Automated depth correction of bathymetric LiDAR point clouds using PointCNN semantic segmentation

Automated depth correction of bathymetric LiDAR point clouds using PointCNN semantic segmentation

The study explores deep learning to perform direct semantic segmentation of bathymetric lidar points to improve bathymetry mapping. Focusing on river bathymetry, the goal is to accurately and simultaneously classify points on the benthic layer, water surface, and ground near riverbanks. These classi...

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Bibliographic Details
Main Authors: Ovi Paul, Nima Ekhtari, Craig L. Glennie
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Remote Sensing
Subjects:
bathymetric lidar
deep learning
3D convolutional neural network
graph neural network
semantic segmentation
PointCNN
Online Access:https://www.frontiersin.org/articles/10.3389/frsen.2025.1521446/full
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