A Point-Based Fully Convolutional Neural Network for Airborne LiDAR Ground Point Filtering in Forested Environments

A Point-Based Fully Convolutional Neural Network for Airborne LiDAR Ground Point Filtering in Forested Environments

Airborne laser scanning (ALS) data is one of the most commonly used data for terrain products generation. Filtering ground points is a prerequisite step for ALS data processing. Traditional filtering methods mainly use handcrafted features or predefined classification rules with preprocessing/post-p...

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Bibliographic Details
Main Authors: Shichao Jin, Yanjun Su, Xiaoqian Zhao, Tianyu Hu, Qinghua Guo
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Digital terrain model (DTM)
deep learning
fully convolutional neural network (FCN)
ground filtering
light detection and ranging (LiDAR)
Online Access:https://ieeexplore.ieee.org/document/9138684/

Internet

https://ieeexplore.ieee.org/document/9138684/

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