Abstract

The patterns of plant species distribution determine the functioning of ecosystems across a wide range of temporal and spatial scales, from biogeochemical cycles and partitioning of the energy budget, to changes in biodiversity, habitat characteristics, and trophic structures. To predict and to maintain functionality and ecosystem services, it is important to know the spatial distribution of plant species and habitat characteristics. This project’s scope is to demonstrate that by integrating taxonomical and spectral field surveys with LIDAR (Light Detection and Ranging) and with very high resolution multispectral satellite imagery (VHR), the important vegetation properties (dominant plant species cover, biomass, litter, bare soil) can be quickly and accurately evaluated, an approach with high potential of application to environmental monitoring and bioeconomy. Subsequently, the relationship between spectral diversity, habitat heterogeneity and plant diversity, that drive ecosystem functionality and services, may be quantitatively measured and employed for decision support systems. The operational model will integrate multi-sensor data (field, airborne, spaceborne) and allow the transfer of the method to end-users (scientists, forest managers, policy and decision makers) as well as ensure repeatability. To meet these requirements, we will develop a geodatabase for each tree and dominant grassland species including spectral, LIDAR-derived traits and test sites-specific attributes. The demonstration model will reveal the workflow and parameters required for rapid and accurate vegetation evaluation and indicate which spectral/spatial features and data combinations give the best results.