Network for novel remote sensing technologies in forest disturbance ecology - RESDiNET

The project develops cooperation between the Institute of Forest Ecology at the Slovak Academy of Sciences (IFE SAS) and high-level counterparts such as the Finnish Geospatial Research Institute, the University of Eastern Finland, and the Swedish University of Agricultural Sciences. The project will enhance IFE SAS’s leadership capacities, administrative skills, and scientific capabilities in the use of new remote sensing techniques in forest disturbance ecology.

Using new remote sensing methods, thorough analyses of severe insect damage will be conducted in test areas representing different forest types and climates: forests in the mountains of Slovakia and boreal forests in Finland and Sweden. We will integrate in situ UAV- and drone-based remote sensing data with existing multitemporal geospatial information and field data, particularly data on bark beetle population densities, visible attack symptoms associated with outbreak phases, and tree physiological parameters measured using electronic dendrometers or sap flow sensors.

The combined datasets will be used to develop new tools for identifying spruce bark beetle infestations at the landscape level and to design models for risk assessment of attacks. The project will leverage the latest advances in drone technology and image analysis techniques, including neural networks based on machine learning and artificial intelligence.

Koordinator: Institutet för Forest Ecology SAS, Zvolen, Slovakia