fd_hvar {habtools}

Calculate fractal Dimension using the height variation method

Description

Calculate fractal Dimension using the height variation method

Usage

fd_hvar(
  data,
  lvec,
  regmethod = "mean",
  keep_data = FALSE,
  plot = FALSE,
  parallel = FALSE,
  ncores = (parallel::detectCores() - 1)
)

Arguments

data

Digital elevation model of class RasterLayer or dataframe (output of hvar function)

lvec

Vector of scales to use for calculation.

regmethod

Method to use for linear regression between scale (lvec) and height range. One of raw (all data), mean (default) median or ends (minimum and maximum scale only)

keep_data

Keep the data used for fd calculation? defaults to FALSE

plot

Logical. Show plot of scales relative to data?

parallel

Logical. Use parallel processing? Note: parallel must be installed.

ncores

Number of cores to use when parallel = TRUE.

Details

Calculates fractal dimension using the height variation regression. If lvec is not specified, a default based on resolution and extent will be used. data can be a DEM or a data.frame with columns labeled l and h for grid cell length and height range of that cell, respectively (output of hvar()). A rule of thumb is that l should range an order of magnitude. However, large ranges also average-out fractal dimension of a surface that might have phase transitions, and therefore a thorough exploration of height ranges is suggested using the plot. regmethod specifies whether data is summarized by taking the mean or median of height ranges across scales or all data is used. regmethod "raw" is not recommended because the regression will give much more weight to the lower scales that include more points and likely underestimate D.

Value

A value for fractal dimension, typically between 2 and 3 or a list if keep_data = TRUE.

Examples

dem <- habtools::dem_crop(horseshoe, x0 = -469, y0 = 1267, L = 2, plot = TRUE)
fd_hvar(dem, lvec = c(0.125, 0.25, 0.5, 1, 2))
fd_hvar(dem, regmethod = "mean", plot = TRUE, keep_data = TRUE)
fd_hvar(dem, regmethod = "median", plot = TRUE, keep_data = TRUE)
fd_hvar(dem)