A Data-Driven Assessment Model for the Adaptive Reuse Potential of Industrial Heritage Buildings

Journal: Architecture Engineering and Science DOI: 10.32629/aes.v7i3.5435

Yunfei Xu

North China University of Technology, Beijing 100144, China

Abstract

This study develops a data-driven model to assess the adaptive reuse potential of industrial heritage buildings using 18,194 listed assets in England. The framework combines statutory grade, transport accessibility, brownfield proximity, conservation clustering, and designation age into a composite reuse index and a logistic classification of high-potential cases. The mean reuse score is 0.515 and 30.0% of assets fall into the high-potential group. Manufacturing and transport-related assets perform best, while grade level and accessibility are the strongest predictors of reuse potential. The model provides a scalable evidence base for conservation prioritisation and heritage-led regeneration.

Keywords

industrial heritage buildings; adaptive reuse; data-driven assessment; planning open data; building conservation; redevelopment potential

References

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