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Sebastiano Trevisani July 29, 2024

SurfRough

Algorithms for surface texture (roughness) and image texture analysis using a geostatistical based approach from https://doi.org/10.1016/j.catena.2023.106927

Installation

To install this package first install the remotes package if you do not have it using the code install.packages("remotes"). Then this package can be installed from github using the code remotes::install_github("strevisani/SurfRough"). This will install SurfRough and its dependencies such as terra which is used for the handling of spatial raster data.

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Install

install.packages('SurfRough')

Monthly Downloads

401

Version

0.0.1.0

License

MIT + file LICENSE

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Maintainer

Sebastiano Trevisani

Last Published

August 30th, 2024

Functions in SurfRough (0.0.1.0)

k1c

basic kernels
k1ck2

basic kernels
k2c

basic kernels
k2ck2

basic kernels
k6c

basic kernels
k4c

basic kernels
Meanscan

Calculate less robust geostatistical indexes (mean of absolute differences raised to an exponent)
Trik2

Improved TRI (with differences of order 2), removing slope dependence.
CalcMedians

Calculate the median of absolute values found in a search window for each raster in a list
Madscan

Calculate MAD basic indexes
KernelRectangular

Build a rectangular kernel of size X x Y
CalcMeans

Calculate the mean of absolute values raised to an exponent found in a search window
RRI

RRI: Radial Roughness index
KernelCircular

Build a circular moving window
anisoDir

Calculate the direction of maximum continuity considering 4 directions
anisoDirL

Calculate the direction of maximum continuity considering 4 directions
circularDispersionGV

Compute circular variance of aspect (i.e. of the gradient vector)
circularEigenNV

Compute circular variance of normal vectors to surface
k05ck2

basic kernels
circularDispersionNV

Compute circular variance of normal vectors to surface
k8c

basic kernels
anisoR

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

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