Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning

arXiv:2312.15084v2 Announce Type: replace
Abstract: Detailed forest inventories are critical for sustainable and flexible management of forest resources, to conserve various ecosystem services. Modern airborne laser scanners deliver high-density point clouds with great potential for fine-scale forest inventory and analysis, but automatically partitioning those point clouds into meaningful entities like individual trees or tree components remains a challenge. The present study aims to fill this gap and introduces a deep learning framework, termed ForAINet, that is able to perform such …

abstract analysis and analysis arxiv automated cs.cv deep learning ecosystem inventory lidar management modern partitioning resources scale services sustainable type