Evidence map›Paper›PMID 40363176›Full record

ArticleSensors (Basel, Switzerland)2025

Quantitative Estimation of Organic Pollution in Inland Water Using Sentinel-2 Multispectral Imager.

Jiayi Li, Ruru Deng, Yu Guo, Cong Lei, Zhenqun Hua, Junying Yang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

6 authors.

Jiayi LiSchool of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China.ORCID 0000-0002-3678-1545
Ruru DengSchool of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China.ORCID 0000-0002-4560-2000
Yu GuoSchool of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China.ORCID 0000-0001-8382-1485
Cong LeiSchool of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China.
Zhenqun HuaSchool of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China.
Junying YangSchool of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China.

Funding

Guangdong Basic and Applied Basic Research Foundation 2020A1515010780 and 2022B1515130001Guangzhou Science and Technology Programme 202102020454National Natural Science Foundation of China 41071230 and 41901352Science and Technology Planning Project of Guangdong Province, China 2017B020216001
6 · The paper itself

Abstract

Organic pollution poses a significant threat to water security, making the monitoring of organic pollutants in water environments essential for the protection of water resources. Remote sensing technology, with its wide coverage, continuous monitoring capability, and cost-efficiency, overcomes the limitations of traditional methods, which are often time-consuming, labor-intensive, and spatially restricted. As a result, it has become an effective tool for monitoring organic pollution in water environments. In this study, we propose a physically constrained remote sensing algorithm for the quantitative estimation of organic pollution in inland waters based on radiative transfer theory. The algorithm was applied to the Feilaixia Basin using Sentinel-2 data. Accuracy assessment results demonstrate good performance in the quantitative assessment of organic pollution, with a coefficient of determination (R

Indexed as

Feilaixia basinorganic pollutionradiative transfer modelSentinel-2water quality remote sensing

Identifiers

PMID40363176
PMCPMC12074346

What OpenQuestion holds

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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.