Taking Hunan Province as a typical case area, this paper integrates heterogeneous data such as iron and steel product data and social variable data, and adopts a bottom-up approach to estimate the steel in-use stock in the five end-use sectors, namely, buildings, infrastructure, transportation, machinery and durable goods from 1990 to 2021, and analyzes the driving mechanism by innovatively integrating the IPAT model, the LMDI model, and the multivariate linear regression method. The results of the study show that the steel in-use stock and the steel in-use stock per capita in Hunan Province have increased by 12 times and 10times in the past 32 years, and will reach 260 million tons and 3.6 tons per person respectively in 2021. In terms of the sectoral distribution of the steel in-use stock, the share of construction steel in-use stock reaches more than 56% every year. The density of the steel in-use stock shows regional unevenness, and the spatial heterogeneity shows "core-edge" gradient differentiation, with the high value area of stock density (>240000 t/km²) expanding along the vertical axis. Detection of driving factors shows that population growth, economic development and built-up area are the most important driving factors for the development and change of urban steel in-use stock. It is recommended to guide the industry to expand to the backward areas, give policy support, promote industrial integration and cluster development; accelerate the transformation of low-carbon industry, encourage technology research and development and application, and promote energy substitution; implement environmental protection related systems and mechanisms, and strengthen environmental protection publicity and education.