Issue |
BIO Web Conf.
Volume 80, 2023
4th International Conference on Smart and Innovative Agriculture (ICoSIA 2023)
|
|
---|---|---|
Article Number | 03003 | |
Number of page(s) | 5 | |
Section | Land and Environmental Management | |
DOI | https://doi.org/10.1051/bioconf/20238003003 | |
Published online | 14 December 2023 |
Can iPhone/iPad LiDAR data improve canopy height model derived from UAV?
1 Department of Forest Management, Faculty of Forestry, Universitas Gadjah Mada, 55281 Yogyakarta, Indonesia
2 Department of Silviculture, Faculty of Forestry, Universitas Gadjah Mada, 55281 Yogyakarta, Indonesia
* Corresponding author: esoraya@ugm.ac.id
Aerial images resulting from unmanned aerial vehicle (UAV) are widely used to estimate tree height. The filtering method is required to distinguish between ground and off-ground point clouds to generate a canopy height model. However, the filtering method is not always perfect since UAV data cannot penetrate canopies into the forest floor. The release of iPhone/iPad devices with built-in LiDAR sensors enables the more affordable use of LiDAR for forestry study, including the measurement of local topography below forest stands. This study investigates to what extent iPhone/iPad LiDAR can improve the accuracy of canopy height model from the UAV. The integration of UAV and iPhone/iPad LiDAR data managed to increase the accuracy of tree height model with a mean absolute error (MAE) of 2.188 m, compared to UAV data (MAE = 2.446 m). This preliminary study showed the potential of combining UAV and iPhone/iPad LiDAR data for estimating tree height.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.