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NLMR: Simulating Neutral Landscape Models in R

NLMR

Neutral Landscape Models with R


NLMR is an R package for simulating neutral landscape models (NLM). Designed to be a generic framework like NLMpy, it leverages the ability to simulate the most common NLM that are described in the ecological literature. NLMR exploits the advantages of the raster-package and returns all simulation as RasterLayer-objects, thus ensuring a direct compability to common GIS tasks and a pretty flexible and simple usage. Furthermore, it simulates NLMs within a self-contained, reproducible framework.


Why NLMR? … and not one of the other software tools*

  • It is so far the only library of NLM in R
    • R is the programming lingua franca for ecologists
    • Open-source + cross-platform
  • Most comprehensive collection of algorithms to simulate NLM
  • Embedded in a native GIS framework
  • Variety of utility functions (classification, merging, visualization, …)
  • Openly developed on github

Getting Started

Install the release version from CRAN:

install.packages("NLMR")

To install the developmental version of NLMR, use the following R code:

# install.packages("devtools")
devtools::install_github("marcosci/NLMR")

Documentation

Documentation is available at NLMR/reference. To get started, please explore our vignettes online, or in R:

vignette(package = "NLMR")

What’s New

We are currently on version 0.2.1. Major changes in this version are:

  • Skip one test on CRAN to keep the Roboto font available
  • Function util_facetplot to plot a list of rasters as ggplot2 facet
  • Small updates to the webpage

See our news page for a detailed changelog.


Citation

citation("NLMR")

Additionally, we keep a record of publications that useNLMR. Hence, if you used NLMR please file an issue on GitHub so we can add it to the list.


Contributor Code of Conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.


Dependencies

NLMR imports many great packages that it depends on. Many thanks to the developers of these tools:

 [1] "R (>= 3.1.0)"  " checkmate"    " dismo"        " dplyr"       
 [5] " ggplot2"      " igraph"       " magrittr"     " purrr"       
 [9] " RandomFields" " raster"       " rasterVis"    " sp"          
[13] " spatstat"     " stats"        " tibble"       " tidyr"       
[17] " viridis"      " extrafont"

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