The major research question of the project is: How should the future multitemporal, multispectral mobile laser scanning (MLS) 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 multispectral MLS measurements and case studies for next-generation forest data, 2) We apply novel computational methods utilizing both spectral and geometric features in MLS 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.

2021

2024