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

Abstract. The nighttime light (NTL) satellite data have been widely

used to investigate the 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 in their spatial resolutions and

sensor design requires a cross-sensor calibration of these two datasets for

analyzing a long-term urbanization process. Different from the traditional

cross-sensor calibration of NTL data by converting NPP-VIIRS to

DMSP-OLS-like NTL data, this study built an extended time series (2000–2018)

of NPP-VIIRS-like NTL data through a new cross-sensor calibration from

DMSP-OLS NTL data (2000–2012) and a composition of monthly NPP-VIIRS NTL

data (2013–2018). The proposed cross-sensor calibration is unique due to the

image enhancement by using a vegetation index and an auto-encoder model.

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 great accuracy by comparing it 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 an excellent 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 socioeconomic activities for a longer time period compared to existing

products. The extended time series (2000–2018) of nighttime light data is

al., 2020).