A novel method for mapping high‐precision animal locations using high‐resolution imagery
Abstract Investigating ecological questions at the scale of individual organisms is necessary to understand and predict the biological consequences of changing environmental conditions. For small organisms, this can be challenging because ecologists need tools with the appropriate accuracy, precision, and resolution to record and quantify their ecological interactions. Unfortunately, many existing tools are only appropriate for medium to large organisms or those that are wide‐ranging, inhibiting our ability to investigate the spatial ecology of small organisms at fine scales. Here, we tested a novel workflow for recording animal locations at very fine (decimeter) spatial scales, which we refer to as high‐resolution orthomosaic location recording (HOLR). The workflow for HOLR combined direct observations with data collection of locations on high‐resolution uncrewed aerial vehicle (UAV) imagery loaded on smartphones. Observers identified landscape features they recognized in the imagery and estimated positions relative to these visual landmarks. We found HOLR was approximately twice as accurate as consumer‐grade GPS devices, with a mean error of 0.75 m and a median error of 0.30 m. We also found that performance varied across landscape features, with the highest accuracy in areas that had more visual landmarks for observers to use as reference points. In addition to submeter accuracy, HOLR was cost‐effective and practical in the field, requiring no bulky equipment and allowing observers to easily record locations away from their own position. This workflow can be used to record locations in a variety of situations, but it will be particularly cost‐effective when users simultaneously utilize the high‐resolution environmental data contained within UAV imagery. Together, these tools can expand the application of spatial ecology research to smaller organisms than ever before.
Authors
- Geoffrey A. Fricker (ORCID: https://orcid.org/0000-0001-6310-3427)
- William T. Bean (ORCID: https://orcid.org/0000-0001-6595-5885)
- Ian J. Axsom
Institutions
- California Polytechnic State University (US)
Publication Details
- Journal
- Ecosphere
- Published
- 2025-02-01
- DOI
- https://doi.org/10.1002/ecs2.70173
- Citations
- 1
- Primary Topic
- Species Distribution and Climate Change
- Type
- article
- Field-Weighted Citation Impact
- 1.84
Funders
- U.S. Bureau of Land Management