Search Results (388)

Biosphere Reserves (BRs), designated by UNESCO, are uniquely positioned to serve as model territories for sustainable development, as they aim to harmonize biodiversity conservation with the socio-economic vitality and cultural identity of local communities. This work examines the commitment of the Spanish Network of Biosphere Reserves to the United Nations 2030 Agenda and the Sustainable Development Goals (SDGs). Using a survey-based research design, this study assesses the extent to which the reserves have integrated the SDGs into their strategic frameworks and operational practices. It also identifies and analyses successful initiatives and best practices implemented across Spain that exemplify this integration. The findings highlight the need for enhanced awareness and understanding of the 2030 Agenda among stakeholders, alongside stronger mechanisms for participation, cooperation, and governance. The conclusion emphasises the importance of equipping all reserves with strategic planning tools and robust systems for monitoring, evaluation, and accountability. Moreover, the analysis of exemplary cases reveals the transformative potential of sustainability-oriented projects—not only in advancing environmental goals but also in revitalizing local economies and reinforcing cultural heritage. These insights contribute to a broader understanding of how BRs can act as dynamic laboratories for sustainable development and heritage preservation. Full article

Different monitoring approaches and techniques have been adopted to estimate and prevent soil erosion and its corresponding phenomena at cultural heritage sites. Remote sensing plays a crucial role in detecting and monitoring soil erosion events by providing a wealth of geospatial data and information that helps to better understand and respond to the mechanisms of soil erosion and mitigate or reduce its impacts. The main aims of this review are to (1) provide an overview of remote sensing methods, applications, and sensor types, (2) discuss the role of remote sensing in the estimation of soil erosion at cultural heritage sites, and (3) present a bibliometric analysis of soil erosion studies at cultural heritage sites covering the period from 1994 to 2025. The results of this study provide insights into the yearly scientific production, methods employed, topics, and trends in this field. This research offers valuable information for future research and the development and promotion of policies and strategies for the effective and sustainable management of cultural heritage sites. Full article

Structural cracks significantly threaten the safety and longevity of historical buildings, which are essential parts of cultural heritage. Conventional inspection techniques, which depend heavily on manual visual evaluations, tend to be inefficient and subjective. This research introduces an automated framework for crack and damage detection using advanced YOLO (You Only Look Once) models, aiming to improve both the accuracy and efficiency of monitoring heritage structures. A dataset comprising 2500 high-resolution images was gathered from historical buildings and categorized into four levels of damage: no damage, minor, moderate, and severe. Following preprocessing and data augmentation, a total of 5000 labeled images were utilized to train and evaluate four YOLO variants: YOLOv5, YOLOv8, YOLOv10, and YOLOv11. The models’ performances were measured using metrics such as precision, recall, mAP@50, mAP@50–95, as well as losses related to bounding box regression, classification, and distribution. Experimental findings reveal that YOLOv10 surpasses other models in multi-target detection and identifying minor damage, achieving higher localization accuracy and faster inference speeds. YOLOv8 and YOLOv11 demonstrate consistent performance and strong adaptability, whereas YOLOv5 converges rapidly but shows weaker validation results. Further testing confirms YOLOv10’s effectiveness across different structural components, including walls, beams, and ceilings. This study highlights the practicality of deep learning-based crack detection methods for preserving building heritage. Future advancements could include combining semantic segmentation networks (e.g., U-Net) with attention mechanisms to further refine detection accuracy in complex scenarios. 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

Three-dimensional (3D) reproduction of artworks has advanced significantly, offering valuable insights for conservation by documenting the objects’ conservative state at both macroscopic and microscopic scales. This paper presents the 3D survey of an earthquake-damaged panel painting, whose wooden support suffered severe deformation during a seismic event, posing unique restoration challenges. Our work focuses on quantifying how shape variations in the support—induced during restoration—affect the surface morphology of the pictorial layers. To this end, we conducted measurements before and after support consolidation using two complementary 3D techniques: structured-light projection to generate 3D models of the painting, tracking global shape changes in the panel, and laser-scanning microprofilometry to produce high-resolution models of localized areas, capturing surface morphology, superficial cracks, and pictorial detachments. By processing and cross-comparing 3D point cloud data from both techniques, we quantified shape variations and evaluated their impact on the pictorial layers. This approach demonstrates the utility of multi-scale 3D documentation in guiding complex restoration interventions. Full article

This article provides a concise overview of the existing tunnels located within the historic cultural heritage site of Gediminas Hill in Vilnius, with particular emphasis on the implications of a recently discovered tunnel. This newly identified tunnel is of particular interest due to its location beneath a retaining wall in close proximity to an adjacent structure. Long-term structural monitoring data indicate that the building has experienced displacement away from the retaining wall. Although the precise cause of this movement remains undetermined, the discovery of the tunnel adjacent to the structure has raised concerns regarding its potential role in the observed displacements. To investigate this hypothesis, a previously developed numerical model was employed to simulate the tunnel’s impact. The simulation results suggest that the tunnel’s construction was executed with careful consideration. During the excavation phase, the retaining wall exhibited displacements in a direction opposite to the expected ground pressure, indicating effective utilization of the wall’s gravitational mass. However, historical records indicate that no retaining structures were present in the area during the tunnel’s initial period of existence. Consequently, an additional simulation phase was introduced to model the behavior of the surrounding loose soil in the absence of retaining support. The results from this phase revealed that the deformations of the retaining wall and the adjacent building were elastically interdependent. The simulated deformation patterns closely matched the temporal trends observed in the monitoring data. These findings support the hypothesis that the tunnel’s construction may have contributed to the displacement of the nearby building. Full article

Enhancing and developing multicultural education is essential in today’s interconnected world, characterized by significant migration and refugee movements, as it serves as a fundamental element for effectively integrating migrant and refugee students within host nations. In Greece, which has long dealt with the challenge of integrating thousands of individuals fleeing conflict and disasters, there is a pressing need to evolve and modernize this educational approach. This qualitative study, based on semi-structured interviews with nine multicultural educators in Greece, seeks to explore how teachers foster a sense of belonging and inclusion in their diverse classrooms. Despite facing systemic challenges, the findings reveal that educators strive to highlight students’ cultural heritages through collaborative group activities that encourage trust, respect, and appreciation for diversity. Additionally, the research delves into how teachers cope with the psychological trauma often experienced by these students. Participants expressed that the inconsistent availability of specialists and monitoring for students dealing with severe psychological issues complicates their teaching efforts. Full article

Authenticity is a core principle in conservation guidelines and a key goal of heritage preservation, especially in Serbia, where many aging objects face ongoing deterioration. The subject of this study is the church within the Blagoveštenje Monastery complex in the Ovčar-Kablar gorge, built using stone from a local quarry at the beginning of the 17th century. The inclination of the structure, observed as progressively increasing over the centuries, raises important concerns regarding its stability. This research focuses on identifying the underlying causes of this phenomenon in order to support its long-term preservation. The methods used the study are long-term in situ observations including analysis, geodetic research, 3D laser imaging, geophysical, geological, archaeological research, evaluation of current condition, determination of structural failures and their cause and monitoring the structural behavior of elements. All methods were carried out in accordance with the definition of rehabilitation measures and the protection of masonry buildings. The main contribution of this study is identifying that the church’s inclination and deviation result from the northern foundation resting on weaker soil and a deeper rock mass compared to the southern side. The research approach and findings presented in this paper can serve as a guide for future endeavors aimed at identifying the causes of deformations and the restoration and structural rehabilitation of masonry buildings as cultural heritage. Full article

Agricultural terraces are critical landscape elements that promote sustainable rural development by enhancing water retention, mitigating soil erosion, and conserving cultural heritage. In northeastern Türkiye, particularly in the mountainous Erikli neighborhood of Uzundere, traditional terraces face growing threats due to land abandonment, topographic fragility, and socio–economic decline. This study applies a spatial–functional assessment framework that integrates UAV–based photogrammetry, GIS analysis, terrain modeling, and DBSCAN clustering to evaluate terrace conditions. UAVs provided high–resolution topographic data, which supported the delineation of terrace boundaries and morphometric classification using an adapted ALPTER model. A combined Terrace Density Index (TDI) and Functional Status Index (FSI) approach identified zones where terraces are structurally intact but functionally degraded. Results indicate that 76.4% of terraces fall within the meso and macro classes, yet 58% show partial or complete degradation. Cohesive terrace clusters are located near settlements, while isolated units in peripheral zones display higher vulnerability. This integrated approach demonstrates the analytical potential of drone–supported spatial diagnostics for monitoring landscape degradation. The method is scalable and adaptable to other terraced regions, offering practical tools for site–specific land use planning, heritage conservation, and resilience–based restoration strategies. Full article

Within museum depots, the largest part of all heritage collections is stored. Often, the preservation of highly sensitive objects is an ongoing challenge, as the materials are constantly subjected to and influenced by ever-present environmental factors—above all the surrounding climate and other physicochemical processes. Biological degradation is also a major risk for collections. Fungal infestation poses a particular threat, in many regions increasingly the result of climate change. Models for damage prediction and risk assessment are still underdeveloped and require a more substantial database. Approaching this need, nine museum depots and archives were selected in this study. Two years of monitoring the indoor microclimate with thermohygrometric sensors, investigating fungal abundance and diversity through culture-dependent and -independent (metagenomics) approaches, and the collection of relevant additional information resulted in a vast amount of diverse data. The main fungal genera identified through cultivation were Cladosporium, Penicillium, Aspergillus, Alternaria and Epicoccum. The cultivation-independent approach identified Aspergillus, Pyronema, Penicillium, Xenodidymella and Blumeria as the main taxa. Data analyses indicated that key drivers involved in similarities, patterns and differences between the locations were their geographic location, immediate outdoor surroundings and indoor (micro)climatic fluctuations. The study also sheds light on a possible shift in focus when developing strategies for preventing mold growth in collection depots beyond the prevailing path of tightest possible climate control. Full article

Bridges are fundamental components of transportation infrastructure, facilitating the efficient movement of people and goods. However, the conservation of heritage bridges introduces additional challenges, encompassing environmental, social, cultural, and economic dimensions of sustainability. This study investigates risk mitigation strategies for a heritage-listed, 120-year-old reinforced concrete bridge in Australia—one of the nation’s earliest examples of reinforced concrete construction, which remains operational today. The structure faces multiple risks, including passage of overweight vehicles, environmental degradation, progressive crack development due to traffic loading, and potential foundation scouring from an adjacent stream. Due to the heritage status and associated legal constraints, only non-invasive testing methods were employed. Ambient vibration testing was conducted to identify the bridge’s dynamic characteristics under normal traffic conditions, complemented by non-contact displacement monitoring using laser distance sensors. A digital twin structural model was subsequently developed and validated against field data. This model enabled the execution of various “what-if” simulations, including passage of overweight vehicles and loss of foundation due to scouring, providing quantitative assessments of potential risk scenarios. Drawing on insights gained from the case study, the article proposes a six-phase Incident Response Framework tailored for heritage bridge management. This comprehensive framework incorporates remote sensing technologies for incident detection, digital twin-based structural assessment, damage containment and mitigation protocols, recovery planning, and documentation to prevent recurrence—thus supporting the long-term preservation and functionality of heritage bridge assets. Full article

In the face of an unprecedented public health crisis (COVID-19), despite tourist perceptions toward cultural heritage tourism having undergone significant transformation, such transitions are increasingly viewed as opportunities to enhance sustainability practices in cultural heritage tourism worldwide. This study traces the evolution of tourist perceptions at Lijiang Old Town, a UNESCO World Heritage Site, across three stages from 2017 to 2024—before the pandemic, during the pandemic, and after the pandemic. Data were collected from major tourism platforms, yielding a comprehensive dataset of 50,022 user-generated reviews. We adopt a mixed-method framework integrating TF-IDF, Social Network Analysis (SNA), and Latent Dirichlet Allocation (LDA) to identify salient terms, semantic structures, and latent themes from large-scale unstructured textual data across time. The findings indicate that cultural heritage tourism demonstrates adaptability and resilience through significant perceptual transitions. After the pandemic, visitors increasingly prioritized cultural depth and high-quality service experiences, whereas before the pandemic, tourists focused more on cultural heritage attractions and commercial experiences. Moreover, during the pandemic period, visitor narratives reflected adaptations toward quieter, safer, and more personalized experiences, highlighting the impact of safety measures on tourism patterns. These findings demonstrate the methodological potential for dynamically monitoring perception shifts and offer empirical grounding for future perception-oriented research and sustainable cultural heritage destination management practices in cultural heritage tourism toward sustainable tourism. Full article

When discussing Cultural Heritage (CH), the risk of causing damage is inherently linked to the artifact itself due to several factors: age, perishable materials, manufacturing techniques, and, at times, inadequate preservation conditions or previous interventions. Thorough study and diagnostics are essential before any intervention, whether for preventive, routine maintenance or major restoration. Given the symbolic, socio-cultural, and economic value of CH artifacts, non-invasive (NI), non-destructive (ND), or As Low As Reasonably Achievable (ALARA) approaches—capable of delivering efficient and long-lasting results—are preferred whenever possible. Electromagnetic (EM) techniques are unrivaled in this context. Over the past 20 years, radiography, tomography, fluorescence, spectroscopy, and ionizing radiation have seen increasing and successful applications in CH monitoring and preservation. This has led to the frequent customization of standard instruments to meet specific diagnostic needs. Simultaneously, the integration of terahertz (THz) technology has emerged as a promising advancement, enhancing capabilities in artifact analysis. Furthermore, Artificial Intelligence (AI), particularly its subsets—Machine Learning (ML) and Deep Learning (DL)—is playing an increasingly vital role in data interpretation and in optimizing conservation strategies. This paper provides a comprehensive and practical review of the key achievements in the application of EM techniques to CH over the past two decades. It focuses on identifying established best practices, outlining emerging needs, and highlighting unresolved challenges, offering a forward-looking perspective for the future development and application of these technologies in preserving tangible cultural heritage for generations to come. Full article

Traditional fermented foods are appreciated worldwide for their cultural significance and health-promoting properties. However, traditional fermentation production suffers from many obstacles such as microbial variability, varying quality, and lack of scalability. The implementation of smart fermentation technologies, including biosensors, the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML), hold the key to the optimization of microbial process control, enhance product consistency, and improve production efficiency. This review summarizes modern developments in real-time microbial monitoring, IoT, AI, and ML tailored to traditional fermented foods. Despite significant technical advancements, challenges related to high costs, the absence of standardized frameworks, and access restrictions for small producers remain substantial limitations. This review proposed a future direction prioritizing modular, scalable solutions, open-source innovation, and environmental sustainability. In alignment with Sustainable Development Goal 9 (Industry, Innovation, and Infrastructure), smart fermentation technologies advance sustainable industry through innovation and serve as a critical bridge between traditional craftsmanship and Industry 4.0, fostering inclusive development while preserving microbial biodiversity and cultural heritage. Full article

With the accelerating pace of urbanization, historic districts are increasingly confronted with the dual challenge of coordinating heritage preservation and sustainable development. This study proposes an intelligent evaluation framework that integrates spatiotemporal street view imagery, affective perception modeling, and scene recognition to reveal the evolutionary dynamics of built environment spatial quality in historic districts. Empirical analysis based on multi-temporal data (2013–2020) from the Wudadao Historic District in Tianjin demonstrates that spatial quality is shaped by a complex interplay of factors, including planning and preservation policies, landscape greening, pedestrian-oriented design, infrastructure adequacy, and equitable resource allocation. These findings validate the framework’s effectiveness as a tool for monitoring urban sustainability. Moreover, it provides actionable insights for the development of resilient, equitable, and culturally vibrant built environments, effectively bridging the gap between technological innovation and sustainable governance in the context of historic districts. Full article