Estimation of Gross Domestic Product at Sub-National Scales using Nighttime Satellite Imagery

By Paul C. Sutton, Christopher D. Elvidge, Tilottama Ghosh. 2007

360 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/92947cb0a704813829dd4ee43a0931e6c36c0d7f

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Citations in the corpus

Regional Inequality, Convergence, and its Determinants - A View from Outer Space (2017, unknown): “Ullman (1958) discusses this issue based on the example of the Manufacturing Belt in the U.S.; however, this issue is similar in the Ruhr area in Germany and many other countries. As noted by Williamson (1965), the discovery of natural resources is often a critical juncture in regional development b”
Forecasting China’s GDP at the pixel level using nighttime lights time series and population images (2017, background): “Previous studies have proven that luminance of nighttime lights is a sound proxy of economic level (Chen and Nordhaus 2010; Doll, Muller, and Morley 2006; Sutton, Elvidge, and Ghosh 2007; Zhao, Currit, and Samson 2011).”
A global poverty map derived from satellite data (2009, background): “Sutton et al. (2007) also made an attempt to estimate sub-national GDP from the nighttime light images for the United States, China, India, and Turkey.”
Using night light emissions for the prediction of local wealth (2017, unknown): “An article by Sutton, Elvidge & Ghosh (2007) conducts such an analysis for four countries (China, India, Turkey, and the USA), showing that night lights track economic output also at this finer level of resolution.”
Using luminosity data as a proxy for economic statistics (2011, background): “(6) improved Ebener’s model by adding estimated urban population at the state level to solve the problem of saturation in traditional luminosity image and applied the new model to four countries: China, India, Turkey, and theUnited States.”
Applications of Satellite Remote Sensing of Nighttime Light Observations: Advances, Challenges, and Perspectives (2019, methodology): “The most significant progress from previous studies is that GDP and its growth rate have been estimated using socioeconomic and NTL data and econometric models.”
Shedding Light on the Global Distribution of Economic Activity (2010, background): “More importantly, in many developing countries, a greater percentage of economic activity is conducted within the informal sector than the formal sectors, and informal sector productivity is often excluded from the formal statistics [7] [9] [10] [11].”
A sharper image? Estimates of the precision of nighttime lights as a proxy for economic statistics (2015, background): “Previous studies, primarily in the field of geoscience and economics, have used nighttime image data as a proxy for socioeconomic development of particular geographic areas (Doll et al., 2000; Sutton and Costanza, 2002; Ebener et al., 2005; Elvidge et al., 2007; 1997; Sutton et al., 2007; Henderson ”
Using Nighttime Satellite Imagery as a Proxy Measure of Human Well-Being (2013, methodology): “The close relation between the spatial distribution of nighttime lights and economic activity has been observed and utilized in several studies before [2–7].”
Intercalibration of DMSP-OLS night-time light data by the invariant region method (2013, background): “…areas: urban expansion (Lo 2002; Elvidge et al. 2007; McDonald, Kareiva, and Formana 2008), economic evaluation (Doll, Muller, and Morley 2006; Sutton, Elvidge, and Ghosh 2007; Elvidge, Sutton, et al. 2009; Ghosh et al. 2010; Raupach, Rayner, and Paget 2010; Chaturvedi, Ghosh, and Bhandari…”
MEASURING ECONOMIC GROWTH FROM OUTER SPACE (2012, unknown): “…researchers have shown that night lights reflect human economic activity (e.g., Croft (1978), Elvidge et al. (1997b), Sutton and Costanza (2002), Ebener et al (2005), Doll et al. (2006) and Sutton et al (2007)) 3 , but have not used lights in a statistical framework to measure real economic growth.”