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Drones
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Drone Advances in Wildlife Research: 2nd Edition
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Drone Advances in Wildlife Research: 2nd Edition

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

Deadline for manuscript submissions: closed (19 February 2025) | Viewed by 6806

Special Issue Editors

Dr. Roxane Francis

E-Mail Website
Guest Editor
Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, UNSW, Randwick, NSW 2052, Australia
Interests: waterbirds; drones; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Kate Brandis

E-Mail Website
Guest Editor
Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, UNSW, Randwick, NSW 2052, Australia
Interests: waterbirds; environmental flows; stable isotopes; wildlife forensics; elemental analysis; bird ecology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Advances in uncrewed aerial vehicles (UAVs) have rapidly expanded their utility and use in the fields of wildlife research and conservation. Applications include monitoring, mapping, sample collection, and detection. In some fields of research, UAVs have provided a means of data collection that was not previously possible.

As a continuation of the last Special Issue on “Drone Advances in Wildlife Research”, this Special Issue still aims to identify new developments, methodologies, best practices, and applications of UAVs directly related to wildlife research (flora and fauna) and conservation. We welcome submissions that provide the community with the most recent advances in the use of UAVs for wildlife research including, but not limited to, the following:

  • UAV data collection methods;
  • Data processing;
  • Machine learning and AI;
  • Multispectral data;
  • Conservation applications;
  • Ecological monitoring;
  • Flora and fauna drone-related research;
  • Aquatic and terrestrial environments;

This SI aims to be gender-diverse, with 50% of manuscripts led by female-identifying authors. We also strongly encourage submissions from the developing world. In addition, this SI will use the non-gendered term ‘uncrewed’ aerial vehicle.

Dr. Roxane Francis
Dr. Kate Brandis
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

  • wildlife
  • UAV
  • fauna
  • flora
  • drones
  • conservation

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Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (4 papers)

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Research

21 pages, 3597 KiB  
Article
Tracking Fin Whale Morphology with Drone Photogrammetry: Growth Tendencies, Developmental Changes, and Sexual Dimorphism
by Dorottya Mészáros, Beatriu Tort and Eduard Degollada
Drones 2025, 9(4), 290; https://doi.org/10.3390/drones9040290 - 9 Apr 2025
Viewed by 647
Abstract
Morphological changes during body development measurements are crucial in understanding growth rates, allometric relationships, and sexual dimorphism. Recent advances in drone technology provide a new perspective enabling an indirect, non-invasive morphological assessment of free-ranging cetaceans. In this study, 10 body parameters were measured [...] Read more.
Morphological changes during body development measurements are crucial in understanding growth rates, allometric relationships, and sexual dimorphism. Recent advances in drone technology provide a new perspective enabling an indirect, non-invasive morphological assessment of free-ranging cetaceans. In this study, 10 body parameters were measured and examined with drone-based aerial photogrammetry across 82 individual fin whales (Balaenoptera physalus) along the Catalan coast of the Northwestern Mediterranean Sea, between 2021 and 2023. The growth pattern of each body parameter relative to the total length was determined as negative allometry. The developmental changes depicted that the head region at first decreases proportionally until the animal reaches approximately 14 m in length. Then, it remains constant until 18 m, subsequently followed by a relative increase. The difference in the growth rates among the sexes leads to a proportional shift between females and males approximately between 15 and 17 m in length. Overall, males exhibit a more rapid body elongation, along with moderate development of the other body parameters, while females display the contrary. The morphological parameters reveal insights into the population status dynamics and provide information on the reproductive status. These parameters are critical for the proper conservation and management of the local population of the species. Full article
(This article belongs to the Special Issue Drone Advances in Wildlife Research: 2nd Edition)
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28 pages, 16135 KiB  
Article
Advances in Surveying Topographically Complex Ecosystems with UAVs: Manta Ray Foraging Algorithms
by Shijie Yang, Jiateng Yuan, Zhibo Chen, Hanchao Zhang and Xiaohui Cui
Drones 2024, 8(11), 631; https://doi.org/10.3390/drones8110631 - 1 Nov 2024
Cited by 1 | Viewed by 1378
Abstract
This study introduces an innovative UAV cruise data collection path planning approach using the manta ray foraging optimization (MRFO) algorithm to enhance efficiency and energy utilization in forest ecosystem monitoring. Traditionally reliant on costly manual patrols, this method leverages UAVs and ground-based sensors [...] Read more.
This study introduces an innovative UAV cruise data collection path planning approach using the manta ray foraging optimization (MRFO) algorithm to enhance efficiency and energy utilization in forest ecosystem monitoring. Traditionally reliant on costly manual patrols, this method leverages UAVs and ground-based sensors for data collection. The approach begins with a self-organized clustering algorithm for sensors, minimizing communication between UAVs and sensors. It then refines the UAV’s energy consumption equation by integrating propulsion energy needs, actual terrain data, and wind effects. Compared to other heuristic algorithms, the MRFO algorithm demonstrates superior performance in path planning, particularly for complex engineering optimization problems, displaying heightened adaptability and efficiency. Comparative experimental results on real terrain data and MATLAB r2018b simulation show that the error between the corrected energy calculation equation and the actual value is controlled within 5%, and the accuracy is improved by 10% over the original equation. Meanwhile, the ability of the MRFO algorithm to quickly construct approximate high-quality solutions with shortest path lengths in a limited number of iterations validates its potential in practical applications. The α-hop clustering algorithm used in this paper has a huge advantage in space and time complexity compared with existing clustering algorithms, and the accuracy of data extraction is relatively improved by 7.57% and 6.95%. Real forest digital elevation model (DEM) terrain data was introduced in this study, and the method improves the energy utilization of UAV data collection and also provides a comprehensive and detailed solution to the existing challenges faced in the field of forest data collection. Future research could consider combining the MRFO algorithm with other evolutionary classes of algorithms to take advantage of the algorithm’s fast convergence and high-precision properties to further enhance the application prospects in different scenarios. Full article
(This article belongs to the Special Issue Drone Advances in Wildlife Research: 2nd Edition)
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22 pages, 5517 KiB  
Article
Vegetation Type Preferences in Red Deer (Cervus elaphus) Determined by Object Detection Models
by Annika Fugl, Lasse Lange Jensen, Andreas Hein Korsgaard, Cino Pertoldi and Sussie Pagh
Drones 2024, 8(10), 522; https://doi.org/10.3390/drones8100522 - 26 Sep 2024
Cited by 1 | Viewed by 1342
Abstract
This study investigates the possibility of utilising a drone equipped with a thermal camera to monitor the spatial distribution of red deer (Cervus elaphus) and to determine their behavioural patterns, as well as preferences for vegetation types in a moor in [...] Read more.
This study investigates the possibility of utilising a drone equipped with a thermal camera to monitor the spatial distribution of red deer (Cervus elaphus) and to determine their behavioural patterns, as well as preferences for vegetation types in a moor in Denmark. The spatial distribution of red deer was mapped according to time of day and vegetation types. Reed deer were separated manually from fallow deer (Dama dama) due to varying footage quality. Automated object detection from thermal camera footage was used to identification of two behaviours, “Eating” and “Lying”, enabling insights into the behavioural patterns of red deer in different vegetation types. The results showed a migration of red deer from the moors to agricultural fields during the night. The higher proportion of time spent eating in agricultural grass fields compared to two natural vegetation types, “Grey dune” and “Decalcified fixed dune”, indicates that fields are important foraging habitats for red deer. The red deer populations were observed significantly later on grass fields compared to the natural vegetation types. This may be due to human disturbance or lack of randomisation of the flight time with the drone. Further studies are suggested across different seasons as well as the time of day for a better understanding of the annual and diurnal foraging patterns of red deer. Full article
(This article belongs to the Special Issue Drone Advances in Wildlife Research: 2nd Edition)
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13 pages, 16692 KiB  
Article
Assessment of Ground and Drone Surveys of Large Waterbird Breeding Rookeries: A Comparative Study
by Roxane J. Francis and Kate J. Brandis
Drones 2024, 8(4), 135; https://doi.org/10.3390/drones8040135 - 2 Apr 2024
Cited by 1 | Viewed by 2359
Abstract
Assessing nesting metrics in large waterbird breeding rookeries is challenging due to their size and accessibility. Drones offer a promising solution, but their comparability with ground surveys remains debated. In our study, we directly compared ground and drone data collected simultaneously over the [...] Read more.
Assessing nesting metrics in large waterbird breeding rookeries is challenging due to their size and accessibility. Drones offer a promising solution, but their comparability with ground surveys remains debated. In our study, we directly compared ground and drone data collected simultaneously over the same breeding areas. Drones excel in accessing remote terrain, enhancing coverage, mapping colony extent and reducing sampling bias. However, flying at the low altitudes required to capture young chicks in nests within densely populated rookeries poses challenges, often requiring observer presence and diminishing the distance advantage. Drones enable rapid data collection and facilitate accurate ibis chick counts, particularly at the “runner” stage when chicks are very mobile, and our surveys found significant differences in the counts between drone and ground surveys at this nesting stage. Ground surveys, on the other hand, provide valuable contextual observations, including water variables and sensory cues concerning the health of the colony. Both methods offer unique insights, with drones providing high-resolution aerial data and ground surveys complementing with human observations. Integrating both methods is ideal for comprehensive waterbird monitoring and conservation. Full article
(This article belongs to the Special Issue Drone Advances in Wildlife Research: 2nd Edition)
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