Evidence map›Paper›PMID 39695222›Full record

ArticleScientific data2024

A global annual simulated VIIRS nighttime light dataset from 1992 to 2023.

Xiuxiu Chen, Zeyu Wang, Feng Zhang, Guoqiang Shen, Qiuxiao Chen

Abstract read
In one paragraph

Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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.

Xiuxiu ChenSchool of Earth Sciences, Zhejiang University, Hangzhou, 310058, China.ORCID http://orcid.org/0009-0008-1867-5125
Zeyu WangSchool of Earth Sciences, Zhejiang University, Hangzhou, 310058, China.
Feng ZhangSchool of Earth Sciences, Zhejiang University, Hangzhou, 310058, China. zfcarnation@zju.edu.cn.
Guoqiang ShenSchool of Spatial Planning and Design, Hangzhou City University, Hangzhou, 310015, China.
Qiuxiao ChenSchool of Spatial Planning and Design, Hangzhou City University, Hangzhou, 310015, China.

Funding

Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology) 2019YFE0127400
6 · The paper itself

Abstract

Nighttime light (NTL) data is recognized as a reliable proxy for measuring the scope and intensity of human activity, finding wide application in studies such as urbanization monitoring, socioeconomic estimation, and ecological environment assessment. However, the substantial discrepancies and limited temporal coverage of existing NTL datasets have constrained their potential for long-term research applications. To address this, a Nighttime Light U-Net super-resolution network is proposed for the cross-sensor calibration between the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) NTL data and the Suomi National Polar-Orbiting Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data. This network is applied to generate a continuous and consistent 500-meter global annual simulated VIIRS NTL dataset (SVNL) from 1992 to 2023. Validation results indicate a high confidence in the quality of the SVNL data, demonstrating its superiority in capturing longer NTL dynamics, maintaining higher temporal consistency, and presenting greater spatial detail compared with other NTL datasets. The SVNL could be utilized for prolonged human activities monitoring, and further research on regional or global urbanization.

Identifiers

PMID39695222
PMCPMC11655983

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Registered trials

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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.