Evidence map›Paper›PMID 40942870›Full record

ArticleSensors (Basel, Switzerland)2025

Intelligent Monitoring and Trend Analysis of Surface Soil Organic Carbon in the Black Soil Region Using Multi-Satellite and Field Sampling: A Case Study from Northeast China.

Chaoqun Chen, Huimin Dai, Kai Liu, Yulei Tang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

4 authors.

Chaoqun ChenShenyang Center of China Geological Survey, Shenyang 110034, China.
Huimin DaiShenyang Center of China Geological Survey, Shenyang 110034, China.
Kai LiuShenyang Center of China Geological Survey, Shenyang 110034, China.
Yulei TangCenter for Geophysical Survey, China Geology Survey, Langfang 065000, China.

Funding

China Geological Survey DD20230089National Key Research and Development Program of China 2023YFD1500801Strategic Priority Research Program of the Chinese Academy of Sciences XDA28020302the Northeast Geological S&T Innovation Center of China Geological Survey QCJJ2023-38
6 · The paper itself

Abstract

The black soil region of northeast China is a critical global grain production base. The dynamic variations in soil organic carbon (SOC) are directly linked to the regional food security. To accurately monitor SOC content and evaluate the potential of integrating Landsat-9 and GF-1 satellite data for SOC inversion, we developed a machine learning framework that combines data from both satellite sources to model SOC. Using the typical black soil region of northeast China in the Tongken River Basin as the study area, we compared the MLR, PLSR, RF, and XGBoost algorithms. And XGBoost demonstrated the highest performance (R

Indexed as

multi-satellitesoil organic carbonTongken River BasinXGBoost

Identifiers

PMID40942870
PMCPMC12431058

What OpenQuestion holds

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LicenceCC BY
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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.