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rassta  

Raster-Based Spatial Stratification Algorithms
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("rassta", "1.0.5")



Attach the package and use:
library("rassta")
Maintained by
Bryan A. Fuentes
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-09-22
Latest Update: 2022-08-30
Description:
Algorithms for the spatial stratification of landscapes, sampling and modeling of spatially-varying phenomena. These algorithms offer a simple framework for the stratification of geographic space based on raster layers representing landscape factors and/or factor scales. The stratification process follows a hierarchical approach, which is based on first level units (i.e., classification units) and second-level units (i.e., stratification units). Nonparametric techniques allow to measure the correspondence between the geographic space and the landscape configuration represented by the units. These correspondence metrics are useful to define sampling schemes and to model the spatial variability of environmental phenomena. The theoretical background of the algorithms and code examples are presented in Fuentes, Dorantes, and Tipton (2021). <doi:10.31223/X50S57>.
How to cite:
Bryan A. Fuentes (2021). rassta: Raster-Based Spatial Stratification Algorithms. R package version 1.0.5, https://cran.r-project.org/web/packages/rassta
Previous versions and publish date:
1.0.0 (2021-09-22 17:00), 1.0.1 (2021-10-14 11:40), 1.0.2 (2021-12-09 10:30), 1.0.3 (2022-02-25 08:50), 1.0.4 (2022-07-25 15:30)
Other packages that cited rassta R package
View rassta citation profile
Other R packages that rassta depends, imports, suggests or enhances
Functions, R codes and Examples using the rassta R package
Some associated functions: dummies . engine . figure . locations . observation . plot3D . predict_functions . select_functions . signature . similarity . som_gap . som_pam . strata . 
Some associated R codes: Full rassta package functions and examples
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