I-MAESTRO data: 42 million trees from three large European landscapes in France, Poland and Slovenia (Q10538)

Here we present three datasets describing three large European landscapes in France (Bauges Geopark -89,000ha), Poland (Milicz forest district -21,000ha) and Slovenia (Snežnik forest - 4,700ha) down to the tree level. Individual trees were generated combining inventory plot data, vegetation maps and Airborne Laser Scanning (ALS) data. Together, these landscapes (hereafter virtual landscapes) cover more than 100,000ha including about 64,000ha of forest and consist of more than 42 million trees of 51 different species.For each virtual landscape we provide a table (in .csv format) with the following columns:- cellID25: the unique ID of each 25x25 m²cell- sp: species latin names- n: number of trees.n is an integer = 1, meaning that a specific set of species "sp", diameter "dbh" and height "h" can be present multiple times in a cell.- dbh: tree diameter at breast height (cm)- h: tree height (m)We also provide, for each virtual landscape, a raster (in .asc format) with the cell IDs (cellID25) which makes data spatialisation possible. The coordinate reference systems are EPSG: 2154 for the Bauges, EPSG: 2180 for Milicz, and EPSG: 3912 for Sneznik.The v2.0.0 presents the algorithm in its final state.Finally, we provide a proof of how our algorithmmakes it possible to reach the total BA and the BA proportion of broadleaf trees provided by the ALS mapping using the alpha correction coefficient and how itmaintains the Dg ratios observed on the field plots between the different species(see algorithm presented in theassociated Open Research Europearticle).Below is an example of R code that opens the datasets and creates a tree density map.------------------------------------------------------------# load packagelibrary(terra)library(dplyr)# set work directorysetwd() # define path to the I-MAESTRO_datafolder# load tree datatree - read.csv2('./sneznik/sneznik_trees.csv', sep = ',')# load spatial datacellID - rast('./sneznik/sneznik_cellID25.asc')# set coordinate reference system# Bauges:# crs(cellID) - "epsg:2154"# Milicz:# crs(cellID) - "epsg:2180"# Sneznik:# crs(cellID) - "epsg:3912"# convert raster into dataframecellIDdf - as.data.frame(cellID)colnames(cellIDdf) - 'cellID25'# calculate tree density from tree dataframedens - tree %% group_by(cellID25) %% summarise(n = sum(n))# merge the two dataframesdens - left_join(cellIDdf, dens, join_by(cellID25))# add density to rastercellID$dens - dens$n# plot density mapplot(cellID$dens)