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Drones
Special Issues
Unmanned Aerial System in Geomatics
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Unmanned Aerial System in Geomatics

A special issue of Drones (ISSN 2504-446X).

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 3577

Special Issue Editors

Prof. Dr. Kamal Jain

E-Mail Website
Guest Editor
Indian Institute of Technology Roorkee, Roorkee - Haridwar Highway, Roorkee, Uttarakhand 247667, India
Interests: photogrammetry; analytical and digital photogrammetry; satellite photogrammetry; close range photogrammetry; mapping; 3D virtual city; topographical survey; engineering survey; rail/road/canal route alignment and layout; GIS; Web GIS; DSS; KBS; GPS; DGPS; vehicle navigation and tracking; unmanned aerial vehicles (UAVs)
Dr. Goutam Chattopadhyay

E-Mail Website
Guest Editor
NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Interests: microwave; millimeter-wave; terahertz heterodyne and direct detector receivers and instruments; high-frequency radars; terahertz sources; the application of nanotechnology at terahertz frequencies
Prof. Dr. Yongjun Zhang

E-Mail Website
Guest Editor
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Interests: digital photogrammetry and remote sensing; computer vision; geometric processing of aerial and space optical imagery; multi-source spatial data integration; integrated sensor calibration and orientation; low-altitude UAV photogrammetry; combined bundle block adjustment of multi-source datasets; LiDAR and image integration; digital city modeling; visual inspection of industrial parts; intelligent extraction of remote sensing information and knowledge modeling
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Biswajeet Pradhan

grade E-Mail Website
Guest Editor
Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), University of Technology Sydney, Sydney, NSW 2007, Australia
Interests: radar image processing remote sensing and GIS applications GIS for engineers forecasting disaster hazard; stochastic analysis and modelling; natural hazards; environmental engineering modelling; geospatial information systems; photogrammetry and remote sensing; unmanned aerial vehicles (UAVs).
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is dedicated to researchers and practitioners addressing new challenges in unmanned aerial vehicle (UAV) manufacturing, geospatial data sensing, representation, processing, visualization, analytics, development, sharing and managing, in all aspects concerning both unmanned aerial system technology and geo-informatics. With this SI we welcome original papers of either practical or theoretical nature, presenting research or applications of a specialized or interdisciplinary nature, addressing any aspect of geographic information systems and UAV technologies. 

Papers may address one or more of the listed sub-topics, although authors should not feel limited by them. Unlisted but related sub-topics are also acceptable, provided they fit in one of the following main topic areas:

  • UAV in photogrammetry and remote sensing;
  • LiDAR point cloud segmentation and classification;
  • micro and mini UAV development;
  • UAV applications/practices in infrastructure mapping and monitoring for smart city development;
  • AI and analytics in UAVs;
  • UAV vulnerabilities and cyber security.

Prof. Dr. Kamal Jain
Dr. Goutam Chattopadhyay
Prof. Dr. Yongjun Zhang
Prof. Dr. Biswajeet Pradhan
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. Drones is an international peer-reviewed open access monthly 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 2600 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

16 pages, 4096 KiB  
Article
Processing and Interpretation of UAV Magnetic Data: A Workflow Based on Improved Variational Mode Decomposition and Levenberg–Marquardt Algorithm
by Yaoxin Zheng, Shiyan Li, Kang Xing and Xiaojuan Zhang
Drones 2022, 6(1), 11; https://doi.org/10.3390/drones6010011 - 03 Jan 2022
Cited by 4 | Viewed by 2566
Abstract
Unmanned aerial vehicles (UAVs) have become a research hotspot in the field of magnetic exploration because of their unique advantages, e.g., low cost, high safety, and easy to operate. However, the lack of effective data processing and interpretation method limits their further deployment. [...] Read more.
Unmanned aerial vehicles (UAVs) have become a research hotspot in the field of magnetic exploration because of their unique advantages, e.g., low cost, high safety, and easy to operate. However, the lack of effective data processing and interpretation method limits their further deployment. In view of this situation, a complete workflow of UAV magnetic data processing and interpretation is proposed in this paper, which can be divided into two steps: (1) the improved variational mode decomposition (VMD) is applied to the original data to improve its signal-to-noise ratio as much as possible, and the decomposition modes number K is determined adaptively according to the mode characteristics; (2) the parameters of target position and magnetic moment are obtained by Euler deconvolution first, and then used as the prior information of the Levenberg–Marquardt (LM) algorithm to further improve its accuracy. Experiments are carried out to verify the effectiveness of the proposed method. Results show that the proposed method can significantly improve the quality of the original data; by combining the Euler deconvolution and LM algorithm, the horizontal positioning error can be reduced from 15.31 cm to 4.05 cm, and the depth estimation error can be reduced from 16.2 cm to 5.4 cm. Moreover, the proposed method can be used not only for the detection and location of near-surface targets, but also for the follow-up work, such as the clearance of targets (e.g., the unexploded ordnance). Full article
(This article belongs to the Special Issue Unmanned Aerial System in Geomatics)
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