Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socioeconomic dynamics

Abstract

Since the late 1990s, remotely sensed night-time lights (NTL) satellite imagery has been shown to correlate with socioeconomic parameters including urbanization, economic activity, and population. More recent research demonstrates that multitemporal NTL data can serve as a reliable proxy for change over time in these variables whether they are increasing or decreasing. Time series analysis of NTL data is especially valuable for detecting, estimating, and monitoring socioeconomic dynamics in countries and subnational regions where reliable official statistics may be lacking. Until 2012, multitemporal NTL imagery came primarily from the Defense Meteorological Satellite Program - Operational Linescan System (DMSP-OLS), for which digital imagery is available from 1992 to 2013. In October 2011, the launch of NASA/NOAA's Suomi National Polar-orbiting Partnership satellite, whose Visible Infrared Imaging Radiometer Suite (VIIRS) sensor has a Day/Night Band (DNB) specifically designed for capturing radiance from the Earth at night, marked the start of a new era in NTL data collection and applications. In light of these advances, this paper reviews progress in using multitemporal DMSP-OLS and VIIRS imagery to analyze urbanization, economic, and population dynamics across a range of geographic scales. An overview of data corrections and processing for comparison of multitemporal NTL imagery is provided, followed by a meta-analysis and integrative synthesis of these studies. Figures are included that visualize the capabilities of DMSP-OLS and VIIRS to capture socioeconomic change in the post-Soviet Russian Far East and war-torn Syria, respectively. Finally, future directions for NTL research are suggested, particularly in the areas of determining the fundamental causes of observed light and in leveraging VIIRS' superior sensitivity and spatial and radiometric resolution.