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Addison, D., & Stewart, B. (2015). Nighttime Lights Revisited: The Use of Nighttime Lights Data as a Proxy for Economic Variables. World Bank Group.
Abstract: The growing availability of free or inexpensive satellite imagery has inspired many researchers to investigate the use of earth observation data for monitoring economic activity around the world. One of the most popular earth observation data sets is the so-called nighttime lights from the Defense Meteorological Satellite Program. Researchers have found positive correlations between nighttime lights and several economic variables. These correlations are based on data measured in levels, with a cross-section of observations within a single time period across countries or other geographic units. The findings suggest that nighttime lights could be used as a proxy for some economic variables, especially in areas or times where data are weak or unavailable. Yet, logic suggests that nighttime lights cannot serve as a good proxy for monitoring the within-in country growth rates all of these variables. Examples examined this paper include constant price gross domestic product, nonagricultural gross domestic product, manufacturing value
added, and capital stocks, as well as electricity consumption, total population, and urban population. The study finds that the Defense Meteorological Satellite Program data are quite noisy and therefore the resulting growth elasticities of Defense Meteorological Satellite Program nighttime lights with respect to most of these socioeconomic variables are low, unstable over time, and generate little explanatory power. The one exception for which Defense Meteorological Satellite Program nighttime lights could serve as a proxy is electricity consumption, measured in 10-year intervals. It is hoped that improved data from the recently launched Suomi National Polar-Orbiting Partnership satellite will help expand or improve these outcomes. Testing this should be an important next step. |
Doll, C. N. H., Muller, J. - P., & Morley, J. G. (2006). Mapping regional economic activity from night-time light satellite imagery. Ecological Economics, 57(1), 75–92.
Abstract: The recognition that the elements of the âanthropoceneâ 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.
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Mazor, T., Levin, N., Possingham, H. P., Levy, Y., Rocchini, D., Richardson, A. J., et al. (2013). Can satellite-based night lights be used for conservation? The case of nesting sea turtles in the Mediterranean. Biological Conservation, 159, 63–72.
Abstract: Artificial night lights pose a major threat to multiple species. However, this threat is often disregarded in conservation management and action because it is difficult to quantify its effect. Increasing availability of high spatial-resolution satellite images may enable us to better incorporate this threat into future work, particularly in highly modified ecosystems such as the coastal zone. In this study we examine the potential of satellite night light imagery to predict the distribution of the endangered loggerhead (Caretta caretta) and green (Chelonia mydas) sea turtle nests in the eastern Mediterranean coastline. Using remote sensing tools and high resolution data derived from the SAC-C satellite and the International Space Station, we examined the relationship between the long term spatial patterns of sea turtle nests and the intensity of night lights along Israelâs entire Mediterranean coastline. We found that sea turtles nests are negatively related to night light intensity and are concentrated in darker sections along the coast. Our resulting GLMs showed that night lights were a significant factor for explaining the distribution of sea turtle nests. Other significant variables included: cliff presence, human population density and infrastructure. This study is one of the first to show that night lights estimated with satellite-based imagery can be used to help explain sea turtle nesting activity at a detailed resolution over large areas. This approach can facilitate the management of species affected by night lights, and will be particularly useful in areas that are inaccessible or where broad-scale prioritization of conservation action is required.
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Miller, S., Straka, W., Mills, S., Elvidge, C., Lee, T., Solbrig, J., et al. (2013). Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band. Remote Sensing, 5(12), 6717–6766.
Abstract: Daytime measurements of reflected sunlight in the visible spectrum have been a staple of Earth-viewing radiometers since the advent of the environmental satellite platform. At night, these same optical-spectrum sensors have traditionally been limited to thermal infrared emission, which contains relatively poor information content for many important weather and climate parameters. These deficiencies have limited our ability to characterize the full diurnal behavior and processes of parameters relevant to improved monitoring, understanding and modeling of weather and climate processes. Visible-spectrum light information does exist during the nighttime hours, originating from a wide variety of sources, but its detection requires specialized technology. Such measurements have existed, in a limited way, on USA Department of Defense satellites, but the Suomi National Polar-orbiting Partnership (NPP) satellite, which carries a new Day/Night Band (DNB) radiometer, offers the first quantitative measurements of nocturnal visible and near-infrared light. Here, we demonstrate the expanded potential for nocturnal low-light visible applications enabled by the DNB. Via a combination of terrestrial and extraterrestrial light sources, such observations are always availableâexpanding many current existing applications while enabling entirely new capabilities. These novel low-light measurements open doors to a wealth of new interdisciplinary research topics while lighting a pathway toward the optimized design of follow-on satellite based low light visible sensors.
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Sutton, P. C. (2003). A scale-adjusted measure of “Urban sprawl” using nighttime satellite imagery. Remote Sensing of Environment, 86(3), 353–369.
Abstract: âUrban Sprawlâ is a growing concern of citizens, environmental organizations, and governments. Negative impacts often attributed to urban sprawl are traffic congestion, loss of open space, and increased pollutant runoff into natural waterways. Definitions of âUrban Sprawlâ range from local patterns of land use and development to aggregate measures of per capita land consumption for given contiguous urban areas (UA). This research creates a measure of per capita land use consumption as an aggregate index for the spatially contiguous urban areas of the conterminous United States with population of 50,000 or greater. Nighttime satellite imagery obtained by the Defense Meteorological Satellite Program's Operational Linescan System (DMSP OLS) is used as a proxy measure of urban extent. The corresponding population of these urban areas is derived from a grid of the block group level data from the 1990 U.S. Census. These numbers are used to develop a regression equation between Ln(Urban Area) and Ln(Urban Population). The âscale-adjustmentâ mentioned in the title characterizes the âUrban Sprawlâ of each of the urban areas by how far above or below they are on the âSprawl Lineâ determined by this regression. This âSprawl Lineâ allows for a more fair comparison of âUrban Sprawlâ between larger and smaller metropolitan areas because a simple measure of per capita land consumption or population density does not account for the natural increase in aggregate population density that occurs as cities grow in population. Cities that have more âUrban Sprawlâ by this measure tended to be inland and Midwestern cities such as MinneapolisâSt. Paul, Atlanta, DallasâFt. Worth, St. Louis, and Kansas City. Surprisingly, west coast cities including Los Angeles had some of the lowest levels of âUrban Sprawlâ by this measure. There were many low light levels seen in the nighttime imagery around these major urban areas that were not included in either of the two definitions of urban extent used in this study. These areas may represent a growing commuter-shed of urban workers who do not live in the urban core but nonetheless contribute to many of the impacts typically attributed to âUrban Sprawlâ. âUrban Sprawlâ is difficult to define precisely partly because public perception of sprawl is likely derived from local land use planning decisions, spatio-demographic change in growing urban areas, and changing values and social mores resulting from differential rates of international migration to the urban areas of the United States. Nonetheless, the aggregate measures derived here are somewhat different than similar previously used measures in that they are âscale-adjustedâ; also, the spatial patterns of âUrban Sprawlâ shown here shed some insight and raise interesting questions about how the dynamics of âUrban Sprawlâ are changing.
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