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| Main Authors: | , , , , , |
|---|---|
| Format: | Artículo científico |
| Language: | en |
| Published: |
Scientific reports
2026
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| Online Access: | https://pubmed.ncbi.nlm.nih.gov/41484156/ |
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Table of Contents:
- The use of multi-sensor drone data for the development and validation of methods to track and characterize marine animals. Sexton, Kristian J Danko, Elise F Boesch, Austin Cheung, Nicholas DiGiacomo, Alexandra E Holt, Robert W Low cost, unmodified, commercially available drones can provide an effective platform for the study and characterization of marine megafauna. We present methods which utilize video and flight data to allow for both the continuous tracking of animals and the determination of animal lengths across a range of flight parameters. We also provide a thorough estimation of error in animal position and length measurements while at the same time introducing methods to correct for errors in reported aircraft altitude and heading. Methods are validated using both ground-based markers and tracking data from free swimming white sharks which includes the simultaneous tracking of individual sharks by two drones as the aircraft undergo changes in altitude, gimbal angle, heading and position. The resultant tracks are seen to be highly congruent (mean distance between measured positions: 4.3 m (95% CI 0 to 10)) and length measurements demonstrate a high level of precision (95% CI −8 to 8%) with accuracy confirmed using ground-based markers (mean error: 0.3% (95% CI −4.8 to 4.8%)). Results demonstrate the effectiveness of these methods across a range of flight conditions encountered in the field. The methods introduced allow flexibility in data capture while still providing accurate information, with the potential to both expand the use of and enhance the value of drone-based data for the quantification of animal behaviors and characteristics. The online version contains supplementary material available at 10.1038/s41598-025-31975-2.