Search Results (1,649)

Rural public art is increasingly used to improve living environments and reactivate place-based culture in rural communities. However, existing evaluations remain fragmented and provide limited support for assessing intervention effectiveness and formulating targeted strategies. To address this gap, this study constructs a multidimensional evaluation system for rural public art interventions and empirically tests it through case studies of 11 villages in Songyang County, China. The system covers three dimensions: material space creation, cultural heritage and innovation, and the reconstruction of social relations. A mixed-methods approach was adopted, combining literature review, field investigation, expert consultation, AHP weighting, and Kano demand classification. The results support the validity of the proposed evaluation system and identify cultural heritage preservation and transmission, basic and cultural facilities, funding safeguards, spatial accessibility, cultural affinity, and local cultural aesthetic compatibility as stable priority indicators. The comparison between expert weighting and stakeholder sensitivity further reveals differences between strategic importance and locally perceived demand. This study provides an operational evaluation system for assessing rural public art interventions and translates the evaluation results into targeted strategies, offering empirical support for more sustainable and context-sensitive rural public art practices. Full article

The humid coastal Lingnan region of South China, including the Chaoshan area of eastern Guangdong, is frequently exposed to disaster-prone weather conditions such as high humidity, typhoon-related winds, heavy rainfall, and salt-laden coastal air. These long-term environmental exposures may contribute to surface deterioration risks of architectural heritage. Located in Shantou, Yingchuan Shijia has shown five visible surface deterioration types—cracks, staining, saltpetering, plants, and spalling—under the combined influence of environmental exposure, material aging, previous disturbance, and insufficient maintenance. To address the limitations of manual inspection, this study explores a conservation-oriented intelligent workflow integrating YOLO-based detection, digital documentation, and screening-level conservation interpretation. Digital documentation used UAV imagery, mobile LiDAR scanning, measured drawings, and SketchUp-based three-dimensional modeling. The dataset was built in three stages: a 99-image preliminary dataset, where YOLOv8 showed only basic learning capability with low performance metrics, including Precision of 33.0 ± 3.0%, Recall of 28.0 ± 1.0%, mAP50 of 25.0 ± 1.0%, and mAP50-95 of 11.0 ± 1.0%; a 362-image non-augmented case-study dataset, where YOLOv8 still showed limited performance, with mAP50 of 20.0 ± 1.0% and mAP50-95 of 8.0 ± 1.0%; and a final YOLO-format case-study dataset of 2000 images after training-set-only augmentation using 11 geometric and photometric transformation methods. After augmentation, YOLOv8 mAP50 increased to 62.0 ± 2.0%. Under the same augmented-data condition, YOLOv13 showed Precision of 89.0 ± 1.0%, Recall of 77.0 ± 1.0%, mAP50 of 84.0 ± 1.0%, and mAP50-95 of 65.0 ± 1.0%, indicating relatively higher validation performance than YOLOv8. In the normalized confusion matrix, the background missed-detection values for cracks and saltpetering were 0.29 and 0.22, respectively, indicating that weak-feature and low-contrast deterioration types remained challenging. Based on YOLOv13, a mini program was developed to organize detection outputs and provide field-oriented preliminary conservation hints. Overall, this study provides a preliminary workflow linking digital collection, image-based deterioration detection, Grad-CAM visualization, and assisted field recording for the preventive conservation of Chaoshan overseas-Chinese residences in humid coastal heritage environments. Full article

Museum collections are at risk from insects. A changing climate or increased amounts of imported materials, exhibition loans and international travel, can increase exotic species. Heritage properties are often monitored for pests, so we used trapping data from 31 Austrian museums, libraries and storerooms. The carpet beetles Anthrenus spp. and Attagenus spp. studied here, showed that the catch of these two species in buildings was correlated. Unheated libraries show high catch rates for Anthrenus spp., Attagenus spp. seemed more often caught in heated/urban museums. Anthrenus verbasci, Anthrenus olgae and Anthrenus museorum account for almost 98% of our catch. Anthrenus verbasci and Anthrenus olgae are commonly found occurring together suggesting they form a core ecological pair, found in most buildings. Rarer Anthrenus fuscus appears typically at locations lacking winter heating. Attagenus smirnovi and Attagenus unicolor accounted for 95% of this genus in the buildings. There are notable differences in the types of carpet beetle across European heritage environments. Anthrenus olgae, often trapped in Austria, is uncommon elsewhere, while Anthrenus sarnicus, fairly common in the UK, is rare elsewhere. Not enough is known about the range of heritage insects across Europe, which is increasingly relevant to management under a changing climate. Full article

Preserving cultural heritage sites requires an interoperable digital framework capable of integrating heterogeneous spatial data and supporting immersive interaction for inspection and management. This study investigates the integration of multiple heritage data representations—including IFC-based Heritage Building Information Modeling (HBIM), terrestrial and UAV LiDAR point clouds, and 3D Gaussian Splatting reconstructions—into a unified digital management environment for the East Hall (Aula Timur) heritage site within the Bandung Institute of Technology (ITB) campus. A semantic–spatial interoperability workflow is proposed to harmonize BIM, point cloud, and landscape-scale data within a common georeferenced context, supported by a CityGML-based base map of the surrounding site. An immersive virtual environment was implemented using a head-mounted display to enable walkthrough-based inspection and damage annotation. All datasets were georeferenced within a unified coordinate system, allowing spatial registration between digital objects and the physical heritage site. The results demonstrate that multi-source heritage datasets can be integrated with high geometric accuracy, achieving TLS registration errors of approximately 2 mm and georeferencing residuals within 11.1 cm (horizontal) and 0.95 cm (vertical), while preserving semantic information and ensuring spatial coherence across HBIM, GIS, and immersive environments. The system is implemented in VR, with an architecture designed to support future MR-based on-site annotation and visualization. The proposed framework establishes a foundation for future heritage digital twin deployments and supports informed conservation decisions. Full article

Multimodal large language models can read architectural images and design instructions but they still struggle to turn architectural rules into editable, executable models in professional modeling environments. To address this limitation, this paper presents MLLMto3D, an MCP-driven closed-loop framework that connects multimodal reasoning with Rhino-based modeling, feedback, and revision. The framework consists of five phases: visual parsing, JSON-based intent serialization, code synthesis, MCP-driven Rhino execution and feedback, and verification with bounded repair. Its core mechanism is JSON-based intent serialization, which converts image-derived architectural information into machine-readable modeling parameters under a predefined JSON schema. The schema separates geometric and compositional constraints, including height, bay rhythm, facade zones, and alignment rules, from design variables such as materials, openings, and ornament. Building on this mechanism, Skills modules externalize facade typology knowledge and safe Rhino scripting patterns, providing callable professional constraints for code synthesis to reduce design-intent deviation and API hallucination. The framework is evaluated through an experimental design case study on a site in Shanghai’s Hengfu Historic District, where the generation of new façades is informed by a nearby heritage architectural reference. The results show that MLLMto3D can generate a parametrically adjustable Rhino model while preserving the main compositional constraints, thereby advancing AI-assisted architectural 3D generation toward a controllable, verifiable, and iterative modeling process. Full article

Historic urban districts are increasingly exposed to rapid urban transformation, resulting in the deterioration of heritage fabric, weakening of spatial identity, and disruption of everyday patterns of use. Although participatory approaches are increasingly recognised in heritage-led regeneration, many applications remain limited by the lack of analytical mechanisms capable of connecting community perspectives with spatial and behavioural evidence in a structured and practical manner. This study develops and applies a participatory decision-support approach based on the People–Place–Behaviour (PPB) framework within the historic district of El-Mokhtalat in Mansoura, Egypt. The study combines spatial documentation, behavioural observation, and stakeholder consultation to examine how everyday urban practices, adaptive reuse, informal interventions, and local perceptions collectively influence regeneration priorities within the historic environment. The findings indicate that regeneration priorities emerge through the interaction between spatial conditions, community perceptions, and behavioural patterns rather than through isolated physical conditions alone. Based on stakeholder consultations (n = 30), the analysis identifies a prioritisation gradient in which architectural conservation and environmental enhancement represent the most immediate intervention priorities, while adaptive reuse and public-space improvements remain dependent on contextual compatibility and local acceptance. The study also demonstrates the analytical value of behavioural evidence in revealing recurring spatial pressures, identity-related transformations, and everyday interaction patterns affecting the continuity of the historic urban fabric. By integrating participatory, spatial, and behavioural evidence within a unified evaluation process, the study proposes a context-sensitive analytical approach capable of supporting more informed and locally responsive heritage-led regeneration strategies. Full article

Automated detection of archaeological stone cairns using high-resolution satellite imagery offers a scalable approach for documenting vulnerable heritage landscapes in the Ennedi Massif, where extensive and remote terrain limits traditional field survey, and rapid documentation is required. This study presents a GIS and deep learning framework based on the YOLOv8 model to identify and map stone cairns using Google Satellite RGB imagery at 28.5 cm spatial resolution. Ground-truth data collected via GPS field survey were used to train and validate YOLOv8n. The study area was divided into two regions with contrasting terrain and illumination conditions to evaluate model transferability. The training region included 149 verified cairns, while the independent test region included 103 cairns. Early stopping reduced overfitting, reaching mAP50 of 99.5% and mAP50–95 of 94.3%. A density-based spatial clustering algorithm was applied to merge overlapping detections and generate circular cairn representations. On the test set, the model achieved 83.5% precision, recall, and F1-score, indicating stable performance under the selected operational configuration. Comparison with YOLOv5n showed slightly higher localization accuracy for YOLOv8n, while YOLOv5n yielded marginally higher precision and F1-score. Overall, the framework provides a non-invasive tool for large-scale archaeological prospection and heritage monitoring in remote desert environments. Full article

As core architectural environments for cultural heritage preservation and public education, museums are evolving from static exhibition spaces into immersive, multisensory interactive environments. The sensory attributes of the architectural environment—including multimodal information such as light, sound, and touch—exhibit a dynamic coupling with visitors’ emotional states. Responding to visitors’ growing emphasis on emotional enhancement, this study aims to improve the emotional experience of museum tours through multisensory compensation strategies. First, we conducted an experiment at the Shaanxi Archaeology Museum, capturing facial videos of participants during their tours and utilizing a facial expression analysis system for continuous emotion recognition. Subsequently, drawing on theories of multisensory interaction and emotion regulation, we constructed a multisensory emotion regulation model to guide the sensory compensation experiment. Visualization analysis of the results confirmed that multisensory compensation strategies within the architectural environment significantly increased positive emotions (from 48.23% to 60.78%). This study focuses on the mechanisms by which sensory compensation strategies in the architectural environment influence visitors’ emotional experiences, aiming to promote the transformation of cultural heritage spaces from “function-oriented” to “emotion-oriented” environments. Full article

Historic districts are complex built heritage environments where conservation, commercial activities, and public use continuously interact. A key challenge is maintaining cultural meaning and spatial authenticity while meeting contemporary demands for leisure and accessibility. Taking the Fuzimiao–Qinhuai Scenic Belt in Nanjing, China, as a representative case, this study develops a computational mixed-methods framework to evaluate visitor perception and diagnose experiential imbalances in the built heritage environment. A total of 2940 online reviews (2020–2025) were analysed using TF-IDF, Latent Dirichlet Allocation (LDA), StructBERT sentiment analysis, and Importance–Performance Analysis (IPA). Six experiential dimensions were identified, covering cultural inheritance, nightscape and leisure, rituals and museum visits, architectural space, value evaluation, and practical services. Results reveal a clear disparity: nightscape and value-related dimensions received the highest attention and positive sentiment, whereas rituals and museum interpretation underperformed despite their central heritage significance. Based on the IPA diagnosis, the study proposes three strategies: reallocating resources from over-supplied services to underperforming cultural cores, integrating immersive digital technologies (VR/AR) to revitalise heritage interpretation, and embedding cultural narratives into nightscape experiences. These strategies support a paradigm shift from visual attraction to cultural resonance in the conservation-oriented regeneration of historic districts. Full article

This study investigates the vanished Fazlı Pasha Palace in Istanbul as a case of lost architectural heritage, addressing the challenges of heritage interpretation, presentation, and integration into contemporary urban contexts. Drawing on contemporary conservation frameworks, the research situates the palace within a broader discourse on cultural and urban sustainability, emphasising the interdependence of tangible and intangible heritage values. As a methodology, this study employs a multi-layered, interdisciplinary framework that synthesises archival empirical data, architectural historiography, and GIS-based geospatial analytics. Unlike traditional descriptive methods, this research introduces an integrated digital heritage interpretation model grounded in an evidence-grading system. This system categorises architectural data into three distinct epistemic levels: documented (empirical), inferred (analogous), and hypothetical (conjectural). By implementing this tripartite structure, the design ensures a structured communication of uncertainty, effectively bridging the gap between historical fragmentation and spatial data and stratification while strictly adhering to contemporary conservation approaches that critically limit speculative reconstruction in the cases of lost urban layers. The findings, supported by GIS spatial mapping, demonstrate how the palace’s administrative footprint influenced 18th-century Ottoman Istanbul’s urban fabric, of which there is very limited spatial knowledge. Moreover, proposals for effectively reintegrating lost architectural heritage into contemporary urban memory without compromising authenticity or the integrity of existing urban fabric are developed. In doing so, the study contributes to urban sustainability by offering a non-intrusive, reversible, and critically evidence-based approach to heritage interpretation. Beyond the specific case of the Fazlı Pasha Palace, the proposed model provides a transferable methodological framework for the interpretation of lost heritage in complex historic cities, supporting the continuity of cultural memory, identity, and place-based narratives. The research thus advances current debates on digital in-situ presentation of lost heritage, authenticity, and sustainable urban conservation by demonstrating how the memory of vanished buildings can be meaningfully presented and communicated within contemporary urban environments. Full article

Indoor environmental conditions must remain stable to preserve the cultural heritage objects exhibited in museums. Fluctuations in temperature and relative humidity accelerate degradation, and for this reason, their control is essential. Based on this, in this study, a machine learning-based framework for indoor microclimate forecasting is developed and evaluated, with application to the Archaeological Museum of Delphi. The analysis was based on indoor hourly temperature and relative humidity data from August 2022 to October 2024, combined with outdoor observational and ERA5-Land reanalysis data. Random Forest, Gradient Boosting and Support Vector Regression models were developed for 48 and 72 h forecast horizons. The RMSE, MAE, and R² methods were used to perform the model, while interpretability techniques, including Permutation Importance analysis and SHAP analysis, were also applied. The models successfully predicted indoor temperature with high accuracy, and the Gradient Boosting model demonstrated superior performance across all forecast horizons. Relative humidity proved to be more complex, with all models showing limited predictive skill. Overall, the findings highlight that temperature prediction depends on the building’s thermal inertia and historical values, while relative humidity is more sensitive to external and seasonal influences. Finally, this study demonstrates the potential of machine learning methods for forecasting microclimatic conditions in museum environments. Full article

This research explores how a multifunctional and multi-experience music institution can thrive in the 21st century. It takes the case of the House of Music Hungary that has evolved into a cultural hub over the recent years, equally appealing to locals, professionals, employees, and tourists. To lay the foundation of tying architecture and music together, this highly exploratory study used a holistic approach by discussing issues related to tangible and intangible heritage, heritage tourism, and music tradition. Data collection included official state statistics, on-site experiences, and interviews. Interviews with the architect of the project, a music historian, a musician, a cultural manager, and a tourism professional were analysed, applying interpretive phenomenological analysis. The result are presented in a kaleidoscopic framework comprising the core elements identified in the analysis. This paper contributes to the knowledge of developing heritage tourism through the interplay of architecture and music. It shows how they reinforce one another to generate complex experiences, while highlighting the importance of respecting local cultural, social and environmental circumstances. Its exploratory nature did not necessitate the inclusion of visitor interviews at this stage; however, investigating visitor satisfaction may be one of the new directions that scholars can embark on. Full article

Urban industrial heritage is increasingly embedded in urban regeneration, public space provision, and community governance, yet existing studies have insufficiently examined how heterogeneous publics perceive its value through everyday digital discourse. Taking the Guangzhou Iron and Steel Plant industrial heritage site (hereafter, the Guanggang industrial heritage site) as a case study, this study used user-generated content from Rednote posts and local WeChat public-account comments to identify platform-mediated expressions of public value perception. A corpus of 745 valid samples comprising 51,459 Chinese characters was constructed after data collection, screening, and text preprocessing. Word-frequency analysis, semantic network analysis, and sentiment analysis were conducted using ROST CM 6.0. The results show that the two retrieved platform-contextual corpora foregrounded different concerns. Rednote discourse foregrounded ruin landscapes, industrial aesthetics, photography-based check-ins, and exploratory experiences, whereas WeChat comments emphasized park construction, public facilities, governance responsiveness, safety, and the residential environment. At the corpus level, lexicon-based sentiment classification indicated that Rednote texts were dominated by positive and neutral categories, while WeChat comments contained a higher proportion of texts classified as negative. This study conceptualizes dual foregrounding as a bounded selection process through which platform affordances, user self-selection, and users’ relationships with the site influence which concerns become visible in each corpus; it does not treat the observed differences as a causal platform effect. It argues that industrial heritage regeneration must translate historical, technological, and aesthetic values into public values that are interpretable, accessible, usable, and trusted by local communities. Full article

Digital twins have become a central paradigm for cultural heritage documentation, monitoring, and preventive preservation. Yet, when cultural heritage systems promise prediction, simulation, intervention planning, and decision support, a more explicit account is needed of the computational commitments behind such claims. This position paper proposes the notion of the heritage world model as a conceptual and architectural abstraction that uses the semantic digital twin as its representational layer and extends it toward prediction, memory, uncertainty-aware reasoning, and intervention evaluation. We define a heritage world model as a structured, temporally updated, semantically grounded, and action-aware model of a heritage asset and its preservation environment, capable of integrating observations, estimating latent risk states, predicting plausible future trajectories, and evaluating interventions under uncertainty. The paper does not present a validated deployed system. Rather, it clarifies the architectural conditions under which a decision-support digital twin infrastructure could support the kind of world-model-like preservation system proposed here. It further argues that such a model becomes operationally meaningful only when it includes a human-supervised controller layer that maps semantic state, predicted risk trajectories, uncertainty, memory, and institutional constraints into preservation-relevant actions, alerts, monitoring adaptations, or requests for expert review. Sensor data, remote sensing, computational models, risk assessments, policies, and conservation actions are interpreted as possible observational, dynamic, and intervention layers of a heritage world model. The paper reviews adjacent work in heritage digital twins, semantic and reactive ontologies, risk-aware preservation, agentic AI, and modern AI world models, and proposes a research agenda for moving toward predictive, memory-bearing, and intervention-aware preservation intelligence. Full article

Acoustic survey provides a measurement-based approach for investigating heritage spaces in which architectural morphology, environmental conditions, and sound-related practices are physically interrelated. This study applies a portable and non-invasive survey protocol to the medieval cave sanctuary of San Michele di Mezzo, located in Fisciano, Southern Italy. The site consists of stratified natural and built spaces, including a lower cave, an upper cave, and a later upper church, and represents a relevant case study for assessing the acoustic behaviour of small, irregular, and fragile cultural heritage environments. The experimental procedure combined calibrated microphone recordings, time-domain signal inspection, third-octave-band analysis, and impulse-response-derived room-acoustic indicators, including reverberation, clarity, and definition parameters. Under the adopted source–receiver configurations, the results show acoustic differentiation among the lower cave, upper cave, and later church. The caves exhibit shorter decay times than the church over most frequency bands, while clarity and definition indicators reveal a frequency-dependent behaviour that does not support a general claim of the acoustic superiority of one space over another. Comparative data from other cave and cave-like environments further contextualize the measured response of San Michele di Mezzo. The findings do not imply intentional acoustic design; rather, in the measured configuration, they show that, under the chosen conditions, the long-lasting devotional centrality of the lower cave is compatible with an acoustic response that does not contradict spoken or sung devotional use. More broadly, the study contributes to applied acoustics by demonstrating that low-invasive field surveys can provide reproducible acoustic indicators for heritage interpretation, conservation-oriented documentation, and the investigation of intangible sound-related dimensions of cultural heritage. Full article