3D Reconstruction and machine learning assisted Ecological Analysis of LiDAR Forest Point Clouds in Sweden

Abstract

Airborne Laser Scanning (ALS) enables high-resolution 3D reconstruction of forest structures, which supports assessments of biodiversity. Standing or lying dead trees provide habitats for fungi, invertebrates, and birds. Forest structure influences biodiversity, and ALS-based machine learning models may effectively analyze habitat complexity, species distribution, and ecological connectivity for conservation.

Keywords

3D Forest Reconstruction; LiDAR Point Clouds; Biodiversity Assessment; Machine Learning in Forestry; Habitat Structure Analysis

Published in

Publisher: Silvilaser

Conference

SilviLaser 2025, September 29 - October 3, 2025, Québec City, Quebec, Canada

SLU Authors

• Martins, José

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    

• Lindberg, Eva

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    

• Sjögren, Jörgen

  • Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences
    

• Parry, Jacob

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    

• Persson, Henrik

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Forest Science
Earth Observation

Permanent link to this page (URI)

https://res.slu.se/id/publ/145009