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Annual time series of global VIIRS nighttime lights for 2000-2021 at 500-m spatial resolution extrapolated using logistic regression - MaRDI portal

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Annual time series of global VIIRS nighttime lights for 2000-2021 at 500-m spatial resolution extrapolated using logistic regression

From MaRDI portal
(Redirected from Dataset:6689230)



DOI10.5281/zenodo.8277198Zenodo8277198MaRDI QIDQ6689230

Dataset published at Zenodo repository.

Author name not available (Why is that?)

Publication date: 19 March 2023

Copyright license: No records found.



The Annual Visible Night Light (VNL) V2 (VIIRS) images at 500-m spatial resolution for the period 2012 to 2021 (Elvidge et al., 2021) have been used to extrapolate the values backwards for years 20002011. This was done by fitting a logistic regression (per pixel) and then predicting the values for the previous years (see nightlights_stack_500m.R). After consistent time-series have been produced, I also derived the difference between average of the years 2020/2021 and years 2000/2021 (nightlights.difference_viirs.v21_m_500m_s_2000_2021_go_epsg4326_v20230318.tif): this shows average rate of change for the 22 years period. Use with caution: extrapolation of values can lead to artifacts. For most of the land surface, however, it appears that the growth of night lights follows exponential growth function and hence nights in the past can be represented accurately by fitting decay / logistic regression function. Original values from the Annual VNL V2 product have been converted from 0200 to 02000 scale and are available as Cloud-Optimized GeoTIFFs. To cite the Annual VNL V2, please use: Elvidge, C. D., Zhizhin, M., Ghosh, T., Hsu, F. C., Taneja, J. (2021). Annual time series of global VIIRS nighttime lights derived from monthly averages: 2012 to 2019. Remote Sensing, 13(5), 922. https://doi.org/10.3390/rs13050922 Historic night light images are also available (but at a much coarser spatial resolution) from: Li, X., Zhou, Y., Zhao, M., Zhao, X. (2020). A harmonized global nighttime light dataset 19922018. Scientific data, 7(1), 168. https://doi.org/10.1038/s41597-020-0510-y






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