Evidence map›Paper›PMID 41381511›Full record

ArticleScientific data2025

1 km HILDA + based land cover/use map time series of China under 1.5 °C climate of this century.

Yifan Gao, Xian Feng, Changqing Song, Yuanhui Wang, Sijing Ye, Min Zhao, Delin Fang, Peichao Gao

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

8 authors.

Yifan GaoState Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
Xian FengState Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
Changqing SongState Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
Yuanhui WangState Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
Sijing YeState Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
Min ZhaoState Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
Delin FangState Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.ORCID http://orcid.org/0000-0003-0238-328X
Peichao GaoState Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China. gaopc@bnu.edu.cn.ORCID http://orcid.org/0000-0003-1714-779X

Funding

National Natural Science Foundation of China (National Science Foundation of China) 42230106National Natural Science Foundation of China (National Science Foundation of China) 42271418
6 · The paper itself

Abstract

Limiting the global temperature rise in this century to 1.5 °C above preindustrial levels has become a critical challenge. One key pathway involves actions in the land sector. Forecasts of land cover/use maps can provide valuable insights for guiding such actions, but the reliability of maps strongly depends on the accuracy of the baseline land cover/use map. In this study, we selected an accurate land cover/use map-HIstoric Land Dynamics Assessment+ (HILDA+), harmonized with multiple historical land cover/use maps-as the baseline land cover/use map. Additionally, we selected a future scenario that aims to achieve the 1.5 °C target and takes into account nationally determined contributions (NDCs). This scenario assumes that all parties would adhere to their submitted NDCs. We forecasted land cover/use maps at a spatial resolution of 1 km from 2020 to 2100 at a 10-year interval in China by integrating the Global Change Analysis Model, the Land-N2N model, and HILDA + land cover/use maps. These maps provide scientific guidance to support land management in addressing climate crises.

Identifiers

PMID41381511
PMCPMC12830754

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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.