Evidence map›Paper›PMID 41150176›Full record

ReviewToxins2025

Harmful Algal Bloom Monitoring with Unmanned Aerial Vehicles: Tools, Challenges, and Public Health Implications.

Kendall Byrd, Jianyong Wu, Jiyoung Lee

Abstract readReview
In one paragraph

Review in Toxins, 2025. 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

3 authors.

Kendall ByrdEnvironmental Sciences Graduate Program, The Ohio State University, Columbus, OH 43210, USA.ORCID 0009-0004-4523-9290
Jianyong WuDivision of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH 43210, USA.ORCID 0000-0002-5864-3186
Jiyoung LeeDivision of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH 43210, USA.ORCID 0000-0001-8936-1555

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Harmful algal blooms (HABs) are an escalating global concern due to their increasing frequency, duration, intensity, and geographic spread. These events threaten public health by contaminating drinking water sources, recreational areas, and food production systems with cyanotoxins. Effective monitoring is critical but remains limited by the spatial and temporal variability of blooms. Unmanned aerial vehicles (UAVs) have recently emerged as a flexible, high-resolution tool for HAB monitoring that can complement satellite and in situ methods. This review synthesizes recent applications of UAVs in HAB detection, mapping, and sampling, with a focus on how these approaches can support public health interventions. Key UAV platforms, sensor types, and data processing workflows are summarized, along with considerations related to flight regulations. Studies linking UAV data to indicators like chlorophyll-a and phycocyanin are discussed, highlighting their relevance for early warning systems and water treatment responses. Finally, the review identifies persistent challenges-including validation, regulatory gaps, and integration with health risk frameworks-and provides recommendations to advance UAV-based monitoring. These insights support the continued development of UAV systems as part of comprehensive strategies to mitigate HAB-related health risks.

Indexed as

Environmental MonitoringHarmful Algal BloomUnmanned Aerial DevicesHumansPublic Healthchlorophyll-acyanotoxinsharmful algal bloomshyperspectral imagingmultispectral imagingphycocyaninpublic healthremote sensingunmanned aerial vehicles

Identifiers

PMID41150176
PMCPMC12567913

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.