The EU LIFE Environment and Resource Efficiency project „Healthy Forest” aims to design and apply advanced methodologies to achieve a more sustainable forest management in the field of control and prevention of forest decline caused by invasive and pathogenic agents. An important step toward this objective is the development of an early detection system and monitoring of forest health in the field, in the laboratory and by remote sensing. The sub-project conducted by the Geographic Information Science (GIScience) group at the Department of Geography of the University of Jena focuses on spatial modeling of forest disease potential at the regional scale, and on the application of computational and statistical techniques to identify significant predictors of forest decline in high-dimensional hyperspectral remote-sensing data.
The integration of ground and space observations leads to a series of new downstream products (light green) that can be either directly interpreted by the user community, or ingested to a statistical system that translate these variables to a general index of change. User community needs to competently address societal challenges will already be integrated during the development of the new analytical and assessment strategies.