Search Results (1,282)

Coastal erosion poses an acute threat to cultural heritage resources, particularly in island contexts where erosional and degradational threats can be amplified by increased exposure and sea-level changes. We present a generalizable, best-practice approach that integrates multi-temporal, multi-resolution, and inconsistently ground-controlled data to demonstrate how suites of remotely sensed data can be integrated under real-world constraints. This approach is used to conduct a longitudinal analysis of cultural resources on the island of Inishark, Western Ireland. Results show evidence of significant and potentially accelerating shoreline erosion and structural loss within the past century, with rates of erosion ranging from 0.15 to 0.3 m/year along shorelines and 3–5 m²/year for structures. Outcomes demonstrate the utility and importance of an integrative data approach for cultural resource management. Full article

The present study analyzes individual differences in the facilitative processing of grammatical gender by heritage speakers of Spanish, asking whether these differences correlate with lexical proficiency. Results from an eye-tracking study in the Visual World Paradigm replicate prior findings that, as a group, heritage speakers of Spanish show facilitative processing of gender. Importantly, in a follow-up within-group analysis, we test whether three measures of lexical proficiency—oral picture-naming, verbal fluency, and LexTALE—predict individual performance. We find that lexical proficiency, as measured by LexTALE, predicts overall word recognition; however, we observe no effects of the other measures and no evidence that lexical proficiency modulates the strength of the facilitative effect. Our results highlight the importance of carefully selecting tools for proficiency assessment in experimental studies involving heritage speakers, underscoring that the absence of evidence for an effect of proficiency based on a single measure should not be taken as evidence of absence. Full article

This study analyzes the durability of brick-faced clay-core walls (BCWs) in the traditional residential architecture of Quanzhou—a UNESCO World Heritage City. Taking the northern gable of Ding Gongchen’s former residence as an example, the mechanical properties, microscopic structure, and changes in chemical symbol, oxides and minerals of the red bricks and clay-cores were analyzed using finite element mechanics analysis (FEM), scanning electron microscopy (SEM), X-ray fluorescence (XRF), and X-ray diffraction (XRD). The results indicate a triple mechanism: (1) The collaborative protection and reinforcement mechanism of “brick-wrapped-clay”. (2) The infiltration and destruction mechanism of external pollutants. (3) The material stability mechanism of silicate minerals. Therefore, the key to maintaining the durability of BCWs lies in the synergistic effect of brick and clay materials and the stability of silicate mineral materials, providing theoretical and methodological support for sustainable research into brick and clay constructions. Full article

This study investigated the nuanced influence of urban morphology on the thermal performance of nine mass housing blocks (21–26, 28–30) in New Belgrade’s Central Zone. These blocks, showcasing diverse structures, provided a robust basis for evaluating the design parameters. ENVI-met simulations were used to assess two scenarios: an “asphalt-only” environment, isolating the urban structure’s impact, and a “real-world” scenario, including green infrastructure (GI). Overall, the findings emphasize that while GI offers mitigation, the inherent urban built structure fundamentally determines thermal outcomes. An urban block’s thermal performance, it turns out, is a complex interplay between morphological factors and local climate. Crucially, simple metrics like Green Area Percentage (GAP) and Building Coverage Ratio (BCR) proved unreliable predictors of thermal performance. This highlights the critical need for urban planning regulations to evolve beyond basic surface indicators and embrace sophisticated, context-sensitive design principles for effective heat mitigation. Optimal performance arises from morphologies that actively manage heat accumulation and facilitate its dissipation, a characteristic exemplified by Block 22’s integrated design. However, even the best-performing Block 22 remains warmer compared to denser central areas, suggesting that urban densification can be a strategy for heat mitigation. Given New Belgrade’s blocks are protected heritage, targeted GI reinforcements remain the only viable approach for improving the outdoor thermal comfort. Full article

Elaeocarpus sylvestris (Lour.) Poir. var. ellipticus (Thunb.) H.Hara, an evergreen tree species native to Jeju Island, South Korea, has experienced a progressive decline associated with phytoplasma infection. This study aimed to evaluate the efficacy of oxytetracycline-based tree injection for suppressing phytoplasma and improving tree vitality. Two formulations—oxytetracycline hydrochloride (4.3%) and oxytetracycline calcium alkyltrimethyl ammonium (17%)—were administered to 40 infected individuals across two sites using a gravity-fed injection system. Treatment efficacy was evaluated based on chlorophyll content as an indicator of physiological recovery, while phytoplasma presence was assessed by PCR at 150 days after injection. The oxytetracycline hydrochloride group showed the highest suppression, with a 70% phytoplasma non-detection rate as determined by PCR analysis. Treated trees exhibited significantly higher chlorophyll content compared to untreated infected controls. These findings suggest that minimally invasive tree injection using oxytetracycline can provide temporary suppression of phytoplasma and support physiological recovery in E. sylvestris. Full article

Lion Grove was established in 1342 during the Yuan Dynasty and is one of the four most famous classical gardens in China. It was recognized as a UNESCO World Heritage Site in 2000. Although Lion Grove is now regarded as a private garden representing the culture of Confucian scholars, it was originally a Chan Buddhist garden during its inception in the Yuan Dynasty. This study examines the natural landscapes of Lion Grove at its inception, focusing on four main aspects: the philosophy of nature, planning intent, creators, and the philosophical ideas they represent. Key findings include the following: Firstly, Lion Grove’s attitude towards nature is rooted in China’s indigenous culture, making it both a physical expression of Chan philosophy and a space reflecting the scholar–bureaucrats’ vision of an ideal landscape. Secondly, from the perspective of landscape planning, the Lion Grove of the Yuan Dynasty placed greater emphasis on natural elements compared to its modern counterpart, with rock landscapes serving as the core element throughout the garden. Thirdly, hermitic philosophy emerged as a significant cultural theme alongside Chan Buddhism during the Yuan Dynasty. Fourthly, the landscape elements of Lion Grove symbolize Chan Buddhist wisdom and the hermit’s idealism, with poetry playing a key role in conveying these cultural ideals, preserving the site’s early philosophical significance. Full article

The impact of soundscapes in religious architecture on public psychology has garnered increasing attention in both research and policy domains. However, the mechanisms by which temple soundscapes influence public emotions remain scientifically unclear. This paper aims to explore how soundscapes in temple architectures designated as World Natural and Cultural Heritage sites affect visitors’ experiences. Considering visitors with diverse social and demographic backgrounds, the research design includes subjective soundscape evaluations and EEG measurements from 193 visitors at two World Heritage temples. The results indicate that visitors’ religious beliefs primarily affect their soundscape perception, while their soundscape preferences show specific correlations with chanting and human voices. Furthermore, compared to males, females exhibit greater sensitivity to emotional variations induced by soundscape experiences. Urban architects can enhance visitors’ positive emotional experiences by integrating soundscape design into the planning of future religious architectures, thereby creating pleasant acoustic environments. Full article

With good reason, Vatican II encourages the Eastern ecclesial realities to preserve and, if necessary, to rediscover their own traditions (also, even if not only, for ecumenical reasons). There are, however, certain aspects of the heritage of the Eastern Churches that require urgent revision in a spirit of consistency with the teachings of the Council. This is undoubtedly the case with regard to the anti-Jewish elements so specific to the entire Christian tradition (more or less generalised insults and judgments; substitutionary and appropriative perspectives; a purely instrumental use of the Jewish scriptures) and, in the absence of full reception of the Council, still reflected in the public prayers of the Romanian Greek-Catholic Church, to the detriment of that spirit of respect, fraternity, and dialogue theoretically embraced throughout the Catholic world today. In the light of Nostra aetate §4 and the subsequent developments that flowed from it, I shall try in this contribution to outline some possible criteria for reforming the offices of Holy Week, aiming to show that—at least in this particular case—it is not enough merely to refer to the OE, let alone to use it to justify a comfortable tendency towards inertia. Apart from the fact that it is this very Decree that speaks of a possible and necessary organic progress, we cannot ignore the more general spirit of renewal of the Council and its other documents (the NA, the SC, the DV, the GS). The challenge would be to engender a creative fidelity, which—while preserving the best of tradition—surpasses certain of its contingent elements. Full article

Modern heritage (MH) is a key component of our built environment; however, it currently lacks widespread recognition and a clear, universally accepted definition, placing it in an emerging phase. This category of heritage, understood within the context of modernisation processes and the changes characteristic of the late modern period, remains underrepresented and warrants further study. The objective of this article is to fill the identified research gap, thereby fostering awareness of MH, improving its accessibility and enhancing its visibility and appreciation. It offers a diagnostic analysis of the corpus on MH through the design and development of a concrete methodology, which is transferable to the other heritage categories. This study reveals insights into the present understanding of the term ‘Modern Heritage’ and its relevance within an international framework. This understanding prompts a reflection on the terminology used to describe this concept, which serves not only as a significant result in itself but also as a foundation for future research. Despite the close association of modern heritage with the 20th century, this research identifies a cross-cutting nature that needs to be recognised, encompassing a wide range of periods, themes and typologies in this category. Full article

Designing optimal heritage tourism routes in secondary cities involves complex trade-offs between cultural richness, travel time, carbon emissions, spatial coherence, and group satisfaction. This study addresses the Personalized Group Trip Design Problem (PGTDP) under real-world constraints by proposing DRL–IMVO–GAN—a hybrid multi-objective optimization framework that integrates Deep Reinforcement Learning (DRL) for policy-guided initialization, an Improved Multiverse Optimizer (IMVO) for global search, and a Generative Adversarial Network (GAN) for local refinement and solution diversity. The model operates within a digital twin of Warin Chamrap’s old town, leveraging 92 POIs, congestion heatmaps, and behaviorally clustered tourist profiles. The proposed method was benchmarked against seven state-of-the-art techniques, including PSO + DRL, Genetic Algorithm with Multi-Neighborhood Search (Genetic + MNS), Dual-ACO, ALNS-ASP, and others. Results demonstrate that DRL–IMVO–GAN consistently dominates across key metrics. Under equal-objective weighting, it attained the highest heritage score (74.2), shortest travel time (21.3 min), and top satisfaction score (17.5 out of 18), along with the highest hypervolume (0.85) and Pareto Coverage Ratio (0.95). Beyond performance, the framework exhibits strong generalization in zero- and few-shot scenarios, adapting to unseen POIs, modified constraints, and new user profiles without retraining. These findings underscore the method’s robustness, behavioral coherence, and interpretability—positioning it as a scalable, intelligent decision-support tool for sustainable and user-centered cultural tourism planning in secondary cities. Full article

Historic cities across the globe have experienced profound changes in their spatial and functional characteristics over time, and the historic core of Patan, Nepal, is no exception. The area surrounding Patan Durbar Square was designated as a UNESCO World Heritage Site in 1979. Between 2003 and 2007, the Kathmandu Valley was placed on UNESCO’s List of World Heritage in Danger, largely due to various factors, including the rapid and unsympathetic transformation of its buffer zone. This study focuses on the Nagbahal neighborhood, a culturally significant locality within this buffer area, to explore a community-rooted and sustainable approach to conservation. Employing a mixed-methods research design, the study integrates qualitative and quantitative data gathered through interviews and surveys of native residents. It investigates the drivers and impacts of changes in the function, ownership, and physical form of traditional residential buildings, and assesses whether these changes align with principles of sustainable heritage conservation—social, cultural, economic, and environmental. While challenges persist, including the proliferation of reinforced concrete structures and limited enforcement of heritage policies, the findings reveal that Nagbahal remains resilient due to strong local traditions, active religious institutions, and cohesive social practices. The study offers transferable lessons for sustainable conservation in living heritage buffer zones globally. Full article

During the long-term preservation of murals, the degradation of mural image information poses significant challenges to the restoration and conservation of world cultural heritage. Currently, mural conservation scholars focus on image segmentation techniques for mural restoration and protection. However, existing image segmentation methods suffer from suboptimal segmentation quality. To improve mural image segmentation, this study proposes an efficient mural image segmentation method termed Adaptive Nonlinear Bernstein-guided Parrot Optimizer (ANBPO) by integrating an adaptive learning strategy, a nonlinear factor, and a third-order Bernstein-guided strategy into the Parrot Optimizer (PO). In ANBPO, First, to address PO’s limited global exploration capability, the adaptive learning strategy is introduced. By considering individual information disparities and learning behaviors, this strategy effectively enhances the algorithm’s global exploration, enabling a thorough search of the solution space. Second, to mitigate the imbalance between PO’s global exploration and local exploitation phases, the nonlinear factor is proposed. Leveraging its adaptability and nonlinear curve characteristics, this factor improves the algorithm’s ability to escape local optimal segmentation thresholds. Finally, to overcome PO’s inadequate local exploitation capability, the third-order Bernstein-guided strategy is introduced. By incorporating the weighted properties of third-order Bernstein polynomials, this strategy comprehensively evaluates individuals with diverse characteristics, thereby enhancing the precision of mural image segmentation. ANBPO was applied to segment twelve mural images. The results demonstrate that, compared to competing algorithms, ANBPO achieves a 91.6% win rate in fitness function values while outperforming them by 67.6%, 69.4%, and 69.7% in PSNR, SSIM, and FSIM metrics, respectively. These results confirm that the ANBPO algorithm can effectively segment mural images while preserving the original feature information. Thus, it can be regarded as an efficient mural image segmentation algorithm. Full article

Groundwater level monitoring is crucial for assessing hydrological responses to climate change and human activities, which pose significant threats to the sustainability of semi-arid aquifers and the cultural heritage they sustain. This study presents an integrated remote sensing and transformer-based deep learning framework that combines diverse geospatial datasets to predict spatiotemporal variations across the plain near the Persepolis and Naqsh-e Rustam archaeological complexes—UNESCO World Heritage Sites situated at the plain’s edge. We assemble 432 synthetic aperture radar (SAR) scenes (2015–2022) and derive vertical ground motion rates greater than −180 mm yr⁻¹, which are co-localized with multisource geoinformation, including hydrometeorological indices, biophysical parameters, and terrain attributes, to train transformer models with traditional deep learning methods. A sparse probabilistic transformer (ConvTransformer) trained on 95 gridded variables achieves an out-of-sample R² = 0.83 and RMSE = 6.15 m, outperforming bidirectional deep learning models by >40%. Scenario analysis indicates that, in the absence of intervention, subsidence may exceed 200 mm per year within a decade, threatening irreplaceable Achaemenid stone reliefs. Our results indicate that attention-based networks, when coupled to synergistic geodetic constraints, enable early-warning quantification of groundwater stress over heritage sites and provide a scalable template for sustainable aquifer governance worldwide. Full article

The TOWCHED project explores how arts and heritage-based educational methodologies can support sustainable development by enhancing key transversal competencies in learners, particularly children and youth. In response to the global challenges outlined in the sustainable development goals (SDGs), this project promotes inclusive and participatory approaches to education that foster social cohesion, intercultural understanding, and civic engagement. Partnering with museums, TOWCHED develops cross-curricular pedagogical interventions, such as experiential, blended, and collection-mediated learning, that link cultural heritage with contemporary social and environmental concerns. These approaches aim to strengthen creativity, critical thinking, collaboration, and self-awareness. TOWCHED demonstrates that heritage collection-based education can play a vital role in transforming schools and other learning environments into hubs for sustainable, lifelong learning. By embedding cultural expression and heritage into educational practices, the project offers a compelling model for empowering individuals to navigate and shape a more equitable and interconnected world. This paper has two aims. First, we introduce TOWCHED, an interdisciplinary project recently funded by the Horizon Europe program of the European Union to preserve and promote education for sustainability in the heritage context. Second, we introduce a set of tools related to the project. Full article

This study employs a deep learning-based object detection model, GoogleNet, to identify cracks in cultural heritage images. Subsequently, a semantic segmentation model, SegNet, is utilized to determine the location and extent of the cracks. To establish a scale ratio between image pixels and real-world dimensions, a parallel laser-based measurement approach is applied, enabling precise crack length calculations. The results indicate that the percentage error between crack lengths estimated using deep learning and those measured with a caliper is approximately 3%, demonstrating the feasibility and reliability of the proposed method. Additionally, the study examines the impact of iteration count, image quantity, and image category on the performance of GoogleNet and SegNet. While increasing the number of iterations significantly improves the models’ learning performance in the early stages, excessive iterations lead to overfitting. The optimal performance for GoogleNet was achieved at 75 iterations, whereas SegNet reached its best performance after 45,000 iterations. Similarly, while expanding the training dataset enhances model generalization, an excessive number of images may also contribute to overfitting. GoogleNet exhibited optimal performance with a training set of 66 images, while SegNet achieved the best segmentation accuracy when trained with 300 images. Furthermore, the study investigates the effect of different crack image categories by classifying datasets into four groups: general cracks, plain wall cracks, mottled wall cracks, and brick wall cracks. The findings reveal that training GoogleNet and SegNet with general crack images yielded the highest model performance, whereas training with a single crack category substantially reduced generalization capability. Full article