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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F23%3A00365191" target="_blank" >RIV/68407700:21110/23:00365191 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1080/22797254.2023.2179942" target="_blank" >https://doi.org/10.1080/22797254.2023.2179942</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/22797254.2023.2179942" target="_blank" >10.1080/22797254.2023.2179942</a>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20101 - Civil engineering

Project

<a href="/en/project/CK03000168" target="_blank" >CK03000168: Intelligent methods of digital data acquisition and analysis for bridge inspections</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

European Journal of Remote Sensing

ISSN

2279-7254

e-ISSN

2279-7254

Volume of the periodical

56

Issue of the periodical within the volume

1

Country of publishing house

GB - UNITED KINGDOM

Number of pages

20

Pages from-to

1-20

UT code for WoS article

000941059900001

EID of the result in the Scopus database

2-s2.0-85149361899