Project

Unsupervised classification of LiDAR point clouds in tropical forests

Code
01SC1920
Duration
01 October 2020 → 30 September 2024
Funding
Regional and community funding: Special Research Fund
Research disciplines
  • Natural sciences
    • Remote sensing
  • Agricultural and food sciences
    • Forestry management and modelling
Keywords
Unsupervised classification tropical forest structure LiDAR
 
Project description

Recent technological advancements in LiDAR scanning allows us to study the tropical forest structure in unprecedented detail. Methods proposed to date to analyze LiDAR point clouds are mainly supervised, and hence semi-automated. In this PhD, unsupervised machine learning strategies will be developed, extracting leaf and woody components from LiDAR point clouds. This will be a big step forward for operational applications.