Capital accumulation, urbanization, and population growth are driving rapid expansion of one of the most essential infrastructures—bridges. Bridges facilitate transportation connectivity, regional development, and enhance logistics and industrial competitiveness. As the bridge stock grows, the shares of dangerous, aging, and low-load bridges increase. In China, roughly 40% of the active bridge fleet has more than 20 years of service life, creating substantial retrofit or reconstruction needs. Meanwhile, understanding the material stock of infrastructure is crucial for resource use accounting, spatial planning, and environmental management. Current visualization of construction material stock in bridges is severely constrained by data limitations, and traditional field surveys are time-consuming and costly. To address this gap, we propose a framework that leverages high-resolution Earth observation data to map the construction-material stock of small- to medium-sized bridges. First, we train a generalizable deep-learning network on Bridge Dataset and a bespoke dataset to identify small- and medium-sized bridges in satellite imagery. Second, given the imagery’s spatial resolution and the detection scope, we apply edge detection and principal component analysis to estimate each target bridge’s area and span. Finally, we integrate highway-bridge design standards to classify materials and estimate stock quantities, producing a micro-scale material-stock map within the satellite-imaged region. We apply the framework in a regional case study in eastern China. The results show that the spatial distribution of construction-material stock for small- to medium-sized bridges is closely aligned with population size and economic activity. By providing a quantitative, map-based description of bridge material stock, the framework can support recyclability analyses during dismantling and reuse, inform maintenance and upgrade decisions, and aid regional material demand and supply-chain planning. In this way, it contributes to an accelerated transition toward circular, low-carbon transport infrastructure.