Special Issue "Latest Developments, Methodologies and Applications Based on UAV Platforms"

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

Deadline for manuscript submissions: 31 March 2018

Special Issue Editors

Guest Editor
Dr. Francesco Nex

Department of Earth Observation,Science (EOS), ITC Faculty, University of Twente PO Box 217, 7500 AE, Enschede, The Netherlands
Website | E-Mail
Interests: geometric and radiometric sensors; sensor fusion; calibration of imageries; signal/image processing; mission planning; navigation and position/orientation; Machine learning; Simultaneous localization and mapping; Regulations, and economic impact; agriculture; geosciences; urban area; architecture; monitoring/change detection; education
Guest Editor
Prof. Dr. Fabio Remondino

Bruno Kessler Foundation (FBK), 3D Optical Metrology (3DOM) unit, Trento, Italy; Vice-President of EuroSDR; President of ISPRS Technical Commission II “Photogrammetry”; Vice-President CIPA Heritage Documentation
Website | E-Mail
Fax: +39 0461 314340
Interests: photogrammetry; laser scanning; 3D reconstruction; 3D modeling; sensor integration

Special Issue Information

Dear Colleagues,

Using small Unmanned Aerial Vehicles (UAV) as data acquisition platforms and autonomous or semi-autonomous measurement instruments has become attractive for many emerging applications. They represent a valid alternative or a complementary solution to traditional platforms especially for extremely high resolution acquisitions on small or inaccessible areas. Thanks to their timely, cheap and extremely rich data acquisition capacity with respect to other acquisition systems, UAVs are emerging as innovative and cost-effective devices to perform numerous urban and environmental tasks.

This Special Issue aims at collecting new developments and methodologies, best practices and applications of UAVs in Geomatics. We welcome submissions which provide the community with the most recent advancements on all aspects of UAV in Geomatics, including but not limited to:

  • Data processing and Photogrammetry
  • Navigation and position/orientation determination
  • Data analysis (image classification, feature extraction, target detection, change detection, biophysical parameter estimation, etc.)
  • Platforms and new sensors on board (multispectral, hyperspectral, thermal, lidar, SAR, gas or radioactivity sensors, etc.)
  • Data fusion: integration of UAV imagery with satellite, aerial or terrestrial data, integration of heterogeneous data captured by UAVs
  • On-line and real time processing / collaborative and fleet of UAVs applied to Geomatics
  • On-board data storage and transmission
  • UAV control, obstacle sense and avoidance
  • Autonomous flight and exploration
  • Applications (3D mapping, urban monitoring, precision farming, forestry, disaster prevention, assessment and monitoring, search and rescue, security, archaeology, industrial plant inspection, etc.)
  • Any use of UAVs related to Geomatics

This Special Issue will also feature selected papers from the UAV-g 2017 conference. Authors wishing to have their work considered for this issue, including those not able to present at the conference, should contact the Guest Editors.

Dr. Francesco Nex
Prof. Dr. Fabio Remondino
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 papers will be 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 quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) is waived for well-prepared manuscripts submitted to this issue. 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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Open AccessArticle UAS Navigation with SqueezePoseNet—Accuracy Boosting for Pose Regression by Data Augmentation
Drones 2018, 2(1), 7; doi:10.3390/drones2010007
Received: 20 December 2017 / Revised: 24 January 2018 / Accepted: 5 February 2018 / Published: 13 February 2018
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The navigation of Unmanned Aerial Vehicles (UAVs) nowadays is mostly based on Global Navigation Satellite Systems (GNSSs). Drawbacks of satellite-based navigation are failures caused by occlusions or multi-path interferences. Therefore, alternative methods have been developed in recent years. Visual navigation methods such as
[...] Read more.
The navigation of Unmanned Aerial Vehicles (UAVs) nowadays is mostly based on Global Navigation Satellite Systems (GNSSs). Drawbacks of satellite-based navigation are failures caused by occlusions or multi-path interferences. Therefore, alternative methods have been developed in recent years. Visual navigation methods such as Visual Odometry (VO) or visual Simultaneous Localization and Mapping (SLAM) aid global navigation solutions by closing trajectory gaps or performing loop closures. However, if the trajectory estimation is interrupted or not available, a re-localization is mandatory. Furthermore, the latest research has shown promising results on pose regression in 6 Degrees of Freedom (DoF) based on Convolutional Neural Networks (CNNs). Additionally, existing navigation methods can benefit from these networks. In this article, a method for GNSS-free and fast image-based pose regression by utilizing a small Convolutional Neural Network is presented. Therefore, a small CNN (SqueezePoseNet) is utilized, transfer learning is applied and the network is tuned for pose regression. Furthermore, recent drawbacks are overcome by applying data augmentation on a training dataset utilizing simulated images. Experiments with small CNNs show promising results for GNSS-free and fast localization compared to larger networks. By training a CNN with an extended data set including simulated images, the accuracy on pose regression is improved up to 61.7% for position and up to 76.0% for rotation compared to training on a standard not-augmented data set. Full article

Figure 1

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Acquisition and Processing Protocols for UAV Images: 3D Modelling of Historical Buildings Using Photogrammetry
A. Murtiyoso, M. Koehl, P. Grussenmeyer, T. Freville


UAV Photogrammetric Workflows: A Best Practice Guideline
A. Federman, M. Santana Quintero, J. Gregg, S. Kretz, M. Lengies, C. Ouimet, J. LaLiberte

Effective Detection of Sub-Surface Archeological Features from Laser Scanning Point Clouds and Imagery Data
A. Fryskowska, P. Walczykowski, M. Kedzierski, D. Wierzbicki, P. Delis, A. Lada 

Modeling the Decay in an HBIM Starting from 3D Point Clouds. A Followed Approach for Cultural Heritage Knowledge
F. Rinaudo, F. Chiabrando, M. Lo Turco

Fort Rodd Hill N.H.S.C.: Benefits in the Use of Photogrammetric and Lidar Documentation for the Production of Construction Tender Documents
S. C. Kretz

Three-Dimensional Digital Documentation of Heritage Sites Using Terrestrial Laser Scanning and Unmanned Aerial Vehicle Photogrammetry
Y. H. Jo, J. Y. Kim

Putting Roman Dams in Context: A Virtual Approach
M. Decker, J. Du Vernay, J. McLeod

Digital Recording and Non-Destructive Techniques for the Understanding of Structural Performance for Rehabilitating Historic Structures at the Kathmandu Valley after Gorkha Earthquake 2015
Shrestha, M. Reina Ortiz, M. Gutland, R. Napolitano, I. Morris, M. Santana Quintero, J. Erochko, S. Kawan, R. G. Shrestha, P. Awal, S. Suwal, S. Duwal, D. K. Maharjan

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