title: Evaluation of NPP-VIIRS Nighttime Light Data for Mapping Global Fossil Fuel Combustion CO2 Emissions: A Comparison with DMSP-OLS Nighttime Light Data.
abstract: Recently, the stable light products and radiance calibrated products from Defense Meteorological Satellite Program's (DMSP) Operational Linescan System (OLS) have been useful for mapping global fossil fuel carbon dioxide (CO2) emissions at fine spatial resolution. However, few studies on this subject were conducted with the new-generation nighttime light data from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) Satellite, which has a higher spatial resolution and a wider radiometric detection range than the traditional DMSP-OLS nighttime light data. Therefore, this study performed the first evaluation of the potential of NPP-VIIRS data in estimating the spatial distributions of global CO2 emissions (excluding power plant emissions). Through a disaggregating model, three global emission maps were then derived from population counts and three different types of nighttime lights data (NPP-VIIRS, the stable light data and radiance calibrated data of DMSP-OLS) for a comparative analysis. The results compared with the reference data of land cover in Beijing, Shanghai and Guangzhou show that the emission areas of map from NPP-VIIRS data have higher spatial consistency of the artificial surfaces and exhibit a more reasonable distribution of CO2 emission than those of other two maps from DMSP-OLS data. Besides, in contrast to two maps from DMSP-OLS data, the emission map from NPP-VIIRS data is closer to the Vulcan inventory and exhibits a better agreement with the actual statistical data of CO2 emissions at the level of sub-administrative units of the United States. This study demonstrates that the NPP-VIIRS data can be a powerful tool for studying the spatial distributions of CO2 emissions, as well as the socioeconomic indicators at multiple scales.
authors.affiliation: School of Geography and Planning, and Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou, China.
authors.forename: Jinpei
authors.initials: J
authors.lastname: Ou
authors.affiliation: School of Geography and Planning, and Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou, China.
authors.forename: Xiaoping
authors.initials: X
authors.lastname: Liu
authors.affiliation: School of Geography and Planning, and Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou, China.
authors.forename: Xia
authors.initials: X
authors.lastname: Li
authors.affiliation: School of Geography and Planning, and Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou, China.
authors.forename: Meifang
authors.initials: M
authors.lastname: Li
authors.affiliation: School of Geography and Planning, and Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou, China.
authors.forename: Wenkai
authors.initials: W
authors.lastname: Li
mesh_terms: D002245:Carbon Dioxide / Q000032:analysis*; D002681:China; D004784:Environmental Monitoring / Q000379:methods; D005060:Europe; D005579:Fossil Fuels / Q000032:analysis*; D017752:Greenhouse Effect; D006801:Humans; D008027:Light; D011210:Power Plants; D063809:Satellite Imagery; D062206:Spatial Analysis; D014481:United States; D014507:Urbanization
chemical_list: D005579:Fossil Fuels; D002245:Carbon Dioxide