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https://doi.org/10.5194/essd-2020-201
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2020-201
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  28 Sep 2020

28 Sep 2020

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This preprint is currently under review for the journal ESSD.

An extended time-series (2000–2018) of global NPP-VIIRS-like nighttime light data from a cross-sensor calibration

Zuoqi Chen1,2, Bailang Yu3,4, Chengshu Yang3,4, Yuyu Zhou5, Xingjian Qian3,4, Congxiao Wang3,4, Bin Wu3,4, and Jianping Wu3,4 Zuoqi Chen et al.
  • 1Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou 35002, China
  • 2The Academy of Digital China, Fuzhou University, Fuzhou 350002, China
  • 3Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
  • 4School of Geographic Sciences, East China Normal University, Shanghai 200241, China
  • 5Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, USA

Abstract. The nighttime light (NTL) satellite data have been widely used to investigate urbanization process. The Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) stable nighttime light data and Suomi National Polar-Orbiting Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data are two widely used NTL datasets. However, the difference of their spatial resolutions and sensor design makes it difficult to directly use these two datasets together for a long-term analysis of urbanization. To solve this issue, an extended time-series (2000–2018) of NPP-VIIRS-like NTL data were proposed in this study through a cross-sensor calibration from DMSP-OLS NTL data (2000–2012) and a composition of monthly NPP-VIIRS NTL data (2013–2018). Compared with the annual composited NPP-VIIRS NTL data in 2012, our product of extended NPP-VIIRS-like NTL data shows a good consistency at the pixel and city levels with R2 of 0.87 and 0.95, respectively. We also found that our product has a good accuracy by comparing with DMSP-OLS radiance calibrated NTL (RNTL) data in 2000, 2004, 2006, and 2010. Generally, our extended NPP-VIIRS-like NTL data (2000–2018) have a good spatial pattern and temporal consistency, which are similar to the composited NPP-VIIRS NTL data. In addition, the resulting product could be easily updated and provide a useful proxy to monitor the dynamics of demographic and socio-economic activities for a longer time period compared to existing products. The extended time-series (2000–2018) of nighttime light data are freely accessible at https://doi.org/10.7910/DVN/YGIVCD (Chen et al., 2020).

Zuoqi Chen et al.

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An extended time-series (2000-2018) of global NPP-VIIRS-like nighttime light data Zuoqi Chen, Bailang Yu, Chengshu Yang, Yuyu Zhou, Xingjian Qian, Congxiao Wang, Bin Wu, and Jianping Wu https://doi.org/10.7910/DVN/YGIVCD

Zuoqi Chen et al.

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Short summary
An extended time-series (2000–2018) of NPP-VIIRS-like nighttime light (NTL) data were proposed through a cross-sensor calibration from DMSP-OLS NTL data (2000–2012) and NPP-VIIRS NTL data (2013–2018). Compared with the annual composited NPP-VIIRS NTL data, our extended NPP-VIIRS-like NTL data has a high accuracy and also shows a good spatial pattern and temporal consistency. It could be a useful proxy to monitor the dynamics of urbanization for a longer time period compared to existing NTL data.
An extended time-series (2000–2018) of NPP-VIIRS-like nighttime light (NTL) data were proposed...
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