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SurfRough  

Calculate Surface/Image Texture Indexes
View on CRAN: Click here


Download and install SurfRough package within the R console
Install from CRAN:
install.packages("SurfRough")

Install from Github:
library("remotes")
install_github("cran/SurfRough")

Install by package version:
library("remotes")
install_version("SurfRough", "0.0.1.0")



Attach the package and use:
library("SurfRough")
Maintained by
Sebastiano Trevisani
[Scholar Profile | Author Map]
First Published: 2024-08-30
Latest Update: 2024-08-30
Description:
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.
How to cite:
Sebastiano Trevisani (2024). SurfRough: Calculate Surface/Image Texture Indexes. R package version 0.0.1.0, https://cran.r-project.org/web/packages/SurfRough. Accessed 20 Feb. 2025.
Previous versions and publish date:
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Complete documentation for SurfRough
Functions, R codes and Examples using the SurfRough R package
Full SurfRough package functions and examples
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