"Forest is the largest terrestrial ecosystem in the European Union (EU) covering around 40% of its areal territory. Forests provide economical, ecological and social benefits to humans, such as timber, biofuel, climate regulation, water supply and regulation, air purification, erosion control, habitats for biodiversity, and many others. EU forests account for 1) € 2 trillion in annual turnover and more than 22 million jobs in bioeconomy; 2) 10% of the global’s annual carbon sinks; and 3) is a home to a significant amount of the bloc’s terrestrial biodiversity. Increasing causes of forest damages include forest fires and insects, often in combination with or intensified by abiotic stresses such as drought or storm. Tree species information is not accurate enough and is highly needed in any commercial use of the forest resources.
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 research studies complemented with other data sources to support future laser scanning programs taking place all around Europe.
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, tree species, and forest fire risk.
The possible outcomes of the project, when all results are put into practise after consecutive applied projects, includes: tree species information at individual tree level advancing European forest industry with 1B€ with better decisions; early warning system for bark beetle infestation affecting already today 20-50% of the total harvested timber in central Europe and for forest fire risk management. The innovative prediction framework allows the assessing of bark beetle infestation hazard on forest stand level. Early warning systems and better decision systems as a result of our studies are needed in all of these three case areas.
We have complementary consortium lead by PI who’s background is fully aligned with the call: his best papers (H-index 68) are on using novel computational methods on new remote sensed/environmental 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 national mapping and forest inventories). PI's selected references in scientific coordination include leading of Centre of Excellence in Laser Scanning Research (funded by Academy of Finland), 30 years experience in research team leadership, 20 years as head of department (managing 40+ researchers), and coordination of 10+ international science projects.
We will develop computation methods for very innovative data leading to better prediction and decisions. Our track record and previous publications support our role in this research area. Our results can be used in early warning systems supporting near-real-time or real-time processing. In international collaboration and co-creation we have collaboration with several universities and SMEs. Our results can lead to standards in the industry leading to global adaptation of the methods. We provide novel and ambitiously improved methods for environmental modelling, including whole systems approaches. We have a partner from widening countries. We have young researchers, high-tech SMEs and first-time participants involved. We publish in Gold Open Access way, and we have been recently rewarded from Open Science (first National Open Science reward in Finland)."
Start date: (36 months)
Funding support: 958 509 €