Evidence map›Paper›PMID 41484156›Full record

ArticleScientific reports2026

The use of multi-sensor drone data for the development and validation of methods to track and characterize marine animals.

Kristian J Sexton, Elise F Danko, Austin Boesch, Nicholas Cheung, Alexandra E DiGiacomo, Robert W Holt

Abstract readValidation Study
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Kristian J SextonMoosh Systems, LLC, Wellfleet, MA, USA. mooshsystems@protonmail.com.
Elise F DankoMoosh Systems, LLC, Wellfleet, MA, USA.
Austin BoeschMoosh Systems, LLC, Wellfleet, MA, USA.
Nicholas CheungMoosh Systems, LLC, Wellfleet, MA, USA.
Alexandra E DiGiacomoBiology Department, Stanford University, Stanford, CA, USA.
Robert W HoltMoosh Systems, LLC, Wellfleet, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

AircraftAquatic OrganismsSharksAnimalsVideo RecordingAnimal trackingDrone accuracyDrone-based measurementsMarine megafaunaQuantitative imagingWhite shark

Identifiers

PMID41484156
PMCPMC12816707

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.