BMAT: A footprint-level building facade material dataset for 73 major cities worldwide

Abstract. Building facade materials are closely associated with urban microclimates, energy consumption, and carbon emissions, yet existing urban building datasets typically capture only building footprints and heights, leaving semantic material information unavailable at the individual-building level. Here we present BMAT, a footprint-level building facade material dataset covering 22.09 million buildings across 73 major cities worldwide. BMAT links individual building footprints with facade material labels inferred from over 147 million temporally stamped street-view images collected between 2007 and 2025, where historical imagery is available. We developed an automated inference pipeline based on a fine-tuned Vision-Language Model trained on 39,405 manually annotated samples, achieving an F1-score of 0.91 against held-out test data. Dataset reliability was further assessed through independent cross-validation against 47,434 Overture Maps building records with known material attributes, yielding an overall accuracy of 0.80. BMAT reveals spatially distinct material signatures associated with climate, geography, and regional building traditions. In cities with sufficient repeated imagery, the temporally stamped records further provide exploratory evidence of facade material transitions, including increasing glass facade adoption in selected rapidly urbanizing regions. By bridging building geometry and semantic surface properties, BMAT supports studies in building energy modelling, embodied carbon accounting, urban microclimate analysis, and urban hazard risk assessment. The dataset is openly available at https://doi.org/10.6084/m9.figshare.31569370 (Yin, 2026).