c(person("Marco", "Sciaini", email = "sciaini.marco@gmail.com", role = c("aut", "cre")),
person("Matthias", "Fritsch", email = "matthias.fritsch@forst.uni-goettingen.de", role =  c("aut")),
person("Craig", "Simpkins", email = "simpkinscraig063@gmail.com", role =  c("aut")),
person("Cédric", "Scherer", email = "cedricphilippscherer@gmail.com", role =  c("ctb"), comment = "Implemented nlm_neigh"))
Provides neutral landscape models
(Gardner et al. 1987 <doi:10.1007/BF02275262>,
With 1997 <doi:10.1046/j.1523-1739.1997.96210.x>) that can easily extend in
existing landscape analyses. Neutral landscape models range from "hard"
neutral models (completely random distributed), to "soft" neutral models (definable spatial characteristics) and
generate landscape patterns that are independent of ecological processes.
Thus, these patterns can be used as null models in landscape ecology. 'NLMR'
combines a large number of algorithms from other published software for simulating neutral landscapes (Saura &
Martínez 2000   <doi:10.1023/A:1008107902848>, Etherington et
al. 2015 <doi:10.1111/2041-210X.12308>) and
includes utility functions to classify and combine the multiple landscapes. The
simulation results are obtained in a geospatial data format (raster* objects
from the 'raster' package) and can, therefore, be used
in any sort of raster data operation that is performed with standard
observation data.
checkmate, dismo, dplyr, ggplot2, igraph, magrittr, purrr,
RandomFields, raster, rasterVis, sp, spatstat, stats, tibble,
tidyr, viridis, extrafont
Marco Sciaini [aut, cre],
Matthias Fritsch [aut],
Craig Simpkins [aut],
Cédric Scherer [ctb] (Implemented nlm_neigh)

checkmate, dismo, dplyr, ggplot2, igraph, magrittr, purrr,
RandomFields, raster, rasterVis, sp, spatstat, stats, tibble,
viridis, extrafont

c(person("Marco", "Sciaini", email = "sciaini.marco@gmail.com", role = c("aut", "cre"), comment = c(ORCID = '0000-0002-3042-5435')),
person("Matthias", "Fritsch", email = "matthias.fritsch@forst.uni-goettingen.de", role = "aut"),
person("Craig", "Simpkins", email = "simpkinscraig063@gmail.com",
role =  "aut", comment = c(ORCID = '0000-0003-3212-1379')),
person("Cédric", "Scherer", email = "cedricphilippscherer@gmail.com",
role =  c("aut"), comment = c(ORCID = '0000-0003-0465-2543')),
person("Laura", "Graham", role = "rev",
comment = "Laura reviewed the package for rOpenSci, see
https://github.com/ropensci/onboarding/issues/188"),
person("Jeffrey", "Hollister", role = "rev",
comment = "Jeffrey reviewed the package for rOpenSci, see
https://github.com/ropensci/onboarding/issues/188"))
Provides neutral landscape models (<doi:10.1007/BF02275262>,
<http://sci-hub.tw/10.1007/bf02275262>).
Neutral landscape models range from "hard"
neutral models (completely random distributed), to "soft" neutral models
(definable spatial characteristics) and generate landscape patterns that are
independent of ecological processes.
Thus, these patterns can be used as null models in landscape ecology. 'nlmr'
combines a large number of algorithms from other published software for
simulating neutral landscapes. The simulation results are obtained in a
geospatial data format (raster* objects from the 'raster' package) and can,
therefore, be used in any sort of raster data operation that is performed
with standard observation data.
checkmate, dplyr, purrr, RandomFields, raster, spatstat,
stats, tibble, fasterize, sf
testthat, covr, knitr, rmarkdown, lintr, classInt, rasterVis
Marco Sciaini [aut, cre] (<https://orcid.org/0000-0002-3042-5435>),
Matthias Fritsch [aut],
Craig Simpkins [aut] (<https://orcid.org/0000-0003-3212-1379>),
Cédric Scherer [aut] (<https://orcid.org/0000-0003-0465-2543>),
Laura Graham [rev] (Laura reviewed the package for rOpenSci, see
https://github.com/ropensci/onboarding/issues/188),
Jeffrey Hollister [rev] (Jeffrey reviewed the package for rOpenSci, see
https://github.com/ropensci/onboarding/issues/188)