Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <s> The Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) has a unique capability to detect low levels of visible and near-infrared (VNIR) radiance at night. With the OLS "VIS" band data, it is possible to detect clouds illuminated by moonlight, plus lights from cities, towns, industrial sites, gas pares, and ephemeral events such as fires and lightning illuminated clouds. This paper presents methods which have been developed for detecting and geolocating VNIR emission sources with nighttime DMSP-OLS data and the analysis of image time series to identify spatially stable emissions from cities, towns, and industrial sites. Results are presented for the United States. <s> BIB001 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <s> Abstract Nightime “city light” footprints derived from DMSP/OLS satellite images were merged with census data and a digital soils map in a continental-scale test of a remote sensing and geographic information system methodology for approximating the extent of built-up land and its potential impact on soil resources in the United States. Using image processing techniques and census data, we generated maps where the “city lights” class represented mean population densities of 947 persons km −2 and 392 housing units km −2 , areas clearly not available to agriculture. By our analysis, such “city lights” representing urban areas accounted for 2.7% of the surface area in the United States, an area approximately equal to the State of Minnesota or one half the size of California. Using the UN/FAO Fertility Capability Classification System to rank soils, results for the United States show that development appears to be following soil resources, with the better agricultural soils being the most urbanized. Some unique soil types appear to be on the verge of being entirely coopted by “urban sprawl.” Urban area figures derived from the DMSP/OLS imagery compare well to those derived from statistical sources. Further testing and refinement of the methodology remain but the technique shows promise for possible extension to global evaluations of urbanization, population and even global productivity. <s> BIB002 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <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> BIB003 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <s> A composite of cloud-free radiance-calibrated Defense Meteorological Satellite Program (DMSP)-Operational Linescan System (OLS) nighttime images of China acquired between March 1996 and January– February 1997 in 30-arc-second grids in byte format is evaluated for its usefulness in extracting urban indicators data of China. With the aid of image-processing and Environmental Systems Research Institute’s ArcView GIS software with 3-D Analysis extension, zonal variations of radiance were extracted and three-dimensional models created using Triangulated Irregular Network (TIN) functionality for thirty-five cities. Two variables were extracted from the TIN model: surface area and volume. These were used separately as independent variables in the form of an allometric growth model to estimate the following urban indicators for individual Chinese cities: nonagricultural population, gross domestic product (GDP), built-up area, and electricity consumption. The estimates obtained were checked against data supplied b... <s> BIB004 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <s> Night-time imagery from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) has been proposed as a useful tool for monitoring urban expansion around the world, but determining appropriate light thresholds for delineating cities remains a challenge. In this paper we present a new approach. We used DMSP stable lights and radiance-calibrated images to delimit urban boundaries for San Francisco, Beijing and Lhasa, cities with different levels of urbanization and economic development, and compared the results against boundaries derived from high-resolution Landsat Thematic Mapper (TM) imagery. Unthresholded DMSP images exaggerate and shift the extent of these urban areas. We then calculated light thresholds that minimized the discrepancies between the DMSP- and TM-derived urban boundaries for each city. Our comparison highlights the difficulty of using DMSP data across areas with disparate urban characteristics, but suggests the possibility of calibrating this data source for ... <s> BIB005 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <s> Abstract The distribution and abundance of the fleet targeting Jumbo flying squid ( Dosidicus gigas ) in the Eastern Pacific is examined during the 1999 fishery season. The commercial fishery consists of a multinational jigging fleet, which fish at night using powerful lights to attract squid. The emission of light from these vessels can be observed using satellite-derived imagery obtained by the United States Defence Meteorological Satellite Program-Operational Linescan System (DMSP-OLS). In order to quantify fishing effort using lights, data on the distribution and abundance of vessels were obtained via satellite tracking using the ARGOS system. The distribution of the fishery as derived from light signatures was found to closely resemble that derived from ship location data. By using ARGOS data to calibrate DMSP-OLS images, we are able to estimate fishing effort in terms of the ‘area illuminated’ by the fishing fleet. Light signatures derived from DMSP-OLS were successfully used to quantify fishing effort, estimating the number of vessels fishing to within ±2 in 85 out of 103 satellite images (83%). High seas fishing was also quantified, with light signatures corresponding to a single fishing vessel observed in 11 out of 103 satellite passes during the fishery season (July–December 1999). This study examines how much light (in terms of area) is emitted by a single squid fishing vessel, and may prove to be a valuable tool in assessing and policing fisheries using satellite remote sensing. <s> BIB006 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <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> BIB007 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <s> On many occasions over the centuries, mariners have reported witnessing surreal nocturnal displays where the surface of the sea produces an intense, uniform, and sustained glow that extends to the horizon in all directions. Although such emissions cannot be fully reconciled with the known features of any light-emitting organism, these so-called “milky seas” are hypothesized to be manifestations of unusually strong bioluminescence produced by colonies of bacteria in association with a microalgal bloom in the surface waters. Because of their ephemeral nature and the paucity of scientific observations, an explanation of milky seas has remained elusive. Here, we report the first satellite observations of the phenomenon. An ≈15,400-km2 area of the northwestern Indian Ocean, roughly the size of the state of Connecticut, was observed to glow over 3 consecutive nights, corroborated on the first night by a ship-based account. This unanticipated application of satellite remote-sensing technology provides insights pertaining to the formation and scale of these poorly understood events. <s> BIB008 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <s> Abstract The recognition that the elements of the ‘anthropocene’ play a critical role in global change processes means that datasets describing elements of the socio-economic environment are becoming increasingly more desirable. The ability to present these data in a gridded format as opposed to the traditionally reported administrative units is advantageous for incorporation with other environmental datasets. Night-time light remote sensing data has been shown to correlate with national-level figures of Gross Domestic Product (GDP). Night-time radiance data is analysed here along with regional economic productivity data for 11 European Union countries along with the United States at a number of sub-national levels. Night-time light imagery was found to correlate with Gross Regional Product (GRP) across a range of spatial scales. Maps of economic activity at 5 km resolution were produced based on the derived relationships. To produce these maps, certain areas had to be excluded due to their anomalously high levels of economic activity for the amount of total radiance present. These areas were treated separately from other areas in the map. These results provide the first detailed examination of night-time light characteristics with respect to local economic activity and highlight issues, which should be considered when undertaking such analysis. <s> BIB009 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <s> Since current administrative unit-based urban land area statistical data in China lack enough spatial information, the urbanization process research at large scale cannot be effectively supported. Based on the current administrative unit-based urban land area statistical data in China, a new approach to quickly and cheaply derive urban land information from the non-radiance-calibrated Defense Meteorological Satellite Program/ Operational Linescan System (DMSP/OLS) nighttime light imagery is presented in this paper. With the new approach, the urban pattern information in China in 1992, 1996 and 1998 was derived with the urbanization processes in China in the 1990s restored by using the non-radiance-calibrated DMSP/OLS nighttime imagery. The accuracy assessment based on the statistical data showed that the relative error between the derived total urban land area and the statistical data at national scale was less than 2% in 1992, and less than 1% in 1996 and 1998, and the maximum relative error at province scale do not exceed 10% with most of the provinces less than 3%. In addition, the urban patterns derived from the high-resolution Landsat TM imagery were compared with those from the DMSP/OLS data. The results showed that the urban pattern characteristics derived from DMSP/OLS were basically coincident with those from TM imagery with the total accuracy of about 80%. Thus it can be seen that our restored urbanization process in China in the 1990s by using the non-radiance DMSP/OLS night-time imagery can be accepted and can represent the actual urban development in China at that time on the whole. <s> BIB010 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <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> BIB011 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <s> The spatial distribution of population density is crucial for analysing the relationships among economic growth, environmental protection and resource use. In this study we simulated China's population density in 1998 at 1 km×1 km resolution by integrating DMSP/OLS non-radiance-calibrated night-time images, SPOT/VGT 10-day maximum NDVI composite, population census data and vector county boundaries. Population density, both inside and outside of light patches, was estimated for four types of counties, which were classified according to their light characteristics. The model for estimating population density inside the light patches was developed based on a significant correlation between light intensity and population, while the model for estimating population density outside of light patches was constructed by combining Coulomb's law with electric field superposition principle. Our method was simpler and less expensive than existing methods for spatializing population density. The results were consistent with other estimates but exhibited more spatial heterogeneity and richer information. <s> BIB012 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <s> The present study describes the night-time active forest fire detection capabilities of Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) satellite data over the forest region of Kerala State, India in 2004. Kerala State had a high incidence of forest fires during 2004 because of the extended dry season, with the unusual absence of intermittent rainfall from January to April. DMSP-OLS data were processed to detect active night-time forest fires over Kerala State and validated with ground data and fine-resolution Indian Remote Sensing (IRS)-P6 Advanced Wide Field Sensor (AWiFS) satellite imagery. DMSP-OLS-derived night-time fire products were compared with synchronous Moderate Resolution Imaging Spectroradiometer (MODIS)-derived daytime fire products to check for the spatial agreement and continuity of fires. To estimate the burnt areas, different atmospheric correction algorithms were applied to the IRS-P6 AWiFS dataset; these included the cosine approximation model (COST), ATCOR2 in ERDAS Imagine and the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) code. Atmospheric corrections to the satellite data indicated significant improvement in burnt area estimates. The results of the study suggest a good correlation between AWiFS data-derived burnt areas, DMSP-OLS-derived fire counts and MODIS-derived fire products. The fire occurrences derived from DMSP-OLS and MODIS data were validated with field records on fire occurrences over the study area. <s> BIB013 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <s> Urbanization process involving increased population size, spatially extended land cover and intensified economic activity plays a substantial role in anthropogenic environment changes. Remotely sensed nighttime lights datasets derived from the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) provide a consistent measure for characterizing trends in urban sprawl over time (Sutton, 2003). The utility of DMSP/OLS imagery for monitoring dynamics in human settlement and economic activity at regional to global scales has been widely verified in previous studies through statistical correlations between nighttime light brightness and demographic and economic variables (Elvidge et al., 2001; Ghosh et al., 2010). The quantitative relationship between long-term nighttime light signals and urbanization variables, required for extensive application of DMSP/OLS data for estimating and projecting the trajectory of urban development, however, are not well addressed for individual cities at a local scale. We here present analysis results concerning quantitative responses of stable nighttime lights derived from time series of DMSP/OLS imagery to changes in urbanization variables during 1994-2009 for more than 200 prefectural-level cities and municipalities in China. To identify the best-fitting model for nighttime lights-based measurement of urbanization processes with different development patterns, we comparatively use three regression models: linear, power-law and exponential functions to quantify the long-term relationships between nighttime weighted light area and four urbanization variables: population, gross domestic product (GDP), built-up area and electric power consumption. Our results suggest that nighttime light brightness could be an explanatory indicator for estimating urbanization dynamics at the city level. Various quantitative relationships between urban nighttime lights and urbanization variables may indicate diverse responses of DMSP/OLS nighttime light signals to anthropogenic dynamics in urbanization process in terms of demographic and economic variables. At the city level, growth in weighted lit area may take either a linear, concave (exponential) or convex (power law) form responsive to expanding human population and economic activities during urbanization. Therefore, in practice, quantitative models for using DMSP/OLS data to estimate urbanization dynamics should vary with different patterns of urban development, particularly for cities experiencing rapid urban growth at a local scale. 2012 Elsevier Inc. <s> BIB014 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <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> BIB015 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <s> Abstract The defense meteorological satellite program (DMSP) operational linescan system (OLS) sensors have imaged emitted light from Earth's surface since the 1970s. Temporal overlap in the missions of 5 OLS sensors allows for intercalibration of the annual composites over the past 19 years ( Elvidge et al., 2009 ). The resulting image time series captures a spatiotemporal signature of the growth and evolution of lighted human settlements and development. We use empirical orthogonal function (EOF) analysis and the temporal feature space to characterize and quantify patterns of temporal change in stable night light brightness and spatial extent since 1992. Temporal EOF analysis provides a statistical basis for representing spatially abundant temporal patterns in the image time series as uncorrelated vectors of brightness as a function of time from 1992 to 2009. The variance partition of the eigenvalue spectrum combined with temporal structure of the EOFs and spatial structure of the PCs provides a basis for distinguishing between deterministic multi-year trends and stochastic year-to-year variance. The low order EOFs and principal components (PC) space together discriminate both earlier (1990s) and later (2000s) increases and decreases in brightness. Inverse transformation of these low order dimensions reduces stochastic variance sufficiently so that tri-temporal composites depict potentially deterministic decadal trends. The most pronounced changes occur in Asia. At critical brightness threshold we find an 18% increase in the number of spatially distinct lights and an 80% increase in lighted area in southern and eastern Asia between 1992 and 2009. During this time both China and India experienced a ∼20% increase in number of lights and a ∼270% increase in lighted area – although the timing of the increase is later in China than in India. Throughout Asia a variety of different patterns of brightness increase are apparent in tri-temporal brightness composites – as well as some conspicuous areas of apparently decreasing background luminance and, in many places, intermittent light suggesting development of infrastructure rather than persistently lighted development. Vicarious validation using higher resolution Landsat imagery verifies multiple phases of urban growth in several cities as well as the consistent presence of low DN ( Small et al., 2011 ). <s> BIB016 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <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> BIB017 </s> Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review <s> Types of DMSP/OLS Datasets <s> In remote-sensing community, radiometric calibration of night-time light images has long been a problem, hindering change detection of images in different dates. Currently, an intercalibration model is regarded as the unique solution for the problem, but prior knowledge is needed to extract reference pixels with stable lights, which are hard to obtain in most of the applications. This study proposed an automatic algorithm to extract the reference pixels for convenient use of the intercalibration model, with an assumption that there are sufficient pixels with stable night-time lights in the multi-temporal images. To automatically extract the stable pixels from images in two dates, all pixels in the two dates were entered into a linear regression model, and the outliers viewed as suspected changed pixels were discarded iteratively. Consequently, some stable pixels were extracted and the intercalibration model was implemented. Annual night-time light composites in Beijing, China, from 1992 to 2010 were taken... <s> BIB018
As mentioned in the previous section, researchers have developed various processing methods to generate appropriate datasets for studying a wide range of topics. Based on our review of the 144 selected articles, we found that five main datasets derived from the DMSP/OLS database are commonly used: "stable light" dataset, daily and monthly dataset, Version 4 time series dataset, radiance-calibrated dataset, and Asia light dataset (in order of the most utilized to date). The characteristics and representative applications of each dataset are provided in Table 1 . * The total number of publications is more than 132 because some studies used multiple datasets. The most popular dataset, the "stable light" dataset, was originally developed by Elvidge et al. BIB001 . It was used in 48 of the selected articles. The earliest stable light dataset used the time series of cloud-free images from 1994 to 1995 to distinguish stable lights produced by cities, towns, and industrial facilities from ephemeral lights. The final output was a geo-referenced composite of nighttime stable light (NSL) images with a spatial resolution of 1 km. These images record the percent frequency at which lights were detected, normalized by the number of cloud-free observations. Due to the high correlation between this dataset and the extent of urban area, it was widely used to estimate the spatial distribution of human activity globally and locally (e.g., urban expansion; BIB005 ) and its impacts on soil BIB002 . However, a lack of light intensity in this dataset hindered further research on the intensity of human activities, such as population density. To overcome this shortcoming, Elvidge et al. BIB003 proposed a method for assembling the first radiance-calibrated annual dataset using images acquired between March 1996 and February 1997. This was the third most popular dataset, used by 23 of the 144 studies, and it uses data acquired through low-and high-gain settings in a time series fashion. It records spatial brightness variation within stable light areas and helps minimize the blooming effect that lights "diffuse" into neighboring cells. The additional spatial information on light intensity helps increase the accuracy of human activity estimations BIB009 , and allows researchers to explore more research topics, especially in studies of urban areas that are mainly concerned with saturation BIB004 . The Version 4 DMSP/OLS Nighttime Lights Time Series dataset was recently developed by NOAA/NGDC. It was used by 33 of the 144 studies because it could be obtained directly and free of charge online as of January 2010. The files in this dataset are cloud-free annual composites from 1992 to 2012 with a spatial resolution of 1 km; the dataset includes 33 annual composites because multiple satellites collected the same data in some years. It consists of three types of data: cloud-free coverage, NSL, and average visible data. Among these, the NSL dataset is most popular one because it removes background noise and records light intensity from cities and townships. The 1992-2012 time series was used to analyze the temporal dynamics of socioeconomic and demographic changes BIB014 BIB016 . The most pressing challenge in using these datasets for long-term analysis is the calibration of the data BIB011 , because the time series data are from six different satellites (F10, F12, F14, F15, F16, and F18) equipped with OLS sensors without onboard calibration. The absence of inter-satellite calibration and onboard calibration strongly limits the inter-annual comparability of light intensity represented by the digital number (DN) values. To overcome this limitation, different inter-calibration methods, largely based on an assumption that light intensity in some areas did not change throughout the timeframe of interest, were proposed by researchers BIB011 BIB015 BIB017 BIB018 . A unique dataset of non-calibrated time series nighttime images was produced by the Japan National Institute of Environmental Studies and Tokyo University BIB010 . It contains extractions of light data for East Asia, which is of lower intensity and has less saturation than lights in developed Western countries. Based on the challenges identified with the stable light-and radiance-calibrated datasets, this dataset provides annual composites of average light intensity information extracted from stable light observations; as such, it combines stable light and light intensity but with less saturation. This dataset was used to map urban expansion BIB010 and model population density in China BIB012 . The final dataset to discuss is composed of daily raw images or monthly composites provided by NOAA/NGDC. Unlike the other four datasets, researchers used the data to observe some unstable and short-term light phenomena, such as fishing vessel dynamics in coastal areas BIB006 , forest fires and burned areas in India BIB013 , damage estimation of natural disasters BIB007 , effects of violent conflicts on refugee movement  , and detection of bioluminescence produced by colonies of bacteria in oceans BIB008 . However, the final datasets are not free, and their applications are strongly limited by the cost of each orbit of data and the complex preprocessing procedures.