Evidence map›Paper›PMID 40121204›Full record

ArticleScientific data2025

Prolonged water body types dataset of urban agglomeration in central China from 1990 to 2021.

Haozheng Ma, Xiaohong Yang, Runyu Fan, Kang He, Lizhe Wang

Abstract read
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Haozheng MaChina University of Geosciences, Wuhan, School of Computer Science, Wuhan, 430078, China.ORCID http://orcid.org/0009-0007-0968-556X
Xiaohong YangChina University of Geosciences, Wuhan, School of Computer Science, Wuhan, 430078, China.
Runyu FanChina University of Geosciences, Wuhan, School of Computer Science, Wuhan, 430078, China.ORCID http://orcid.org/0000-0002-5259-5670
Kang HeChina University of Geosciences, Wuhan, Key Laboratory of Geological Survey and Evaluation of Ministry of Education, Wuhan, 430074, China.
Lizhe WangChina University of Geosciences, Wuhan, School of Computer Science, Wuhan, 430078, China. lizhe.wang@gmail.com.

Funding

National Natural Science Foundation of China (National Science Foundation of China) No.41925007 and No.U21A2013
6 · The paper itself

Abstract

Data and knowledge of spatial-temporal dynamics of multiple types of water body are significant for water resources management but remain very limited. Using the Landsat satellite data and weakly supervised deep learning techniques for long term mapping, we report annual maps of multiple types of inland water bodies on urban agglomeration scale in the middle reaches of the Yangtze River (MRYR) during 1990-2021 at 30m spatial resolution. Accuracy assessment from 14000 validation points in seven years indicates an overall accuracy of 94.50%. Quantitative and qualitative comparison with other water related mapping products further demonstrates the superiority on long time span, refined classification system, and the high precision. The Water-MRYR could support the government and the public in the challenging water resources management and wetland conservation.

Identifiers

PMID40121204
PMCPMC11929797

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.