Here we present three datasets describing three large European landscapes in France (Bauges Geopark - 89,000 ha), Poland (Milicz forest district - 21,000 ha) and Slovenia (Snežnik forest - 4,700 ha) 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 100,000 ha including about 64,000 ha 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 m² cell- 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 algorithm makes 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 it maintains the Dg ratios observed on the field plots between the different species (see algorithm presented in the associated Open Research Europe article). Below is an example of R code that opens the datasets and creates a tree density map. ------------------------------------------------------------# load package library(terra) library(dplyr) # set work directory setwd() # define path to the I-MAESTRO_data folder # load tree data tree % group_by(cellID25) %>% summarise(n = sum(n)) # merge the two dataframes dens <- left_join(cellIDdf, dens, join_by(cellID25)) # add density to raster cellID$dens <- dens$n # plot density map plot(cellID$dens)

This work was carried out within the framework of the I-Maestro project, supported under the umbrella of ERA-NET Cofund ForestValue by ADEME (FR), FNR (DE), MIZS (SI), NCN (PL). ForestValue has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement n°773324. This work was also supported by the GRAINE program of ADEME (FR) in the framework of the PROTEST project (convention n°1703C0069).