Advancing vegetation segmentation from ALS point clouds: From benchmarking to GreenSegNet-A

Abstract

Accurate large-scale vegetation segmentation is essential to maintain vegetation inventories, which are vital for informed ecological planning, landscape management, and long-term sustainability and liveability of the environment. Advancements in deep learning (DL) coupled with the increasing availability of airborne laser scanning (ALS) point clouds hold significant potential for detailed and large-scale vegetation segmentation. Yet, ALS-based vegetation segmentation has received limited attention, leading to ambiguity in model selection. To address this research gap, we present a comprehensive benchmarking of point-based DL models for vegetation segmentation. Seven representative DL models..