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Daniel Ziskin

Bio: Daniel Ziskin is an academic researcher from University of Colorado Boulder. The author has contributed to research in topics: Population & Impervious surface. The author has an hindex of 8, co-authored 14 publications receiving 1259 citations. Previous affiliations of Daniel Ziskin include University of Denver & Cooperative Institute for Research in Environmental Sciences.

Papers
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Journal ArticleDOI
07 Aug 2009-Energies
TL;DR: In this article, the authors used low light imaging data acquired by the Defense Meteorological Satellite Program (DMSP) from 1994 through 2008 to estimate national and global gas flaring.
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 satellite data will spur improved utilization of gas that was simply burnt as waste in previous years.

796 citations

Journal ArticleDOI
31 Dec 2010
TL;DR: The Stable Lights product as discussed by the authors is a global annual cloud-free composite, which averages the OLS visible band data for one satellite from the cloud free segments of individual orbits.
Abstract: Since 1994, NGDC has had an active program focused on global mapping of nighttime lights using the data collected by the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) sensors. The basic product is a global annual cloud-free composite, which averages the OLS visible band data for one satellite from the cloud-free segments of individual orbits. Over the years, NGDC has developed automatic algorithms for screening the quality of the nighttime visible band observations to remove areas contaminated by sunlight, moonlight, and the presence of clouds. In the Stable Lights product generation, fires and other ephemeral lights are removed based on their high brightness and short duration. Background noise is removed by setting thresholds based on visible band values found in areas known to be free of detectable lights. In 2010, NGDC released the version 4 time series of Stable Lights, spanning the years 1992-2009. These are available online at .

197 citations

Journal ArticleDOI
08 Dec 2010-Energies
TL;DR: In this paper, the authors developed 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).
Abstract: 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.

142 citations

Proceedings ArticleDOI
20 May 2009
TL;DR: The Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) has a unique capability to collect low-light imaging data of the earth at night as discussed by the authors.
Abstract: The Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) has a unique capability to collect low-light imaging data of the earth at night. The OLS and its predecessors have collected this style of data on a nightly global basis since 1972. The digital archive of OLS data extends back to 1992. Over the years several global nighttime lights products have been generated. NGDC has now produced a set of global cloud-free nighttime lights products, specifically processed for the detection of changes in lighting emitted by human settlements, spanning 1992-93 to 2008. While the OLS is far from ideal for observing nighttime lights, the DMSP nighttime lights products have been successfully used in modeling the spatial distribution of population density, carbon emissions, and economic activity.

73 citations

Journal ArticleDOI
31 Dec 2010
TL;DR: In this article, a limited set of observations have been obtained at low lunar illumination were obtained where the gain of the detector was set significantly lower than its typical operational setting (sometimes by a factor of 100).
Abstract: The Operational Linescan System (OLS) flown on the Defense Meteorological Satellite Program (DMSP) satellites, has a unique capability to record low light imaging data at night worldwide. These data are archived at the National Oceanic and Atmospheric Administration (NOAA) National Geophysical Data Center (NGDC). The useful data record stretches back to 1992 and is ongoing. The OLS visible band detector observes radiances about one million times dimmer than most other Earth observing satellites. The sensor is typically operated in a high gain setting to enable the detection of moonlit clouds. However, with six bit quantization and limited dynamic range, the recorded data are saturated in the bright cores of urban centers. A limited set of observations have been obtained at low lunar illumination were obtained where the gain of the detector was set significantly lower than its typical operational setting (sometimes by a factor of 100). By combining these sparse data acquired at low gain settings with the operational data acquired at high gain settings, we have produced a global nighttime lights product for 2006 with no sensor saturation. This product can be related to radiances based on the pre-flights sensor calibration.

73 citations


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TL;DR: A statistical framework is developed that uses satellite data on lights growth to augment existing income growth measures, under the assumption that measurement error in using observed light as an indicator of income is uncorrelated with measurementerror in national income accounts.
Abstract: GDP growth is often measured poorly for countries and rarely measured at all for cities or subnational regions. We propose a readily available proxy: satellite data on lights at night. We develop a statistical framework that uses lights growth to augment existing income growth measures, under the assumption that measurement error in using observed light as an indicator of income is uncorrelated with measurement error in national income accounts. For countries with good national income accounts data, information on growth of lights is of marginal value in estimating the true growth rate of income, while for countries with the worst national income accounts, the optimal estimate of true income growth is a composite with roughly equal weights. Among poor-data countries, our new estimate of average annual growth differs by as much as 3 percentage points from official data. Lights data also allow for measurement of income growth in sub- and supranational regions. As an application, we examine growth in Sub Saharan African regions over the last 17 years. We find that real incomes in non-coastal areas have grown faster by 1/3 of an annual percentage point than coastal areas; non-malarial areas have grown faster than malarial ones by 1/3 to 2/3 annual percent points; and primate city regions have grown no faster than hinterland areas. Such applications point toward a research program in which "empirical growth" need no longer be synonymous with "national income accounts."

1,449 citations

Journal ArticleDOI
TL;DR: In this paper, satellite data on lights at night is used to augment existing income growth measures, under the assumption that measurement errors in using observed light as an indicator of income is uncorrelated with measurement error in national income accounts.
Abstract: GDP growth is often measured poorly for countries and rarely measured at all for cities or subnational regions. We propose a readily available proxy: satellite data on lights at night. We develop a statistical framework that uses lights growth to augment existing income growth measures, under the assumption that measurement error in using observed light as an indicator of income is uncorrelated with measurement error in national income accounts. For countries with good national income accounts data, information on growth of lights is of marginal value in estimating the true growth rate of income, while for countries with the worst national income accounts, the optimal estimate of true income growth is a composite with roughly equal weights. Among poor-data countries, our new estimate of average annual growth differs by as much as 3 percentage points from official data. Lights data also allow for measurement of income growth in sub- and supranational regions. As an application, we examine growth in Sub Saharan African regions over the last 17 years. We find that real incomes in non-coastal areas have grown faster by 1/3 of an annual percentage point than coastal areas; non-malarial areas have grown faster than malarial ones by 1/3 to 2/3 annual percent points; and primate city regions have grown no faster than hinterland areas. Such applications point toward a research program in which "empirical growth" need no longer be synonymous with "national income accounts."

1,216 citations

Journal ArticleDOI
TL;DR: This work uses recently available data on infrastructure, land cover and human access into natural areas to construct a globally standardized measure of the cumulative human footprint on the terrestrial environment at 1 km2 resolution from 1993 to 2009.
Abstract: Human pressures on the environment are changing spatially and temporally, with profound implications for the planet’s biodiversity and human economies. Here we use recently available data on infrastructure, land cover and human access into natural areas to construct a globally standardized measure of the cumulative human footprint on the terrestrial environment at 1 km2 resolution from 1993 to 2009. We note that while the human population has increased by 23% and the world economy has grown 153%, the human footprint has increased by just 9%. Still, 75% the planet’s land surface is experiencing measurable human pressures. Moreover, pressures are perversely intense, widespread and rapidly intensifying in places with high biodiversity. Encouragingly, we discover decreases in environmental pressures in the wealthiest countries and those with strong control of corruption. Clearly the human footprint on Earth is changing, yet there are still opportunities for conservation gains. Habitat loss and urbanization are primary components of human impact on the environment. Here, Venter et al.use global data on infrastructure, agriculture, and urbanization to show that the human footprint is growing slower than the human population, but footprints are increasing in biodiverse regions.

1,027 citations

Journal ArticleDOI
TL;DR: The results emphasize the key role of vegetation feedbacks in attenuating SUHII of big cities during the day, in particular during the growing season, further highlighting that increasing urban vegetation cover could be one effective way to mitigate the urban heat island effect.
Abstract: Urban heat island is among the most evident aspects of human impacts on the earth system. Here we assess the diurnal and seasonal variation of surface urban heat island intensity (SUHII) defined as the surface temperature difference between urban area and suburban area measured from the MODIS. Differences in SUHII are analyzed across 419 global big cities, and we assess several potential biophysical and socio-economic driving factors. Across the big cities, we show that the average annual daytime SUHII (1.5 ± 1.2 °C) is higher than the annual nighttime SUHII (1.1 ± 0.5 °C) (P < 0.001). But no correlation is found between daytime and nighttime SUHII across big cities (P = 0.84), suggesting different driving mechanisms between day and night. The distribution of nighttime SUHII correlates positively with the difference in albedo and nighttime light between urban area and suburban area, while the distribution of daytime SUHII correlates negatively across cities with the difference of vegetation cover and activity between urban and suburban areas. Our results emphasize the key role of vegetation feedbacks in attenuating SUHII of big cities during the day, in particular during the growing season, further highlighting that increasing urban vegetation cover could be one effective way to mitigate the urban heat island effect.

840 citations