover, type = "coma", threshold = 0.9, window = 2000)
landcover_coma
landcover_comp = lsp_signature(landcover, type = "composition", threshold = 0.9)
landcover_comp
[Package
motif version 0.6.4
Index]