Forest understory trees can be segmented accurately within sufficiently dense airborne laser scanning point clouds
Abstract Airborne laser scanning (LiDAR) point clouds over large forested areas can be processed to segment individual trees and subsequently extract tree-level information. Existing segmentation procedures typically detect more than 90% of overstory trees, yet they barely detect 60% of understory t...
Enregistré dans:
Auteurs principaux: | Hamid Hamraz, Marco A. Contreras, Jun Zhang |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2017
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/94cf7ffc6e48403f9ce1178f103a7b24 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Research on the improvement of single tree segmentation algorithm based on airborne LiDAR point cloud
par: Chen Qiuji, et autres
Publié: (2021) -
Harnessing terrestrial laser scanning to predict understory biomass in temperate mixed forests
par: Shun Li, et autres
Publié: (2021) -
Structural Wall Facade Reconstruction of Scanned Scene in Point Clouds
par: NING, X., et autres
Publié: (2021) -
Possibilities to determine biometric parameters using airborne laser scanning data
par: Polyakova Mariya, et autres
Publié: (2021) -
A Post-Scan Point Cloud Colorization Method for Cultural Heritage Documentation
par: Ting On Chan, et autres
Publié: (2021)