Mapping of forest health, species and forest risks using Novel ICT Data and Approaches

Wider research context: Forests have high economic and ecological importance. Increasing causes of forest damages are forest fires and insects (bark beetles in particular), often in combination with or intensified by abiotic stresses such as drought or storm. Tree species information is not accurate enough and is needed in any commercial use of the forest resources. Research objectives: The major research question of the project is: How should the future multitemporal, multispectral laser scanning data be processed in order to provide information for environmental sustainability and especially for mapping of the forest health (e.g. bark beetle risk assessment), tree species, and forest fire risk. Approach: What is common to mapping of forest health, tree species, and forest fire risk, is that they are correlated to moisture of canopies. On the other hand, lidar backscatter is strongly dependent on the moisture and recent studies indicate that it can be derived using e.g. bispectral airborne lidar. Collection of such data is possible even at country level at a few years interval. FGI has the world-first multispectral, mobile laser scanner that can be used for such studies complemented with other data sources to support future scanning programs taking all around Europe. Level of innovation: We develop computation methods for very innovative data leading to better prediction and decisions. Our results can be used in early warning systems supporting near-real-time or real-time processing. The possible outcomes of the project, when all results put into practise after consecutive applied projects includes: tree species information at individual tree level advancing European forest industry with 1B€ with better decisions; increasingly climate change is causing e.g. bark beetle infestation affection already today that 20-50% of the total harvested timber in central Europe is due to this infestation and thus, disrupt ecosystem dynamics and have significant economic consequences to the entire forest sector. The innovative prediction framework allows the assessing of bark beetle infestation hazard on forest stand level under particular consideration of drought. Additionally, forest fires are causing massive damages. Early warning systems and better decision systems as a result of our studies are needed in all these 3 areas. Primary researchers involved: We have a complementary consortium led by the PI, Juha Hyyppä of Finnish Geospatial Research Institute (FGI), whose background is fully aligned with the call: his best papers (H-index 68) are on using novel computational methods on new data that have initiated large impact already on Scandinavian economies (about 50M€ annual impact from national laser scanning of Finland, Sweden and Estonia used for mapping and forest inventories). PIs of the consortium have expertise in forest entomology and forest pest risk assessment (Sigrid Netherer, BOKU Wien), laser scanning change detection-based forest inventories (Markus Hollaus, TU Wien; Peter Surový, University of Life Sciences Prague; José A. Gonçalves, University of Porto), and mobile Lidar research (Juha Hyyppä, FGI; Pedro Arias-Sanchez, University of Vigo). Co-PIs at FGI are Prof. Harri Kaartinen, Prof. Dr. Antero Kukko, Xiaowei Yu, Yunsheng Wang, and Markus Holopainen.