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Applied Sciences
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Advances, Challenges and Applications in Unmanned Aerial Vehicle Remote Sensing...
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Advances, Challenges and Applications in Unmanned Aerial Vehicle Remote Sensing Techniques

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (20 December 2022) | Viewed by 5547

Special Issue Editor

Dr. Wilhelm Alexander Friess

E-Mail Website
Guest Editor
Department of Mechanical Engineering, University of Maine, Orono, ME 04469, USA
Interests: UAV; remote sensing; engineering education; engineering design; engineering leadership

Special Issue Information

Dear Colleagues,

Unmanned Aerial Vehicle (UAVs) constitute highly effective tools for remote sensing applications in a wide range of disciplines, including Earth science, structural inspections, agriculture, archaeology and many more. The rapid development over the past two decades of flight vehicles; guidance, navigation and control algorithms; and science-specific sensors has increased their capabilities to become useful to not only specialized technicians but to the general scientific and technical community.

This Special Issue seeks original contributions addressing the advances, challenges and applications of UAVs in civilian remote sensing missions. Topics can include specific science applications and techniques, as well as fieldwork case studies; flight vehicle design topics such as aerodynamics, flight dynamics and control; sensor technology related to UAV applications; AI applications; safety and airspace considerations; routing and autonomy; regulatory issues; as well as education efforts.

Remote sensing includes all civilian use fields where aerial observations are made, ranging from Earth science to structural and infrastructural inspections and even extending to planetary exploration. All categories of UAVs will be considered, including rotary wing, fixed wing, lighter than air and combinations thereof.

Dr. Wilhelm Alexander Friess
Guest Editor

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. Applied Sciences 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 2400 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.

Keywords

  • drone
  • UAV
  • remote sensing
  • airborne sensors
  • guidance
  • navigation
  • control
  • aerodynamics
  • propulsion

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Published Papers (2 papers)

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Research

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12 pages, 5402 KiB  
Article
Novel Method for Monitoring Mining Subsidence Featuring Co-Registration of UAV LiDAR Data and Photogrammetry
by Jibo Liu, Xiaoyu Liu, Xieyu Lv, Bo Wang and Xugang Lian
Appl. Sci. 2022, 12(18), 9374; https://doi.org/10.3390/app12189374 - 19 Sep 2022
Cited by 9 | Viewed by 2413
Abstract
Addressing the problem that traditional methods cannot reliably monitor surface subsidence in coal mining, a novel method has been developed for monitoring subsidence in mining areas using time series unmanned aerial vehicle (UAV) photogrammetry in combination with LiDAR. A dynamic subsidence basin based [...] Read more.
Addressing the problem that traditional methods cannot reliably monitor surface subsidence in coal mining, a novel method has been developed for monitoring subsidence in mining areas using time series unmanned aerial vehicle (UAV) photogrammetry in combination with LiDAR. A dynamic subsidence basin based on the differential digital elevation model (DEM) was constructed and accuracy of the proposed method was verified, with the uncertainty of the DEM of difference (DoD) being quantified via co-registration of a dense matching point cloud of the time series UAV data. The root mean square error calculated for the monitoring points on the subsidence DEM was typically between 0.2 m and 0.3 m with a minimum of 0.17 m. The relative error between the maximum subsidence value of the extracted profile line on the main section after fitting and the measured maximum subsidence value was not more than 20%, and the minimum value was 0.7%. The accuracy of the UAV based method was at the decimeter level, and high accuracy in monitoring the maximum subsidence value was attained, confirming that an innovative strategy for monitoring mining subsidence was realized. Full article
(This article belongs to the Special Issue Advances, Challenges and Applications in Unmanned Aerial Vehicle Remote Sensing Techniques)
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Review

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27 pages, 6263 KiB  
Review
Review of Target Geo-Location Algorithms for Aerial Remote Sensing Cameras without Control Points
by Yiming Cai, Yao Zhou, Hongwen Zhang, Yuli Xia, Peng Qiao and Junsuo Zhao
Appl. Sci. 2022, 12(24), 12689; https://doi.org/10.3390/app122412689 - 11 Dec 2022
Cited by 7 | Viewed by 2377
Abstract
Aerial cameras are one of the main devices for obtaining ground images in the air. Since the industrial community sets higher requirements of aerial cameras’ self-locating performance yearly using aerial cameras to locate ground targets has become a research hotspot in recent years. [...] Read more.
Aerial cameras are one of the main devices for obtaining ground images in the air. Since the industrial community sets higher requirements of aerial cameras’ self-locating performance yearly using aerial cameras to locate ground targets has become a research hotspot in recent years. Based on the situation that no ground control point exists in target areas, the calculation principle of the aerial remote sensing image positioning algorithm has been analyzed by establishing different positioning models. Several error analysis models of the positioning algorithm based on the total differential method and the Monte Carlo method are established, and relevant factors that cause the positioning error are summarized. The last section proposes the optimization direction of aerial camera positioning algorithms in the future, which are verified by related simulation experiments. This paper provides a certain degree of guidelines in this area for researchers, who can quickly understand the current development and optimization direction of target geo-location algorithms of aerial remote sensing imagery. Full article
(This article belongs to the Special Issue Advances, Challenges and Applications in Unmanned Aerial Vehicle Remote Sensing Techniques)
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