ArticleEnvironmental science and pollution research international2026
The promise and pitfalls of monitoring harmful algal blooms (HABs) with remote sensing in pond-sized waterbodies.
Article in Environmental science and pollution research international, 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Harmful algal blooms (HABs) pose water quality risks, including the depletion of dissolved oxygen and human health impacts. Remote sensing is a proven tool for monitoring HABs, yet knowledge is limited about its effectiveness in pond-sized waterbodies, whose size and shape may preclude multi-spectral platforms with large spatial resolutions and increase the probability of mixed pixels. This comparative limnology case study evaluates whether optical remote sensing is a viable tool to monitor HABs in pond-sized waterbodies. We use Sentinel-2 imagery with previously studied chlorophyll-a and cyanobacteria detection algorithms and performed targeted in situ sampling in four small waterbodies in Boulder, CO, USA, from June to August 2021 to validate the algorithms and better understand underlying biogeochemical processes. The chlorophyll-a algorithm indicated persistent algal growth occurred in all waterbodies, yet only Sombrero Marsh chlorophyll-a expressed a statistically significant relationship with the remote sensing output (p < 0.0005, r
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.