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

• Published in: Earth system science data Vol. 13; no. 3; pp. 889 - 906
• Main Authors: Chen, Zuoqi, Yu, Bailang, Yang, Chengshu, Zhou, Yuyu, Yao, Shenjun, Qian, Xingjian, Wang, Congxiao, Wu, Bin, Wu, Jianping
• Format: Journal Article
• Language: English
• Published: Katlenburg-Lindau Copernicus GmbH 05.03.2021; Copernicus Publications
• Subjects: Calibration; Coders; Consistency; Data; Datasets; Defense programs; DMSP satellites; Image enhancement; Imaging radiometers; Infrared imaging; Infrared radiometers; Light; Meteorological satellite program; Meteorological satellites; Neural networks; Night; Night-time; Nighttime; Power; Radiance; Radiometers; Radiometry; Satellite data; Sensors; Time series; Urbanization; Vegetation; Vegetation index
• ISSN: 1866-3516; 1866-3508; 1866-3516
• DOI: 10.5194/essd-13-889-2021

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 freely accessible at https://doi.org/10.7910/DVN/YGIVCD (Chen et al., 2020).