FOR-Age: AI and 3D LiDAR open a new frontier for non-destructive tree age estimation
Estimating the age of a tree has long required invasive and labor-intensive methods such as dendrochronological coring. Despite decades of forestry research, determining tree age accurately and at scale remains […]
Paper: Towards precision forestry: A systematic review of optimisation methods for individual-tree decisions in forest management
Niál Perry, Janine Schweier, Leo Gallus Bont, Sunni Kanta Prasad Kushwaha, Heli Peltola, Kyle Eyvindson, Rasmus Astrup, Melissa Chapman, Clemens Blattert,Towards precision forestry: A systematic review of optimisation methods for […]
Paper: FOR-age: Benchmarking individual tree age estimation using 3D deep learning on dense laser scanning data
Stefano Puliti, Binbin Xiang, Maciej Wielgosz, Eivind Handegard, Nicolas Cattaneo, Marta Vergarechea, Terje Gobakken, Juha Hyyppä, Erik Næsset, Mikko Vastaranta, Tuomas Yrttimaa, Rasmus Astrup,FOR-age: Benchmarking individual tree age estimation using […]
Deliverable 6.2: Report on description of first communication activities
Deliverable 4.1: Methodology for single tree traceability
Deliverable 2.1: Criteria for adaptive single tree level management
SCA & Living Lab North: SingleTree Innovation in Action
SingleTree Progress and Outlook: Building a Strong Foundation for Impact
The SingleTree project has reached an important milestone, closing its first 18-month reporting period within the broader four-year initiative running from 1 September 2024 to 31 August 2028. These opening […]