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Elvidge, C. D., Ghosh, T., Hsu, F. - C., Zhizhin, M., & Bazilian, M. (2020). The Dimming of Lights in China during the COVID-19 Pandemic. Remote Sensing, 12(17), 2851.
Abstract: A satellite survey of the cumulative radiant emissions from electric lighting across China reveals a large radiance decline in lighting from December 2019 to February 2020—the peak of the lockdown established to suppress the spread of COVID-19 infections. To illustrate the changes, an analysis was also conducted on a reference set from a year prior to the pandemic. In the reference period, the majority (62%) of China’s population lived in administrative units that became brighter in March 2019 relative to December 2018. The situation reversed in February 2020, when 82% of the population lived in administrative units where lighting dimmed as a result of the pandemic. The dimming has also been demonstrated with difference images for the reference and pandemic image pairs, scattergrams, and a nightly temporal profile. The results indicate that it should be feasible to monitor declines and recovery in economic activity levels using nighttime lighting as a proxy.
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Elvidge, C. D., Keith, D. M., Tuttle, B. T., & Baugh, K. E. (2010). Spectral identification of lighting type and character. Sensors (Basel), 10(4), 3961–3988.
Abstract: We investigated the optimal spectral bands for the identification of lighting types and the estimation of four major indices used to measure the efficiency or character of lighting. To accomplish these objectives we collected high-resolution emission spectra (350 to 2,500 nm) for forty-three different lamps, encompassing nine of the major types of lamps used worldwide. The narrow band emission spectra were used to simulate radiances in eight spectral bands including the human eye photoreceptor bands (photopic, scotopic, and “meltopic”) plus five spectral bands in the visible and near-infrared modeled on bands flown on the Landsat Thematic Mapper (TM). The high-resolution continuous spectra are superior to the broad band combinations for the identification of lighting type and are the standard for calculation of Luminous Efficacy of Radiation (LER), Correlated Color Temperature (CCT) and Color Rendering Index (CRI). Given the high cost that would be associated with building and flying a hyperspectral sensor with detection limits low enough to observe nighttime lights we conclude that it would be more feasible to fly an instrument with a limited number of broad spectral bands in the visible to near infrared. The best set of broad spectral bands among those tested is blue, green, red and NIR bands modeled on the band set flown on the Landsat Thematic Mapper. This set provides low errors on the identification of lighting types and reasonable estimates of LER and CCT when compared to the other broad band set tested. None of the broad band sets tested could make reasonable estimates of Luminous Efficacy (LE) or CRI. The photopic band proved useful for the estimation of LER. However, the three photoreceptor bands performed poorly in the identification of lighting types when compared to the bands modeled on the Landsat Thematic Mapper. Our conclusion is that it is feasible to identify lighting type and make reasonable estimates of LER and CCT using four or more spectral bands with minimal spectral overlap spanning the 0.4 to 1.0 um region.
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Elvidge, C. D., Sutton, P. C., Ghosh, T., Tuttle, B. T., Baugh, K. E., Bhaduri, B., et al. (2009). A global poverty map derived from satellite data. Computers & Geosciences, 35(8), 1652–1660.
Abstract: A global poverty map has been produced at 30 arcsec resolution using a poverty index calculated by dividing population count (LandScan 2004) by the brightness of satellite observed lighting (DMSP nighttime lights). Inputs to the LandScan product include satellite-derived land cover and topography, plus human settlement outlines derived from high-resolution imagery. The poverty estimates have been calibrated using national level poverty data from the World Development Indicators (WDI) 2006 edition. The total estimate of the numbers of individuals living in poverty is 2.2 billion, slightly under the WDI estimate of 2.6 billion. We have demonstrated a new class of poverty map that should improve over time through the inclusion of new reference data for calibration of poverty estimates and as improvements are made in the satellite observation of human activities related to economic activity and technology access.
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Letu, H., Hara, M., Tana, G., Bao, Y., & Nishio, F. (2015). Generating the Nighttime Light of the Human Settlements by Identifying Periodic Components from DMSP/OLS Satellite Imagery. Environ Sci Technol, 49(17), 10503–10509.
Abstract: Nighttime lights of the human settlements (hereafter, “stable lights”) are seen as a valuable proxy of social economic activity and greenhouse gas emissions at the subnational level. In this study, we propose an improved method to generate the stable lights from Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) daily nighttime light data for 1999. The study area includes Japan, China, India, and other 10 countries in East Asia. A noise reduction filter (NRF) was employed to generate a stable light from DMSP/OLS time-series daily nighttime light data. It was found that noise from amplitude of the 1-year periodic component is included in the stable light. To remove the amplitude of the 1-year periodic component noise included in the stable light, the NRF method was improved to extract the periodic component. Then, new stable light was generated by removing the amplitude of the 1-year periodic component using the improved NRF method. The resulting stable light was evaluated by comparing it with the conventional nighttime stable light provided by the National Oceanic and Atmosphere Administration/National Geophysical Data Center (NOAA/NGDC). It is indicated that DNs of the NOAA stable light image are lower than those of the new stable light image. This might be attributable to the influence of attenuation effects from thin warm water clouds. However, due to overglow effect of the thin cloud, light area in new stable light is larger than NOAA stable light. Furthermore, the cumulative digital numbers (CDNs) and number of light area pixels (NLAP) of the generated stable light and NOAA/NGDC stable light were applied to estimate socioeconomic variables of population, electric power consumption, gross domestic product, and CO2 emissions from fossil fuel consumption. It is shown that the correlations of the population and CO2FF with new stable light data are higher than those in NOAA stable light data; correlations of the EPC and GDP with NOAA stable light data are higher those in the new stable light data.
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Lopez-Ruiz, H., Nezamuddin, N., Al Hassan, R., & Muhsen, A. (2019). Estimating Freight Transport Activity Using Nighttime Lights Satellite Data in China, India and Saudi Arabia. EconPapers, ks--2019-mp07.
Abstract: This paper focuses on the methodology for estimating total freight transport activity (FTA) for three countries — China, India and Saudi Arabia — with the objective of building on current state-of-the-art transportation modeling in three key areas: Studying the relationship between nighttime lights (NTL) and FTA allows for an estimation of full transportation datasets for countries where only a few observation points exist or where data is unavailable. Establishing the foundation for future work on how to use this approach in transport flow estimation (origin-destination matrices). Determining whether this approach can be used globally, given the coverage of the satellite data used. The paper uses the KAPSARC Transport Analysis Framework (KTAF), which estimates transport activity from freely available global data sources, satellite images and NTL. It is a tool for estimating freight transport activity that can be used in models to measure the impact of an accelerated transport policy planning approach. The methodology offers a solution to inadequate data access and allows for scenario building in policy planning for transportation. This approach allows for quick estimation of the effects of policy measures and economic changes on transportation activities at a global level. The paper also includes a detailed guide on how to replicate the methodology used in this analysis.
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