Using Drones for Large Mammal Monitoring

Elchik, CC, Hudson, M, Buckland, S, Longmore, S ORCID: 0000-0001-6353-0170 and Wich, S ORCID: 0000-0003-3954-5174 (2026) Using Drones for Large Mammal Monitoring. Mammal Review, 56 (3). ISSN 0305-1838

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Abstract

Introduction: The emergence of drones has profoundly transformed the field of large mammal monitoring, offering unprecedented capabilities for data collection on both terrestrial and aquatic species but challenges remain for data collection and analyses. Aims: In this Practice Insights article we provide a succinct review of drone types, their sensors and main applications to monitor large terrestrial mammals. We focus on obtaining key ecological metrics through using drones: presence/absence, population density and overall abundance, including spatial distribution. We also review machine learning efforts to automate animal detection and tracking, as well as the statistical methods to estimate animal density. Methods: We provide a new method to determine animal locations from RGB videos obtained with drones. The geolocation method shows promising results with an accuracy of between 1.58 and 3.1 m on a small test sample, which is an improvement over those from crewed aircraft. Discussion: Challenges for drone usage in terms of data collection and analyses remain but both are becoming increasingly more user friendly. There are still challenges such as the lack of open-source deep learning models to detect mammals and classify them but we expect this to be solved in the coming years. In addition the analytical workflows to move from such detections and classifications will likely become more user friendly as well.

Item Type:	Article
Uncontrolled Keywords:	3109 Zoology; 3103 Ecology; 31 Biological Sciences; Bioengineering; Networking and Information Technology R&D (NITRD); Machine Learning and Artificial Intelligence; Generic health relevance; 0602 Ecology; 0608 Zoology; Ecology; 3103 Ecology; 3109 Zoology
Subjects:	G Geography. Anthropology. Recreation > GE Environmental Sciences Q Science > QH Natural history > QH301 Biology T Technology > T Technology (General)
Divisions:	Astrophysics Research Institute Biological and Environmental Sciences (from Sep 19)
Publisher:	Wiley
Date of acceptance:	19 June 2026
Date of first compliant Open Access:	4 September 2026
Date Deposited:	04 Sep 2026 08:48
Last Modified:	04 Sep 2026 08:48
DOI or ID number:	10.1111/mam.70044
URI:	https://researchonline.ljmu.ac.uk/id/eprint/29322

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