Evidence map›Paper›PMID 40596591›Full record

ArticleScientific reports2025

Ice velocity in the Yellow River bends using unmanned aerial vehicle imagery.

Zhongshu Xue, Honglan Ji, Hongchun Luo, Bin Liu

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. Not yet cited in PubMed.

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

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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

4 authors.

Zhongshu XueCollege of Water Resources and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, Inner Mongolia, China.
Honglan JiCollege of Water Resources and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, Inner Mongolia, China. honglanji@imau.edu.cn.
Hongchun LuoCollege of Water Resources and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, Inner Mongolia, China.
Bin LiuCollege of Water Resources and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, Inner Mongolia, China.

Funding

Inner Mongolia Autonomous Region Science and Technology Leading Talent Team 2022LJRC0007Inner Mongolia Natural Science Foundation Grant No. 2023QN05026the Excellent Doctoral Talent Program of Inner Mongolia Agricultural University NDYB2022-28the National Natural Science Foundation of China Grant No. 52379014
6 · The paper itself

Abstract

Ice velocity is a critical parameter in river ice monitoring, playing a vital role in analyzing ice blockages, the freeze-up process, and ice jam locations. It provides essential references for freeze-up forecasting. This study utilized UAV (Unmanned Aerial Vehicle) remote sensing imagery from December 2023, during the ice run period, combined with the Pyramidal Lucas-Kanade Optical Flow Algorithm to quantify ice velocity distribution across multiple bends during the Yellow River's ice run period. The study identified low ice velocity cross-sections at bend apexes, where velocity decreased sharply, leading to ice floe accumulation and an increased probability of ice jams. Significant spatial variations in ice velocity within bends were observed. Curvature and constriction ratios were identified as key factors influencing ice velocity distribution. Bends with high curvature and significant constriction should be prioritized for monitoring and early warning. The study also revealed a correlation between the low ice velocity cross-section at the apex of Shisifenzi Bend and the location of the initial ice jam during the ice run period, suggesting its potential as a scientific guide for ice jam risk forecasting. These findings provide valuable insights for freeze-up forecasting and flood prevention in the Yellow River.

Indexed as

BendsIce velocityPyramidal Lucas-Kanade Optical Flow AlgorithmThe Yellow River

Identifiers

PMID40596591
PMCPMC12215903

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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.