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

TLDR

Nighttime light satellite data, especially DMSP‑OLS and NPP‑VIIRS, are widely used to study urbanization, but their differing spatial resolutions and sensor designs necessitate cross‑sensor calibration. The authors constructed a 2000–2018 NPP‑VIIRS‑like nighttime light series by cross‑calibrating DMSP‑OLS 2000–2012 data with monthly NPP‑VIIRS 2013–2018 data, employing a vegetation‑index‑based image enhancement and an auto‑encoder model. The resulting series shows strong agreement with existing datasets (R² = 0.87–0.95), excellent spatial and temporal consistency, and can be readily updated, making it a valuable proxy for long‑term socioeconomic monitoring, and is freely available online. Abstract.

Abstract

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