anisoRL

The input is represented by a list of rasters with the spatial variability index (e.g., MAD, variogram, etc.) computed
in four directions (N-S, NE-SW, E-W, SE-NW)

Methods for the computation of surface/image texture indices using a geostatistical based approach (Trevisani et al. (2023) <doi:10.1016/j.geomorph.2023.108838>). It provides various functions for the computation of surface texture indices (e.g., omnidirectional roughness and roughness anisotropy), including the ones based on the robust MAD estimator. The kernels included in the software permit also to calculate the surface/image texture indices directly from the input surface (i.e., without de-trending) using increments of order 2. It also provides the new radial roughness index (RRI), representing the improvement of the popular topographic roughness index (TRI). The framework can be easily extended with ad-hoc surface/image texture indices.

Sebastiano Trevisani

SurfRough

Calculate Surface/Image Texture Indexes

Ilich Alexander

anisoRL function

<dl><dt>x</dt>
<dd>A list of rasters with the spatial variability along 4 directions (see function anisoR())</dd></dl>

Arguments

Calculate the index of anisotropy considering the spatial variability along 4 directions — anisoRL

<dl>

<dt>x</dt>
<dd>A list of rasters with the spatial variability along 4 directions (see function anisoR())</dd>

</dl>

anisoRL: Calculate the index of anisotropy considering the spatial variability along 4 directions

Description

Usage

Value

Arguments