The world’s forests are affected by ongoing climate change and new research is needed in remote sensing with the aim of increasing knowledge about the state and change of the forest. In order to meet this challenge, it is necessary to collect different types of remote sensing data (optical, laser, and radar data) from different platforms (towers, drones, aircrafts, and satellites) to be used in combination with field data (reference data, e.g. data from harvesters) for modelling both traditional and new forest variables. In a changing climate, biotic and abiotic forest damage is also expected to increase, which makes it desirable to intensify remote sensing research within this area as well. This post-doctoral project aims to meet these challenges by developing new tools for the next generation of digital and dynamic forest maps as a basis for forest planning and to the benefit of forest management. Particular focus is on developing new and improved estimates of forest variables (state and changes), as well as mapping and forecasting forest damage. A large part of the research data will be collected via drone flights over forested experimental test sites. The project is also expected to generate valuable results of great benefit to future digital and dynamic forest management plans.
The project is connected to Horizon 2020 project ForestMap, which aims to produce the next generation of forest maps with AI and to the research program FRAS II (Future Forest Management in Southern Sweden), which is run jointly by Linnaeus University, Skogforsk, and the Swedish University of Agricultural Sciences in close cooperation with the forestry sector in southern Sweden.