Visual experience is a primary channel through which the values of tangible cultural heritage are perceived and governed, making visual evaluation and management central to conservation and to Sustainable Development Goal (SDG) 11.4. However, practice remains fragmented across scales, and many statutory toolkits lag behind advances in geographic information systems (GIS)-based visibility analysis, 3D visualization, remote sensing, and perception-based evidence. We compile, code, and cross-analyze a multi-level corpus spanning 26 international instruments, 293 national items from 112 countries, and 867 World Heritage properties. Using a four-dimensional framework (values, typology, visual-evaluation methods, and visual-management strategies), we apply k-medoids clustering with multidimensional scaling (MDS) at the national level, mask-aware association mapping at the property level, and cross-level diagnostics. Across levels, practice converges on a technical-spatial regime. At the property level, GIS-based viewshed and visual sensitivity analysis, verified visuals and 3D visualization techniques, and GIS-based spatial-historical analysis form a near-universal methodological core and are most frequently translated into zoning and spatial regulation and height or massing controls. Participatory and perception- or experience-based methods remain sporadic. Value framings are dominated by Historic, Social and Political, and Aesthetic emphases, while Ecological and Scientific are comparatively marginal. Cross-level coherence is strongest where governance frameworks are mature, and portfolios are coherent; it weakens where portfolios are heterogeneous or in federated or lower-capacity settings. National portfolios cluster into four method-strategy regimes that explain characteristic object-method-strategy sequences. In response, we outline operational bridges including tiered standards for visibility and 3D evidence, deployable perception protocols, participation modules linked to Heritage Impact Assessment (HIA) or Visual Impact Assessment (VIA) triggers, and auditable communication packages. These are organized within a Global Peer Network aligned to portfolio archetypes and method-strategy regimes. The study contributes a reusable global dataset and map of visual-heritage practice and an integration framework that supports more transparent, comparable, and context-sensitive decisions across levels.

Historic urban areas (HUAs) are visually and culturally sensitive environments where blue-green infrastructure (BGI) plays an increasingly important role in shaping spatial identity and environmental quality. While BGI's ecological functions are well documented, its influence on human visual perception, particularly within HUAs, remains largely unexplored. Addressing this gap, this paper proposes an integrative framework to assess how BGI affects visual experiences in heritage contexts, bridging methodological, perceptual, and user-group dimensions. By combining UAV-based photogrammetry with a three-layered perception model, the research integrates spatial analysis and empirical methods across seeing (eye-tracking), feeling (questionnaire), and understanding (interviews) layers. Street-level BGI exposure was spatially quantified and used to inform perception experiments involving both expert and general public groups. This multi-methodological, multi-layered, cross-group approach extends existing research by providing a comprehensive examination of BGI's visual impact at different cognitive levels, particularly within historic settings. Findings reveal that BGI enhances perceptual diversity, visual preference evaluation, and cognitive engagement across both groups. Although it may slightly divert attention from dominant heritage features, BGI fosters broader visual exploration and higher environmental ratings. Experts interpret BGI through more systemic and functional perspectives, while the public emphasizes emotional, aesthetic, and recreational values. Overall, this study presents a replicable framework integrating digital spatial modeling with layered perception analysis, offering new insights for evaluating and enhancing visual environments in HUAs. It supports more inclusive visual assessments and provides a basis for informed planning and selective design interventions in heritage contexts.