ArticleScientific reports2026
The use of multi-sensor drone data for the development and validation of methods to track and characterize marine animals.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.