Remote sensing data has the potential to revolutionize social science. One of the most prominent examples of this is the Nighttime Lights dataset, which provides digital measures of nighttime luminosity from 1992 to 2013. This study evaluates the Nighttime Lights data against detailed rural electrification data from the 2011 Census of India. The results suggest that many nighttime luminosity measures derived from satellite data are surprisingly accurate for measuring rural electrification, even at the village level and using simple statistical tools. We also demonstrate that this accuracy can be substantially improved by using of better GIS maps, basic geoprocessing tools, and particular aggregations of nighttime luminosity. Nightt...
A technique has been developed to estimate the percent population having electric power access based...
Remotely sensed artificial lighting radiances at night can provide spatially explicit proxy measures...
Nighttime lights (night-lights) data are useful in predicting gross domestic product (GDP), a key ec...
<p>Remote-sensing data has the potential to revolutionize social science. One of the most prominent ...
Unreliable electricity supplies are common in developing countries and impose large socio-economic c...
This paper investigates the association between night-time lights and socio-economic metrics at the ...
When observing the Earth from above at night, it is clear that the human settlement and major econom...
Abstract: One emerging application of night-time light imagery focuses on estimating levels of acces...
Access to electricity (the proportion of the population with access to electricity) is a key indica ...
Electric power services are fundamental to prosperity and economic development. Disruptions in the e...
Electricity is essential in the modern world. Although India is near reaching 100% electrification, ...
Nighttime lights satellite imagery has been used for decades as a uniform, global source of data for...
© 2017 Elsevier Inc. Since the late 1990s, remotely sensed night-time lights (NTL) satellite imager...
We report on a systematic ground-based validation of DMSP-OLS night lights imagery to detect rural e...
The traditional ways of measuring global sustainable development and economic development schemes an...
A technique has been developed to estimate the percent population having electric power access based...
Remotely sensed artificial lighting radiances at night can provide spatially explicit proxy measures...
Nighttime lights (night-lights) data are useful in predicting gross domestic product (GDP), a key ec...
<p>Remote-sensing data has the potential to revolutionize social science. One of the most prominent ...
Unreliable electricity supplies are common in developing countries and impose large socio-economic c...
This paper investigates the association between night-time lights and socio-economic metrics at the ...
When observing the Earth from above at night, it is clear that the human settlement and major econom...
Abstract: One emerging application of night-time light imagery focuses on estimating levels of acces...
Access to electricity (the proportion of the population with access to electricity) is a key indica ...
Electric power services are fundamental to prosperity and economic development. Disruptions in the e...
Electricity is essential in the modern world. Although India is near reaching 100% electrification, ...
Nighttime lights satellite imagery has been used for decades as a uniform, global source of data for...
© 2017 Elsevier Inc. Since the late 1990s, remotely sensed night-time lights (NTL) satellite imager...
We report on a systematic ground-based validation of DMSP-OLS night lights imagery to detect rural e...
The traditional ways of measuring global sustainable development and economic development schemes an...
A technique has been developed to estimate the percent population having electric power access based...
Remotely sensed artificial lighting radiances at night can provide spatially explicit proxy measures...
Nighttime lights (night-lights) data are useful in predicting gross domestic product (GDP), a key ec...