Tree species identification using deep learning

• ETH Zurich
• Forest Resources Management Other organizations: Photogrammetry and Remote Sensing (Prof. Schindler)

Tree species maps are crucial for effective forest management, biomass assessment, and biodiversity monitoring. Remote sensing products offer flexible and cost-effective ways to assess forest characteristics, while deep learning methods promise high predictive accuracy and transformative applications in forestry. This study aims to apply novel deep learning approaches to detect and identify individual trees and tree species in mixed forests. By addressing the challenges of tree species identification, this research will enhance biodiversity assessment, forest resilience understanding, and management strategies.

• Artificial Intelligence and Signal and Image Processing, Forestry Sciences, Geomatic Engineering
• ETH Zurich (ETHZ), Master Thesis