Evidence map›Paper›PMID 41429884›Full record

ArticleScientific reports2025

Decadal spatiotemporal dynamics of surface water bodies in Zhengzhou, China: remote sensing monitoring and analysis of driving factors.

Wei Song, Qingfeng Hu, Shilian Liu, Yaqian Hou

Abstract read
In one paragraph

Article in Scientific reports, 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

4 authors.

Wei SongCollege of Surveying and Geo-informatics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, Henan, People's Republic of China. songwei@ncwu.edu.cn.
Qingfeng HuCollege of Surveying and Geo-informatics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, Henan, People's Republic of China.
Shilian LiuCollege of Surveying and Geo-informatics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, Henan, People's Republic of China.
Yaqian HouCollege of Surveying and Geo-informatics, North China University of Water Resources and Electric Power, Zhengzhou, 450046, Henan, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Water is essential for life, human activities, and ecological balance. Understanding the spatiotemporal dynamics of urban water bodies is critical for sustainable water management, especially in fast-growing cities like Zhengzhou. This study investigates the evolution of water bodies in Zhengzhou from 2014 to 2023, using multi-seasonal Landsat 8 imagery and GIS analysis. Three water extraction methods-thresholding, random forest (RF), and a hybrid RF model incorporating spectral indices (NDWI, MNDWI, EWI) and GLCM-based texture features-were evaluated. The hybrid RF approach demonstrated the highest classification accuracy and was applied to generate seasonal water body maps for the target years. The results show a general increase in surface water area, with seasonal peaks in July–September, and spatial expansion mainly in the northern and northeastern regions. These changes are driven by both natural (e.g., precipitation) and anthropogenic (e.g., urban development, artificial lake construction) factors. Compared to previous studies, this research offers three key innovations: (1) a decade-long, seasonal-scale analysis of water dynamics; (2) a robust multi-feature classification framework for complex urban settings; and (3) an integrated interpretation of natural and human influences. The findings provide valuable references for water resource planning and urban ecological restoration, and the methods used may be transferable to similar inland cities under monsoon climates.

Identifiers

PMID41429884
PMCPMC12749583

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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.