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Drones
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Acquisition and Reliability of Geospatial Data from UAV Platforms for...
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Acquisition and Reliability of Geospatial Data from UAV Platforms for Environmental Management and Monitoring

A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drones in Ecology".

Deadline for manuscript submissions: closed (20 December 2024) | Viewed by 2475

Special Issue Editors

Dr. Domenica Costantino

E-Mail Website
Guest Editor
Dipartimento di Ingegneria Civile, Ambientale, del Territorio, Edile e di Chimica, Polytechnic University of Bari, Via E. Orabona 4, 70125 Bari, Italy
Interests: DTM; surveying; photogrammetry; geomatics; environment; geographic information system; remote sensing; spatial analysis; geography; navigation
Special Issues, Collections and Topics in MDPI journals
Dr. Vincenzo Saverio Alfio

E-Mail Website
Guest Editor
Dipartimento di Ingegneria Civile, Ambientale, del Territorio, Edile e di Chimica, Polytechnic University of Bari, Via E. Orabona 4, 70125 Bari, Italy
Interests: 3D surveying; photogrammetry; terrestrial laser scanner; remote sensing; geographic information system; UAV; cultural heritage; heritage; building information modeling
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Massimiliano Pepe

E-Mail Website
Guest Editor
Department of Engineering and Geology (InGeo), “G. d’Annunzio” University of Chieti-Pescara, Viale Pindaro, 42, 65127 Pescara, Italy
Interests: photogrammetry; terrestrial laser scanner; remote sensing; geographic information system; UAV; cultural heritage; heritage; building information modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The use of UAVs today represents an advanced geospatial data acquisition strategy that enables the effective mapping of land and infrastructure. Thanks to the possibility of reaching inaccessible places and flying at varying altitudes, surveying from UAVs allows detailed and up-to-date data to be collected efficiently and accurately. In this way, it is possible to investigate the different phenomena that characterize the environment and to reconstruct a multi-level overview of the surveyed object. Furthermore, these devices can be equipped with a wide range of sensors that enable them to acquire different types of information. The most common sensors include high-resolution cameras, thermal sensors, LiDAR (Light Detection And Ranging), multi-spectral sensors and environmental monitoring sensors. By integrating data from these different sensors, it is possible to obtain a complete and detailed view of the investigated area, facilitating spatial planning, natural resource management, environmental and structural monitoring, and many other applications.

The aim of this Special Issue is to collect new research topics developed not only on the three-dimensional representation and processing of datasets acquired from UAV platforms, but also on the use of specific algorithms for the automatic extraction of features, evaluating the accuracy and detail of the products obtained. Furthermore, this SI aims to analyze possible applications in the field of structural analysis, as well as in environmental management and protection, focusing on the processing, integration and interpretation of data from multi-sensor platforms in order to obtain accurate and meaningful results.

Articles may cover, but are not limited to, the following topics:

- Mapping through photogrammetry from UAVs;
- Innovative techniques for 3D reconstruction of land structures and infrastructures;
- Innovative sensors and tools for 3D data acquisition;
- AI algorithms applied to UAV images;
- Image classification, feature extraction and change detection;
- Data processing and multi-sensor data fusion;
- Urban monitoring applications;
- Environmental and/or structural monitoring through UAVs;
- Multi-spectral and thermal imagery from UAVs for disaster prevention and monitoring.

We are looking forward to receiving your original research articles and reviews.

Dr. Domenica Costantino
Dr. Vincenzo Saverio Alfio
Prof. Dr. Massimiliano Pepe
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.

Keywords

  • UAV platforms
  • geospatial data
  • UAVs with LiDAR
  • feature extraction
  • change detection
  • 3D reconstruction
  • artificial intelligence

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Published Papers (2 papers)

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Research

21 pages, 17676 KiB  
Article
Comparative Assessment of the Effect of Positioning Techniques and Ground Control Point Distribution Models on the Accuracy of UAV-Based Photogrammetric Production
by Muhammed Enes Atik and Mehmet Arkali
Drones 2025, 9(1), 15; https://doi.org/10.3390/drones9010015 - 27 Dec 2024
Viewed by 894
Abstract
Unmanned aerial vehicle (UAV) systems have recently become essential for mapping, surveying, and three-dimensional (3D) modeling applications. These systems are capable of providing highly accurate products through integrated advanced technologies, including a digital camera, inertial measurement unit (IMU), and Global Navigation Satellite System [...] Read more.
Unmanned aerial vehicle (UAV) systems have recently become essential for mapping, surveying, and three-dimensional (3D) modeling applications. These systems are capable of providing highly accurate products through integrated advanced technologies, including a digital camera, inertial measurement unit (IMU), and Global Navigation Satellite System (GNSS). UAVs are a cost-effective alternative to traditional aerial photogrammetry, and recent advancements demonstrate their effectiveness in many applications. In UAV-based photogrammetry, ground control points (GCPs) are utilized for georeferencing to enhance positioning precision. The distribution, number, and location of GCPs in the study area play a crucial role in determining the accuracy of photogrammetric products. This research evaluates the accuracy of positioning techniques for image acquisition for photogrammetric production and the effect of GCP distribution models. The camera position was determined using real-time kinematic (RTK), post-processed kinematic (PPK), and precise point positioning-ambiguity resolution (PPP-AR) techniques. In the criteria for determining the GCPs, six models were established within the İstanbul Technical University, Ayazaga Campus. To assess the accuracy of the points in these models, the horizontal, vertical, and 3D root mean square error (RMSE) values were calculated, holding the test points stationary in place. In the study, 2.5 cm horizontal RMSE and 3.0 cm vertical RMSE were obtained with the model containing five homogeneous GCPs by the indirect georeferencing method. The highest RMSE values of all three components in RTK, PPK, and PPP-AR methods were obtained without GCPs. For all six models, all techniques have an error value of sub-decimeter. The PPP-AR technique yields error values that are comparable to those of the other techniques. The PPP-AR appears to be an alternative to RTK and PPK, which usually require infrastructure, labor, and higher costs. Full article
(This article belongs to the Special Issue Acquisition and Reliability of Geospatial Data from UAV Platforms for Environmental Management and Monitoring)
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17 pages, 3285 KiB  
Article
Methodology and Uncertainty Analysis of Methane Flux Measurement for Small Sources Based on Unmanned Aerial Vehicles
by Degang Xu, Hongju Da, Chen Wang, Zhihe Tang, Hui Luan, Jufeng Li and Yong Zeng
Drones 2024, 8(8), 366; https://doi.org/10.3390/drones8080366 - 31 Jul 2024
Viewed by 1156
Abstract
The top–down emission rate retrieval algorithm (TERRA) method for calculating the net flux out of a box has been employed by other researchers to assess large sources of methane release. This usually requires a manned aircraft drone with powerful performance to fly over [...] Read more.
The top–down emission rate retrieval algorithm (TERRA) method for calculating the net flux out of a box has been employed by other researchers to assess large sources of methane release. This usually requires a manned aircraft drone with powerful performance to fly over the boundary layer. Few studies have focused on low-altitude box sampling mass balance methods for small sources of methane release, such as at maximum flight altitudes of less than 100 m. The accuracy and sources of uncertainty in such a method still need to be determined as they differ from the conditions of large sources. Nineteen flights were conducted to detect methane emissions from Chinese oil field well sites using a measurement system consisting of a quadcopter and methane, wind speed, wind direction, air pressure, and temperature sensors. The accuracy and uncertainty of the method are discussed. The average absolute relative error of the measurement is 18.5%, with an average uncertainty of 55.75%. The uncertainty is mainly caused by the wind speed and direction, and the background CH4 concentration. The main paths to reduce uncertainty and improve accuracy for low-altitude box sampling include subtracting the background concentration during flux retrieval, enhancing the accuracy of methane measurements, selecting a period of downwind dominant or wind direction change of less than 30 degrees, and ensuring a maximum flight height greater than 50 m with a horizontal distance from the pollution source center of less than 75 m. The results show that TERRA-based low-altitude box sampling is suitable for quantifying methane release rates from small sources. Full article
(This article belongs to the Special Issue Acquisition and Reliability of Geospatial Data from UAV Platforms for Environmental Management and Monitoring)
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