Evidence map›Paper›PMID 42135315›Full record

ArticleScientific data2026

A 30 m vegetation map for the source regions of the Yangtze and Yellow Rivers from 2020-2025 ground surveys.

Defu Zou, Xiaodong Wu, Guojie Hu, Tonghua Wu, Qiu Jin, Liangang Chen, Yanjun Bian, Cong Wang, Yuting Lan, Lin Zhao and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2026. 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

11 authors.

Defu ZouCryosphere Research Station on Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China.
Xiaodong WuCryosphere Research Station on Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China. wuxd@lzb.ac.cn.
Guojie HuCryosphere Research Station on Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China.
Tonghua WuCryosphere Research Station on Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China.
Qiu JinState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, 210029, China.
Liangang ChenState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, 210029, China.
Yanjun BianSchool of Civil and Hydraulic Engineering, Lanzhou University of Technology, Lanzhou, 730050, China.
Cong WangSchool of Civil and Hydraulic Engineering, Lanzhou University of Technology, Lanzhou, 730050, China.
Yuting LanQinghai Haibei National Field Research Station of Alpine Grassland Ecosystem, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810001, China.
Lin ZhaoSchool of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing, 210044, China. lzhao@nuist.edu.cn.
Zhibin LiSchool of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing, 210044, China.

Funding

National Key Research and Development Program of China 2023YFC3206301National Key Research and Development Program of China 2023YFC3206305
6 · The paper itself

Abstract

An up-to-date vegetation map is essential for characterizing current ecosystem conditions in the source regions of the Yangtze and Yellow Rivers (SRYYR) under ongoing climate change. Here, we release a region-specific 30 m vegetation type dataset that represents typical conditions in the early 2020s. The map was created using systematic ground survey data from 1,168 georeferenced sites collected from 2020 to 2025. A random forest classifier was trained using Landsat imagery and environmental predictors to generate the vegetation type map. Sample representativeness was quantified by comparing predictor distributions between survey sites and the study area. The Euclidean distance ranged from 2.99% to 8.85% and Pearson's r from 0.59 to 0.97. The final map had an overall accuracy of 79.56% and a Cohen's kappa of 0.74. Unlike existing plateau-wide products, this dataset explicitly delineates alpine swamp meadows (ASMs) and improves the spatial representation of alpine shrublands (ASHs), providing an updated baseline for permafrost-vegetation coupling and related ecohydrological processes in the SRYYR.

Identifiers

PMID42135315
PMCPMC13408836

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.