Evidence map›Paper›PMID 42761572›Full record

ArticleMethodsX2026

Open-source satellite image pre-processing and annotation workflows: Stranded whale and dolphin case study.

Penny J Clarke, Hannah C Cubaynes, Karen A Stockin, Ellen Bowler, Kris Carlyon, Marie R G Attard, Peter T Fretwell, Aliaksandra Skachkova, Asha de Vos, Kaitlin M McConnell and 3 more

Abstract read
In one paragraph

Article in MethodsX, 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

13 authors.

Penny J ClarkeBritish Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, United Kingdom.
Hannah C CubaynesBritish Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, United Kingdom.
Karen A StockinCetacean Ecology Research Group, School of Natural Sciences, Massey University, Auckland, New Zealand.
Ellen BowlerBritish Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, United Kingdom.
Kris CarlyonMarine Conservation Program, Department of Natural Resources and Environment Tasmania (NRE Tas), Tasmanian Government, 134 Macquarie St, Hobart TAS 7000, Australia.
Marie R G AttardBritish Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, United Kingdom.
Peter T FretwellBritish Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, United Kingdom.
Aliaksandra SkachkovaBritish Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, United Kingdom.
Asha de VosOceanswell, Colombo, Sri Lanka.
Kaitlin M McConnellEstación Científica Fundación San Ignacio del Huinay, Fiordo Comau, Región de Los Lagos, Chile.
Encarni Medina-LopezUniversity of Edinburgh, King's Buildings, Thomas Bayes Road, Edinburgh, EH9 3FG, United Kingdom.
Sergio Lopez DubonUniversity of Edinburgh, King's Buildings, Thomas Bayes Road, Edinburgh, EH9 3FG, United Kingdom.
Jennifer A JacksonBritish Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Very high-resolution (VHR) satellite imagery can increase the temporal frequency and spatial scale of wildlife studies and complement conventional monitoring methods, to address data gaps globally. However, most gaps in wildlife monitoring, particularly the study of stranded cetaceans, coincide with less-resourced countries, and commercially operated VHR satellite imagery are costly. Increasing access to imagery, expertise, resources, and open access tools is therefore, essential to achieving a globally scalable solution for wildlife monitoring using VHR satellite imagery. This study provides open access workflows to pre-process and annotate satellite imagery by publishing:•a step-by-step VHR satellite image pre-processing and annotation workflow for detecting features of interest (geolocated point, bounding box and image chip outputs), developed using QGIS 3.28.•a replicable step-by-step VHR satellite image pre-processing and annotation workflow in Python 3.10.•a data standard for the 'satellites to study stranded cetaceans' community, including a template for recording annotation metadata and accompanying training document, to enable data sharing internationally.In the long term, greater equity of access to satellite imagery and workflows like those shared here, will innovate applications and methodological developments to improve environmental management outcomes and empower local communities to lead in this space.

Indexed as

Cetacean strandingColonial scienceMachine learningRemote sensingStandardised training dataVHR optical satellite imageryWildlife

Identifiers

PMID42761572
PMCPMC13586820

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.