| Records |
| Author |
Addison, D.; Stewart, B. |
| Title |
Nighttime Lights Revisited: The Use of Nighttime Lights Data as a Proxy for Economic Variables |
Type |
Report |
| Year |
2015 |
Publication |
World Bank Group Policy Research Working Papers |
Abbreviated Journal |
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| Volume |
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Pages |
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| Keywords |
Economics; earth observation; satellite imagery; DMSP-OLS; NPP-VIIRS; gross domestic product; electric power consumption; capital; population; linear regression; night-time light data; economic monitoring |
| 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. |
| Address |
DAddison(at)worldbank.org |
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Thesis |
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| Publisher |
World Bank Group |
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| Language |
English |
Summary Language |
English |
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IDA @ john @ |
Serial |
1363 |
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| Author |
Falchi, F.; Furgoni, R.; Gallaway, T.A.; Rybnikova, N.A.; Portnov, B.A.; Baugh, K.; Cinzano, P.; Elvidge, C.D. |
| Title |
Light pollution in USA and Europe: The good, the bad and the ugly |
Type |
Journal Article |
| Year |
2019 |
Publication |
Journal of Environmental Management |
Abbreviated Journal |
Journal of Environmental Management |
| Volume |
248 |
Issue |
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Pages |
109227 |
| Keywords |
Remote Sensing; gross domestic product; light pollution; Economics |
| Abstract |
Light pollution is a worldwide problem that has a range of adverse effects on human health and natural eco-systems. Using data from the New World Atlas of Artificial Night Sky Brightness, VIIRS-recorded radiance and Gross Domestic Product (GDP) data, we compared light pollution levels, and the light flux to the population size and GDP at the State and County levels in the USA and at Regional (NUTS2) and Province (NUTS3) levels inEurope. We found 6800-fold differences between the most and least polluted regions in Europe, 120-fold differences in their light flux per capita, and 267-fold differences influx per GDP unit. Yet, we found even greater differences between US counties: 200,000-fold differences in sky pollution, 16,000-fold differences in light flux per capita, and 40,000-fold differences in light flux per GDP unit. These findings may inform policy-makers, helping to reduce energy waste and adverse environmental, cultural and health consequences associated with light pollution. |
| Address |
STIL – Istituto di Scienza e Tecnologia dell'Inquinamento Luminoso, Light Pollution Science and Technology Institute, Thiene, Italy; Italy. falchi@lightpollution.it(at)istil.it |
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Thesis |
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| Publisher |
Elsevier |
Place of Publication |
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| Language |
English |
Summary Language |
English |
Original Title |
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Edition |
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| ISSN |
0301-4797 |
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Approved |
no |
| Call Number |
IDA @ john @ |
Serial |
2593 |
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| Author |
Liang, H.; Guo, Z.; Wu, J.; Chen, Z. |
| Title |
GDP spatialization in Ningbo City based on NPP/VIIRS night-time light and auxiliary data using random forest regression |
Type |
Journal Article |
| Year |
2019 |
Publication |
Advances in Space Research |
Abbreviated Journal |
Advances in Space Research |
| Volume |
in press |
Issue |
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Pages |
S0273117719307136 |
| Keywords |
Remote Sensing; GDP; gross domestic product; spatialization; VIIRS-DNB; Nighttime light; numerical methods |
| Abstract |
Accurate spatial distribution information on gross domestic product (GDP) is of great importance for the analysis of economic development, industrial distribution and urbanization processes. Traditional administrative unit-based GDP statistics cannot depict the detailed spatial differences in GDP within each administrative unit. This paper presents a study of GDP spatialization in Ningbo City, China based on National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL) data and town-level GDP statistical data. The Landsat image, land cover, road network and topographic data were also employed as auxiliary data to derive independent variables for GDP modelling. Multivariate linear regression (MLR) and random forest (RF) regression were used to estimate GDP at the town scale and were assessed by cross-validation. The results show that the RF model achieved significantly higher accuracy, with a mean absolute error (MAE) of 109.46 million China Yuan (CNY)·km-2 and a determinate coefficient (R2=0.77) than the MLR model (MAE=161.8 million CNY·km-2, R2=0.59). Meanwhile, by comparing with the estimated GDP data at the county level, the town-level estimated data showed a better performance in mapping GDP distribution (MAE decreased from 115.1 million CNY·km-2 to 74.8 million CNY·km-2). Among all of the independent variables, NTL, land surface temperature (Ts) and plot ratio (PR) showed higher impacts on the GDP estimation accuracy than the other variables. The GDP density map generated by the RF model depicted the detailed spatial distribution of the economy in Ningbo City. By interpreting the spatial distribution of the GDP, we found that the GDP of Ningbo was high in the northeast and low in the southwest and formed continuous clusters in the north. In addition, the GDP of Ningbo also gradually decreased from the urban centre to its surrounding areas. The produced GDP map provides a good reference for the future urban planning and socio-economic development strategies. |
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0273-1177 |
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| Call Number |
GFZ @ kyba @ |
Serial |
2680 |
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