Uncovering the hidden resource cost of urbanization: A globally scalable open-source framework for urban housing vacancy monitoring

Abstract

Rapid urbanization often outpaces population growth, creating massive resource inefficiencies. Quantifying this structural mismatch between housing supply and actual occupancy remains a global challenge due to costly censuses and imprecise proxy data. Here, we present a globally scalable, low-cost framework integrating open-source 3D building data with gridded population data to monitor block-level urban housing vacancy rates (HVR). Applying this framework to China, we produced the first high-resolution national vacancy map across 2813 spatial cities, revealing an average HVR of 23.46%. This equates to 77 million vacant units and 10.8 billion square meters of unutilized floor space. Our block-level analysis further reveals substantial intra-urban heterogeneity, including systematic core–periphery occupancy gradients and localized mismatches between housing supply and resident population. Evaluated using complementary agreement, classification, and external-consistency assessments, this open-source tool empowers nations to monitor housing resources (SDG 11), mitigate embodied carbon waste, and support evidence-based sustainable development.