Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 614

The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.

A harmonized global nighttime light dataset 1992–2018

Open access
Li, Xuecao, Zhou, Yuyu, Zhao, Min, Zhao, Xia·2020·Scientific Data

Abstract

Nighttime light (NTL) data from the Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership satellite provide a great opportunity for monitoring human activities from regional to global scales. Despite the valuable records of nightscape from DMSP (1992–2013) and VIIRS (2012–2018), the potential of the historical archive of NTL observations has not been fully explored because of the severe inconsistency between DMSP and VIIRS. In this study, we generated an integrated and consistent NTL dataset at the global scale by harmonizing the inter-calibrated NTL observations from the DMSP data and the simulated DMSP-like NTL observations from the VIIRS data. The generated global DMSP NTL time-series data (1992–2018) show consistent temporal trends. This temporally extended DMSP NTL dataset provides valuable support for various studies related to human activities such as electricity consumption and urban extent dynamics.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41597-020-0510-y

Cites

36 of 36 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 36 references

Research works printed but not linked: 7

  1. Li, X. & Zhou, Y. Urban mapping using DMSP/OLS stable night-time light: a review. Int. J. Remote. Sens. 38, 1–17 (2017).
  2. Isobe, S. & Hamamura, S. Monitoring light energy loss estimated by the DMSP satellites. Mem. della Società astronomica Ital. 71, 131 (2000).
  3. Falchi, F. & Cinzano, P. Maps of artificial sky brightness and upward emission in Italy from DMSP satellite measurements. arXiv preprint astro-ph/9811234 (1998). · arXiv
  4. Zheng, Q., Weng, Q. & Wang, K. Developing a new cross-sensor calibration model for DMSP-OLS and Suomi-NPP VIIRS night-light imageries. ISPRS-J. Photogramm. Remote. Sens. 153, 36–47 (2019). · doi:10.1016/j.isprsjprs.2019.04.019
  5. Li, X. & Zhou, Y. A Stepwise Calibration of Global DMSP/OLS Stable Nighttime Light Data (1992–2013). Remote. Sens. 9, 637 (2017). · doi:10.3390/rs9060637
  6. Zhang, Q., Pandey, B. & Seto, K. C. A Robust Method to Generate a Consistent Time Series From DMSP/OLS Nighttime Light Data. IEEE Trans. Geosci. Remote. Sens. 54, 5821–5831 (2016). · doi:10.1109/tgrs.2016.2572724
  7. Cinzano, P., Falchi, F. & Elvidge, C. Recent progresses on a second world atlas of the night-sky brightness, LPTRAN/LPDART realistic models, tomography of light pollution, accurate validation methods and extended satellite data analysis. In Proc. Starlight 2007 Conference, La Palma, Spain. 19–20 (2007).

Cited by

See all 614

Metadata

Authors
Li, X., Zhou, Y., Zhao, M., & Zhao, X.
Venue
Scientific Data
Published
2020-06-04
Volume
7
Issue
1
Pages
168-168
ISSN
2052-4463 (ISSN-L)
OpenAlex
W3033973892
Cited by
614
References
36
Type
data paper
Language
en
Open access
gold
Licence
Funders
We acknowledge funding support from the U.S. Department of Energy, Office of Science, as part of research in Multi-Sector Dynamics, Earth and Environmental System Modeling Program.

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A harmonized global nighttime light dataset 1992–2018. https://app.cochat.ai/papers/10.1038/s41597-020-0510-y
The paper
Li, X., Zhou, Y., Zhao, M., & Zhao, X. (2020). A harmonized global nighttime light dataset 1992–2018. Scientific Data. https://doi.org/10.1038/s41597-020-0510-y

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.