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 satellite data will spur improved utilization of gas that was simply burnt as waste in previous years.

The potential use of satellite observed nighttime lights for estimating carbon-dioxide (CO₂) emissions has been demonstrated in several previous studies. However, the procedures for a moderate resolution (1 km² grid cells) global map of fossil fuel CO₂ emissions based on nighttime lights are still in the developmental phase. We report on the development of a method for mapping distributed fossil fuel CO₂ emissions (excluding electric power utilities) at 30 arc-seconds or approximately 1 km² resolution using nighttime lights data collected by the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS). A regression model, Model 1, was initially developed based on carbon emissions from five sectors of the Vulcan data produced by the Purdue University and a nighttime satellite image of the U.S. The coefficient derived through Model 1 was applied to the global nighttime image but it resulted in underestimation of CO₂ emissions for most of the world’s countries, and the states of the U.S. Thus, a second model, Model 2 was developed by allocating the distributed CO₂ emissions (excluding emissions from utilities) using a combination of DMSP-OLS nighttime image and population count data from the U.S. Department of Energy's (DOE) LandScan grid. The CO₂ emissions were distributed in proportion to the brightness of the DMSP nighttime lights in areas where lighting was detected. In areas with no DMSP detected lighting, the CO₂ emissions were distributed based on population count, with the assumption that people who live in these areas emit half as much CO₂ as people who live in the areas with DMSP detected lighting. The results indicate that the relationship between satellite observed nighttime lights and CO₂ emissions is complex, with differences between sectors and variations in lighting practices between countries. As a result it is not possible to make independent estimates of CO₂ emissions with currently available coarse resolution panchromatic satellite observed nighttime lights. However, the nighttime lights image in conjunction with the population grid can help in more accurate disaggregation of national CO₂ emissions to a moderate resolution spatial grid.

This paper proposes an experimental methodology toward describing and quantifying coral reef bleaching using very high spatial resolution optical satellite imagery. Sea surface temperature-based bleaching alerts issued by NOAA's Coral Reef Watch triggered image acquisition and served as an indication for high bleaching probability. Images of suspected coral reef bleaching events and reference images of the same reefs during previous unbleached conditions were coregistered and radiometrically normalized for change detection. An experimental methodology was developed to describe the severity and extent of the bleaching. The methodology hinges on the creation of the Coral Bleaching Index (CBI), constructed from change detected in the green, blue, and red wavelength bands. Results are provided in the form of colorized difference images showing areas of observed bleaching in gold, as well as CBI images, visualizing varying bleaching intensities. Comparison of the CBI with available field validation data yielded a correlation, however additional reference data would be needed for more detailed quality assessment. This technique is seen as a step toward the routine detection and long-term monitoring of coral reef bleaching from space and serves as a proposed tool for detecting bleaching in remote areas where observers cannot be deployed.

Mapping the Constructed Surface Area Density for China