Who's in the dark__satellite based estimates of electrification rates - Urban Remote Sensing: Monitoring, Synthesis and Modeling in the Urban Environment - page 212

as the USA, France and New Zealand, which are believed to
have near 100% electrification but fall 1-2% short of this in
the DMSP estimates (Table 15.2). This style of error may be
larger in the developing countries that have lower electric power
consumption levels, such as China and India. There may errors
of commission, or overcounting of the population with access
to electricity in areas that have street lighting and commercial
lighting, yet no electric power access in a portion of the homes
in the same pixel. Another source of discrepancy arises from
homes with intermittent or sporadic electric power service. In
the case of Iraq the IEA only tallied population with reliable
electric power service in the estimation of the electrification rate.
The DMSP data were processed to detect intermittent lighting,
yielding a substantially higher estimate of the electrification rate.
Finally, it should be noted that the DMSP electrification rate
estimates were derived from areas that are devoid of lighting
from gas flares. That is to say, in areas with onshore gas flares, the
electrification rate has been estimated outside of the area lit by
the gas flares. This includes portions of countries listed by Elvidge
et al . (2009b), including Russia, Nigeria, Iran, Iraq, Algeria, Libya,
and others.

placed on reducing carbon emissions, Mills (2005) developed low
cost photovoltaic panels and light emitting diode (LED) fixtures
that enable families to produce light using locally generated
electricity without the expense of extending the electric power
grid. This approach has similarity to the rapid expansion of cell
phone usage in places where the land line telephone system is
antiquated and decrepit.
While there are some known sources of error in the cur-
rent product, the method does provide electrification rates using
a standardized definition and standardized data sources, with
complete global coverage. We anticipate that there will be
improvements to the night-time lights approach to estimat-
ing electrification rates. We also anticipate that night-time lights
will be useful for detecting changes in electric power access. This
could include both expansions and contractions in access to
electric power.

Acknowledgments

One of the authors of this manuscript is an employee of UT-
Battelle, LLC, under contract DE-AC05-00OR22725 with the
US Department of Energy. Accordingly, the United States Gov-
ernment retains and the publisher, by accepting the article for
publication, acknowledges that the United States Government
retains a non-exclusive, paid-up, irrevocable, worldwide license
to publish or reproduce the published form of this manuscript,
or allow others to do so, for United States Government purposes.

Conclusion

We derived the first systematic global assessment of electrification
rates by combining DMSP night-time lights with a population
density grid. In this analysis, the electrification rate was estimated
by tallying the population count in areas having DMSP lighting
as compared to the total population. Using this technique we
have a standardized product, with reporting for 232 countries
and more than 2000 sub-national units. In contrast, the only
other available reporting on international electrification rates
comes from the International Energy Agency (IEA), which in
2006 reported electrification rates for 86 countries.
There are several potential areas for improvement in the
estimation of electrification rates based on night-time lights. It
would be good to place error bars on the estimated electrification
rates, to have estimates of the errors of omission and commission,
and to be able to rate the stability of the electric service. In most
parts of the world the DMSP is able to collect twenty to fifty
cloud-free dark night coverages in a year, which may be enough
repeat coverages to assess the stability of electric power service
(i.e., the ratio of lights detected versus lights not detected). The
most serious constraint on these improvements is the current
lack of validation data on electrification rates collected at a spatial
resolution compatible with DMSP and Landscan (about 1 km 2
resolution). To address the problem with gas flares obscuring
lights from small towns and villages the best solution would be
to collect the night-time lights data at higher spatial resolution
(Elvidge et al ., 2007b).
One of the applications for the full resolution grid of the
population count in areas without DMSP detected lighting is to
identify areas of the world that could benefit from installation
of sustainable solar and wind energy systems. In many of these
areas, people are burning kerosene to produce subsistence levels
of heat and lighting that cannot be detected by DMSP. Mills et al .
(2005) have shown that liquid fuels are extremely inefficient and
costly light sources. The only thing cheap about this approach
to lighting is the cost of the lanterns. Given the emphasis being

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