A4 Conference proceedings

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


Publication Details
Authors: Gyawali Arun, Peuhkurinen Jussi, Villikka Maria, Aalto Mika, Ranta Tapio
Publication year: 2021
Language: English
Related journal or series: European Biomass Conference And Exhibition
Title of parent publication: 29th European Biomass Conference and Exhibition
Start page: 310
End page: 314
Number of pages: 5
ISBN: 978-88-89407-21-9
eISSN: 2282-5819
JUFO level of this publication: 0
Open Access: Not an Open Access publication

Abstract

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 2021-29-07 at 10:08