spatialAutoRange: Measure spatial autocorrelation in the predictor raster files

In blockCV: Spatial and Environmental Blocking for K-Fold and LOO Cross-Validation

Measure spatial autocorrelation in the predictor raster files

Description

This function is deprecated and will be removed in future updates! Please use cv_spatial_autocor instead!

Usage

spatialAutoRange(
  rasterLayer,
  sampleNumber = 5000L,
  border = NULL,
  speciesData = NULL,
  doParallel = NULL,
  nCores = NULL,
  showPlots = TRUE,
  degMetre = 111325,
  maxpixels = 1e+05,
  plotVariograms = FALSE,
  progress = TRUE
)

Arguments

rasterLayer	A raster object of covariates to find spatial autocorrelation range.
sampleNumber	Integer. The number of sample points of each raster layer to fit variogram models. It is 5000 by default, however it can be increased by user to represent their region well (relevant to the extent and resolution of rasters).
border	deprecated option!
speciesData	A spatial or sf object (optional). If provided, the sampleNumber is ignored and variograms are created based on species locations. This option is not recommended if the species data is not evenly distributed across the whole study area and/or the number of records is low.
doParallel	deprecated option!
nCores	deprecated option!
showPlots	Logical. Show final plot of spatial blocks and autocorrelation ranges.
degMetre	Numeric. The conversion rate of metres to degree. This is for constructing spatial blocks for visualisation. When the input map is in geographic coordinate system (decimal degrees), the block size is calculated based on deviding the calculated range by this value to convert to the input map's unit (by default 111325; the standard distance of a degree in metres, on the Equator).
maxpixels	Number of random pixels to select the blocks over the study area.
plotVariograms	deprecated option!
progress	Logical. Shows progress bar. It works only when doParallel = FALSE.

See Also

cv_spatial_autocor

blockCV documentation built on June 7, 2023, 5:55 p.m.