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Application of UAV with LiDAR Data

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 2377

Special Issue Editors


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Guest Editor
Institute of Aerospace Science and Technology, Wuhan University, Wuhan 430079, China
Interests: UAV LiDAR technology; point cloud understanding

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Guest Editor
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Interests: point clouds processing

Special Issue Information

Dear Colleagues,

The arrival of unmanned aerial vehicles (UAVs) has democratized the development and application of LiDAR forever. Everyday UAV LiDAR can be flown easier and faster, with sensors becoming lighter, more accurate and flexible, enabling their use in multiple platforms or combined with other techniques to obtain everything in a single survey. In terms of data processing, new LiDAR tools and algorithms are continuously being developed, performing tasks and processing better and faster than ever. In recent years, research has evolved from just a few big specialized companies to hundreds of new players bringing new approaches, fresh perspectives and innovative solutions.

All technical changes create new situations, most of them positive. From our perspective, the key is to turn the data you can obtain into value. We are constantly surprised by how many individuals approach every single step with great care and professionalism until it comes to transforming raw data into value. Then, they seem to assume that all automated solutions are equally good and use the most valuable option possible.

This Special Issue welcomes contributions showcasing recent advancements in UAV LiDAR technical developments and applications. Point clouds obtained from UAVs have the unique features of true three dimensionalities, varied point densities, heterogeneous distributions, scene complexity and data incompleteness. It is still challenging to provide an efficient and effective point cloud understanding that includes point cloud registration and fusion, feature extraction, semantic labelling, segmentation and classification, as well as urban environmental monitoring, intelligent transportation systems, geospatial big data analysis, 3D modelling and visualization and high-performance computing. We are pleased to announce a request for the submission of papers aiding in the understanding of UAV LiDAR point clouds.

Areas of interest include, but are not necessarily restricted to:

  • UAV LiDAR system development;
  • Three-dimensional object detection, extraction, recognition and reconstruction in UAV point clouds;
  • Machine/deep learning for large-scale point cloud understanding;
  • Multispectral/hyperspectral point clouds for classification and objects extraction of wetlands, cultivated and vegetated areas;
  • Fusion of point clouds with optical/multispectral/hyperspectral imagery.

Prof. Dr. Qingzhou Mao
Dr. Cheng Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (1 paper)

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Research

22 pages, 9406 KiB  
Article
Analysis of Internal Angle Error of UAV LiDAR Based on Rotating Mirror Scanning
by Hao Zhou, Qingzhou Mao, Yufei Song, Anlei Wu and Xueqing Hu
Remote Sens. 2022, 14(20), 5260; https://doi.org/10.3390/rs14205260 - 20 Oct 2022
Cited by 4 | Viewed by 1886
Abstract
UAV LiDAR is a powerful tool for rapidly acquiring ground-based 3D spatial information and has been used in various applications. In addition to the ranging mechanism, the scanning method is also an important factor, affecting the performance of UAV LiDAR, and the internal [...] Read more.
UAV LiDAR is a powerful tool for rapidly acquiring ground-based 3D spatial information and has been used in various applications. In addition to the ranging mechanism, the scanning method is also an important factor, affecting the performance of UAV LiDAR, and the internal angle error of LiDAR will seriously affect its measurement accuracy. Starting from the rotary scanning model of a single-sided mirror, this paper presents a comparative study of the characteristics of 45° single-sided mirror scanning, polygon prism scanning, polygon tower mirror scanning, and wedge mirror scanning. The error sources of the quadrangular tower mirror scanning are analyzed in detail, including the angle deviation between the direction of emitted laser and the rotation axis (typical 0.13 ± 0.18° and 0.85° ± 0.26°), the angle deviation between the mirror’s reflection plane and the rotation axis, and the surface angle deviation between multiple surfaces (typical ± 0.06°). As a result, the measurement deviation caused by the internal angle error can be as high as decimeter to meter, which cannot be fully compensated by simply adjusting the installation angle between the UAV and the LiDAR. After the calibration of the internal angle error, the standard deviation of the elevation difference between the point cloud and the control point is only 0.024 m in the flight experiment at 300 m altitude. Full article
(This article belongs to the Special Issue Application of UAV with LiDAR Data)
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