Abstract Refugee and internally displaced people (IDP) settlements are highly dynamic, with rapid changes to demographic and geographical structures. Knowledge of the population size, disaggregated by demographic attributes, is essential to informing humanitarian programming and settlement planning by humanitarian organizations. However, access to such data, when formal censuses of settlements have not been conducted, creates a significant barrier. In this paper, we present a methodological framework for estimating settlement censuses by combining globally available satellite imagery with aggregate national census data from the population’s country of origin to generate a spatially disaggregated synthetic population of the settlement. The creation of such synthetic populations serves as a foundational layer for digital twins and simulation models, enabling the integration of these disparate datasets at different levels of granularity, providing decision-makers with a spatially disaggregated dynamic model of the population to inform response requirements before sending humanitarian teams into new settlements and later informing survey methods, or used to simulate scenarios for policy planning and public health responses among others. We develop and validate our framework in three diverse contexts: the Zaatari and Cox’s Bazar settlements in Jordan and Bangladesh, and the Kismayo displacement settlement in Somalia.
Shi et al. (Wed,) studied this question.