Evidence map›Paper›PMID 41233404›Full record

ArticleScientific data2025

A 40-year dataset of soil salinity dynamics (1985-2024) at 100 m resolution in the Western Songnen Plain, China.

Bin Wang, Xiaojie Li, Zirui Gao, Zhongjun Jia, Zhengwei Liang

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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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.

Bin WangState Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China.
Xiaojie LiState Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China. lixiaojie@iga.ac.cn.ORCID http://orcid.org/0000-0003-1796-5266
Zirui GaoState Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China.
Zhongjun JiaState Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China.
Zhengwei LiangState Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China. liangzw@iga.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soil salinization leads to land degradation, reduced agricultural productivity, and heightened food security risks. Accurate assessment of saline soil distribution and severity is critical for sustainable land management. However, challenges such as broad spatial extent, high heterogeneity, and limited field observations hinder mapping accuracy. Existing datasets in China show large discrepancies in salinized area estimates due to coarse spatial and temporal resolution. In this study, we classified soil salinity degree across the western Songnen Plain from 1985 to 2024 using field surveys, remote sensing imagery, and machine learning algorithms, achieving high accuracy (overall accuracy = 0.893, Kappa = 0.782). A regional soil EC prediction model (R

Identifiers

PMID41233404
PMCPMC12615692

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.