Data-driven tree allometry of a planted forest in New Zealand, using machine learning and airborne lidar
Author:
Affiliation:
1. University of Canterbury,Waterways Centre for Freshwater Management,Christchurch,New Zealand
2. Vadis Geomatics,Christchurch,New Zealand
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10543250/10544374/10544786.pdf?arnumber=10544786
Reference13 articles.
1. Extraction of individual trees based on Canopy Height Model to monitor the state of the forest
2. Mapping urban forest leaf area index with airborne lidar using penetration metrics and allometry
3. Airborne LiDAR Remote Sensing for Individual Tree Forest Inventory Using Trunk Detection-Aided Mean Shift Clustering Techniques
4. LIDAR-Based Forest Biomass Remote Sensing: A Review of Metrics, Methods, and Assessment Criteria for the Selection of Allometric Equations;Borsah;Forests,2023
5. A fine-scale model for area-based predictions of tree-size-related attributes derived from LiDAR canopy heights
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