deforestable: Classify RGB Images into Forest or Non-Forest
Implements two out-of box classifiers presented in <doi:10.1002/env.2848> for distinguishing forest and non-forest terrain images. Under these algorithms, there are frequentist approaches: one parametric, using stable distributions, and another one- non-parametric, using the squared Mahalanobis distance. The package also contains functions for data handling and building of new classifiers as well as some test data set.
| Version: | 3.1.2 |
| Depends: | R (≥ 4.1.0) |
| Imports: | terra,jpeg,plyr,StableEstim,Rcpp (≥ 1.0.9) |
| LinkingTo: | Rcpp,RcppArmadillo |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2025-10-19 |
| DOI: | 10.32614/CRAN.package.deforestable |
| Author: | Jesper Muren [aut], Dmitry Otryakhin [aut, cre] |
| Maintainer: | Dmitry Otryakhin <d.otryakhin.acad at protonmail.ch> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| SystemRequirements: | GDAL (>= 2.2.3), GEOS (>= 3.4.0), PROJ (>= 4.9.3),sqlite3 |
| Citation: | deforestable citation info |
| CRAN checks: | deforestable results |
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