Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> −1° <s> Abstract Nocturnal lighting is a primary method for enabling human activity. Outdoor lighting is used extensively worldwide in residential, commercial, industrial, public facilities, and roadways. A radiance calibrated nighttime lights image of the United States has been assembled from Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS). The satellite observation of the location and intensity of nocturnal lighting provide a unique view of humanities presence and can be used as a spatial indicator for other variables that are more difficult to observe at a global scale. Examples include the modeling of population density and energy related greenhouse gas emissions. <s> BIB001 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> −1° <s> Nightsat is a concept for a satellite system capable of global observation of the location, extent and brightness of night-time lights at a spatial resolution suitable for the delineation of primary features within human settlements. Based on requirements from several fields of scientific inquiry, Nightsat should be capable of producing a complete cloud-free global map of lights on an annual basis. We have used a combination of high-resolution field spectra of outdoor lighting, moderate resolution colour photography of cities at night from the International Space Station, and high-resolution airborne camera imagery acquired at night to define a range of spatial, spectral, and detection limit options for a future Nightsat mission. The primary findings of our study are that Nightsat should collect data from a near-synchronous orbit in the early evening with 50 to 100 m spatial resolution and have detection limits of 2.5E-8 Watts cm-2sr-1µm-1 or better. Although panchromatic low-light imaging data would be useful, multispectral low-light imaging data would provide valuable information on the type or character of lighting; potentially stronger predictors of variables such as ambient population density and economic activity; and valuable information to predict response of other species to artificial night lighting. The Nightsat mission concept is unique in its focus on observing a human activity, in contrast to traditional Earth observing systems that focus on natural systems. <s> BIB002 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> −1° <s> We have produced annual estimates of national and global gas flaring and gas flaring efficiency from 1994 through 2008 using low light imaging data acquired by the Defense Meteorological Satellite Program (DMSP). Gas flaring is a widely used practice for the disposal of associated gas in oil production and processing facilities where there is insufficient infrastructure for utilization of the gas (primarily methane). Improved utilization of the gas is key to reducing global carbon emissions to the atmosphere. The DMSP estimates of flared gas volume are based on a calibration developed with a pooled set of reported national gas flaring volumes and data from individual flares. Flaring efficiency was calculated as the volume of flared gas per barrel of crude oil produced. Global gas flaring has remained largely stable over the past fifteen years, in the range of 140 to 170 billion cubic meters (BCM). Global flaring efficiency was in the seven to eight cubic meters per barrel from 1994 to 2005 and declined to 5.6 m 3 per barrel by 2008. The 2008 gas flaring estimate of 139 BCM represents 21% of the natural gas consumption of the USA with a potential retail market value of $68 billion. The 2008 flaring added more than 278 million metric tons of carbon dioxide equivalent (CO 2 e) into the atmosphere. The DMSP estimated gas flaring volumes indicate that global gas flaring has declined by 19% since 2005, led by gas flaring reductions in Russia and Nigeria, the two countries with the highest gas flaring levels. The flaring efficiency of both Russia and Nigeria improved from 2005 to 2008, suggesting that the reductions in gas flaring are likely the result of either improved utilization of the gas, reinjection, or direct venting of gas into the atmosphere, although the effect of uncertainties in the satellite data cannot be ruled out. It is anticipated that the capability to estimate gas flaring volumes based on satellite data will spur improved utilization of gas that was simply burnt as waste in previous years. <s> BIB003 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> −1° <s> We evaluate the joint use of satellite-observed intensity of urban nightlights and census-based population density data as constraints on the spatial structure of CO2 emissions from fossil fuels. Findings are: (1) the probability that population density exceeds a given value follows a power-law distribution over two orders of magnitude of population density, encompassing the 40% of the global population at the highest densities. (2) The corresponding probability distribution for nightlights intensity also follows a power-law, departing near instrumental saturation. (3) Assuming that the true nightlights intensity distribution follows the power-law above instrumental saturation, we obtain a correction for saturation errors in the nightlights data. The amplification of nightlights intensity required to correct for saturation errors is estimated to be a factor of 1.15-1.23 globally and much greater in regions with high nightlights intensities. (4) Correcting for saturation, we observe clear empirical relationships between nightlights intensity and areal densities of energy consumption, fossil-fuel emissions and economic activity, holding throughout the development spectrum. (5) We indicate how these relationships underpin a fossil-fuel data assimilation system (FFDAS) for estimating fossil-fuel CO2 emissions. <s> BIB004 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> −1° <s> Timely and accurate information about the dynamics of urban expansion is vital to reveal the relationships between urban expansion and the ecosystem, to optimize land use patterns, and to promote the effective development of cities in China. Nighttime stable light data from the Defense Meteorological Satellite Program's Operational Line-scan System (DMSP-OLS) Nighttime Lights Time Series dataset provide a new source of information that can quickly reveal the dynamics of urban expansion. However, the DMSP-OLS sensor has no on-board calibration, which makes it difficult to directly compare time series data from multiple satellites. This study developed a new method for systematically correcting multi-year multi-satellite nighttime stable lights data and rapidly extracting the dynamics of urban expansion based on this corrected data for China from 1992 to 2008. The results revealed that the proposed method effectively reduced abnormal discrepancy within the nighttime stable light data and improved continuity and comparability. The dynamics of urban expansion in China from 1992 to 2008 were extracted with an average overall accuracy of 82.74% and an average Kappa of 0.40. <s> BIB005 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> −1° <s> Several studies have clarified that electric power consumption can be estimated from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) stable light imagery. As digital numbers (DNs) of stable light images are often saturated in the center of city areas, we developed a saturated light correction method for the DMSP/OLS stable light image using the nighttime radiance calibration image of the DMSP/OLS. The comparison between the nonsaturated part of the stable light image for 1999 and the radiance calibration image for 1996-1997 in major areas of Japan showed a strong linear correlation (R2 = 92.73) between the DNs of both images. Saturated DNs of the stable light image could therefore be corrected based on the correlation equation between the two images. To evaluate the new saturated light correction method, a regression analysis is performed between statistic data of electric power consumption from lighting and the cumulative DNs of the stable light image before and after correcting for the saturation effects by the new method, in comparison to the conventional method, which is, the cubic regression equation method. The results show a stronger improvement in the determination coefficient with the new saturated light correction method (R2 = 0.91, P = 1.7 ·10-6 <; 0.05) than with the conventional method (R2 = 0.81, P = 2.6 ·10-6 <; 0.05) from the initial correlation with the uncorrected data (R2 = 0.70, P = 4.5 · 10-6 <; 0.05). The new method proves therefore to be very efficient for saturated light correction. <s> BIB006 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> −1° <s> DMSP-OLS Defense Meteorological Satellite Program Operational Linescan System night-time light data can accurately reflect the scope and intensity of human activities. However, the raw data cannot be used directly for temporal analyses due to the lack of inflight calibration. There are three problems that should be addressed in intercalibration. First, because of differences between sensors, the data are not identical even when obtained in the same year. Second, different acquisition times may lead to random or systematic fluctuations in the data obtained by satellites in different orbits. Third, a pixel saturation phenomenon also exists in the urban centres of the image. Therefore, an invariant region method was used in this article, and the relative radiometric calibration and saturation correction achieved the desired results. In the meantime, intercalibration models for each satellite year of DMSP-OLS night-time light data were produced. Finally, intercalibration accuracy was evaluated, and the intercalibration results were tested with the corresponding gross domestic product GDP data. <s> BIB007 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> −1° <s> The science and policy communities increasingly require information about inter-urban variability in form, infrastructure, and energy use for cities globally and in a timely manner. Nighttime light (NTL) data from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) are able to provide information on nighttime luminosity, a correlate of the built environment and energy consumption. Although NTL data are used to map aggregate measures of urban areas such as total area extent, their ability to characterize inter-urban variation is limited due to saturation of the data values, especially in urban cores. Here we propose a new spectral index, the Vegetation Adjusted NTL Urban Index (VANUI), which combines MODIS NDVI with NTL, to achieve three key goals. First, the index reduces the effects of NTL saturation. Second, the index increases variation of the NTL signal, especially within urban areas. Third, the index corresponds to biophysical and urban characteristics. Additionally, the index is intuitive, simple to implement, and enables rapid characterization of inter-urban variability in nighttime luminosity. Assessments of VANUI show that it significantly reduces NTL saturation and increases variation of data values in core urban areas. As such, VANUI can be useful for studies of urban structure, energy use, and carbon emissions. <s> BIB008
Watts/cm 2 /sr range. There are two spatial resolutions of nighttime images: "fine" resolution data have a nominal spatial resolution of 0.56 km, while "smooth" data have a nominal spatial resolution of 2.7 km with 5 × 5 block averaging. Given the sensitivity of the sensor at night, DMSP/OLS data can be used as a proxy to detect a variety of VNIR emissions. The availability of long-term daily data with moderate spatial resolution (e.g., 1 km) has enabled researchers to explore a series of global, national, and regional research questions; in particular, the free download of the long-term Version 4 dataset since 2010 has significantly increased the use of these data. DMSP/OLS nighttime data have been used to directly observe natural phenomena (e.g., forest fires) and estimate social, demographic, and economic changes in lit areas, and have also been used indirectly as an ancillary database to facilitate other studies. A more detailed summary is provided in Section 5. Although the advantages of nighttime DMSP/OLS data are commonly recognized, several disadvantages in using this sensor to observe nighttime emissions have been identified BIB002 . These include the (1) relatively low spatial resolution; (2) absence of onboard calibration; (3) lack of inter-satellite calibration; (4) lack of records of in-flight gain changes; (5) limited 6-bit quantization of digital numbers; (6) light saturation in highly populated urban centers because of the standard operation at the high gain setting; (7) the blooming effect (i.e., overestimation of lit area) due to the coarse spatial resolution of data and reflectance of light from adjacent areas (e.g., water bodies); and (8) limited accessibility to high-quality daily OLS data. Several strategies were developed to overcome some of these shortcomings. For example, to overcome the lack of onboard calibration, Elvidge et al. BIB001 assembled a radiance-calibrated nighttime image of the United States acquired at reduced gain setting between March 1996 and February 1997. Compared to the previous 1994-1995 stable light data, the major advantage of this new dataset is providing detailed, brightness variations within lit areas and a detailed spatial distribution of nighttime light intensity. Empirical studies have proved that the radiance-calibrated data is a useful spatial indicator for energy related human activity (e.g., electric power consumption and greenhouse gas emission) BIB001 and urbanization related demographic and socioeconomic data  . In addition, the "light diffuse" phenomena in densely populated rural areas can be restrained to a certain extent BIB001 . However, the calibration procedure is complex and sensitive to some regional conditions (e.g., presence of snow cover in winter and vegetation phenology in spring and autumn BIB001 ). Neither the algorithm nor the original time series nighttime light images can be accessed easily. Thus, only several radiance-calibrated datasets were produced at regional scales and for a few years BIB001  . Several methods were proposed to overcome the lack of inter-satellite calibration. These include the invariant region and the quadratic regression method proposed by Elvidge et al. BIB003 , the second-order regression and optimal threshold method proposed by Liu et al. BIB005 , and a power-law regression method proposed by Wu et al. BIB007 . Although studies based on these calibration methods showed performance improvement after the rectification BIB005 BIB007 , the assumption that the nighttime light remains stable over time in a particular area requires a careful choice of the invariant region manually. In addition, researchers also developed different algorithms to overcome the saturation phenomenon in urban centers; for example, Raupach et al. BIB004 amplified the saturated light data based on a hypothesis of a power-law distribution of light density. Lo  developed a three-dimensional model to extract light volume using the triangulated irregular network functionality in ArcGIS. Letu et al. BIB006 used the 1996-1997 radiance-calibrated data, the 1999 stable light data, and the regression method for generating saturation-corrected data in 1999. Zhang et al. BIB008 proposed a method for combining nighttime data with MODIS NDVI data to reduce saturation effects in urban cores. All of these studies showed that using the saturation-calibrated data could improve the estimation of human activity and human impacts on the environment. However, in situ observations of the real distribution of light intensity within saturated areas are lacking, which will impede the validation of the saturation-calibrated data.