A4 Conference proceedings

Estimation and Comparison of Tree Attributes in Young Forest Using Different Remote Sensing: Drone LiDAR, Aerial Photogrammetry, and Open Forest Data.

Open Access publication

Publication Details
Authors: Gyawali Arun, Aalto Mika, Ranta Tapio, Peuhkurinen Jussi, Villikka Maria
Publication year: 2021
Language: English
Title of parent publication: European biomass conference and exhibition
ISBN: 978-88-89407-21-9
ISSN: 2282-5819
JUFO level of this publication: 0
Permanent website address: https://www.eubce.com/
Open Access: Open Access publication
Location of the parallel saved publication: http://www.etaflorence.it/proceedings/?detail=19014


The biomass stored in young forests has enormous potential of energy to reduce fossils fuel consumption in Finland. Nowadays, accurate measurement and providing 3D information of the tree at a low cost is necessary to manage the growth and yield of the forest. Remote Sensing (RS) methods can replace the efficiency of traditional field-based forest inventory methods. The RS method using Unmanned Aerial Vehicle (UAV) Light Detection and Ranging (LiDAR) and Digital Aerial Photogrammetry (DAP) is now increasingly popular in forest inventory. This study utilized both individual tree detection method LiDAR and DAP and area-based approach (ABA) open forest data (OFD)from the Finnish forest centre to estimate tree attributes in the young forest. The result shows a strong correlation between LiDAR and DAP; both have a reasonable correlation with OFD. UAV DAP or area-based approach OFD could be the best alternative to UAV LiDAR considering cost-effectiveness in forest inventory. However, further study in the more significant and larger area should be further investigated to select the best options in forest inventory.

Research Areas

Last updated on 2021-21-07 at 14:47