similarity_buffer: Gower similarity analysis

In clhs: Conditioned Latin Hypercube Sampling

Description

Calculates Gower's similarity index for every pixel within an given radius buffer of each sampling point

Usage

similarity_buffer(
  covs,
  pts,
  buffer,
  fac = NA,
  metric = "gower",
  stand = FALSE,
  ...
)

Arguments

covs	raster stack of environmental covariates
pts	sampling points, object of class SpatialPointsDataframe
buffer	Radius of the disk around each point that similarity will be calculated
fac	numeric, can be > 1, (e.g., fac = c(2,3)). Raster layer(s) which are categorical variables. Set to NA if no factor is present
metric	character string specifying the similarity metric to be used. The currently available options are "euclidean", "manhattan" and "gower" (the default). See daisy from the cluster package for more details
stand	logical flag: if TRUE, then the measurements in x are standardized before calculating the dissimilarities.
...	passed to plyr::llply

Value

a RasterStack

Author(s)

Colby Brungard

References

Brungard, C. and Johanson, J. 2015. The gate's locked! I can't get to the exact sampling spot... can I sample nearby? Pedometron, 37:8–10.

Examples

library(raster)
library(sp)

data(meuse.grid)
coordinates(meuse.grid) = ~x+y
proj4string(meuse.grid) <- CRS("+init=epsg:28992")
gridded(meuse.grid) = TRUE
ms <- stack(meuse.grid)

suppressWarnings(RNGversion("3.5.0"))
set.seed(1)
pts <- clhs(ms, size = 3, iter = 100, progress = FALSE, simple = FALSE)
gw <- similarity_buffer(ms, pts$sampled_data, buffer = 500)
plot(gw)

clhs documentation built on Oct. 14, 2021, 9:06 a.m.