The major research question of the project is: How should the future high-resolution, multitemporal, multispectral laser scanning data be computationally processed to provide timely information for environmental sustainability and especially for mapping of the forest health, tree species classification, mapping of dead trees, and forest fire risk. The sub-objectives include: 1) We conduct pioneering measurements and case studies for next-generation forest data, 2) We apply novel computational methods utilizing both spectral and geometric features in point cloud analysis to improve estimation and prediction for tree species, forest health and forest risk management, 3) We take the international collaboration into account and accomplish a global benchmarking study of new computational methods, especially for tree species and dead wood, inside the project.
forest fire risk
Funding organisation or partners
Academy of Finland