Optimization of Design Resources in the Transformation of Industrial Heritage Space Environment

An empirical framework for the spatio-environmental transformation of industrial heritage parks was proposed to address urban renewal challenges, such as single spatial structures, unsustainable environments, and inefficient information management. Based on information resource management theory, a multi-source information integration approach was adopted, integrating remote sensing, behavior logs, policy documents, and social survey data into a space–environment–society–policy dynamic coupling model. Findings show that multidimensional social feedback and policy adjustment increased these variables' weight by 23.6%, mitigating information heterogeneity and quality instability. Results also highlight spatial heterogeneity, with environmental gains varying across units and not always synchronizing with social satisfaction. This study demonstrates that heritage transformation is a dynamic, iterative process, providing a practical data-driven path for synergizing spatial renewal, ecological health, and community needs, as well as a verifiable information resource management framework.