A Novel Approach to the Automatic Designation of Predefined Census Enumeration Areas and Population Sampling Frames : A Case Study in Somalia
Enumeration areas are the operational geographic units for the collection, dissemination, and analysis of census data and are often used as a national sampling frame for various types of surveys. Traditionally, enumeration areas are created by manu...
| Main Authors: | , , , , , , , |
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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/810771565268760366/A-Novel-Approach-to-the-Automatic-Designation-of-Predefined-Census-Enumeration-Areas-and-Population-Sampling-Frames-A-Case-Study-in-Somalia http://hdl.handle.net/10986/32224 |
| Summary: | Enumeration areas are the operational
geographic units for the collection, dissemination, and
analysis of census data and are often used as a national
sampling frame for various types of surveys. Traditionally,
enumeration areas are created by manually digitizing small
geographic units on high-resolution satellite imagery or
physically walking the boundaries of units, both of which
are highly time, cost, and labor intensive. In addition,
creating enumeration areas requires considering the size of
the population and area within each unit. This is an
optimization problem that can best be solved by a computer.
This paper, for the first time, produces an automatic
designation of predefined census enumeration areas based on
high-resolution gridded population and settlement data sets
and using publicly available natural and administrative
boundaries. This automated approach is compared with
manually digitized enumeration areas that were created in
urban areas in Mogadishu and Hargeisa for the United Nations
Population Estimation Survey for Somalia in 2014. The
automatically generated enumeration areas are consistent
with standard enumeration areas, including having
identifiable boundaries to field teams on the ground, and
appropriate sizing and population for coverage by an
enumerator. Furthermore, the automated urban enumeration
areas have no gaps. The paper extends this work to rural
Somalia, for which no records exist of previous enumeration
area demarcations. This work shows the time, labor, and
cost-saving value of automated enumeration area delineation
and points to the potential for broadly available tools that
are suitable for low-income and data-poor settings but
applicable to potentially wider contexts. |
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