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Implements two out-of box classifiers presented in <doi:10.48550/arXiv.2112.01063> 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: | 3.1.1 |
Depends: | R (≥ 4.1.0) |
Imports: | terra, jpeg, plyr, StableEstim, Rcpp (≥ 1.0.9) |
LinkingTo: | Rcpp, RcppArmadillo |
Suggests: | testthat (≥ 3.0.0) |
Published: | 2022-10-15 |
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: | C++11, GDAL (>= 2.2.3), GEOS (>= 3.4.0), PROJ (>= 4.9.3), sqlite3 |
CRAN checks: | deforestable results |
Reference manual: | deforestable.pdf |
Package source: | deforestable_3.1.1.tar.gz |
Windows binaries: | r-devel: deforestable_3.1.1.zip, r-release: deforestable_3.1.1.zip, r-oldrel: deforestable_3.1.1.zip |
macOS binaries: | r-release (arm64): deforestable_3.1.1.tgz, r-oldrel (arm64): deforestable_3.1.1.tgz, r-release (x86_64): deforestable_3.1.1.tgz, r-oldrel (x86_64): deforestable_3.1.1.tgz |
Old sources: | deforestable archive |
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