Estimating Forest Structure from UAV-Mounted LiDAR Point Cloud Using Machine Learning

Monitoring the structure of forest stands is of high importance for forest managers to help them in maintaining ecosystem services. For that purpose, Unmanned Aerial Vehicles (UAVs) open new prospects, especially in combination with Light Detection and Ranging (LiDAR) technology. Indeed, the shorter...

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Veröffentlicht in:	Remote sensing (Basel, Switzerland) Jg. 13; H. 3; S. 352 - 19
Hauptverfasser:	Neuville, Romain, Bates, Jordan Steven, Jonard, François
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	MDPI AG 20.01.2021
Schlagworte:	Accurate estimation Aircraft detection algorithms Antennas Application contexts Biologie végétale (sciences végétales, sylviculture, mycologie...) canopy Clustering algorithms Computer science data collection Density-Based Spatial Clustering Diameter-at-breast heights Earth sciences & physical geography Ecosystems Engineering, computing & technology Environmental sciences & ecology forest stands Forestry forests HDBSCAN Hierarchical clustering Ingénierie, informatique & technologie LiDAR Life sciences Light detection and ranging Machine learning Omission and commission errors Optical radar PCA Physical, chemical, mathematical & earth Sciences Physique, chimie, mathématiques & sciences de la terre Phytobiology (plant sciences, forestry, mycology...) Point cloud principal component analysis Sciences de la terre & géographie physique Sciences de l’environnement & écologie Sciences du vivant Sciences informatiques Segmentation procedure Semantics Site-specific parameters tree and stand measurements Tree diameter Tree stem segmentation trees UAV Unmanned aerial vehicles (UAV)
ISSN:	2072-4292, 2072-4292
Online-Zugang:	Volltext
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