Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Other Applications <s> The disaster information system, the Early Damaged Area Estimation System (EDES), was developed to estimate damaged areas of natural disaster using the night-time imagery of the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS). The system employs two estimation methods to detect the city lights loss or reduction as possible impacted areas; one is the bi-temporal images (BTI) method and the other is the time-series images (TSI) method. Both methods are based on significance tests assuming that brightness of city lights fluctuates as normal random variables, and the BTI method is simplified by introducing the assumption that the standard deviation of city lights fluctuation is constant. The validity of the estimation method is discussed based on the result of the application to the 2001 Western India earthquake disaster. The estimation results identify the damaged areas distant from the epicentre fairly well, especially when using the TSI method. The system is designed to esti... <s> BIB001 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Other Applications <s> Baghdad Nights: Evaluating the US Military ‘Surge’ Using Nighttime Light Signatures John Agnew Thomas W. Gillespie Jorge Gonzalez Brian Min CCPR-064-08 December 2008 Latest Revised: December 2008 California Center for Population Research On-Line Working Paper Series <s> BIB002 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Other Applications <s> [1] We describe a system for constraining the spatial distribution of fossil fuel emissions of CO 2 . The system is based on a modified Kaya identity which expresses emissions as a product of areal population density, per capita economic activity, energy intensity of the economy, and carbon intensity of energy. We apply the methodology of data assimilation to constrain such a model with various observations, notably, the statistics of national emissions and data on the distribution of nightlights and population. We hence produce a global, annual emission field at 0.25° resolution. Our distribution of emissions is smoother than that of the population downscaling traditionally used to describe emissions. Comparison with the Vulcan inventory suggests that the assimilated product performs better than downscaling for distributions of either population or nightlights alone for describing the spatial structure of emissions over the United States. We describe the complex structure of uncertainty that arises from combining pointwise and area-integrated constraints. Uncertainties can be as high as 50% at the pixel level and are not spatially independent. We describe the use of 14 CO 2 measurements to further constrain national emissions. Their value is greatest over large countries with heterogeneous emissions. Generated fields may be found online (http://ffdas.org/). <s> BIB003 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Other Applications <s> The potential use of satellite observed nighttime lights for estimating carbon-dioxide (CO 2 ) emissions has been demonstrated in several previous studies. However, the procedures for a moderate resolution (1 km 2 grid cells) global map of fossil fuel CO 2 emissions based on nighttime lights are still in the developmental phase. We report on the development of a method for mapping distributed fossil fuel CO 2 emissions (excluding electric power utilities) at 30 arc-seconds or approximately 1 km 2 resolution using nighttime lights data collected by the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS). A regression model, Model 1, was initially developed based on carbon emissions from five sectors of the Vulcan data produced by the Purdue University and a nighttime satellite image of the U.S. The coefficient derived through Model 1 was applied to the global nighttime image but it resulted in underestimation of CO 2 emissions for most of the world’s countries, and the states of the U.S. Thus, a second model, Model 2 was developed by allocating the distributed CO 2 emissions (excluding emissions from utilities) using a combination of DMSP-OLS nighttime image and population count data from the U.S. Department of Energy's (DOE) LandScan grid. The CO 2 emissions were distributed in proportion to the brightness of the DMSP nighttime lights in areas where lighting was detected. In areas with no DMSP detected lighting, the CO 2 emissions were distributed based on population count, with the assumption that people who live in these areas emit half as much CO 2 as people who live in the areas with DMSP detected lighting. The results indicate that the relationship between satellite observed nighttime lights and CO 2 emissions is complex, with differences between sectors and variations in lighting practices between countries. As a result it is not possible to make independent estimates of CO 2 emissions with currently available coarse resolution panchromatic satellite observed nighttime lights. However, the nighttime lights image in conjunction with the population grid can help in more accurate disaggregation of national CO 2 emissions to a moderate resolution spatial grid. <s> BIB004 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Other Applications <s> Abstract. Emissions of CO 2 from fossil fuel combustion are a critical quantity that must be accurately given in established flux inversion frameworks. Work with emerging satellite-based inversions requires spatiotemporally-detailed inventories that permit analysis of regional natural sources and sinks. Conventional approaches for disaggregating national emissions beyond the country and city levels based on population distribution have certain difficulties in their application. We developed a global 1 km×1 km annual fossil fuel CO 2 emission inventory for the years 1980–2007 by combining a worldwide point source database and satellite observations of the global nightlight distribution. In addition to estimating the national emissions using global energy consumption statistics, emissions from point sources were estimated separately and were spatially allocated to exact locations indicated by the point source database. Emissions from other sources were distributed using a special nightlight dataset that had fewer saturated pixels compared with regular nightlight datasets. The resulting spatial distributions differed in several ways from those derived using conventional population-based approaches. Because of the inherent characteristics of the nightlight distribution, source regions corresponding to human settlements and land transportation were well articulated. Our distributions showed good agreement with a high-resolution inventory across the US at spatial resolutions that were adequate for regional flux inversions. The inventory can be extended to the future using updated data, and is expected to be incorporated into models for operational flux inversions that use observational data from the Japanese Greenhouse Gases Observing SATellite (GOSAT). <s> BIB005 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Other Applications <s> Urban areas now house more than half the world's population, and are estimated to contribute over 70% of global energy-related CO_2 emissions. Many cities have emission reduction policies in place, but lack objective, observation-based methods for verifying their outcomes. Here we demonstrate the potential of satellite-borne instruments to provide accurate global monitoring of megacity CO_2 emissions using GOSAT observations of column averaged CO_2 dry air mole fraction (X_(CO_2)) collected over Los Angeles and Mumbai. By differencing observations over the megacity with those in nearby background, we observe robust, statistically significant X_(CO_2) enhancements of 3.2 ± 1.5 ppm for Los Angeles and 2.4 ± 1.2 ppm for Mumbai, and find these enhancements can be exploited to track anthropogenic emission trends over time. We estimate that X_(CO_2) changes as small as 0.7 ppm in Los Angeles, corresponding to a 22% change in emissions, could be detected with GOSAT at the 95% confidence level. <s> BIB006 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Other Applications <s> Estimation of electric power and power plant CO2 emissions using satellite remote sensing data is essential for the management of energy consumption and greenhouse gas monitoring. For estimation, the relationship between Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS) annual nighttime stable light product (NSL) for 2006 and statistical data on power generation, power consumption, and power plant CO2 emissions in 10 electric power supply regions of Japan was investigated. Unlike other power plants, thermal plants directly emit CO2 by burning fossil fuels when generating electricity. Among the nighttime lights in the NSL, only light from thermal power is related to power plant CO2 emission. The percentage of thermal power generation to total power generation (K%) is thus a key parameter for estimating nighttime light by power consumption from thermal power plants. In this study, the DMSP/OLS annual nighttime radiance-calibrated product (RCI) for 2006 and the NSL data correcte... <s> BIB007
The final category of applications contained miscellaneous interdisciplinary research, and subcategories VIII to X fell into this category. The number of publications in this category was relatively small, because the research topics were mostly novel and interdisciplinary. Intuitively, the methods developed to extract this information were relatively immature or at the trial stage, but using DMSP/OLS nighttime light data to explore interdisciplinary themes in research remains promising. For example, a key research area in climate science is assessing CO 2 emissions from urban areas. Previous studies depended on the relationship between population and CO 2 emission alone to map the spatial distribution of CO 2 emission. Several studies started to combine nighttime lights and population together, which was found to be better than using population alone BIB003 BIB004 . Several other studies combined CO 2 emission from point sources like power plants with nighttime lights data, which was in agreement with existing inventory dataset BIB005 BIB007 . DMSP/OLS nighttime light data in combination with spatially explicit estimation of CO 2 concentrations from the Japanese Greenhouse Gases Observing Satellite have been used to understand the anthropogenic emissions of CO 2 from megacities such as Los Angeles BIB006 . In addition to the above topic, nighttime lights data were used in more new areas (Table 6) . By comparing the nighttime light loss after a major disaster such as earthquake, Kohiyama et al. BIB001 developed a system that provides timely (within 24 h) information on the spatial distribution of the impacted urban area. Another example is that by comparing the nighttime lights intensity before and after certain military actions in Bagdad, Agnew et al. BIB002 assessed whether those military actions actually achieved their goals-to stabilize the region. We envision that more new areas of study will be using nighttime lights data in the near future, as this type of dataset accumulated and additional sensors provide finer spatial resolution.