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Against the background of industrial transformation and urban regeneration in old industrial bases, understanding the spatial pattern and driving mechanisms of industrial heritage is essential for its conservation and sustainable use. This study investigates 277 industrial heritage sites in Liaoning Province (including nationally designated sites, potential heritage within cultural relic protection units at all levels, and sites recognized by the China Association for Science and Technology) using kernel density estimation, standard deviation ellipse, and the GeoDetector model. The results reveal a significantly clustered distribution characterized by “dense in central–southern Liaoning, sparse in the periphery,” forming three major agglomerations: the Shenyang core, the Anshan–Benxi–Liaoyang heavy industry triangle, and the Dalian coastal industrial belt. Temporally, the distribution shows distinct phases closely linked to industrial development history and major socio-political events. Land use, GDP, and climatic factors dominate the spatial differentiation, with GDP and annual average temperature exhibiting the strongest combined explanatory power (41.67%). Based on these dominant factors and the identified core agglomeration areas, differentiated protection and utilization strategies should be formulated for core versus peripheral areas, different industrial types, and various historical periods. This provides direct empirical evidence for industrial heritage management and cultural revitalization in old industrial regions.
Liu et al. (Sun,) studied this question.
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