Meanscan: Calculate less robust geostatistical indexes (mean of...

In SurfRough: Calculate Surface/Image Texture Indexes

Calculate less robust geostatistical indexes (mean of absolute differences raised to an exponent)

Description

With this you can compute variogram and madogram (but remember that for classical geostatistical indexes you need to divide the derived isotropic index by 2!). Moreover you can calibrate the exponent in order to filter or enhance hotspots and discontinuities

Usage

Meanscan(inRaster, kernels, w, exponent)

Arguments

inRaster	The DEM/residual-dem from which to compute the indexes
kernels	The kernels to be used for computing the directional differences (e.g. order 1 or 2 for various lags)
w	The moving window adopted for computing the geostatistical index (i.e., MAD)
exponent	The exponent: increasing the exponent increase the sensitivity to outliers. Set 2 for Variogram and 1 for Madogram.

Value

A SpatRaster with 3 layers: 1)isotropic roughness; 2) direction of anisotropy; 3)index of anisotropy.

Examples

#' Variogram-like for lag 2 with differences of order 2 using a circular search window of radius 3.
# Using differences of order 1, you should
# apply these on a detrended surface/image.
library(terra)
dem=rast(paste(system.file("extdata", package = "SurfRough"), "/trento1.tif",sep=""))
w=KernelCircular(3)
rough2c=Meanscan(dem,k2ck2, w,2)
#(divide by two if you need classical estimator)
plot(rough2c$IsoRough)

SurfRough documentation built on April 4, 2025, 2:19 a.m.