Abstract
Enumeration Areas (EAs) are the operational geographic units for the collection and dissemination of census data and are often used as a national sampling frame for various types of surveys. In many poor or conflict-affected countries, EA demarcations are incomplete, outdated, or missing. Even for countries that are stable and prosperous, creating and updating EAs is one of the most challenging yet essential tasks in the preparation for a national census. Commonly, EAs are created by manually digitising small geographic units on high-resolution satellite imagery or physically walking the boundaries of units, both of which are highly time, cost, and labour intensive. In addition, creating EAs requires considering population and area size within each unit. This is an optimisation problem that can best be solved by a computer. Here, for the first time, we produce a semi-automatic mapping of pre-defined census EAs based on high-resolution gridded population and settlement datasets and using publicly available natural and administrative boundaries. We demonstrate the approach in generating rural EAs for Somalia where such mapping is not existent. In addition, we compare our automated approach against manually digitised EAs created in urban areas of Mogadishu and Hargeysa. Our semi-automatically generated EAs are consistent with standard EAs, including having identifiable boundaries for field teams to follow on the ground, and appropriate sizing and population for coverage by an enumerator. Furthermore, our semi-automated urban EAs have no gaps, in contrast, to manually drawn urban EAs. Our work shows the time, labour and cost-saving value of automated EA delineation and points to the potential for broadly available tools suitable for low-income and data-poor settings but applicable to potentially wider contexts.
Highlights
Population data count and distribution data in the form of census enumerations, are used for population segmentation, planning, and a myriad of other functions that support the government
The first category is in towns or highly populated areas where Enumeration Areas (EAs) boundaries are well-matched with logical ground natural boundaries such as roads (Fig. 5a)
The population size per Population Estimation Survey (PESS) urban EA in Mogadishu, ranges from zero to 17,000 and the area ranges from 5 m2 to 7 km2
Summary
Population data count and distribution data in the form of census enumerations, are used for population segmentation, planning, and a myriad of other functions that support the government. Regardless of being created manually or digitally, the design of EAs should take several criteria into account including (i) be mutually exclusive (none-overlapping) and exhaustive (cover the entire country), (ii) have boundaries that are identifiable on the ground, (iii) be consistence with the administrative boundary hierarchy, (iv) be compact without pockets or disjoint sections, (v) have populations of approximately equal size (vi) be small enough and accessible to be covered by an enumerator within the census period, (vii) be small and flexible enough to allow the widest range of tabulations for different statistical reporting units, (viii) be large enough to guarantee data privacy, (ix) be useful for other types of censuses and data collection activities, (x) be satisfactory to the needs of government departments and other data users (BUCEN, 1978; Unite, 2000). With the availability of data on population density at a sufficiently high spatial resolution (e.g., 100 m), the process of designing EAs can be semi-automated, which could accelerate the census mapping process
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