nerc.ac.uk

Review of Satellite Remote Sensing and Unoccupied Aircraft Systems for Counting Wildlife on Land

Attard, Marie R.G. ORCID: https://orcid.org/0000-0002-8509-3677; Phillips, Richard A.; Bowler, Ellen; Clarke, Penny J. ORCID: https://orcid.org/0000-0002-2648-9639; Cubaynes, Hannah ORCID: https://orcid.org/0000-0002-9497-154X; Johnston, David W.; Fretwell, Peter T. ORCID: https://orcid.org/0000-0002-1988-5844. 2024 Review of Satellite Remote Sensing and Unoccupied Aircraft Systems for Counting Wildlife on Land. Remote Sensing, 16 (4), 627. 23, pp. https://doi.org/10.3390/rs16040627

Before downloading, please read NORA policies.
[img]
Preview
Text (Open Access)
© 2024 by the authors. Licensee MDPI, Basel, Switzerland.
remotesensing-16-00627.pdf - Published Version
Available under License Creative Commons Attribution 4.0.

Download (3MB) | Preview

Abstract/Summary

Although many medium-to-large terrestrial vertebrates are still counted by ground or aerial surveys, remote-sensing technologies and image analysis have developed rapidly in recent decades, offering improved accuracy and repeatability, lower costs, speed, expanded spatial coverage and increased potential for public involvement. This review provides an introduction for wildlife biologists and managers relatively new to the field on how to implement remote-sensing techniques (satellite and unoccupied aircraft systems) for counting large vertebrates on land, including marine predators that return to land to breed, haul out or roost, to encourage wider application of these technological solutions. We outline the entire process, including the selection of the most appropriate technology, indicative costs, procedures for image acquisition and processing, observer training and annotation, automation, and citizen science campaigns. The review considers both the potential and the challenges associated with different approaches to remote surveys of vertebrates and outlines promising avenues for future research and method development.

Item Type: Publication - Article
Digital Object Identifier (DOI): https://doi.org/10.3390/rs16040627
ISSN: 20724292
Additional Keywords: aerial counts; drone; ground counts; remote sensing; unmanned aerial vehicle; wildlife; research
Date made live: 13 Feb 2024 13:57 +0 (UTC)
URI: https://nora.nerc.ac.uk/id/eprint/536793

Actions (login required)

View Item View Item

Document Downloads

Downloads for past 30 days

Downloads per month over past year

More statistics for this item...