UAV DTM acquisition in a forested area – comparison of low-cost photogrammetry (DJI Zenmuse P1) and LiDAR solutions (DJI Zenmuse L1)

ABSTRACT

In this paper, we evaluated the results in terms of accuracy and coverage of the LiDAR-UAV system DJI Zenmuse L1 and Digital Aerial Photogrammetric system (DAP – UAV) DJI Zenmuse P1 in a forested area under leaf-off conditions on three sites with varying terrain ruggedness/tree type combinations. Detailed reference clouds were obtained using terrestrial scanning by Leica P40. Our results show that branches pose no problem to the accuracy of LiDAR-UAV and DAP-UAV derived terrain clouds. Elevation accuracies for photogrammetric data were even better than for LiDAR data – as low as 0.015 m on all sites. However, the LiDAR system provided better coverage, with almost full coverage at all sites, while the DAP-UAV coverage declined with the increasing density of branches (being worst in the young forest). In the very dense young forest (Site 1), the coverage by photogrammetrically extracted terrain cloud using high calculation quality and no filtering achieved 80.7% coverage, while LiDAR-UAV reached almost 100% coverage. The importance of the use of multiple (or last) returns when using LiDAR-UAV systems was demonstrated by the fact that on the site with the densest vegetation, only 11% of the ground points were represented by first returns.

KEYWORDS:

• UAV
• SfM
• photogrammetry
• LiDAR, accuracy
• DTM
• Forest

Acknowledgments

We would also like to thank Ing. Ondřej Kočí from the company Hrdlička spol. s r.o., for piloting the flights and supplying us with the data.

Disclosure statement

No potential conflict of interest was reported by the authors.

The data that support the findings of this study are available from the corresponding author [RU] upon reasonable request.

Author contributions

Conceptualization, MŠ and RU; methodology, MŠ and RU; data acquisition, TK and JB; data processing, MŠ and RU; writing – original draft preparation, MŠ; writing – review and editing, RU; visualization, MŠ; supervision, RU; funding acquisition, RU. All authors have read and agreed to the published version of the manuscript.

Additional information

Funding

This research was funded by the Grant Agency of CTU in Prague — Grant Number SGS22/046/OHK1/1T/11 “Optimization of acquisition and processing of 3D data for purpose of engineering surveying, geodesy in underground spaces and 3D scanning” and by the Technology Agency of the Czech Republic – Grant Number CK03000168 „„Intelligent methods of digital data acquisition and analysis for bridge inspections“