Artificial intelligence-based algorithms using image recognition in high-resolution drone data equipped with optical sensors, can be used today for digital and advanced forest management (e.g. in precision forestry) for monitoring individual trees. This concept is examined in this project for the use of mapping individual trees in seed orchards.

The project will use spruce seed orchards as a test site to estimate the number of spruce flowers per tree from high-resolution drone images taken with multi- and hyperspectral cameras to investigate the possibility to observe cone quality with respect to insect and/or fungal disease infestation.

Information collected at flowering time could be used to inform the planning of tree-specific management measures in seed orchards and cone collection in late autumn, especially if a a comprehensive and detailed monitoring of cone condition could be carried out before collection. Furthermore, the collection of flowering data per tree clone would allow a more accurate analysis of the genetic quality and diversity of the annual seed crop.

FLOWER is led and coordinated by the Natural Resources Institute Finland (Luke) in cooperation with Finnish Geospatial Research Institute FGI and Linnaeus University, and is a joint project between Finnish and Swedish experts in remote sensing, geospatial information, sensors and seed cultivation. The results of the project will be openly available for use by companies collecting spatial data and by companies producing forest tree seeds.