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

Deadline for manuscript submissions: closed (20 February 2024) | Viewed by 21572

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Special Issue Editors

Dr. Miroslaw Zimnoch

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Guest Editor

Department of Applied Nuclear Physics, Faculty of Physics and Applied Computer Science, AGH-University of Science and Technology, 30-059 Kraków, Poland
Interests: atmosphere dynamics and composition; application of isotope tracers for greenhouse gas cycling studies; application of UAVs (unmanned aerial vehicles) in atmospheric studies; numerical modeling of the atmospheric circulation and greenhouse gas transport
Special Issues, Collections and Topics in MDPI journals

Dr. Paweł Ćwiąkała

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Guest Editor

Department of Engineering Surveying and Civil Engineering, AGH University of Science and Technology in Kraków, 30-059 Krakow, Poland
Interests: surveying and mapping; photogrammetric computer vision; UAV; deformation monitoring in mining areas; buildings and civil structures monitoring; cultural heritage; archaeological prospecting

Special Issue Information

Dear Colleagues,

We are pleased to invite you to submit manuscripts to a MDPI Drones Special Issue on “Unmanned Aerial Vehicles in Atmospheric Research”.

The ever-expanding range of drone applications observed in recent years is also taking place in the field of atmospheric research. The increasing availability and reliability of these platforms opens new opportunities in the study of various processes occurring in the planetary boundary layer and at the interface between the Earth's surface and atmosphere. These studies allow us to fill the gap between surface measurements and methods, enabling the observation of atmospheric profiles at higher altitudes (aircraft, LIDAR, satellite observations). Additionally, the acquisition of surface images from relatively low altitudes allows us to drastically increase the resolution of these images and develop downscaling methods for satellite products. On the other hand, the availability of a variety of low-cost sensors that allow the measurement of trace gas or pollutant concentrations opens opportunities for the development of methods to identify the emission sources of these components and estimate their emission rates.

Within this context, we invite manuscripts for this Special Issue on “Unmanned Aerial Vehicles in Atmospheric Research”. Papers are welcome in areas directly related to these topics, both conceptual and applied in nature, including (but not limited to) the following:

Profiling of the planetary boundary layer;
Urban meteorology;
Influence of topography and land use on boundary layer dynamics;
High-resolution atmospheric modelling;
Identification of GHG or pollutant surface emissions;
Estimation of GHG or pollutant emission rates;
Application of machine-learning algorithms to interpret airborne datasets;
Development of down-scaling algorithms based on UAV-collected datasets;
New developments in the area of drone-based sensors and measurement systems;
Investigation of in-cloud processes;
Estimation of surface energy balance components using drone data.

Dr. Miroslaw Zimnoch
Dr. Paweł Ćwiąkała
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

boundary layer dynamics
greenhouse gases
air pollution
urban meteorology
surface emission estimates
drones
UAV
remote sensing
surface–atmosphere interaction
surface energy balance

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Published Papers (6 papers)

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Research

14 pages, 4004 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Exploring Meteorological Conditions and Microscale Temperature Inversions above the Great Barrier Reef through Drone-Based Measurements

by Christian Eckert, Kim I. Monteforte, Daniel P. Harrison and Brendan P. Kelaher

Drones 2023, 7(12), 695; https://doi.org/10.3390/drones7120695 - 4 Dec 2023

Cited by 2 | Viewed by 2767

Abstract

Understanding the atmospheric conditions in remote areas contributes to assessing local weather phenomena. Obtaining vertical profiles of the atmosphere in isolated locations can introduce significant challenges for the deployment and maintenance of equipment, as well as regulatory obstacles. Here, we assessed the potential of consumer drones equipped with lightweight atmospheric sensors to collect vertical meteorological profiles off One Tree Island (Great Barrier Reef), located approximately 85 km off the east coast of Australia. We used a DJI Matrice 300 drone with two InterMet Systems iMet-XQ2 UAV sensors, capturing data on atmospheric pressure, temperature, relative humidity, and wind up to an altitude of 1500 m. These flights were conducted three times per day (9 a.m., 12 noon, and 3 p.m.) and compared against ground-based weather sensors. Over the Austral summer/autumn, we completed 72 flights, obtaining 24 complete sets of daily measurements of atmospheric characteristics over the entire vertical profile. On average, the atmospheric temperature and dewpoint temperature were significantly influenced by the time of sampling, and also varied among days. The mean daily temperature and dewpoint temperature reached their peaks at 3 p.m., with the temperature gradually rising from its morning low. The mean dewpoint temperature obtained its lowest point around noon. We also observed wind speed variations, but changes in patterns throughout the day were much less consistent. The drone-mounted atmospheric sensors exhibited a consistent warm bias in temperature compared to the reference weather station. Relative humidity showed greater variability with no clear bias pattern, indicating potential limitations in the humidity sensor’s performance. Microscale temperature inversions were prevalent around 1000 m, peaking around noon and present in approximately 27% of the profiles. Overall, the drone-based vertical profiles helped characterise atmospheric dynamics around One Tree Island Reef and demonstrated the utility of consumer drones in providing cost-effective meteorological information in remote, environmentally sensitive areas. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles in Atmospheric Research)

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19 pages, 43158 KiB

Open AccessArticle

Self-Calibration of UAV Thermal Imagery Using Gradient Descent Algorithm

by Radosław Szostak, Mirosław Zimnoch, Przemysław Wachniew and Alina Jasek-Kamińska

Drones 2023, 7(11), 683; https://doi.org/10.3390/drones7110683 - 20 Nov 2023

Cited by 1 | Viewed by 2381

Abstract

Unmanned aerial vehicle (UAV) thermal imagery offers several advantages for environmental monitoring, as it can provide a low-cost, high-resolution, and flexible solution to measure the temperature of the surface of the land. Limitations related to the maximum load of the drone lead to the use of lightweight uncooled thermal cameras whose internal components are not stabilized to a constant temperature. Such cameras suffer from several unwanted effects that contribute to the increase in temperature measurement error from ±0.5 °C in laboratory conditions to ±5 °C in unstable flight conditions. This article describes a post-processing procedure that reduces the above unwanted effects. It consists of the following steps: (i) devignetting using the single image vignette correction algorithm, (ii) georeferencing using image metadata, scale-invariant feature transform (SIFT) stitching, and gradient descent optimisation, and (iii) inter-image temperature consistency optimisation by minimisation of bias between overlapping thermal images using gradient descent optimisation. The solution was tested in several case studies of river areas, where natural water bodies were used as a reference temperature benchmark. In all tests, the precision of the measurements was increased. The root mean square error (RMSE) on average was reduced by 39.0% and mean of the absolute value of errors (MAE) by 40.5%. The proposed algorithm can be called self-calibrating, as in contrast to other known solutions, it is fully automatic, uses only field data, and does not require any calibration equipment or additional operator effort. A Python implementation of the solution is available on GitHub. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles in Atmospheric Research)

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23 pages, 6362 KiB

Open AccessArticle

In Situ VTOL Drone-Borne Observations of Temperature and Relative Humidity over Dome C, Antarctica

by Philippe Ricaud, Patrice Medina, Pierre Durand, Jean-Luc Attié, Eric Bazile, Paolo Grigioni, Massimo Del Guasta and Benji Pauly

Drones 2023, 7(8), 532; https://doi.org/10.3390/drones7080532 - 15 Aug 2023

Cited by 2 | Viewed by 2174

Abstract

The Antarctic atmosphere is rapidly changing, but there are few observations available in the interior of the continent to quantify this change due to few ground stations and satellite measurements. The Concordia station is located on the East Antarctic Plateau (75° S, 123° E, 3233 m above mean sea level), one of the driest and coldest places on Earth. Several remote sensing instruments are available at the station to probe the atmosphere, together with operational meteorological sensors. In order to observe in situ clouds, temperature, relative humidity and supercooled liquid water (SLW) at a high vertical resolution, a new project based on the use of an unmanned aerial vehicle (drone) vertical take-off and landing from the DeltaQuad Company has been set up at Concordia. A standard Vaisala pressure, temperature and relative humidity sensor was installed aboard the drone coupled to an Anasphere SLW sensor. A total of thirteen flights were conducted from 24 December 2022 to 17 January 2023: nine technology flights and four science flights (on 2, 10, 11 and 13 January 2023). Drone-based temperature and relative humidity profiles were compared to (1) the balloon-borne meteorological observations at 12:00 UTC, (2) the ground-based microwave radiometer HAMSTRAD and (3) the outputs from the numerical weather prediction models ARPEGE and AROME. No SLW clouds were present during the period of observations. Despite technical issues with drone operation due to the harsh environments encountered (altitude, temperature and geomagnetic field), the drone-based observations were consistent with the balloon-borne observations of temperature and relative humidity. The radiometer showed a systematic negative bias in temperature of 2 °C, and the two models were, in the lowermost troposphere, systematically warmer (by 2–4 °C) and moister (by 10–30%) than the drone-based observations. Our study shows the great potential of a drone to probe the Antarctic atmosphere in situ at very high vertical resolution (a few meters). Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles in Atmospheric Research)

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12 pages, 20895 KiB

Open AccessArticle

Wind Speed Measurement by an Inexpensive and Lightweight Thermal Anemometer on a Small UAV

by Jun Inoue and Kazutoshi Sato

Drones 2022, 6(10), 289; https://doi.org/10.3390/drones6100289 - 3 Oct 2022

Cited by 9 | Viewed by 6943

Abstract

Profiling wind information when using a small unmanned aerial vehicle (sUAV) is vital for atmospheric profiling and monitoring attitude during flight. Wind speed on an sUAV can be measured directly using ultrasonic anemometers or by calculating its attitude control information. The former method requires a relatively large payload for an onboard ultrasonic anemometer, while the latter requires real-time flight log data access, which depends on the UAV manufacturers. This study proposes the feasibility of a small thermal anemometer to measure wind speeds inexpensively using a small commercial quadcopter (DJI Mavic2: M2). A laboratory experiment demonstrated that the horizontal wind speed bias increased linearly with ascending sUAV speed. A smoke experiment during hovering revealed the downward wind bias (1.2 m s

^{- 1}

) at a 12-cm height above the M2 body. Field experiments in the ice-covered ocean demonstrated that the corrected wind speed agreed closely with the shipboard wind data observed by a calibrated ultrasonic anemometer. A dual-mount system comprising thermal anemometers was proposed to measure wind speed and direction. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles in Atmospheric Research)

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11 pages, 13603 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Investigating Errors Observed during UAV-Based Vertical Measurements Using Computational Fluid Dynamics

by Hayden Hedworth, Jeffrey Page, John Sohl and Tony Saad

Drones 2022, 6(9), 253; https://doi.org/10.3390/drones6090253 - 13 Sep 2022

Cited by 7 | Viewed by 4197

Abstract

Unmanned Aerial Vehicles (UAVs) are a popular platform for air quality measurements. For vertical measurements, rotary-wing UAVs are particularly well-suited. However, an important concern with rotary-wing UAVs is how the rotor-downwash affects measurement accuracy. Measurements from a recent field campaign showed notable discrepancies between data from ascent and descent, which suggested the UAV downwash may be the cause. To investigate and explain these observed discrepancies, we use high-fidelity computational fluid dynamics (CFD) simulations to simulate a UAV during vertical flight. We use a tracer to model a gaseous pollutant and evaluate the impact of the rotor-downwash on the concentration around the UAV. Our results indicate that, when measuring in a gradient, UAV-based measurements were ∼50% greater than the expected concentration during descent, but they were accurate during ascent, regardless of the location of the sensor. These results provide an explanation for errors encountered during vertical measurements and provide insight for accurate data collection methods in future studies. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles in Atmospheric Research)

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10 pages, 2128 KiB

Open AccessArticle

Using Semicircular Sampling to Increase Sea-Wind Retrieval Altitude with a High-Altitude UAV Scatterometer

by Alexey Nekrasov, Alena Khachaturian and Colin Fidge

Drones 2022, 6(9), 223; https://doi.org/10.3390/drones6090223 - 26 Aug 2022

Cited by 2 | Viewed by 1660

Abstract

Currently, unmanned aerial vehicles (UAVs) are widely used due to their low cost and flexibility. In particular, they are used in remote sensing as airborne platforms for various instruments. Here, we investigate the capability of a conical scanning radar operated as a scatterometer mounted on a high-altitude UAV to perform sea surface wind retrieval based on an appropriate geophysical model function (GMF). Increasing the maximum altitude of the wind retrieval method’s applicability is an important problem for UAV or manned aircraft scatterometers. For this purpose, we consider the possibility of increasing the method’s maximum altitude by applying a semicircular scheme for azimuth normalized radar cross section (NRCS) sampling instead of a whole 360° circular scheme. We developed wind retrieval algorithms for both semicircular and circular NRCS sampling schemes and evaluated them using Monte Carlo simulations. The simulations showed that the semicircular scheme for azimuth NRCS sampling enables twice the maximum altitude for wind retrieval compared to a 360° circular scheme. At the same time, however, the semicircular scheme requires approximately three times the number of integrated NRCS samples in each azimuth sector to provide equivalent wind retrieval accuracy. Nonetheless, our results confirm that the semicircular azimuth NRCS sampling scheme is well-suited for wind retrieval, and any wind retrieval errors are within the typical range for scatterometer wind recovery. The obtained results can be used for enhancing existing UAV and aircraft radars, and for the development of new remote sensing systems. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles in Atmospheric Research)

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