filter_create: Create filters or kernel matrices for raster neighborhood...

In NINAnor/oneimpact: Tools for the assessment of the cumulative impacts of anthropogenic features in ecological studies

Create filters or kernel matrices for raster neighborhood analyses

Description

This function creates matrices of weights following different functions to be used in neighborhood analyses for rasters. In the context of cumulative impact analysis, they represent the Zone of Influence (ZOI) of each infrastructure point/pixel, to be used to calculate the cumulative ZOI. It is possible to export these matrices as text files, for use with external software such as the r.mfilter module within GRASS GIS.

Usage

filter_create(
  r = 100,
  radius = NULL,
  type = c("exp_decay", "bartlett", "circle", "threshold_decay", "gaussian_decay",
    "Gauss", "rectangle")[1],
  zoi_limit = 0.05,
  half_life = NULL,
  zoi_hl_ratio = NULL,
  sigma = NULL,
  min_intensity = 0.01,
  max_dist = 5000,
  normalize = FALSE,
  divisor = 1,
  round_vals = NULL,
  save_txt = FALSE,
  save_format = c("GRASS_rmfilter", "raw")[1],
  save_folder = NULL,
  save_file = NULL,
  parallel = TRUE,
  ...
)

Arguments

r	⁠[numeric,SpatRaster,RasterLayer]⁠ Either a numeric value corresponding to the resolution (pixel size) that each pixel in the filter matrix should correspond to; or a raster object (SpatRaster from the terra package or RasterLayer, RasterBrick, or RasterStack from the raster package) from which such resolution can be extracted.
radius	⁠[numeric(1)=NULL]⁠ Zone of Influence (ZOI) radius, in map units (preferentially meters). The ZOI radius is the distance, scale, or buffer size around a feature up to which we consider there is an effect or influence of an infrastructure or variable. In filter_create, the interpretation of the radius differ depending on the shape of the zoi (parameter type): For the circle neighborhood (type = "circle" or type = "threshold" or type = "step"), the radius corresponds to the radius (or threshold) of the circle, beyond which the filter is zero. For the rectangular neighborhood (type = "rectangle" or type = "box"), the radius corresponds to half the size of the square size, or ⁠square size = 2*radius⁠. For a rectangular filter with different size of the sides, use terra::focal() (but please note the interpretation of the parameters is different). For the Bartlett neighborhood (type = "bartlett" or type = "linear_decay" or type = "tent_decay"), the radius corresponds to the distance beyond which the filter is zero. For the exponential decay neighborhood (type = "exp_decay") and the Gaussian decay neighborhood (type = "Gauss" or type = "gaussian_decay"), the radius corresponds to the distance where the exponential decay function goes below a given limit distance defined by zoi_limit. See zoi_functions() for details. If radius = NULL, the exponential or gaussian decay matrices are defined based on other parameters – see below. This option will raise an error for the other types of filters.
type	⁠[character(1)="exp_decay"]{"exp_decay", "bartlett", "circle", "threshold_decay", "gaussian_decay", "Gauss", "rectangle"}⁠ Shape of the Zone of Influence of weight matrix. It can be any of: "circle", "threshold", "threshold_decay", "step" or "step_decay" for a threshold decay ZOI; "exp_decay" for exponential decay ZOI; "Gauss", "gaussian", or "gaussian_decay" for Gaussian decay ZOI; "bartlett", "bartlett_decay", "linear_decay", or "tent_decay" for linear decay ZOI; "rectangle" or "box" for a rectangular ZOI. There might be some correspondence between the weight matrix type in filter_create and other similar functions (e.g. type = "rectangle" and type = "boxcar" in smoothie::kernel2dmeitsjer() or type = "Gauss" in terra::focalMat() with parameter type = "gauss" n smoothie::kernel2dmeitsjer); however, the interpretation of the parameters used to define these matrices is different between functions.
zoi_limit	⁠[numeric(1)=0.05]⁠ For non-vanishing filters (e.g. exp_decay, gaussian_decay), this value is used to set the relationship between the ZOI radius and the decay functions: radius is defined as the minimum distance x at which the ZOI assumes values below zoi_limit. The default is 0.05. This parameter is used only if radius is not NULL.
half_life	⁠[numeric(1)=NULL]⁠ Half life of the exponential decay function, in meters. By definition, the half life is the distance where the exponential decay function reaches 0.5 of its maximum value. For the exp_decay function, if the ZOI radius parameter is null (radius = NULL), the value of the exponential half life (half_life = log(2)/lambda) can used to parameterize the exponential decay function. See details in zoi_functions().
zoi_hl_ratio	⁠[numeric(1)=6]⁠ For the exp_decay function, if both the ZOI radius radius and zoi_hl_ratio are given and half_life is NULL, this value is used to set the ZOI radius (and zoi_limit is ignored). zoi_hl_ratio is the ratio between the ZOI radius value and the half life of the exponential function. For instance, if radius = 1200 and zoi_hl_ratio = 6, this means half_life is 200. As a consequence, the exponential decay ZOI function decreases to 0.5 at distance 200, and the ZOI radius = 1200 is defined as the distance at which the ZOI decreases to 0.5**6 = 0.015625.
sigma	⁠[numeric(1)=NULL]⁠ Standard deviation of the Gaussian function. It related to the Gaussian decay rate \lambda as lambda = 1/(2*sigma^2). Only considered to compute the ZOI for the gaussian_decay function when the ZOI radius parameter is null (radius = NULL).
min_intensity	⁠[numeric(1)=0.01]⁠ Minimum intensity of the exponential and Gaussian decay functions to define the radius of the window that define the filter.
max_dist	⁠[numeric(1)=50000]⁠ Maximum size (in meters) to define the radius of the window that defines the filter. Only applicable for exponential and Gaussian decay functions.
normalize	⁠[logical(1)=FALSE]⁠ Whether the matrix should be normalized (sum of all cells is 1 if normalize = TRUE) or kept as it is (default, normalize = FALSE).
divisor	⁠[numeric(1)=1]⁠ By default, 1. This is the divisor of the neighborhood matrix when used within r.mfilter. According the the module documentation, "The filter process produces a new category value for each cell in the input raster map layer by multiplying the category values of the cells in the n x n neighborhood around the center cell by the corresponding matrix value and adding them together. If a divisor is specified, the sum is divided by this divisor." If the divisor is zero, "then the divisor is computed for each cell as the sum of the MATRIX values where the corresponding input cell is non-null." In other words, the output map will be rescaled to the interval $0,1$. If normalize = TRUE, the divisor is set to n*n.
round_vals	⁠[numeric(1)=NULL]⁠ Number of digits for rounding the weights in the output matrix. If NULL (default), weights are not rounded.
save_txt	⁠[logical(1)=FALSE]⁠ Should the ZOI matrix be saved in an external text file? If FALSE (default), the output matrix is just printed within the R session.
save_format	⁠[character(1)="GRASS_rmfilter"]{"GRASS_rmfilter", "raw"}⁠ Format in which the function should be saved. Currently, either of the two options: GRASS GIS format for the module r.mfilter (save_format = "GRASS_rmfilter"), see details here); raw matrix (save_format = "raw"), in which only the values of the matrix are printed.
save_folder	⁠[character(1)=NULL]⁠ Path to the folder where the matrix file should be written. If NULL, the current working directory is used.
save_file	⁠[character(1)=NULL]⁠ Name of the output file, generally a ".txt" file. If NULL, a standard filename is created, using the type and radius. E.g. "filter_bartlett2000.txt".
parallel	⁠[logical(1)=TRUE]⁠ Whether the computation should be paralelized or not (details in the documentation of the r.mfilter module).
...	Additional parameters (none implemented).

Details

The function creates n x n ZOI or weight matrices based on functions with different shapes and parameterized with the ZOI radius, where n is the dimension of the matrix. For some functions (e.g. threshold decay, linear decay), the size of the matrix is defined by the ZOI radius, in meters, given the intended resolution (parameter r), potentially adding new lines and columns with value zero to keep n an odd number. For non-vanishing function (e.g. exponential or Gaussian decay), even though the function is parameterized with the ZOI radius the size of the matrix can go beyond this radius. In this case, the size of the matrix n is defined either by a minimum intensity function value (parameter min_intensity) or by a maximum distance for the matrix radius (parameter min_dist, which can be set to be the radius). Keeping n at a reasonable size guarantees that the neighborhood analysis using such input weight matrices is computationally feasible.

Possible future implementation: compare results with smoothie::kernel2dsmooth() and smoothie::kernel2dmeitsjer(), maybe wrap some options here.

Value

A matrix with the weight values. In the context of cumulative impact assessment, we call it a zone of influence (ZOI) matrix used to compute the cumulative zone of influence. If save_txt = TRUE, the matrix is saved in an output text file, e.g. to be used with external software.

See Also

See zoi_functions() for some ZOI function shapes and filter_save() for options to save the ZOI matrix as a text file.
See also smoothie::kernel2dmeitsjer(), terra::focalMat(), and raster::focalWeight() for other functions to create filters or weight matrices.
See r.mfilter, r.resamp.filter, and r.neighbors for GRASS GIS uses of filters in neighborhood analysis.

Examples

library(terra)

# load example - raster of tourist private cabins
f <- system.file("raster/sample_area_cabins.tif", package="oneimpact")
r <- terra::rast(f)
# terra::ext(r)[1:2] %>% diff

# set value zero where there are no cabins
r[is.na(r)] <- 0

# create exponential filter
filt_exp1000 <- filter_create(r, radius = 1000,
                              zoi_limit = 0.01,
                              type = "exp_decay",
                              max_dist = 5000,
                              normalize = T)
filt_exp3000 <- filter_create(r, radius = 3000,
                              zoi_limit = 0.01,
                              type = "exp_decay",
                              max_dist = 5000,
                              normalize = T)
# use exponential filter
neigh_r_exp1000 <- terra::focal(r, filt_exp1000, fun = "sum",
                                na.policy = "omit", na.rm = TRUE)
neigh_r_exp3000 <- terra::focal(r, filt_exp3000, fun = "sum",
                                na.policy = "omit", na.rm = TRUE)

# plot
plot(c(r, neigh_r_exp1000, neigh_r_exp3000),
     main = c("original", "exp filter 1000m", "exp filter 3000m"))

# create step filter
filt_step3000 <- filter_create(r, radius = 3000, type = "step",
                               normalize = T)
# use step filter
neigh_r_step3000 <- terra::focal(r, filt_step3000, fun = "sum",
                                 na.policy = "omit", na.rm = TRUE)

# plot
plot(c(neigh_r_exp3000, neigh_r_step3000),
     main = c("exp filter 3000m", "step filter 3000m"))
# plot(app(c(neigh_r_exp3000, neigh_r_step3000), "diff"))

# create bartlett (linear/tent decay) filter
filt_bart3000 <- filter_create(r, radius = 3000, type = "bartlett",
                               normalize = T)
# use bartlett filter
neigh_r_bart3000 <- terra::focal(r, filt_bart3000, fun = "sum",
                                 na.policy = "omit", na.rm = TRUE)

# create Gaussian filter - parameterized with zoi
filt_gauss3000 <- filter_create(r, radius = 3000,
                                type = "Gauss",
                                zoi_limit = 0.01,
                                normalize = T)
# use Gaussian filter
neigh_r_gauss3000 <- terra::focal(r, filt_gauss3000, fun = "sum",
                                  na.policy = "omit", na.rm = TRUE)

# plot
plot(c(neigh_r_exp3000, neigh_r_step3000, neigh_r_bart3000, neigh_r_gauss3000),
     main = c("exp filter 3000m", "step filter 3000m",
              "Bartlett filter 3000m", "Gaussian filter 3000m"))
# plot(app(c(neigh_r_exp3000, neigh_r_bart3000), "diff"))
# plot(app(c(neigh_r_step3000, neigh_r_bart3000), "diff"))

# Not run
# save outside R for use in GRASS GIS
## Not run: 
  filter_create(r, radius = 1000,
                type = "bartlett",
                max_dist = 5000,
                normalize = T, save_txt = TRUE)

## End(Not run)

NINAnor/oneimpact documentation built on June 14, 2025, 12:27 a.m.