Vegetation layers from Copernicus Global Land Service (LAI, NDVI) and Pan-European high-resolution products (tree cover density, forest type) will be prepared for fast-track ingestion in flow models. Products will be prepared for dynamic mesoscale modeling and intermediate exploitation. Based on user requirements from WP2, new algorithms will be developed for retrieval of drag force parameters from SAR (Sentinel-1), optical data (Sentinel-2), and high-resolution digital elevation models. These will be used to generate novel data layers for ingestion into canopy-resolving flow models and validation against ground-truth data will be performed.
Task 1.1 Preparation of Copernicus vegetation layers
The archive of existing Copernicus data layers will be screened and the products categorized according to their relevance for wind energy modeling and the potential for exploitation. Products that are found suitable for fast-track exploitation will be downloaded and prepared for ingestion in flow models.
Expected outcome:
- An inventory of Copernicus products with identification of the products, which are suitable for exploitation in their original form to users in the wind energy industry.
- Copernicus vegetation layers prepared for ingestion into mesoscale models.
Task 1.2 Preparation of dynamic roughness layers
The potential for increasing the spatial and temporal coverage and resolution of land cover maps through the use of Copernicus data layers will be investigated. Dynamic roughness layers will be prepared for selected regions based on existing look-up tables linking the land cover to the aerodynamic roughness length, which is needed as input for conventional wind energy modeling.
Expected outcome:
- Method developed for dynamical roughness assessment from satellite data.
- Dynamic roughness layers prepared for mesoscale modeling
Task 1.3 Novel products for surface parameterization
A new method will be developed for retrieval of drag force parameters from SAR (Sentinel-1), optical data (Sentinel-2), and high-resolution digital elevation models. The approach will follow state-of-the-art research based on aerial lidar scans.
Expected outcome:
- Method developed for SAR-based surface parameterization.
- Novel products developed for surface parameterization at the micro-scale.
Task 1.4 Comparison with aerial scans and ground truth
At selected sites, data products generated in T1.1-T1.3 will be compared to information gathered from aerial scans, high-resolution optical imagery (Google Earth and similar), and field visits. The results will be documented.
Expected outcome:
- Comparisons of novel data layers with aerial scans and ground truth.
- Documentation of results through contribution to report on global case studies.