UAVs for Photogrammetry, 3D Modeling, Obtrusive Light and Sky Glow Measurements

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

Deadline for manuscript submissions: 20 April 2025 | Viewed by 8969

Special Issue Editors


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Guest Editor
Department of Geodesy, Faculty of Civil and Environmental Engineering, Gdansk Technical University, Narutowicza St. 11/12, Gdansk, Poland
Interests: unmanned aerial vehicle technology; autonomous navigation; neural networks; non-GNSS navigation; photogrammetry; real-time photogrammetry; computer vision
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Geodesy, Faculty of Civil and Environmental Engineering, Gdansk Technical University, Narutowicza St. 11/12, 80-233 Gdansk, Poland
Interests: photogrammetry; remote sensing; light pollution; obtrusive light and sky glow; UAV

Special Issue Information

Dear Colleagues,

The Special Issue focuses on new trends in photogrammetry and remote sensing with UAVs. In recent years, there have been a lot of new developments strictly concerning UAVs, but also measurements from these devices in general. New sensors, procedures, and algorithms are being developed which improve the quality of photogrammetric studies, photos, and 3D models. Many new algorithms use neural networks, while continuous miniaturization allows achieving an increasingly better accuracy of measurements using small sensors mounted on UAVs. New measurement procedures are also being developed, and the number of UAV applications is constantly increasing especially in environmental and civil engineering. This Special Issue will gather all types of solutions—technical, procedural, and algorithmic—aiming to improve the quality of photogrammetric studies, 3D models, and remote sensing with UAVs. In addition, we invite papers on new trends in artificial light measurements and photogrammetry at night. Night measurements with UAVs, especially those toward light pollution measurements, are becoming important from an environmental point of view, and in this issue, we will showcase new developments in this area.

Dr. Pawel Burdziakowski
Dr. Katarzyna Bobkowska
Guest Editors

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Keywords

  • unmanned aerial vehicles (UAVs)—technical solutions for remote sensing
  • UAV photogrammetry—procedures, technical solutions
  • UAVs in civil engineering
  • UAVs in environmental engineering
  • UAV image georeferencing accuracy
  • UAV image quality enhancement
  • mobile GNSS RTK camera positioning accuracy
  • neural networks for UAV photogrammetry and remote sensing
  • sensors for UAV measurements
  • algorithms for increasing 3D model quality
  • obstructive light pollution UAVs measurements
  • UAV photogrammetry at night
  • UAV obtrusive light and sky glow measurements
  • UAV artificial light measurements
  • UAV probes for environmental measurements
  • 3D mapping accuracy

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Published Papers (4 papers)

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Research

27 pages, 9090 KiB  
Article
Optimized Autonomous Drone Navigation Using Double Deep Q-Learning for Enhanced Real-Time 3D Image Capture
by Javier Sánchez-Soriano, Miguel Ángel Rojo-Gala, Guillermo Pérez-Pérez, Sergio Bemposta Rosende and Natalia Gordo-Herrera
Drones 2024, 8(12), 725; https://doi.org/10.3390/drones8120725 - 30 Nov 2024
Viewed by 722
Abstract
The proposed system assists in the automatic creation of three-dimensional (3D) meshes for all types of objects, buildings, or scenarios, using drones with monocular RGB cameras. All these targets are large and located outdoors, which makes the use of drones for their capture [...] Read more.
The proposed system assists in the automatic creation of three-dimensional (3D) meshes for all types of objects, buildings, or scenarios, using drones with monocular RGB cameras. All these targets are large and located outdoors, which makes the use of drones for their capture possible. There are photogrammetry tools on the market for the creation of 2D and 3D models using drones, but this process is not fully automated, in contrast to the system proposed in this work, and it is performed manually with a previously defined flight plan and after manual processing of the captured images. The proposed system works as follows: after the region to be modeled is indicated, it starts the image capture process. This process takes place automatically, with the device always deciding the optimal route and the framing to be followed to capture all the angles and details. To achieve this, it is trained using the artificial intelligence technique of Double Deep Q-Learning Networks (reinforcement learning) to obtain a complete 3D mesh of the target. Full article
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19 pages, 9060 KiB  
Article
An Innovative New Approach to Light Pollution Measurement by Drone
by Katarzyna Bobkowska, Pawel Burdziakowski, Pawel Tysiac and Mariusz Pulas
Drones 2024, 8(9), 504; https://doi.org/10.3390/drones8090504 - 19 Sep 2024
Viewed by 1414
Abstract
The study of light pollution is a relatively new and specific field of measurement. The current literature is dominated by articles that describe the use of ground and satellite data as a source of information on light pollution. However, there is a need [...] Read more.
The study of light pollution is a relatively new and specific field of measurement. The current literature is dominated by articles that describe the use of ground and satellite data as a source of information on light pollution. However, there is a need to study the phenomenon on a microscale, i.e., locally within small locations such as housing estates, parks, buildings, or even inside buildings. Therefore, there is an important need to measure light pollution at a lower level, at the low level of the skyline. In this paper, the authors present a new drone design for light pollution measurement. A completely new original design for an unmanned platform for light pollution measurement is presented, which is adapted to mount custom sensors (not originally designed to be mounted on a unmanned aerial vehicles) allowing registration in the nadir and zenith directions. The application and use of traditional photometric sensors in the new configuration, such as the spectrometer and the sky quality meter (SQM), is presented. A multispectral camera for nighttime measurements, a calibrated visible-light camera, is used. The results of the unmanned aerial vehicle (UAV) are generated products that allow the visualisation of multimodal photometric data together with the presence of a geographic coordinate system. This paper also presents the results from field experiments during which the light spectrum is measured with the installed sensors. As the results show, measurements at night, especially with multispectral cameras, allow the assessment of the spectrum emitted by street lamps, while the measurement of the sky quality depends on the flight height only up to a 10 m above ground level. Full article
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18 pages, 50277 KiB  
Article
Generation of Virtual Ground Control Points Using a Binocular Camera
by Ariel Vazquez-Dominguez, Andrea Magadán-Salazar, Raúl Pinto-Elías, Jorge Fuentes-Pacheco, Máximo López-Sánchez and Hernán Abaunza-González
Drones 2024, 8(5), 195; https://doi.org/10.3390/drones8050195 - 12 May 2024
Viewed by 1401
Abstract
This paper presents a methodology for generating virtual ground control points (VGCPs) using a binocular camera mounted on a drone. We compare the measurements of the binocular and monocular cameras between the classical method and the proposed one. This work aims to decrease [...] Read more.
This paper presents a methodology for generating virtual ground control points (VGCPs) using a binocular camera mounted on a drone. We compare the measurements of the binocular and monocular cameras between the classical method and the proposed one. This work aims to decrease human processing times while maintaining a reduced root mean square error (RMSE) for 3D reconstruction. Additionally, we propose utilizing COLMAP to enhance reconstruction accuracy by solely utilizing a sparse point cloud. The results demonstrate that implementing COLMAP for pre-processing reduces the RMSE by up to 16.9% in most cases. We prove that VGCPs further reduce the RMSE by up to 61.08%. Full article
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24 pages, 10632 KiB  
Article
Automatic Real-Time Creation of Three-Dimensional (3D) Representations of Objects, Buildings, or Scenarios Using Drones and Artificial Intelligence Techniques
by Jorge Cujó Blasco, Sergio Bemposta Rosende and Javier Sánchez-Soriano
Drones 2023, 7(8), 516; https://doi.org/10.3390/drones7080516 - 5 Aug 2023
Viewed by 4359
Abstract
This work presents the development and evaluation of a real-time 3D reconstruction system using drones. The system leverages innovative artificial intelligence techniques in photogrammetry and computer vision (CDS-MVSNet and DROID-SLAM) to achieve the accurate and efficient reconstruction of 3D environments. By integrating vision, [...] Read more.
This work presents the development and evaluation of a real-time 3D reconstruction system using drones. The system leverages innovative artificial intelligence techniques in photogrammetry and computer vision (CDS-MVSNet and DROID-SLAM) to achieve the accurate and efficient reconstruction of 3D environments. By integrating vision, navigation, and 3D reconstruction subsystems, the proposed system addresses the limitations of existing applications and software in terms of speed and accuracy. The project encountered challenges related to scheduling, resource availability, and algorithmic complexity. The obtained results validate the applicability of the system in real-world scenarios and open avenues for further research in diverse areas. One of the tests consisted of a one-minute-and-three-second flight around a small figure, while the reconstruction was performed in real time. The reference Meshroom software completed the 3D reconstruction in 136 min and 12 s, while the proposed system finished the process in just 1 min and 13 s. This work contributes to the advancement in the field of 3D reconstruction using drones, benefiting from advancements in technology and machine learning algorithms. Full article
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