How multiple dimensions of viewpoint-specific spatial structure relate directionally to recurrent visual behavior in heritage settings remains insufficiently specified at the level of matched scenes. This paper examines this relationship in Jichang Garden, China, by combining immersive eye-tracking with viewpoint-matched spatial features derived from three-dimensional visibility analysis. Gaze data from 51 participants across 22 useable viewpoints were used to identify four recurrent visual behavior patterns, exploratory scanning, hotspot attention, near-far alternation, and route-oriented attention, together with three broader exploration strategies. These behavioral patterns were then related to viewpoint-level spatial features, including openness, depth, complexity, orientation, viewpoint geometry, and scene composition. In the mixed-effects models, higher complexity was associated with more exploratory scanning and less hotspot attention, whereas greater openness was independently associated with less exploratory scanning. Viewpoint geometry showed differentiated behavioral profiles: greater upward visibility was associated with more exploratory scanning but less hotspot attention and near-far alternation, whereas greater eye-level visibility was associated with less route-oriented attention. Greater vegetation visibility was associated with more exploratory scanning, while greater water visibility was associated with more route-oriented attention. Random Forest diagnostics indicated moderate predictive performance and range-dependent relationships, particularly for openness. Brief post-session debriefs provided additional context for selected scenes in which specific focal elements, including a particular tree, koi, and inscriptions, were not represented as separate predictors in the spatial models. Overall, the study provides case-based, scene-level evidence from one heritage setting on how viewpoint-matched spatial features relate to recurrent visual behavior and where additional interpretive context remains useful. ... Read more

Urban greenery is increasingly recognised for its potential to address urban challenges, necessitating effective methods for its measurement to inform research and guide practical interventions. Conventional greenery measurements primarily rely on indicators derived from remote sensing and street view imagery, whereas emerging social media image data offers novel opportunities to capture greenery from a subjective, user-oriented perspective. However, the characteristics and comparative performance of these greenery measurements remain unclear, and limited attention has been paid to their appropriate application scenarios. Employing Rotterdam as a case study, this research compares three urban greenery measurements: greenery derived from social media, the Green View Index (GVI), and the Normalised Difference Vegetation Index (NDVI), and examines their interrelationships at street and neighbourhood scales. The results indicate that, although these measurements are interrelated and broadly reflect consistent patterns, notable differences exist. Social media greenery aligns closely with NDVI and captures overall greenery conditions, but exhibits greater variability and subjectivity. GVI, while moderately correlated with NDVI, shows higher sensitivity but may underrepresent densely vegetated areas. Spatial analysis reveals coherent structures across measurements, with low clusters in the city centre and high clusters toward the periphery, but further examination shows varying local heterogeneity in measurement relations, with strong coefficients concentrated in selected central areas and fluctuating or negative associations in peripheral and residential or commercial districts. These findings highlight the influence of measurement characteristics, biases, and analytical scale selections in urban greenery measurements, and clarify the strengths and limitations of each measurement to guide context-appropriate method selection. ... Read more

Urbanization often produces mismatches between where ecosystem services are supplied and where people demand them, leading to pronounced service deficits in dense urban cores. Yet planners still lack integrative tools that can both diagnose these spatial inequities and directly inform targeted interventions. This paper develops a cross-scale framework that couples regional ecosystem service assessment with microscale greening design to mitigate inequities in provisioning ecosystem services. Using South Holland Province (Netherlands) as a case, we construct a Per Capita Provisioning Services Index (PSI) that links ecosystem service supply to population distribution and define “ecosystem service poverty” as areas falling into the lowest PSI class. Local spatial statistics (Getis–Ord G*) are then applied to identify statistically significant “coldspots” of ecosystem service poverty, contrasted with peripheral service “hotspots.” A six-dimensional performance matrix (food, water, energy, soil support and nutrients, habitat support, and cooling) is used to characterize coldspot types, revealing, for example, zones dominated by habitat and climate regulation deficits versus areas facing multi-dimensional shortages. Three-dimensional building data and explicit physical thresholds are subsequently used to identify suitable rooftops for greening in each coldspot type, and to match rooftop typologies with differentiated intervention strategies. The results demonstrate how targeted green roof configurations can respond to distinct local needs. By bridging macro-scale diagnosis and micro-scale design, the framework offers a transferable technical pathway for addressing ecosystem service poverty and advancing spatially just urban sustainability planning. ... Read more

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. ... Read more

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. ... Read more

Estuarine delta regions (EDRs) face escalating compound tidal-fluvial-pluvial flooding under climate change and rapid urbanization, yet impact assessments often rely on single-time or extreme-value indicators that obscure when blue-green-gray infrastructure (BGGI) benefits emerge, how robust they remain under uncertainty, and how they drive flood resilience. We propose a scenario-process-pattern (SPP) framework that evaluates flood resilience across the initial, peak, and recession phases, linking the hydrodynamic responses to BGGI spatial attributes. Applied to the Pearl River–East River–Shiziyang EDR using MIKE FLOOD simulations of seven design plans under 12 hydroclimatic scenarios, SPP combines tipping-point detection, principal component analysis, and Bayesian mixed-effects modeling to assess phase-specific and integrated resilience. Phase-specific responses include constructed-area water volume, blue-green and drainage-system storage volume, and high depth–velocity flooded area; GIS-derived predictors quantify BGGI spatial attributes including storage capacity, connectivity, and interface coupling. Results show pronounced spatiotemporal heterogeneity in how BGGI shapes flood resilience: plan differences are limited in initial and recession phases but widen at peak, with spatial effects showing subregional asymmetry and clustering around hydraulic control points; under high-hazard scenarios, adaptive plans halve peak constructed-area water volume and shorten high-hazard duration by 4 h, whereas rigid-defense plans exhibit threshold-type failure and inferior integrated resilience robustness. Gray systems primarily curb early risk, green storage and coupling dominate peak attenuation, and connectivity accelerates recession yet can amplify initial flood convergence. SPP provides a transferable, process-based evidence chain to support alternatives appraisal, adaptive flood management, and resilient spatial planning in EDRs. ... Read more

Understanding public experiences in urban greenspace is essential for supporting more human-centric design and management. While traditional survey methods are often time- and labor-intensive, user-generated content (UGC) offers a rapid and scalable alternative for capturing public experiential insights. However, extracting detailed user experience information from this data remains methodologically challenging. This study proposes a novel multimodal analytical framework based on online review data and natural language processing techniques, combining LoRA fine-tuned RoBERTa language model with CLIP vision-language model to analyze multidimensional ecosystem service experience patterns in urban greenspace from user-generated text and image reviews. Results demonstrate that the proposed approach achieves more robust extraction and analysis of user experience insights compared to conventional deep learning and lexicon-based methods, exhibiting greater capacity to process contextually embedded experiential information. The multimodal framework enables more comprehensive capture of user experiences than either text or image data alone, with particular gains on dimensions that are difficult to represent through a single modality. Applying the analytical framework to Amsterdam and Rotterdam as case studies, statistical and spatial analysis reveals heterogeneity in user urban greenspace experiences and identifies key experiential bundles alongside their associated synergies and trade-offs. This study offers a novel approach to quantifying urban greenspace experiences from a user perspective, and provides insights for evidence-based urban greening practices. ... Read more

We are grateful for Darwish's interest in our paper, Fouad et al. (2025, https://doi.org/10.1029/2024EF004883). In this reply, we show that Fouad et al. (2025, https://doi.org/10.1029/2024EF004883) did not attribute building collapses in Alexandria solely to hydroclimatic factors, as stated in the comment. Instead, we emphasize that hydroclimatic drivers are presented as accelerators, with other anthropogenic influences explicitly stated in the original paper. Moreover, our response proves that Darwish (2026, https://doi.org/10.1029/2025ef006885)'s simplistic statistical approach is physically incorrect and obscures absolute risk by normalizing actual building collapse rates to the total number of buildings within a city. Furthermore, our reply shows that the comment conflates the distinct measurement of soil relaxation using shallow isotope mapping at the city scale, as conducted in Fouad et al. (2025, https://doi.org/10.1029/2024EF004883), with deep structural geotechnical assessments for foundation design of individual buildings. The utility and complementarity of both methods are already discussed in Fouad et al. (2025, https://doi.org/10.1029/2024EF004883). We acknowledge that the statement on the “7,000 at-risk buildings” is only mentioned in the abstract and is inadvertently missed in the main text; however, the calculation leading to this result is detailed in our supplementary data set and methods. Accordingly, Darwish (2026, https://doi.org/10.1029/2025ef006885)'s comment, while appreciated, misinterprets Fouad et al. (2025, https://doi.org/10.1029/2024EF004883) and overlooks the contemporary literature on Alexandria's hydrogeological and coastal dynamic contexts and their implications for infrastructure instability. ... Read more

Urban agriculture and farming (UAF) initiatives are recognised for their potential to enhance urban resilience, support local food systems, and deliver ecosystem services. However, current scholarship remains fragmented, treating UAF initiatives as isolated green interventions, rather than integrated components of urban fabric. This study examines how landscape-based approaches (LbAs) and systems thinking (ST) have been applied concurrently to analyse and design these initiatives. We argue that LbA is necessary to provide the spatial logic for physical integration, while ST provides the functional logic for metabolic efficiency. This systematic literature review screened 92 records across Scopus, Web of Science, and Google Scholar, resulting in a refined corpus of 12 peer-reviewed articles published between 2015 and 2025. This reflects the nascent state of an interdisciplinary approach at this intersection. Utilising VOSviewer and Atlas.ti, the study identified four thematic clusters: urban green infrastructure, urban food systems, landscape planning, and socio-ecological systems. A cross-comparative analysis of these clusters and their underlying methodologies led to a new theoretical dual-lens systemic landscape framework to evaluate the sustainability outcomes of UAF. The findings reveal limited integration of spatial analysis with systems thinking across scales. This review contributes a novel multi-scale methodology that emphasises the need for integrated spatial and systemic interdependencies to achieve truly resilient urban food systems. ... Read more

As cultural landscapes increasingly evolve within urban environments, a persistent gap has emerged between their heritage spatial characteristics and public heritage value perception, undermining urban identity and sustainability. This study introduces the Perceptual–Spatial Landscape Planning Model, an integrative framework that positions route optimization as a strategic planning intervention to bridge this gap. Taking Chengde Mountain Resort as a case, we constructed a spatial network of 144 scenes and collected 43,879 user-generated social media comments to quantify public perception. We achieved perceptual–spatial coupling through: 1) a few-shot learning paradigm based on a large language model generates five distinct perception scores of each scene; 2) the resulting scores are then integrated with heritage spatial characteristics in graph neural networks using graph attention networks and deep graph infomax. Based on the coupling process, the optimized routes were generated by a multi-objective evolutionary algorithm. The optimized routes outperformed official and greedy baselines, achieving higher spatial diversity, perceptual coherence, lower variance, and broader coverage of marginal yet meaningful scenes. These routes avoided overconcentration in perceptual hotspots as conventional tourism planning while enhancing interpretive richness across various spaces. This model provides strong contextual transferability, offering interpretable framework for integrating public perception into cultural landscape planning, thereby advancing both the methodological rigor and spatial intelligence of cultural landscapes’ development in urban environments. ... Read more

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. ... Read more

Visual landscape research on heritage landscapes has expanded rapidly since 1995, yet its themes, study objects, and methods remain dispersed across disciplinary traditions. This review synthesizes 203 peer-reviewed studies published between 1995 and 2025 using a three-layered analytical framework that combines thematic coding, VOSviewer-based keyword co-occurrence analysis, and exploratory cross-dimensional Sankey mapping. Thematic coding shows that the field is concentrated around analysis/evaluation and management/conservation themes, with study objects dominated by formally recognized and spatially bounded heritage landscapes and methods centered on perception-based empirical approaches, GIS-based analysis, digital documentation, mixed methods, and multi-criteria evaluation. Keyword co-occurrence and cross-dimensional mapping further show that these distributions are organized through recurring but uneven theme–object–method associations. Three gaps are especially evident: perceptual and spatial evidence are often weakly coupled; less formalized, everyday, hybrid, and cross-scalar heritage landscapes remain underrepresented; and visual evidence is inconsistently translated into assessment, planning, and management contexts. Based on these findings, the review develops a review-derived organizing synthesis that relates research themes, heritage landscape types and scales, and methodological approaches. This synthesis clarifies the current structure of visual heritage landscape research, identifies underexplored intersections, and provides a basis for more transparent comparison and future empirical work. ... Read more

Urban analysis often relies on separate geospatial mapping, street-level image analysis, point-cloud analysis and 3D urban modeling workflows, which can lead to semantic and spatial inconsistencies when structural, visual and volumetric results are interpreted together. This paper develops an SPC-guided Smart 3D Gaussian Splatting (S3DGS) analytical framework to address this fragmentation. Using the Aula–library block in Delft as a case study, we construct a CityGML-inspired Smart Point Cloud from laser-scanning data, generate street-level and aerial 3DGS components from multi-view imagery, align and fuse them into a common coordinate frame, and propagate SPC-derived semantics to Gaussian primitives. The resulting S3DGS base supports projection-based semantic composition, observer-centered visual exposure, volumetric spatial-presence aggregation and layered scene typing within the same reference. Cross-layer interpretation links volumetric and visual-exposure types in the same spatial units, revealing conditions such as physically present but visually recessive building mass. This layered reading allows surface composition, visual experience and three-dimensional spatial presence to be traced within the same urban unit. Evaluation results indicate a stable workflow, with an alignment RMSE of 0.0439 m and a kNN label consistency of 92.24%. By turning Gaussian scenes into semantically traceable and spatially co-referenced analytical bases, S3DGS offers a practical pathway from isolated urban measurements toward integrated, viewpoint-aware and three-dimensional interpretation of the built environment. ... Read more

Business districts currently lack the socio-ecologically inclusive standards of workscapes. This study addresses this gap through a comparative design analysis of international precedents, translating best practices into transferable spatial design knowledge for workscape development. The findings demonstrate that the transformation of business districts can be achieved by activating and reconfiguring existing spatial elements to generate ecological, social and spatial value. Five recurring spatial design patterns are identified as key drivers of this transition on the spatial district scale: zone-crossing corridors, mobility-driven green space, active cores, multitone environments and spatial enrichment. Together, these patterns foster biodiversity, climate adaptivity, spatial diversity, and improved everyday use. The research shows that these patterns are adaptable and scalable across contexts, offering a practical framework for policymakers and designers to transform monotonous business districts into more liveable and resilient workscapes. While the study primarily draws on Northwestern European cases and non-heavy industrial contexts, it establishes a foundation for further validation through research-by-design approaches and Living Lab setups. By linking spatial analysis with design synthesis, this study advances the methodological framework for evidence-based landscape architecture and contributes to the broader discourse on sustainable and socio-ecologically inclusive urban development. ... Read more

Urban agriculture is increasingly recognized as a multifunctional lever for urban sustainability, yet the mechanisms through which planning policies enable or constrain its integration into city systems remain poorly understood. This gap limits the development of evidence-based frameworks that can bridge policy intent and implementation practice. This study develops a transparent, multilingual content-analysis pipeline and a landscape-informed coupling framework to evaluate urban agriculture policy–practice alignment across three contrasting governance contexts: Havana (Cuba), New York City (USA), and Chongming Island (China). Using a PRISMA-ScR literature synthesis (n = 3145), we construct a five-domain, 40-keyword evaluation matrix and apply it to official policy corpora and flagship project documentation. Results show that human-centered approaches effectively translate social equity and food-provisioning aims but exhibit limited spatial integration; nature-based approaches advance ecological and morphological targets but underperform on participation; and the landscape-informed model achieves more balanced alignment across all five domains, though gaps persist in inter-layer connectivity. Situating these findings within the broader discourse on urban sustainability governance, we propose a multi-layered landscape framework spanning ecological, institutional, social, and spatial dimensions. This framework offers planners a structured diagnostic and prescriptive tool for embedding urban agriculture into integrated urban transitions. ... Read more

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. ... Read more

Cultural landscapes are increasingly vulnerable to the compounded effects of potential risks, ecological degradation, and imbalanced heritage value perceptions under intensifying climate change and global urbanization pressures. However, there is a lack of framework that systematically integrates geographical hazards, ecological sensitivity, and both expert and public heritage value perceptions to guide differentiated conservation and development of cultural landscapes. This study proposes a Hazard-Ecology-Perception Landscape Planning (HEPLP) framework to provide a spatially explicit decision-support tool that unifies hazard, ecology, and perception dimensions for cultural landscape planning. HEPLP is evaluated in a case study of Chengde Mountain Resort. A GIS-based methodology is employed to characterize geographical hazards and ecological sensitivity by combining concept of entropy and Analytic Hierarchy Process. Expert scoring and large language model content analysis are used to map heritage value perceptions. Risk-based analysis and three-dimensional clustering revealed nine distinct clusters in cultural landscape, providing spatially grounded evidence for targeted conservation and development strategies. This includes many scenes where previously implemented landscape planning strategies have been designated for complete conservation, as well as clusters where trade-offs between ecological sensitivity and heritage value perception are carefully balanced. Unlike previous frameworks that focused on single or dual dimensions, HEPLP offers an integrative tool for sustainable cultural landscape conservation and development under environmental and social challenges. ... Read more

This research explores landscape-based solutions (LBS) as an integrated, transdisciplinary approach to address the interlinked challenges of climate change, biodiversity loss, and water insecurity. LBS aim to regenerate living landscapes by combining ecological science, indigenous knowledge, and spatial design. Rooted in local conditions—such as climate, ecology, water, and cultural history—LBS support inclusive, multifunctional landscapes that enhance both ecological resilience and social equity. Using a mixed-methods approach, the study combines global mapping of Indigenous and Traditional Ecological Knowledge (IEK/TEK), a survey of practical LBS applications, and engagement in real-time landscape projects in Indonesia, the Netherlands, and Germany. A cross-case analysis reveals diverse strategies and shared success factors, including grounding in local systems, strong community involvement, and adaptive, multi-scalar design. The ultimate goal is to influence global water governance by demonstrating the value of integrating ancestral knowledge into contemporary landscape strategies. In alignment with the Sustainable Development Goals—especially SDG 6 (Clean Water and Sanitation), SDG 13 (Climate Action), and SDG 15 (Life on Land)—this research promotes ecologically sound and culturally rooted solutions. It contributes to a transferable framework for sustainable landscape planning in both urban and rural contexts. ... Read more

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. ... Read more

The increasing recognition of the health benefits of blue spaces highlights their crucial role in constructing Healthy Cities and advancing Sustainable Development Goals. Given that promoting recreational running represents a fundamental pathway to harnessing these benefits, integrating it into spatial planning and design is imperative. Nevertheless, this integration process necessitates substantiated evidence, especially concerning variances among population groups. To address this gap, utilising crowdsourced data and a machine learning approach, this study investigates heterogeneous spatial distributions of recreational running across various age demographics in Rotterdam, with a specific emphasis on visual perceptions and built environments. The mapping results illustrate the varied allure of blue spaces for recreational running, exhibiting a trend of increased clustering in running activities with age, extending beyond the city centre. The outcomes of GWR and spatial regression models indicate significant associations between various visual perception factors and built environment indicators with individual running preferences. Crucially, disparities and spatial heterogeneity are evident in the impacts of different environmental factors on running across age groups. Accordingly, tailored planning strategies and patterns are proposed, informed by age-specific environmental perceptions and preferences, contributing to a deeper understanding of the blue-health mechanism and offering practical insights for creating health-promoting blue spaces. ... Read more