Gridded dataset of European Forest Types

The present deliverable describes the methodology used to generate gridded European forest types (EFTs) maps across Europe. The first section introduces the Forest Types (FT) classification schemes existing in Europe, highlighting their strengths and limitations. It also includes a detailed overview of the EFTs classification used for creating the EFTs map, which is the primary goal of this deliverable. The main characteristics of each EFTs category are described, including details on species composition and an overview of the environmental features based on a comprehensive literature review. In the second section, a thorough analysis of spatial datasets available at the European level, which are useful for mapping EFTs, is presented. This deliverable specifically provides an overview of the three largest datasets of "relative probability of presence (RPP) maps" of forest tree species available for Europe. This is particularly relevant because there is currently no consistent forest tree species map at the EU level, except for the High-Resolution Layer of Copernicus Land Monitoring Service's "Forest tree species." To grid the EFTs, the consortium used the dataset provided by JRC, which comprises a 39 forest tree species RPP map. The third section provides a description of available geospatial data and raster grid maps that are also useful for identifying the different EFT categories. Mapping the EFTs requires not only information on species composition but also access to environmental diversity, which can be obtained through the identified geospatial datasets. The last three sections report the methodology used to classify the EFT categories. Firstly, a description is provided on the development of eight different forest masks (i.e., braking point masks) that identify the environmental diversity necessary to differentiate the different EFT categories. These masks are developed using different spatial dataset available at EU level. Then, a detailed description of the preparation of the RPP maps for the classification of EFT categories is provided. Finally, in the last part of the deliverable, the details of the rule-based expert system algorithm developed to classify the 14 EFT categories are presented. This section provides a comprehensive explanation of the 14 rules used for classifying the EFT categories. At the end, the resulting raster grid EFTs map is provided at a resolution of 100 metres.