Open AccessDetection of trees features from a forestry area using airborne LiDAR data
Author(s) -
Ioana Vizireanu,
Andreea Calcan,
Georgiana Grigoraș,
Dan Răducanu
Publication year - 2020
Publication title -
incas buletin
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.282
H-Index - 10
eISSN - 2247-4528
pISSN - 2066-8201
DOI - 10.13111/2066-8201.2021.13.1.23
Subject(s) - lidar , remote sensing , point cloud , context (archaeology) , forest inventory , terrain , digital elevation model , canopy , vegetation (pathology) , environmental science , tree (set theory) , geography , forestry , crown (dentistry) , tree canopy , ranging , forest management , computer science , cartography , mathematics , computer vision , medicine , mathematical analysis , archaeology , dentistry , pathology , geodesy
The impact of anthropogenic actions on the environment and climate has recently increased the need to map the afforested areas. In this context, the three-dimensional (3D) measurement of vegetation structures plays an important role in having an efficient forest inventory and management. Nowadays, the airborne LiDAR (Light Detection And Ranging) system offers high horizontal resolution as well as vertical dimension information, making it possible to estimate both three-dimensional characteristics of individual trees and to identify the distribution of forest resources in the region. This study aims to present a processing approach for the determination of each tree’s position (X and Y location, as well as tree height) and its dimensions (crown diameter, area and volume) using geometrically accurate 3D point clouds (data sets were collected in a forested area in Argeș County, Romania). To a better understanding of the forest features and to explore the potential of remote sensing for such analysis, it was further exploited Digital Terrain Model (DTM), Digital Surface Model (DSM), and Canopy Height Model (CHM) derivation.