Incremental urban and community expansion in rural heritage landscapes often produces cumulative visual impacts, yet planning rarely specifies a clear endpoint for acceptable change. This paper proposes an integrated Visual Impact Assessment (VIA) framework, aligned with SDG 11, to determine “when to stop” using stage-comparable evidence across past, present, and future conditions. The framework is organized in three modules. First, a point cloud-enhanced GIS module quantifies visibility and spatial change across development stages. Second, an enhanced Key Observation Point (KOP) module derives matched eye-level evidence from multi-temporal street-level panoramas and scenario visualizations, for example using Street View Imagery (SVI) time series and 3D Gaussian Splatting (3DGS) rendering. Third, a decision layer integrates structured public acceptability from a questionnaire covering different respondent groups with in-depth expert interviews and synthesis, with virtual reality (VR) eye- and head-tracking used as supportive behavioral evidence. Applied to the Middenbeemster expansion in the Beemster Polder, the Netherlands, the framework yields a case-calibrated reference package for decision support: KOP-based construction intensity serves as the primary reference line for review, perception indicators serve as supporting guardrails, spatial character metrics act as case-specific reference checks to protect the polder framework, and visibility diagnostics remain a necessary screening layer. More broadly, the framework provides a transparent and replicable procedure that can be transferred and locally recalibrated for heritage-sensitive rural-urban fringes where change is incremental and cumulative, supporting a stage-comparable VIA approach.

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.

Street view imagery (SVI) is widely used in urban visual analysis and often treated as equivalent to eye-level perception. Yet its limitations and contextual applicability remain underexplored. This paper conducts a diagnostic viewpoint-level comparison of an image-based SVI pipeline and a 3D model-based field-of-view (FOV) method to clarify their respective weaknesses, strengths, and how they can be combined in practice (rather than treated as interchangeable or numerically fused). Using the West Lake ring road in Hangzhou as a case study, we analyze 2140 panoramas at 1075 viewpoints. The comparison shows systematic differences: SVI produces higher green shares (+0.16 on average), while FOV yields higher paved ground (+0.13) and building shares (+0.08). Sky differs little overall, water remains minor, and cross-method consistency varies by segment; SVI displays greater local variability linked to canopy occlusion and near-field heterogeneity. A small perception survey validates these findings. Terrain relief and building height were recognized more consistently in FOV, while vegetation and water abundance aligned more closely with SVI. Participants also judged overall ambience more easily from FOV’s structural stability, even though SVI conveyed greater visual realism. These results reveal clear complementarities: FOV provides structure-aware metrics, SVI emphasizes appearance cues, and neither alone captures lived perception. On this basis, we propose a combination-oriented three-layer workflow, with perception as a required validation layer to support reliable applications in skyline and openness control, interface and character management, greenery maintenance, and equity assessment.

Unmanned aerial vehicles (UAVs) are widely used for documentation, surveying, and 3D modeling in the built environment, yet their outputs often remain difficult to reuse for immersive comparison of alternative construction scenarios. This study presents a low-cost UAV-to-3DGS-to-VR workflow for constructing scenario-comparable immersive environments for built-environment review. The workflow combines multi-angle UAV imagery, point-cloud-based geometric anchoring, 3D Gaussian Splatting (3DGS), and Unity-based virtual reality (VR) to transform drone-captured reality into a reusable scene for controlled scenario comparison. The workflow is demonstrated in Middenbeemster, the central town of the Beemster polder World Heritage property. One present-condition scene (M0) and three alternative construction scenarios (M1 to M3) were created within a shared spatial reference. Reconstruction quality was assessed using PSNR and SSIM, and the VR scenes were further evaluated through eye-tracking, head-motion recording, and subjective ranking. The results indicate that the workflow can generate visually reliable and directly comparable immersive scenes from UAV data in this case study. Behavioral and subjective findings showed a consistent pattern, with M1 appearing more compatible than M2 and M3 in this pilot evaluation. The study contributes a pilot UAV-based workflow that links reality capture, immersive scenario comparison, and supplementary behavioral evidence within one process.

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.

Heritage landscapes are experienced, interpreted, and governed through what people see. Visual qualities such as skyline continuity, landmark prominence, enclosure, openness, and view accessibility influence how heritage value is perceived and how spatial interventions are accepted. Meanwhile, urbanization, tourism development, and infrastructure expansion increasingly reshape visual environments, making visual governance a central concern in heritage conservation and landscape planning. Although visual heritage landscape research has grown rapidly, it often remains fragmented: studies tend to privilege either spatial-technical modelling or perception-based evaluation, and the connections between data, methods, and research aims are frequently implicit. This fragmentation limits cross-case comparability, weakens methodological accumulation, and reduces the usability of research outputs for practice. Therefore, the main objective of this thesis is to establish a pathway-oriented framework that links data-method-content configurations, enabling visual evidence to be translated into structured knowledge and practical guidance for spatial decision-making.
A pathway-oriented framework for visual heritage landscape research
This thesis conceptualizes visual heritage landscape research as a set of pathways that integrate three core components: the data used to describe visual environments, the methods used to analyze them, and the content outcomes expected for interpretation and decision support. Instead of treating methods as isolated techniques, the framework emphasizes how different components can be assembled in coherent sequences to match research purposes, spatial scales, and heritage contexts. Based on this logic, four expanded pathway types (EP-1 to EP-4) are proposed to bridge commonly separated approaches and to support more systematic, integrative study designs. Each pathway highlights a distinct integration focus, but collectively they provide a transferable structure for organizing visual research questions, selecting appropriate evidence, and producing outputs that are both analytically rigorous and implementation-oriented.
Pathway implementation through four case studies
The framework is implemented through four case studies that test the expanded pathways across diverse heritage landscape contexts and multi-scale conditions. EP-1 demonstrates an integrated spatial-perceptual pathway that connects spatial structure with perceptual evidence, enabling the interpretation of visual mechanisms and the validation of experienced visual qualities. EP-2 develops a digitally supported perception evaluation pathway that extends visual assessment to larger spatial coverage and multiple viewpoints through digital capture and modelling, providing scalable insight into visual quality and environmental preference. EP-3 proposes a multi-source visual-spatial pathway that integrates heterogeneous geo-data and multi-view analyses to strengthen interpretation across viewpoints and spatial levels, supporting a richer understanding of how visual patterns emerge from landscape structure. EP-4 advances a perception-informed decision pathway that couples perceptual evidence with visibility modelling to generate threshold-style rules and decision-ready outputs for visual impact assessment, planning control, and governance. Across cases, the thesis produces reusable indicators, spatial typologies, and pattern-based knowledge that can inform conservation strategies, design interventions, and management priorities.
Synthesis, navigation, and contributions
Building on cross-case synthesis, the thesis develops a navigational model that supports pathway selection and configuration according to objectives, constraints, data availability, and implementation needs. This model encourages modular entry points, allowing studies to begin from data constraints, methodological strengths, or governance questions, while still remaining comparable within a shared pathway system. Overall, the thesis contributes by structuring a fragmented field into a coherent framework of pathways, offering modular workflows that connect data acquisition-computation-assessment, and translating visual heritage landscape research into evidence-informed, interpretable, and actionable tools. These contributions aim to strengthen the integration of visual evidence into heritage landscape conservation, planning, and design, and to support more transparent and robust decision-making in visually sensitive heritage contexts.

Highlights: What are the main findings? An end-to-end workflow integrates UAV photogrammetry, LiDAR, and VR for heritage. Three-layer evaluation shows focused attention, edge-anchored movement, and clearer cultural understanding. What is the implication of the main finding? UAV-enabled completeness improves both geometric fidelity and user experience in VR. The workflow is affordable and transferable, supporting under-resourced heritage sites. Urban heritage documentation often separates 3D data acquisition from immersive interaction, limiting both accuracy and user impact. This study develops and validates an end-to-end workflow that integrates UAV photogrammetry with terrestrial LiDAR and deploys the fused model in a VR environment. Applied to Piazza Vittorio Emanuele II in Rovigo, Italy, the approach achieves centimetre-level registration, completes roofs and upper façades that ground scanning alone cannot capture, and produces stable, high-fidelity assets suitable for real-time interaction. Effectiveness is assessed through a three-layer evaluation framework encompassing vision, behavior, and cognition. Eye-tracking heatmaps and scanpaths show that attention shifts from dispersed viewing to concentrated focus on landmarks and panels. Locomotion traces reveal a transition from diffuse roaming to edge-anchored strategies, with stronger reliance on low-visibility zones for spatial judgment. Post-VR interviews confirm improved spatial comprehension, stronger recognition of cultural values, and enhanced conservation intentions. The results demonstrate that UAV-enabled completeness directly influences how users perceive, navigate, and interpret heritage spaces in VR. The workflow is cost-effective, replicable, and transferable, offering a practical model for under-resourced heritage sites. More broadly, it provides a methodological template for linking drone-based data acquisition to measurable cognitive and cultural outcomes in immersive heritage applications.

Urban greenery is essential for environmental quality, visual comfort, and residents’ well-being, and it becomes especially critical in high-density residential compounds where outdoor space is limited. This study proposes a pedestrian-scale visibility framework that integrates solid 3D models (DEM, extruded buildings, water) with voxelized LiDAR point clouds to reconstruct fine-resolution outdoor scenes and to quantify visual perception indicators, including green view factor (GVF), sky view factor (SVF), and average green distance (AGD). A residential community in Nanjing is used as the case study. Line-of-sight sampling was performed on 223 viewpoints distributed across three empirically identified activity zones, and a resident questionnaire was conducted in parallel (279 valid responses). The results show that the visually open zone, characterized by relatively high SVF, moderate GVF, and larger vegetation setback (higher AGD), is also the zone most preferred by residents, whereas the zone with the highest GVF but strong enclosure is least preferred. This consistency between modeled indicators and survey responses confirms that excessive, close-range planting may reduce usability, while a balanced combination of greenery and openness better supports everyday outdoor activities. The proposed Point-Cloud-Based approach, therefore, provides a data-driven basis for planning, evaluating, and managing outdoor environments in dense urban residential areas, and ultimately reaching the purpose of more livable urban communities in the era of intelligent and sustainable cities.

This systematic literature review critically examines the application of digital technologies in architectural heritage risk management from 2014 to 2024, focusing exclusively on English-language publications. As the significance of architectural heritage continues to be recognized globally, there is an increasing shift towards integrating digital solutions to ensure its preservation and management. This paper explores the evolution and application of digital technologies such as Building Information Modeling (BIM), Geographic Information Systems (GIS), and advanced imaging techniques within the field. It highlights how these technologies have facilitated the non-destructive evaluation of heritage sites and enhanced accessibility and interaction through virtual and augmented reality applications. By synthesizing data from various case studies and scholarly articles, the review identifies current trends and the expanding scope of digital interventions in heritage conservation. It discusses the interplay between traditional conservation approaches and modern technological solutions, providing insights into their complementary roles. The analysis also addresses the challenges and limitations encountered in the digital preservation of architectural heritage, such as data integration, the compatibility of different technologies, and the need for more comprehensive frameworks to guide the implementation of digital tools in heritage conservation practices. Ultimately, this review underscores the transformative impact of digital technology in managing architectural heritage risks, suggesting directions for future research and the potential for innovative applications in the field.

Urban heritage landscapes, with their layered cultural and aesthetic values, require precise visual analysis to support conservation and planning. However, existing visual analysis methods are often fragmented and fail to fully capture their complex visual-spatial characteristics. To address this gap, this paper proposes a combined visual analysis framework that integrates four GIS-based visual analysis methods—cumulative viewshed (CV), visual magnitude (VM), field of view (FOV) analysis, and street-view image (SVI) segmentation. These methods were applied to the UNESCO World Heritage Site of West Lake in Hangzhou, China, to explore lake–city–landscape relationships, classify lakeside landscape types, and interpret the spatial composition of iconic viewpoints. Findings indicate that: (a) four zones with both high CV and VM values coincide with key architectural and scenic landmarks, suggesting intentional spatial design strategies, while half of the “Ten Scenic Places” are influenced by symbolic or experiential factors beyond visibility; (b) 37 landscape types were identified along lakeside roads, revealing areas where vegetation obscures potential lake views and where design trade-offs are evident; (c) only two of ten potential city-to-lake visual corridors remain unobstructed, pointing to unmanaged vegetation as a critical barrier; and (d) these insights inform targeted visual management strategies, including vegetation control, viewpoint activation, and circulation optimization. This study highlights the limitations of single-method approaches, such as SVI's insensitivity to topographic variation, and suggests that a multi-perspective integration of VAMs can yield deeper spatial insights and more actionable guidance for managing urban heritage landscapes.

This paper investigates the role of 3D Gaussian Splatting (3DGS) within point cloud–dominated workflows for modern architectural heritage digitization. While 3DGS enables real-time, photorealistic visualization, its integration into LiDAR-based documentation pipelines remains underexplored. Using Bouwpub, a modern heritage building in the Netherlands, as a case study, the paper compares 3DGS and LiDAR across data acquisition and preservation, visualization, semantic segmentation, and dissemination. Results show that 3DGS offers superior visual expressiveness and user responsiveness, whereas LiDAR provides greater structural accuracy and segmentation reliability. Based on these findings, two integration strategies are proposed: a Blender-based multi-angle rendering workflow and a Level of Detail 3DGS (LOD3DGS) pipeline. Moving from isolated assessment to applied integration, the study positions 3DGS as a complementary visualization and dissemination module rather than a replacement. This hybrid approach supports immersive, scalable, and semantically enriched digital heritage systems, offering new directions for enhancing both expert documentation and public engagement.

Historic gardens, regarded as a significant genre of cultural heritage, encapsulate the enduring essence of bygone eras while concurrently transcending temporal boundaries to resonate with the present and future. These gardens provide us vitality and inspiration, holding a collective repository of human memory and serving as a testament to our shared heritage. However, like landscapes, gardens constantly change through natural processes and human interventions. How can we preserve these gardens, though changes are unavoidable? Spatial and visual characteristics are the gardens' essential characteristics, and point-cloud (LiDAR) technologies are powerful tools to reveal and analyze gardens’ spatial-visual relationships and characteristics. Therefore, this paper aims to present a point-cloud-based approach to identifying spatial-visual design principles and making them operational to protect and develop historic gardens. Additionally, several methods have been proposed in this research, including (a) a voxel-based method to transfer points into a solid model for GIS-based computation, (b) a novel method to analyze the field of view (FOV), and (c) a systemic framework to reveal historic gardens’ spatial-visual characteristics based on the voxelized model. Jichang Garden, a historic garden in Wuxi, China, known for its visual design and spatial arrangement, has been selected as a case study to showcase how to apply the methods proposed by this paper. The findings include the design principles for the water body, the arrangement for a route, and the planting strategies of the garden. The conservational strategies have been formed based on the findings, and the appliable potentials and limitations of the methods have also been discussed.

[Objective] Human perception of landscape and environment is primarily through visual senses, making visual landscape research a central theme in landscape architecture research. Conducting a visual analysis of the spatial characteristics of traditional Chinese gardens and exploring their visual features can provide valuable guidance for inheriting the essence of spatial design. In recent years, many scholars have employed quantitative analytical methods to identify the visual space of traditional gardens. However, few of these studies have used detailed models to analyze the spatial features of traditional garden spaces. Compared to traditional digital models, point cloud models collected through LiDAR (light detection and ranging) offer more detailed spatial information for visual landscape research. Therefore, this research aims to take Jichang Garden in Wuxi as an example to explore the possibilities and applications of in-depth visual and spatial analysis of traditional Chinese gardens using point cloud technology. This aim can be further broken into several components: 1) Establishing analytical methods and selecting analysis indicators; 2) applying these methods and indicators to analyze the visual space of Jichang Garden; 3) uncovering the characteristics and features of traditional Chinese gardens through the interpretation of analysis results. [Method] This research establishes a set of methods for quantifying the analysis of visual space using point cloud data, including three main steps. 1) Establishment of a model based on point cloud for calculating the analysis results of visual space. In detail, this research applies a voxel-based method to build multidimensional digital models for buildings, vegetation, and rockery, and build a digital elevation model (DEM) based on the point cloud data on the ground. Then, the aforesaid two kinds of models are integrated with water surface to finalize the modeling process. 2) Establishment of a visual analysis method (line of sight method) based on the three-dimensional digital model for obtaining visual space information. 3) Proposal of indicators for evaluating visual landscape utilizing the visual space information obtained, including “3D visibility”, “visual spread” and “feature ratio of visual field” indicators. A total of 11 viewpoints (viewpoints 1, 2, 3 ... 11) on the west side of Jinhuiyi Pond are analyzed using the above methods. [Results] This research’ s main findings consist of three parts. 1) 3D visibility calculation results. From the visibility analysis results of 11 viewpoints, it is evident that viewpoints 1, 5, 6, 7, and 10 have a relatively broad visual field, with some line of sight reaching a length of 100 meters. 2) Evaluation results of visual space indicators. The viewpoint with the highest 3D visibility is labeled as viewpoint 1, located at the Xianyuexie water viewing platform, while the one with the minimum 3D visibility is labeled as viewpoint 2. The viewpoint with the highest “visual spread” is viewpoint 10, situated in the plaza at the south of the Jiashutang building, while the one with the minimum “visual spread” is viewpoint 11. Except for viewpoint 1 (dominated by buildings) and viewpoint 10 (dominated by the ground), the highest “feature ratio of visual field” is occupied by vegetation. 3) Interpretation of the calculation results. […]

This paper focuses on GIS-based visibility analysis to explore landscape architecture com-positions as a means to understand visual-spatial characteristics and identify related design principles. More specifically, the paper elaborates a practical method to employ high-resolution data acquired by terrestrial LiDAR (Light Detection and Ranging or Laser Imaging Detection and Ranging) for this pur-pose. Though LiDAR provides a powerful means to digitally capture the real-world, methods like GIS-based visual landscape research that utilize viewshed analysis ideally require a continuous Digital Landscape Model conduct visibility computation. Therefore, one of the obstacles before the visual analysis is to process the points into surface or solid models. Voxel-based algorithms are powerful means to process LiDAR data. There are many applications known of voxel-based visibility analysis but requires often specialist software that is hard to handle or unavailable to landscape architects in practice. This paper showcases an attempt to use standard software for voxel-based visibility analysis. It presents a practical method for applications in landscape architecture analysis. Jichang Garden (Wuxi, China) is used as an example. The historical garden is an evocative example of a landscape architecture compo-sition that displays skilful applications of spatial-visual design principles and therefore worthy of ana-lyse.

Visual perception is crucial in landscape experience. Therefore, visual landscape research is an important field of inquiry that needs further development and applications (NIJHUIS 2011), and visibility analysis is the basis for further research. There are many methods and applications of landscape visibility analysis that have been developed and applied in the past decades. The pioneering work of Llobera explores the concept of “visual exposure”. He defined the visual exposure (V-E) as a measure of the visible portion of whatever is the focus of the investigation, which is about the surface area covered on the retina (LLOBERA 2003). In this research, a newly developed V-E computation algorithm for complex environments has been developed, which enables the analysis of views from multiple viewpoints. The West-Lake, a UNESCO world heritage site in Hangzhou (China), is used as a case study to compute the V-Es’ value for viewpoints on routes beside and around the lake. Finally, the method’s accuracy and the algorithm’s adoption potential have been evaluated.