Estimating global economic well-being with unlit settlements.

It is well established that nighttime radiance, measured from satellites, correlates with economic prosperity across the globe. In developing countries, areas with low levels of detected radiance generally indicate limited development - with unlit areas typically being disregarded. Here we combine satellite nighttime lights and the world settlement footprint for the year 2015 to show that 19% of the total settlement footprint of the planet had no detectable artificial radiance associated with it. The majority of unlit settlement footprints are found in Africa (39%), rising to 65% if we consider only rural settlement areas, along with numerous countries in the Middle East and Asia. Significant areas of unlit settlements are also located in some developed countries. For 49 countries spread across Africa, Asia and the Americas we are able to predict and map the wealth class obtained from ~2,400,000 geo-located households based upon the percent of unlit settlements, with an overall accuracy of 87%.

Terrorism, geopolitics, and oil security: Using remote sensing to estimate oil production of the Islamic State.

As the world's most traded commodity, oil production is typically well monitored and analyzed. It also has established links to geopolitics, international relations, and security. Despite this attention, the illicit production, refining, and trade of oil and derivative products occur all over the world and provide significant revenues outside of the oversight and regulation of governments. A prominent manifestation of this phenomenon is how terrorist and insurgent organizations-including the Islamic State group, also known as ISIL/ISIS or Daesh-use oil as a revenue source. Understanding the spatial and temporal variation in production can help determine the scale of operations, technical capacity, and revenue streams. This information, in turn, can inform both security and reconstruction strategies. To this end, we use satellite multi-spectral imaging and ground-truth pre-war output data to effectively construct a real-time census of oil production in areas controlled by the ISIL terrorist group. More broadly, remotely measuring the activity of extractive industries in conflict-affected areas without reliable administrative data can support a broad range of public policy and decisions and military operations.

Modeling of Electric Demand for Sustainable Energy and Management in India Using Spatio-Temporal DMSP-OLS Night-Time Data.

Changes in the pattern of electric power consumption in India have influenced energy utilization processes and socio-economic development to greater extent during the last few decades. Assessment of spatial distribution of electricity consumption is, thus, essential for projecting availability of energy resource and planning its infrastructure. This paper makes an attempt to model the future electricity demand for sustainable energy and its management in India. The nighttime light database provides a good approximation of availability of energy. We utilized defense meteorological satellite program-operational line-scan system (DMSP-OLS) nighttime satellite data, electricity consumption (1993-2013), gross domestic product (GDP) and population growth to construct the model. We also attempted to examine the sensitiveness of electricity consumption to GDP and population growth. The results revealed that the calibrated DMSP and model has provided realistic information on the electric demand with respect to GDP and population, with a better accuracy of r 2 = 0.91. The electric demand was found to be more sensitive to GDP (r = 0.96) than population growth (r = 0.76) as envisaged through correlation analysis. Hence, the model proved to be useful tool in predicting electric demand for its sustainable use and management.

Artificially lit surface of Earth at night increasing in radiance and extent.

A central aim of the "lighting revolution" (the transition to solid-state lighting technology) is decreased energy consumption. This could be undermined by a rebound effect of increased use in response to lowered cost of light. We use the first-ever calibrated satellite radiometer designed for night lights to show that from 2012 to 2016, Earth's artificially lit outdoor area grew by 2.2% per year, with a total radiance growth of 1.8% per year. Continuously lit areas brightened at a rate of 2.2% per year. Large differences in national growth rates were observed, with lighting remaining stable or decreasing in only a few countries. These data are not consistent with global scale energy reductions but rather indicate increased light pollution, with corresponding negative consequences for flora, fauna, and human well-being.

The new world atlas of artificial night sky brightness.

Artificial lights raise night sky luminance, creating the most visible effect of light pollution-artificial skyglow. Despite the increasing interest among scientists in fields such as ecology, astronomy, health care, and land-use planning, light pollution lacks a current quantification of its magnitude on a global scale. To overcome this, we present the world atlas of artificial sky luminance, computed with our light pollution propagation software using new high-resolution satellite data and new precision sky brightness measurements. This atlas shows that more than 80% of the world and more than 99% of the U.S. and European populations live under light-polluted skies. The Milky Way is hidden from more than one-third of humanity, including 60% of Europeans and nearly 80% of North Americans. Moreover, 23% of the world's land surfaces between 75°N and 60°S, 88% of Europe, and almost half of the United States experience light-polluted nights.

A thermodynamic geography: night-time satellite imagery as a proxy measure of emergy.

Night-time satellite imagery enables the measurement, visualization, and mapping of energy consumption in an area. In this paper, an index of the "sum of lights" as observed by night-time satellite imagery within national boundaries is compared with the emergy of the nations. Emergy is a measure of the solar energy equivalent used, directly or indirectly, to support the processes that characterize the economic activity in a country. Emergy has renewable and non-renewable components. Our results show that the non-renewable component of national emergy use is positively correlated with night-time satellite imagery. This relationship can be used to produce emergy density maps which enable the incorporation of spatially explicit representations of emergy in geographic information systems. The region of Abruzzo (Italy) is used to demonstrate this relationship as a spatially disaggregate case.

Citizen science provides valuable data for monitoring global night sky luminance.

The skyglow produced by artificial lights at night is one of the most dramatic anthropogenic modifications of Earth's biosphere. The GLOBE at Night citizen science project allows individual observers to quantify skyglow using star maps showing different levels of light pollution. We show that aggregated GLOBE at Night data depend strongly on artificial skyglow, and could be used to track lighting changes worldwide. Naked eye time series can be expected to be very stable, due to the slow pace of human eye evolution. The standard deviation of an individual GLOBE at Night observation is found to be 1.2 stellar magnitudes. Zenith skyglow estimates from the "First World Atlas of Artificial Night Sky Brightness" are tested using a subset of the GLOBE at Night data. Although we find the World Atlas overestimates sky brightness in the very center of large cities, its predictions for Milky Way visibility are accurate.

Suomi satellite brings to light a unique frontier of nighttime environmental sensing capabilities.

Most environmental satellite radiometers use solar reflectance information when it is available during the day but must resort at night to emission signals from infrared bands, which offer poor sensitivity to low-level clouds and surface features. A few sensors can take advantage of moonlight, but the inconsistent availability of the lunar source limits measurement utility. Here we show that the Day/Night Band (DNB) low-light visible sensor on the recently launched Suomi National Polar-orbiting Partnership (NPP) satellite has the unique ability to image cloud and surface features by way of reflected airglow, starlight, and zodiacal light illumination. Examples collected during new moon reveal not only meteorological and surface features, but also the direct emission of airglow structures in the mesosphere, including expansive regions of diffuse glow and wave patterns forced by tropospheric convection. The ability to leverage diffuse illumination sources for nocturnal environmental sensing applications extends the advantages of visible-light information to moonless nights.

Limiting the impact of light pollution on human health, environment and stellar visibility.

Light pollution is one of the most rapidly increasing types of environmental degradation. Its levels have been growing exponentially over the natural nocturnal lighting levels provided by starlight and moonlight. To limit this pollution several effective practices have been defined: the use of shielding on lighting fixture to prevent direct upward light, particularly at low angles above the horizon; no over lighting, i.e. avoid using higher lighting levels than strictly needed for the task, constraining illumination to the area where it is needed and the time it will be used. Nevertheless, even after the best control of the light distribution is reached and when the proper quantity of light is used, some upward light emission remains, due to reflections from the lit surfaces and atmospheric scatter. The environmental impact of this "residual light pollution", cannot be neglected and should be limited too. Here we propose a new way to limit the effects of this residual light pollution on wildlife, human health and stellar visibility. We performed analysis of the spectra of common types of lamps for external use, including the new LEDs. We evaluated their emissions relative to the spectral response functions of human eye photoreceptors, in the photopic, scotopic and the 'meltopic' melatonin suppressing bands. We found that the amount of pollution is strongly dependent on the spectral characteristics of the lamps, with the more environmentally friendly lamps being low pressure sodium, followed by high pressure sodium. Most polluting are the lamps with a strong blue emission, like Metal Halide and white LEDs. Migration from the now widely used sodium lamps to white lamps (MH and LEDs) would produce an increase of pollution in the scotopic and melatonin suppression bands of more than five times the present levels, supposing the same photopic installed flux. This increase will exacerbate known and possible unknown effects of light pollution on human health, environment and on visual perception of the Universe by humans. We present quantitative criteria to evaluate the lamps based on their spectral emissions and we suggest regulatory limits for future lighting.

Spectral identification of lighting type and character.

We investigated the optimal spectral bands for the identification of lighting types and the estimation of four major indices used to measure the efficiency or character of lighting. To accomplish these objectives we collected high-resolution emission spectra (350 to 2,500 nm) for forty-three different lamps, encompassing nine of the major types of lamps used worldwide. The narrow band emission spectra were used to simulate radiances in eight spectral bands including the human eye photoreceptor bands (photopic, scotopic, and "meltopic") plus five spectral bands in the visible and near-infrared modeled on bands flown on the Landsat Thematic Mapper (TM). The high-resolution continuous spectra are superior to the broad band combinations for the identification of lighting type and are the standard for calculation of Luminous Efficacy of Radiation (LER), Correlated Color Temperature (CCT) and Color Rendering Index (CRI). Given the high cost that would be associated with building and flying a hyperspectral sensor with detection limits low enough to observe nighttime lights we conclude that it would be more feasible to fly an instrument with a limited number of broad spectral bands in the visible to near infrared. The best set of broad spectral bands among those tested is blue, green, red and NIR bands modeled on the band set flown on the Landsat Thematic Mapper. This set provides low errors on the identification of lighting types and reasonable estimates of LER and CCT when compared to the other broad band set tested. None of the broad band sets tested could make reasonable estimates of Luminous Efficacy (LE) or CRI. The photopic band proved useful for the estimation of LER. However, the three photoreceptor bands performed poorly in the identification of lighting types when compared to the bands modeled on the Landsat Thematic Mapper. Our conclusion is that it is feasible to identify lighting type and make reasonable estimates of LER and CCT using four or more spectral bands with minimal spectral overlap spanning the 0.4 to 1.0 um region.

Global Distribution and Density of Constructed Impervious Surfaces.

We present the first global inventory of the spatial distribution and density ofconstructed impervious surface area (ISA). Examples of ISA include roads, parking lots,buildings, driveways, sidewalks and other manmade surfaces. While high spatialresolution is required to observe these features, the new product reports the estimateddensity of ISA on a one-km² grid based on two coarse resolution indicators of ISA - thebrightness of satellite observed nighttime lights and population count. The model wascalibrated using 30-meter resolution ISA of the USA from the U.S. Geological Survey.Nominally the product is for the years 2000-01 since both the nighttime lights andreference data are from those two years. We found that 1.05% of the United States landarea is impervious surface (83,337 km²) and 0.43 % of the world's land surface (579,703km²) is constructed impervious surface. China has more ISA than any other country(87,182 km²), but has only 67 m² of ISA per person, compared to 297 m² per person in theUSA. The distribution of ISA in the world's primary drainage basins indicates that watersheds damaged by ISA are primarily concentrated in the USA, Europe, Japan, China and India. The authors believe the next step for improving the product is to include reference ISA data from many more areas around the world.

Detection of a bioluminescent milky sea from space.

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 approximately 15,400-km(2) 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.

Mapping and modeling the biogeochemical cycling of turf grasses in the United States.

Turf grasses are ubiquitous in the urban landscape of the United States and are often associated with various types of environmental impacts, especially on water resources, yet there have been limited efforts to quantify their total surface and ecosystem functioning, such as their total impact on the continental water budget and potential net ecosystem exchange (NEE). In this study, relating turf grass area to an estimate of fractional impervious surface area, it was calculated that potentially 163,800 km2 (+/- 35,850 km2) of land are cultivated with turf grasses in the continental United States, an area three times larger than that of any irrigated crop. Using the Biome-BGC ecosystem process model, the growth of warm-season and cool-season turf grasses was modeled at a number of sites across the 48 conterminous states under different management scenarios, simulating potential carbon and water fluxes as if the entire turf surface was to be managed like a well-maintained lawn. The results indicate that well-watered and fertilized turf grasses act as a carbon sink. The potential NEE that could derive from the total surface potentially under turf (up to 17 Tg C/yr with the simulated scenarios) would require up to 695 to 900 liters of water per person per day, depending on the modeled water irrigation practices, suggesting that outdoor water conservation practices such as xeriscaping and irrigation with recycled waste-water may need to be extended as many municipalities continue to face increasing pressures on freshwater.