envimetR is a collection of scripts supporting the generation of Envimet model domains and meaningful simple plant types with a focus on typical managed low mountain forests.
The aim is to derive area-wide input data for a reproducible and sufficiently realistic model domain from RGB aerial LiDAR or UAV point clouds and satellite data. This includes the following
- land use and vegetation area data
- derivation of tree types to generate Envimet compliant simple plant types
- export of the necessary vector and plant database data in an EnviMet compliant format.
The following analyses are performed:
- ML-based classification of RGB aerial imagery to determine tree types.
- Segmentation of trees based on the Lidar/UAV point clouds.
- Derivation of LAD classes from the lidar data.
- Calculate and extract the corresponding LAI data from the sentinel data.
- Calculation of albedo from sentinel data
- Typification using an extended cluster analysis of typical tree classes based on all available data to generate hybrid (or synthetic) tree types for EnviMet modelling purposes.
- Envimet-compliant export of synthetic EnviMEt tree classes