deforestable: Classify RGB Images into Forest or Non-Forest

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

Documentation:

Reference manual:

deforestable.pdf

Downloads:

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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