AI-based Ger detection reveals post-pandemic delay in informal housing progress in Mongolia

Abstract Mongolia is among the countries undergoing rapid urbanization, and its temporary nomadic dwellings—known as Ger—have expanded into urban areas. Newly formed ger communities in cities are potentially recognized as informal settlements, or slums. The distinctive circular, tent-like shape of gers enables their detection through very-high-resolution satellite imagery. We develop a computer vision algorithm to detect gers in Ulaanbaatar, the capital of Mongolia, utilizing satellite images collected from 2015 to 2025. Results reveal that ger settlements have relocated towards the capital’s peripheral areas. The predicted ger household ratio based on our results exhibits a significant correlation (r = 0.85) with the World Bank’s district-level poverty data. Our nationwide extrapolation suggests that housing improvements in informal settlements have fallen short of official projections by an average of 2.8% since the COVID-19 pandemic. We discuss the potential of machine learning on satellite imagery in providing insights into urbanization patterns and sustainable development.