Mapping Temperate Savanna in Northeastern China Through Integrating UAV and Satellite Imagery.

Xiaoya Li, Tao Duan, Kaijie Yang, Bin Yang, Chunmei Wang, Xin Tian, Qi Lu, Feng Wang

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. 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

8 authors.

Xiaoya LiInstitute of Desertification Studies, Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing, 100091, China.

Tao DuanCollege of Resources and Environmental Sciences, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, 010010, China.

Kaijie YangInstitute of Desertification Studies, Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing, 100091, China.

Bin YangSchool of Electronics and Information Engineering, Wuxi University, Wuxi, Jiangsu, 214105, China.

Chunmei WangAerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China.ORCID http://orcid.org/0000-0002-4675-0291

Xin TianInstitute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, China.

Qi LuInstitute of Desertification Studies, Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing, 100091, China.

Feng WangInstitute of Desertification Studies, Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing, 100091, China. wangfeng@caf.ac.cn.ORCID http://orcid.org/0000-0003-3595-515X

Funding

Chinese Academy of Forestry (CAF) CAFYBB2020QD002National Natural Science Foundation of China (National Science Foundation of China) 32171875

6 · The paper itself

Abstract

Temperate savannas are globally distributed ecosystems that play a crucial role in regulating the global carbon cycle and significantly contribute to human livelihoods. This study aims to develop a novel method for identifying temperate savannas and to map their distribution in Northeastern China. To achieve this objective, Unmanned Aerial Vehicle (UAV) imagery was integrated with Sentinel-2 and Sentinel-1 satellite imagery using Random Forest (RF) regression and Classification and Regression Tree (CART) algorithms. The training and validation datasets were derived from UAV imagery covering a ground area of 5 × 10

Identifiers

PMID40263367

DOI10.1038/s41597-025-05012-w

PMCPMC12015479

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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.