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).
- Version1.0.6
- R versionunknown
- LicenseAGPL (≥ 3)
- Needs compilation?No
- rassta citation info
- Last release08/19/2024
Documentation
- VignetteClassification Units
- Vignettesource
- VignetteR code
- VignettePredictive Modeling Engine
- Vignettesource
- VignetteR code
- VignetteStratified Non-Probability Sampling
- Vignettesource
- VignetteR code
- VignetteSpatial Signature of Classification Units
- Vignettesource
- VignetteR code
- VignetteLandscape Similarity to Stratification Units
- Vignettesource
- VignetteR code
- VignetteStratification Units
- Vignettesource
- VignetteR code
- MaterialREADME
- MaterialNEWS
Team
Bryan A. Fuentes
Minerva J. Dorantes
John R. Tipton
Show author detailsRolesAuthorRobert J. Hijmans
Andrew G. Brown
Show author detailsRolesContributor
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- Imports17 packages
- Suggests6 packages