Estimating Small Area Population Density Using Survey Data and Satellite Imagery : An Application to Sri Lanka
Country-level census data are typically collected once every 10 years. However, conflict, migration, urbanization, and natural disasters can cause rapid shifts in local population patterns. This study uses Sri Lankan data to demonstrate the feasibi...
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| Language: | English |
| Published: |
World Bank, Washington, DC
2019
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/920771552394454183/Estimating-Small-Area-Population-Density-Using-Survey-Data-and-Satellite-Imagery-An-Application-to-Sri-Lanka http://hdl.handle.net/10986/31402 |
| Summary: | Country-level census data are typically
collected once every 10 years. However, conflict, migration,
urbanization, and natural disasters can cause rapid shifts
in local population patterns. This study uses Sri Lankan
data to demonstrate the feasibility of a bottom-up method
that combines household survey data with contemporaneous
satellite imagery to track frequent changes in local
population density. A Poisson regression model based on
indicators derived from satellite data, selected using the
least absolute shrinkage and selection operator, accurately
predicts village-level population density. The model is
estimated in villages sampled in the 2012/13 Household
Income and Expenditure Survey to obtain out-of-sample
density predictions in the nonsurveyed villages. The
predictions approximate the 2012 census density well and are
more accurate than other bottom-up studies based on
lower-resolution satellite data. The predictions are also
more accurate than most publicly available population
products, which rely on areal interpolation of census data
to redistribute population at the local level. The
accuracies are similar when estimated using a random forest
model, and when density estimates are expressed in terms of
population counts. The collective evidence suggests that
combining surveys with satellite data is a cost-effective
method to track local population changes at more frequent intervals. |
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