Methodology for drone-based assessment of phenology, flowering abundance and cone yield Problem & aims Phenology variation is associated with high genetic diversity We aim to create fast drone-based monitoring of phenology variability = genetic diversity Other benefits: intermating groups, field testing or tracking illegal non local plantations with discrete phenology The same for fast cone/flower yield scoring Faculty of Forest Science and Ecology Aleksandras Stulginskis university , Lithuania Scoring phenology in a Betula bendula stand in spring 2017 at 20 m height for calibrating the camera, altitude and image resolution

Phenology scoring in a Scots pine seed orchard The on-land scoring scale female Phenology scoring in a Scots pine seed orchard 8 m 16 m 24 m In spring 2017 at 4 occasions, we scored on-land phenology of vegetative, male and female buds of 25 clones At each scoring, we flew a drone at 3 altitudinal modes to photograph these clones at variable resolution Image analysis on going Which areal mode gave the closest scores to the on land measurements?

Cone yield in mature stands of Scots pine Important for forecasting seed crops on tall trees, seed trees for natural regeneration Counting cones manually on an image segment on the crown section with the greatest cone yield In spring 2017, we flew drone over mature stands at variable H, resolution Testing image analysis: counting an 1, 2, 3 squares Image at 10 m above the crowns

Image analysis With color selection tools clicking cone/shoot/flower patches in an image and automatically assessing their % in fixed sections of the image More advanced spectral grading, estimating % of certain color groups