Public participation in architectural heritage protection is a crucial part of promoting the development of heritage conservation. However, even in the same country, different regions protect heritage at different levels. This study, taking national wooden arch corridor bridges as the research object, analyzes the public participation level in wooden arch corridor bridge protection in the last 5 years, studying the factors that influence public participation and the change in rules of public participation caused by geography, providing a theoretical reference for the sustainable development of the protection of wooden arch corridor bridges. The results indicate (1) public participation in the protection of wooden arch corridor bridges has been increasing annually under government guidance; (2) there is a positive correlation between the concentration of wooden arch corridor bridges and the level of public participation; (3) the better the planning is regarding wooden arch corridor bridges and their surrounding areas, the higher the level of public participation, while the lower the level of residents’ participation and willing; (4) the higher the development and better the transportation in the areas where wooden arch corridor bridges are located, the higher the level of public participation; and (5) increasing the popularity of wooden arch corridor bridges, as well as the areas they are located in, can enhance public participation. These conclusions and research methods also provide methodological guidance and theoretical support for other public participation in the study of architectural heritage.

Highway under-bridge areas represent a valuable land resource while simultaneously constituting a sensitive ecological zone. Achieving a balance between its redevelopment and ecological preservation constitutes a critical challenge within the field of ecological engineering. Although prior research has addressed urban elevated underbridge space, investigations specifically focusing on highway underpasses remain limited. The absence of standardized criteria for assessing the suitability of these spaces has resulted in uncoordinated and fragmented utilization. In response, this study proposes a comprehensive evaluation framework that integrates multi-criteria decision-making (MCDM) methodologies with optimized backpropagation neural networks, specifically genetic-algorithm-optimized BP (GA-BP) and particle-swarm-optimization-optimized BP (PSO-BP). The model incorporates indicators spanning physical characteristics, environmental factors, safety considerations, and accessibility metrics, and is applied to an empirical dataset comprising 134 highway bridge underpasses in Fuzhou City. The results indicate that (1) both the GA-BP and PSO-BP models enhance convergence speed and classification accuracy, with the GA-BP model demonstrating superior stability and suitability for classifying underpass suitability; (2) the principal determinants of suitability include traffic accessibility, safety parameters, and spatial relationships with adjacent water bodies and agricultural lands; and (3) underpasses characterized as hub-type, single-sided road-adjacent, and cross-connection configurations exhibit greater potential for redevelopment. This investigation represents the first integration of MCDM and optimized neural network techniques in this context, offering a robust tool to support the scientific planning and ecological conservation of underbridge space environments.