| Records |
| Author |
Elvidge, C.D.; Ziskin, D.; Baugh, K.E.; Tuttle, B.T.; Ghosh, T.; Pack, D.W.; Erwin, E.H.; Zhizhin, M. |
Title  |
A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data |
Type |
Journal Article |
| Year |
2009 |
Publication |
Energies |
Abbreviated Journal |
Energies |
| Volume |
2 |
Issue |
3 |
Pages |
595-622 |
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| Abstract |
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 m3 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 (CO2e) 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 satell |
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gas flaring; carbon emissions; nighttime lights; DMSP-OLS; remote sensing; light at night; satellite |
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1996-1073 |
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IDA @ john @ |
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231 |
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Swaddle, J.P.; Francis, C.D.; Barber, J.R.; Cooper, C.B.; Kyba, C.C.M.; Dominoni, D.M.; Shannon, G.; Aschehoug, E.; Goodwin, S.E.; Kawahara, A.Y.; Luther, D.; Spoelstra, K.; Voss, M.; Longcore, T. |
| Title |
A framework to assess evolutionary responses to anthropogenic light and sound |
Type |
Journal Article |
| Year |
2015 |
Publication |
Trends in Ecology & Evolution |
Abbreviated Journal |
Trends in Ecology & Evolution |
| Volume |
30 |
Issue |
9 |
Pages |
550–560 |
| Keywords |
animals, biology, ecology, evolution |
| Abstract |
Human activities have caused a near-ubiquitous and evolutionarily-unprecedented increase in environmental sound levels and artificial night lighting. These stimuli reorganize communities by interfering with species-specific perception of time-cues, habitat features, and auditory and visual signals. Rapid evolutionary changes could occur in response to light and noise, given their magnitude, geographical extent, and degree to which they represent unprecedented environmental conditions. We present a framework for investigating anthropogenic light and noise as agents of selection, and as drivers of other evolutionary processes, to influence a range of behavioral and physiological traits such as phenological characters and sensory and signaling systems. In this context, opportunities abound for understanding contemporary and rapid evolution in response to human-caused environmental change. |
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0169-5347 |
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LoNNe @ christopher.kyba @ |
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1202 |
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Li, K.; Chen, Y. |
| Title |
A Genetic Algorithm-Based Urban Cluster Automatic Threshold Method by Combining VIIRS DNB, NDVI, and NDBI to Monitor Urbanization |
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Journal Article |
| Year |
2018 |
Publication |
Remote Sensing |
Abbreviated Journal |
Remote Sensing |
| Volume |
10 |
Issue |
2 |
Pages |
277 |
| Keywords |
Remote Sensing |
| Abstract |
Accurate and timely information related to quantitative descriptions and spatial distributions of urban areas is crucial to understand urbanization dynamics and is also helpful to address environmental issues associated with rapid urban land-cover changes. Thresholding is acknowledged as the most popular and practical way to extract urban information from nighttime lights. However, the difficulty of determining optimal threshold remains challenging to applications of this method. In order to address the problem of selecting thresholds, a Genetic Algorithm-based urban cluster automatic threshold (GA-UCAT) method by combining Visible-Infrared Imager-Radiometer Suite Day/Night band (VIIRS DNB), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-up Index (NDBI) is proposed to distinguish urban areas from dark rural background in NTL images. The key point of this proposed method is to design an appropriate fitness function of GA by means of integrating between-class variance and inter-class variance with all these three data sources to determine optimal thresholds. In accuracy assessments by comparing with ground truth—Landsat 8 OLI images, this new method has been validated and results with OA (Overall Accuracy) ranging from 0.854 to 0.913 and Kappa ranging from 0.699 to 0.722 show that the GA-UCAT approach is capable of describing spatial distributions and giving detailed information of urban extents. Additionally, there is discussion on different classifications of rural residential spots in Landsat remote sensing images and nighttime light (NTL) and evaluations of spatial-temporal development patterns of five selected Chinese urban clusters from 2012 to 2017 on utilizing this proposed method. The new method shows great potential to map global urban information in a simple and accurate way and to help address urban environmental issues. |
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2072-4292 |
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GFZ @ kyba @ |
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2340 |
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| Author |
Levin, N.; Zhang, Q. |
| Title |
A global analysis of factors controlling VIIRS nighttime light levels from densely populated areas |
Type |
Journal Article |
| Year |
2017 |
Publication |
Remote Sensing of Environment |
Abbreviated Journal |
Remote Sensing of Environment |
| Volume |
190 |
Issue |
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Pages |
366-382 |
| Keywords |
Remote Sensing |
| Abstract |
Remote sensing of nighttime lights has been shown as a good surrogate for estimating population and economic activity at national and sub-national scales, using DMSP satellites. However, few studies have examined the factors explaining differences in nighttime brightness of cities at a global scale. In this study, we derived quantitative estimates of nighttime lights with the new VIIRS sensor onboard the Suomi NPP satellite in January 2014 and in July 2014, with two variables: mean brightness and percent lit area. We performed a global analysis of all densely populated areas (n = 4153, mostly corresponding to metropolitan areas), which we defined using high spatial resolution Landscan population data. National GDP per capita was better in explaining nighttime brightness levels (0.60 < Rs < 0.70) than GDP density at a spatial resolution of 0.25° (0.25 < Rs < 0.43), or than a city-level measure of GDP per capita (in proportion to each city's fraction of the national population; 0.49 < Rs < 0.62). We found that in addition to GDP per capita, the nighttime brightness of densely populated areas was positively correlated with MODIS derived percent urban area (0.46 < Rs < 0.60), the density of the road network (0.51 < Rs < 0.67), and with latitude (0.31 < Rs < 0.42) at p < 0.001. NDVI values (representing vegetation cover) were found to be negatively correlated with cities' brightness in winter time (− 0.48 < Rs < − 0.22), whereas snow cover (enhancing artificial light reflectance) was found to be positively correlated with cities' brightness in winter time (0.17 < Rs < 0.35). Overall, the generalized linear model we built was able to explain > 45% of the variability in cities' nighttime brightness, when both physical and socio-economic variables were included. Within the generalized linear model, the percent of national GDP derived from income (rents) from natural gas and oil, was also found as one of the statistically significant variables. Our findings show that cities' nighttime brightness can change with the seasons as a function of vegetation and snow cover, two variables affecting surface albedo. Explaining cities' nighttime brightness is therefore affected not only by country level factors (such as GDP), but also by the built environment and by climatic factors. |
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0034-4257 |
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LoNNe @ kyba @ |
Serial |
1628 |
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Zhou, Y.; Smith, S.J.; Zhao, K.; Imhoff, M.; Thomson, A.; Bond-Lamberty, B.; Asrar, G.R.; Zhang, X.; He, C.; Elvidge, C.D. |
| Title |
A global map of urban extent from nightlights |
Type |
Journal Article |
| Year |
2015 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
| Volume |
10 |
Issue |
5 |
Pages |
054011 |
| Keywords |
Remote Sensing |
| Abstract |
Urbanization, a major driver of global change, profoundly impacts our physical and social world, for example, altering not just water and carbon cycling, biodiversity, and climate, but also demography, public health, and economy. Understanding these consequences for better scientific insights and effective decision-making unarguably requires accurate information on urban extent and its spatial distributions. We developed a method to map the urban extent from the defense meteorological satellite program/operational linescan system nighttime stable-light data at the global level and created a new global 1 km urban extent map for the year 2000. Our map shows that globally, urban is about 0.5% of total land area but ranges widely at the regional level, from 0.1% in Oceania to 2.3% in Europe. At the country level, urbanized land varies from about 0.01 to 10%, but is lower than 1% for most (70%) countries. Urbanization follows land mass distribution, as anticipated, with the highest concentration between 30° N and 45° N latitude and the largest longitudinal peak around 80° W. Based on a sensitivity analysis and comparison with other global urban area products, we found that our global product of urban areas provides a reliable estimate of global urban areas and offers the potential for producing a time-series of urban area maps for temporal dynamics analyses. |
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1748-9326 |
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LoNNe @ christopher.kyba @ |
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1174 |
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