Image Processing Reference
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Infrastructure like street lights, roads, etc. are not nearly as developed as they are in
wealthier nations; consequently nocturnal emissions captured by sensors like DMSP
are greatly reduced. Moreover, household consumption of energy in Guatemala makes
measurement of population density using DMSP difficult. For example, the government
offers a social subsidy whereby users who consume less than 300 kilowatt hours
(kWh) per month receive discounts on their energy bills paid by businesses and
factories that consume larger amounts of energy. Also, despite a massive electrifi-
cation program that reached large portions of Guatemala's rural residents, most of
the rural residents cannot afford to pay for services and thus only use electricity to
power a single light bulb for several hours each evening (Taylor 2005 ). The eco-
nomic situation of Guatemala's majority prevents us, at this stage, from making
useful population estimates using DMSP.
Figure 17.7 contrasts the nighttime image product derived from DMSP OLS
imagery with the LandScan population dataset produced at Oak Ridge National
Laboratory (Dobson et al. 2000 ). Urban clusters identified by a threshold in the
Fig. 17.7 Population density (Landscan) and nighttime imagery (DMSP OLS) for Guatemala
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