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Drones
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Unmanned Aerial Vehicles in Geomatics
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Unmanned Aerial Vehicles in Geomatics

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

Deadline for manuscript submissions: closed (28 February 2020) | Viewed by 21893

Special Issue Editors

Prof. Dr. Francesco Nex

E-Mail Website
Guest Editor
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands
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; unmanned aerial vehicles (UAV)
Special Issues, Collections and Topics in MDPI journals
Dr. Daniele Giordan

E-Mail Website
Guest Editor
CNR IRPI, Turin, Italy
Interests: unmanned aerial vehicles; natural hazards; engineering geology
Special Issues, Collections and Topics in MDPI journals
Dr. Ewelina Rupnik

E-Mail Website
Guest Editor
Univ. Paris-Est, LaSTIG ACTE, IGN, ENSG, 94160 Saint-Mande, France
Interests: image orientation and calibration; sensor fusion; dense image matching; metrology; mobile mapping; geoscience
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The use of unmanned aerial vehicles (UAV) has boomed in the last decade, making these flying platforms an instrument for everyday data acquisition in different applications ranging from advanced autonomous navigation to monitoring of environmental parameters. Their flexibility and (relatively) limited costs have made them a valid alternative to traditional measurement techniques, such as land surveying or terrestrial and airborne acquisitions. This has been reflected by the incredible number of contributions in different scientific communities dealing with the use of UAVs.

This Special Issue aims at collecting the most recent developments in the use of UAVs in Geomatics. We welcome submissions dealing with different aspects of the scientific developments in this field, including algorithmic and hardware innovations as well as new methodological best practices. Studies conducted in adjacent domains, such robotics and computer vision, and having the navigation, mapping, and understanding of real world as a main topic are also welcome in this Special Issue.

A list of the relevant topics relevant for this Special Issue includes but is not limited to:

  • Image orientation and accurate georeferencing;
  • Autonomous navigation and obstacle sense and avoidance;
  • Simultaneous localization and mapping (SLAM) and visual odometry;
  • 3D reconstruction from images and laser sensors;
  • 2D and 3D mapping with UAV data;
  • Semantic scene understanding from UAV images and videos;
  • On board sensors fusion;
  • Integration of UAV data with other data sources (LiDAR, airborne, satellite, SAR, etc.);
  • New platforms, payloads and instruments for Geomatics;
  • Online and real time processing/collaborative and fleet of UAVs applied to Geomatics and Remote Sensing’
  • Emerging applications such as the use of UAV for: Search & Rescue, precision farming, natural hazards and environmental monitoring and mapping, change detection, infrastructure monitoring, etc.;
  • Technological challenges and new applications of UAVs;
  • UAV Regulations.

This Special Issue will also feature selected papers from the UAV-g 2019 conference and the EGU 2019 session on Remotely Piloted Aircraft Systems and Geosciences. Authors wishing to have their work considered for this issue, including those not able to present at the conference, should contact the Guest Editors.

You may choose our Joint Special Issue in Remote Sensing.

Dr. Francesco Nex
Dr. Daniele Giordan
Dr. Ewelina Rupnik
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 (3 papers)

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19 pages, 14040 KiB  
Article
Coastal Mapping Using DJI Phantom 4 RTK in Post-Processing Kinematic Mode
by Yuri Taddia, Francesco Stecchi and Alberto Pellegrinelli
Drones 2020, 4(2), 9; https://doi.org/10.3390/drones4020009 - 30 Mar 2020
Cited by 104 | Viewed by 10804
Abstract
Topographic and geomorphological surveys of coastal areas usually require the aerial mapping of long and narrow sections of littoral. The georeferencing of photogrammetric models is generally based on the signalization and survey of Ground Control Points (GCPs), which are very time-consuming tasks. Direct [...] Read more.
Topographic and geomorphological surveys of coastal areas usually require the aerial mapping of long and narrow sections of littoral. The georeferencing of photogrammetric models is generally based on the signalization and survey of Ground Control Points (GCPs), which are very time-consuming tasks. Direct georeferencing with high camera location accuracy due to on-board multi-frequency GNSS receivers can limit the need for GCPs. Recently, DJI has made available the Phantom 4 Real-Time Kinematic (RTK) (DJI-P4RTK), which combines the versatility and the ease of use of previous DJI Phantom models with the advantages of a multi-frequency on-board GNSS receiver. In this paper, we investigated the accuracy of both photogrammetric models and Digital Terrain Models (DTMs) generated in Agisoft Metashape from two different image datasets (nadiral and oblique) acquired by a DJI-P4RTK. Camera locations were computed with the Post-Processing Kinematic (PPK) of the Receiver Independent Exchange Format (RINEX) file recorded by the aircraft during flight missions. A Continuously Operating Reference Station (CORS) located at a 15 km distance from the site was used for this task. The results highlighted that the oblique dataset produced very similar results, with GCPs (3D RMSE = 0.025 m) and without (3D RMSE = 0.028 m), while the nadiral dataset was affected more by the position and number of the GCPs (3D RMSE from 0.034 to 0.075 m). The introduction of a few oblique images into the nadiral dataset without any GCP improved the vertical accuracy of the model (Up RMSE from 0.052 to 0.025 m) and can represent a solution to speed up the image acquisition of nadiral datasets for PPK with the DJI-P4RTK and no GCPs. Moreover, the results of this research are compared to those obtained in RTK mode for the same datasets. The novelty of this research is the combination of a multitude of aspects regarding the DJI Phantom 4 RTK aircraft and the subsequent data processing strategies for assessing the quality of photogrammetric models, DTMs, and cross-section profiles. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles in Geomatics)
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23 pages, 7094 KiB  
Article
Estimating the Threshold of Detection on Tree Crown Defoliation Using Vegetation Indices from UAS Multispectral Imagery
by Kaori Otsu, Magda Pla, Andrea Duane, Adrián Cardil and Lluís Brotons
Drones 2019, 3(4), 80; https://doi.org/10.3390/drones3040080 - 29 Oct 2019
Cited by 23 | Viewed by 4763
Abstract
Periodical outbreaks of Thaumetopoea pityocampa feeding on pine needles may pose a threat to Mediterranean coniferous forests by causing severe tree defoliation, growth reduction, and eventually mortality. To cost–effectively monitor the temporal and spatial damages in pine–oak mixed stands using unmanned aerial systems [...] Read more.
Periodical outbreaks of Thaumetopoea pityocampa feeding on pine needles may pose a threat to Mediterranean coniferous forests by causing severe tree defoliation, growth reduction, and eventually mortality. To cost–effectively monitor the temporal and spatial damages in pine–oak mixed stands using unmanned aerial systems (UASs) for multispectral imagery, we aimed at developing a simple thresholding classification tool for forest practitioners as an alternative method to complex classifiers such as Random Forest. The UAS flights were performed during winter 2017–2018 over four study areas in Catalonia, northeastern Spain. To detect defoliation and further distinguish pine species, we conducted nested histogram thresholding analyses with four UAS-derived vegetation indices (VIs) and evaluated classification accuracy. The normalized difference vegetation index (NDVI) and NDVI red edge performed the best for detecting defoliation with an overall accuracy of 95% in the total study area. For discriminating pine species, accuracy results of 93–96% were only achievable with green NDVI in the partial study area, where the Random Forest classification combined for defoliation and tree species resulted in 91–93%. Finally, we achieved to estimate the average thresholds of VIs for detecting defoliation over the total area, which may be applicable across similar Mediterranean pine stands for monitoring regional forest health on a large scale. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles in Geomatics)
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9 pages, 860 KiB  
Conference Report
UAV-g 2019: Unmanned Aerial Vehicles in Geomatics
by Francesco Nex
Drones 2019, 3(3), 74; https://doi.org/10.3390/drones3030074 - 19 Sep 2019
Cited by 5 | Viewed by 5385
Abstract
Unmanned aerial vehicle in geomatics (UAV-g) is a well-established scientific event dedicated to UAVs in geomatics and remote sensing. In the different editions of the journal, new scientific challenges have increased their synergy with adjacent domains, such as robotics and computer vision, thereby [...] Read more.
Unmanned aerial vehicle in geomatics (UAV-g) is a well-established scientific event dedicated to UAVs in geomatics and remote sensing. In the different editions of the journal, new scientific challenges have increased their synergy with adjacent domains, such as robotics and computer vision, thereby increasing the impact of this conference. The 2019 edition has been hosted by the University of Twente (The Netherlands) and has attracted about 300 participants for the full three-day program. Researchers from 36 different countries (from all continents) have presented 89 accepted papers in 17 oral and 2 poster sessions. The presented papers covered multi-disciplinary topics, such as photogrammetry, natural resources monitoring, autonomous navigation, and deep learning. All these contributions have in common the use of UAV platforms for the innovative acquisition and processing of the acquired data and information extracted from the surrounding environment. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles in Geomatics)
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