Comparaison visuelle de Zanzibar City, en Tanzanie. carte de la densité de population en haute résolution (à gauche) et avec POMELO (à droite)
Comparaison visuelle de Zanzibar City, en Tanzanie. carte de la densité de population en haute résolution ( à gauche ) et avec POMELO ( à droite ) - Researchers from EPFL and ETH Zurich, working together with the International Committee of the Red Cross (ICRC) and Bin Khalifa Unversity (Qatar), have developed a program that can generate population density estimates with unparalleled precision, and only needs a rough estimate at the regional level to learn. In most countries where the ICRC operates - whether in response to crisis or conflict or to support reconstruction - no updated census data are available. And where census counts are taken, they often become outdated quickly as a result of rapid population growth and demographic shifts. But when humanitarian workers need to restore the water supply, distribute food or assess the feasibility of a prevention program, they can work much more efficiently if they know how many people are in a given area. That's why EPFL and ETH Zurich engineers teamed up with the ICRC to develop an artificial-intelligence-based program, called Pomelo. The software compiles large sets of public data from remote sensing systems - such as data on building counts, average building sizes, proximity to roads, road maps and night lighting- and aggregates them based on weightings learned by a neural network.
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