Machine Learning Forest Simulator (MLFS) is the first complete data-driven forest development model, organized as R package. The main motivation behind the development was to remove the need for model parametrization and to provide easy to use and freely available tool, applicable to all forest ecosystems, from even-aged monocultures to mixed forests with diverse vertical structures. MLFS is freely available, age- and spatially-independent forest development tool. It requires data from at least two inventory periods, which is used to 1) model basal area increments (BAI), 2) update tree and crown heights in each simulation step, 3) simulate individual tree mortality, 4) ingrowth of new trees, and 5) harvesting. The main input tables consist of forest inventory plot data, and site descriptors, which are used to train specific sub-models.
You can install MLFS using:
library("devtools")
devtools::install_github("jernejjevsenak/MLFS") # current version under development
install.packages("MLFS") # from CRAN- Jernej Jevšenak