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Camera trapping with photos and videos: implications for ecology and citizen science

Green, Sian E. and Stephens, Philip A. and Whittingham, Mark J. and Hill, Russell A. (2022) 'Camera trapping with photos and videos: implications for ecology and citizen science.', Remote Sensing in Ecology and Conservation .


Camera traps are increasingly used in wildlife monitoring and citizen science to address an array of ecological questions on a wide variety of species. However, despite the ability of modern camera traps to capture high-quality video, the majority of studies collect still images, in part because of concerns with video performance. We conducted a camera trap survey of a forested landscape in the UK, using a grid of paired camera traps, to quantify the impact of using video compared to photos on the outcomes of ecological research and for participation and engagement of citizen scientists. Ecological outputs showed no difference between photo and video datasets, but comparison between expert and citizen science classifications showed citizen scientists were able to classify videos more accurately (average accuracy of 95% for video, 86% for photo). Furthermore, citizen scientists were more likely to volunteer additional information on age (provided for 61% videos, 30% photos) and sex (provided for 63% videos, 45% photos) of animals in video footage. Concerns over slow trigger speeds for videos did not appear to affect our datasets or the inferences gained. When combined with citizen science, video datasets are likely to be of higher quality due to increased classification accuracy. Consequently, we encourage researchers to consider the use of video for future camera trapping projects.

Item Type:Article
Full text:Publisher-imposed embargo
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Available under License - Creative Commons Attribution 4.0.
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Publisher statement:© 2022 The Authors. Remote Sensing in Ecology and Conservation published by John Wiley & Sons Ltd on behalf of Zoological Society of London. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Date accepted:10 September 2022
Date deposited:12 September 2022
Date of first online publication:24 September 2022
Date first made open access:12 October 2022

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