Testing the accuracy and characteristics of data acquired using DJI Zenmuse L1 and L2 lidar systems and photogrammetric data acquired using DJI Zenmuse P1 in a quarry environment

The present study aimed to compare the performance of the DJI Zenmuse L2 lidar scanner for unmanned aerial vehicles (UAV) with that of the previous generation of the same system (DJI Zenmuse L1) and a cloud derived by photogrammetry (DJI Zenmuse P1) in a quarry area. A reference cloud was acquired using a terrestrial laser scanner Leica P40. The results show a major improvement in the L2 accuracy compared with the older L1 scanner, particularly where the overall accuracy after smoothing (RMSES = 0.03 m for L2, compared to 0.05 m for L1) and noise (RMSENOISE of 0.026 and 0.045 m for L2 and L1) are concerned. Color displacement, however, remained practically identical between L1 and L2, reaching a maximum of almost 0.35 m. The accuracy of the photogrammetric point cloud was still somewhat better than the new generation L2 scanner (RMSEO = 0.017 m); however, where practical applicability is concerned, the accuracy provided by the new generation lidar scanner is sufficient for a vast majority of applications and considering other advantages of lidar over photo-grammetry, the new generation scanning technology has the potential to replace photogrammetry in the acquisition of point clouds using UAV in the foreseeable future.

Authors

Institutions

Publication Details

Journal
European Journal of Remote Sensing
Published
2025-12-07
DOI
https://doi.org/10.1080/22797254.2025.2595361
Citations
1
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
2.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Testing the accuracy and characteristics of data acquired using DJI Zenmuse L1 and L2 lidar systems and photogrammetric data acquired using DJI Zenmuse P1 in a quarry environment

Ľudovít Kovanič, Jaroslav Braun, Martin Štroner, Peter Blišťan et al.
1 citations
European Journal of Remote Sensing
3D Surveying and Cultural Heritage
2.35
article

Testing the accuracy and characteristics of data acquired using DJI Zenmuse L1 and L2 lidar systems and photogrammetric data acquired using DJI Zenmuse P1 in a quarry environment

Ľudovít Kovanič, Jaroslav Braun, Martin Štroner, Peter Blišťan, Tomáš Křemen, Branislav Topitzer, Patrik Peťovský, Rudolf Urban
article en
1 citations

Abstract

The present study aimed to compare the performance of the DJI Zenmuse L2 lidar scanner for unmanned aerial vehicles (UAV) with that of the previous generation of the same system (DJI Zenmuse L1) and a cloud derived by photogrammetry (DJI Zenmuse P1) in a quarry area. A reference cloud was acquired using a terrestrial laser scanner Leica P40. The results show a major improvement in the L2 accuracy compared with the older L1 scanner, particularly where the overall accuracy after smoothing (RMSES = 0.03 m for L2, compared to 0.05 m for L1) and noise (RMSENOISE of 0.026 and 0.045 m for L2 and L1) are concerned. Color displacement, however, remained practically identical between L1 and L2, reaching a maximum of almost 0.35 m. The accuracy of the photogrammetric point cloud was still somewhat better than the new generation L2 scanner (RMSEO = 0.017 m); however, where practical applicability is concerned, the accuracy provided by the new generation lidar scanner is sufficient for a vast majority of applications and considering other advantages of lidar over photo-grammetry, the new generation scanning technology has the potential to replace photogrammetry in the acquisition of point clouds using UAV in the foreseeable future.

European Journal of Remote SensingVol. 58(1)
Geographical Institute (HU), Czech Technical University in Prague (CZ)
Openalex Percentile: Top 9%
3D Surveying and Cultural Heritage
2.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.