contains many irregular shapes and donuts which make it difficult for the tool to merge the neighboring EAs considering all given criteria. In addition, some region merging techniques are better than others at ensuring all final regions match the desired criteria. In some cases, techniques become stuck in configurations with no solution (e.g. with small unmerged areas along the map borders or surrounded by fully formed regions that cannot be merged more). Such errors could be eliminated by incorporating harder constraints or additional constraints that are more appropriate to the use of many small areas.

Our use of AZTool in the context of Somalia also pointed to potential extensions of the region-merging approach other criteria based on socio-economic variables such that socio-economic metrics are homogenous within the produced EAs. For instance, if the purpose of a survey is to collect data on poverty, the existence of high-resolution poverty maps (Tatem et al. 2014; Steele et al 2017) could be used to provide a weighting constraint which the tool could use to merge regions with the aim of ensuring that poverty levels with EAs were relatively homogeneous. This approach could help to ensure that selected samples are more representative, but still the priority is to have excellent population data, and if only low-resolution socio-economic data are available, the combination still can be made. In addition, a compactness metric based on the comparison of the longest length in a shape to the diameter of a circle of same area would provide a more robust selection criterion during the merging process and lead to more compact EAs, as it is insensitive to shape size, unlike the compactness metric used in the AZ tool. Furthermore, if available data have consistent and reliable labeling, the hierarchy approach will be adopted in terms of prioritizing the features to be merged in the merging process. By doing this, traversability will be accounted as well through ranking of split lines, and additional data sources such as the building delineation derived from satellite imagery (San and Turker 2010; Vakalopoulou et al. 2015) would supplement road data, especially in rural areas and could contribute to more targeted EAs by clustering building locations. Identified buildings could also help to inform the delineation of rural EAs, as well as providing spatial variables (building size and layout) that may be linked to socioeconomic indicators.

Based on the experience in the present study, we aim to develop a software tool that can be used to generate optimal and practical EAs with minimal user interaction and tailored to a wider set of needs. The tool has the capability of working directly with shapefiles and a wider. The tool will have the ability to consider several varieties of parameters to produce constructive EAs, as well as the integration of socio-economic variables as described above. It could also have broad development impact since it can update existing EAs with the condition if the old EA boundary should be kept or not or generate the new set of EAs and turning them into national sample frame within time, cost and quality constraints.

# **Conclusion**

Somalia presents an example of a country where the need for basic spatial demographic data such as EAs is crucial to continued development, but where on-the-ground logistical constraints, security and data limitations remain significant barriers. Here, we show how a novel approach to creating predefined census EAs in such contexts where the census data are badly outdated and EA data are needed to progress development efforts. In addition, by highlighting existing freely-available, up-to-date highresolution gridded population data and settlement maps, we hope to help remove a further barrier to broader uptake of this method. Future research will aim to improve the accessibility of the approach by providing user-friendly tools that will automate the data access, splitting and merging process according to user specifications. By presenting the approach in the challenging context of Somalia and providing the first up-to-date rural EAs in decades, we aim to demonstrate the feasibility of the approach and the potential for application in other contexts.

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