Evidence map›Paper›PMID 39843535›Full record

ArticleScientific data2025

An improved spatially downscaled solar-induced chlorophyll fluorescence dataset from the TROPOMI product.

Siyuan Chen, Liangyun Liu, Lichun Sui, Xinjie Liu, Yan Ma

Abstract readDataset
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

5 authors.

Siyuan ChenPowerChina Northwest Engineering Corporation Limited, Xi'an, 710065, China.ORCID http://orcid.org/0000-0003-2656-8203
Liangyun LiuInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China. liuly@radi.ac.cn.ORCID http://orcid.org/0000-0002-7987-037X
Lichun SuiCollege of Geological Engineering and Geomatics, Chang' an University, Xi'an, 710054, China.
Xinjie LiuInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.ORCID http://orcid.org/0000-0002-7689-3031
Yan MaZhejiang Academy of Surveying and Mapping, Hangzhou, 310001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Solar-induced chlorophyll fluorescence (SIF) is an indicator of vegetation photosynthesis, and multiple satellite SIF products have been generated in recent years. However, current SIF products are limited for applications toward vegetation photosynthesis monitoring because of low spatial resolution or spatial discontinuity. This study uses a spatial downscaling method to obtain a redistribution of the original TROPOspheric Monitoring Instrument (TROPOMI) SIF (OSIF). As a result, a downscaled SIF dataset (TroDSIF) with fine spatio-temporal resolutions (500 m, 16 days) was generated. Compared with a machine learning (ML) SIF product and OSIF, TroDSIF can better reproduce the OSIF signals with higher R

Indexed as

ChlorophyllSunlightClimate ChangeFluorescenceMachine LearningPhotosynthesisChlorophyll

Identifiers

PMID39843535
PMCPMC11754917

What OpenQuestion holds

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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.