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rassta: Raster-Based Spatial Stratification Algorithms

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 et al. (2022). <doi:10.32614/RJ-2022-036>.

Version:	1.0.6
Imports:	cluster (≥ 2.1.2),data.table (≥ 1.14.0),dplyr (≥ 1.0.7),DT (≥ 0.18),foreach (≥ 1.5.1),GGally (≥ 2.1.2),ggplot2 (≥ 3.3.5), grDevices,histogram (≥ 0.0.25),KernSmooth (≥2.23.18),kohonen (≥ 3.0.10),plotly (≥ 4.9.4.1),rlang (≥0.4.11),scales (≥ 1.1.1),shiny (≥ 1.6.0), stats,stringdist (≥ 0.9.6.3),stringi (≥ 1.7.2),terra (≥ 1.3.4), utils
Suggests:	testthat (≥ 3.0.0),tinytest (≥ 1.3.1),doParallel (≥1.0.16),mgcv (≥ 1.8.40),knitr,rmarkdown
Published:	2024-08-19
DOI:	10.32614/CRAN.package.rassta
Author:	Bryan A. Fuentes [aut, cre], Minerva J. Dorantes [aut], John R. Tipton [aut], Robert J. Hijmans [ctb], Andrew G. Brown [ctb]
Maintainer:	Bryan A. Fuentes <bryandrep at gmail.com>
BugReports:	https://github.com/bafuentes/rassta/issues/
License:	AGPL (≥ 3)
URL:	https://bafuentes.github.io/rassta/
NeedsCompilation:	no
Citation:	rassta citation info
Materials:	README,NEWS
CRAN checks:	rassta results

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