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rassta

Raster-Based Spatial Stratification Algorithms

v1.0.6 · Aug 18, 2024 · AGPL (>= 3)

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

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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Dependency Network

Dependencies Reverse dependencies cluster data.table dplyr DT foreach GGally ggplot2 histogram KernSmooth (>= 2.23.18) kohonen plotly rlang (>= 0.4.11) scales shiny stringdist +2 more dependencies rassta

Version History

new 1.0.6 Mar 9, 2026