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:
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