Cultural Heritage Recognition, Spatial Accumulation and Dynamics: An Institutional Spatial Perspective on Sustainable Spatial Planning in Fujian, China

Cultural heritage spatial patterns reflect both the long-term accumulation of historical resources and their successive recognition within national heritage protection systems. Here, the recognition year specifically refers to the time when a heritage resource was incorporated into the national protection system, rather than the period when the heritage itself was formed. Existing studies have extensively examined heritage distribution and spatiotemporal evolution, but rarely treat successive recognition batches as a time-ordered institutional spatial sequence. Taking four national-level heritage types in Fujian, China—Chinese Traditional Villages (CTVs), National Key Cultural Relic Protection Units (NKCRPUs), National Intangible Cultural Heritage (NICH), and Chinese Historical and Cultural Towns (CHCTs)—this study constructs cumulative recognition spatial sequences from recognition batches and examines overall spatial patterns, cumulative spatial dynamics, and inter-type spatial associations. The results show that: (1) CTVs, NKCRPUs, and NICH exhibit significant clustering, whereas CHCTs do not show a statistically significant departure from random distribution when a common study area is used, with high-density cores mainly concentrated in coastal areas; (2) CTVs and NICH show relatively strong spatial persistence, NKCRPUs transition from early expansion to stable extension, and CHCTs show more pronounced restructuring followed by stabilization, although their small sample size limits the robustness of this result; and (3) spatial associations among heritage types are scale-dependent, with positive associations between CTVs–CHCTs and NKCRPUs–NICH, while other pairs show weaker or more localized associations. A benchmark analysis further shows that the stabilization in later stages is largely consistent with the cumulative design, with only limited evidence for genuine stage-specific spatial adjustment. By transforming recognition batches into time-sequenced spatial data, this study reveals cumulative, expansion, and restructuring processes that static heritage inventories cannot capture, providing a spatial basis for identifying potential cultural heritage clusters and spatially connected heritage combinations, thereby supporting sustainable spatial planning.