How can DeepTrees improve biodiversity monitoring?
What role does machine learning play in automating urban forestry management?
How does DeepTrees contribute global conservation efforts?
The DeepTrees Symposium will focus on cutting-edge advancements in machine learning and computer vision for tree monitoring, particularly leveraging deep learning models for automated tree inventorying from orthoimages, focusing on the Digital Orthophotos (DOP) aerial imaging program of various federal states in Germany. Tree monitoring is essential for urban planning, environmental conservation, and forestry management. The symposium will highlight the project’s goals, including standardized workflows for tree crown detection, analysis of tree allometry and classes, and the creation of a database to support local environmental monitoring efforts in the Federal States of Saxony and Saxony-Anhalt in Germany. The symposium will bring together experts from various fields to discuss DeepTrees updates, community results, and future use cases for the system in biodiversity assessment, urban forest management, and ecosystem services modeling.
