Search Results (101)

Landscape observatories have gained increasing relevance as socio-ecological observation systems aimed at monitoring, analysing and communicating landscape transformations and landscape evolution, although the field remains characterised by conceptual fragmentation and the absence of systematised international inventories. This study addresses this gap through the development and analysis of a curated inventory of 113 landscape observatories and related initiatives, constructed from a systematic web-based search and an explicit process of data screening and coding. The research examines the territorial distribution, temporal evolution, declared objectives, methodologies, operational scales and temporal continuity of the identified initiatives through descriptive and interpretative analyses supported by the existing literature, including the role of remote sensing, spatial analysis and repeat photography. The results reveal a strong European predominance, particularly in France, and a marked concentration of initiatives operating at regional scales, temporally associated with the implementation of the European Landscape Convention. The dated subset suggests a marked expansion after 2000, although many initiatives lack explicit chronological information. The analysis also highlights substantial heterogeneity in functional orientations, distinguishing between observatories with continuous photographic monitoring, temporally limited observation systems, landscape study centres, documentary repositories and other initiatives with non-systematic uses of photography. Furthermore, the study identifies a recurrent gap between declared objectives and the explicit articulation of methodologies and temporal monitoring schemes. Overall, the paper proposes a typological synthesis of landscape observatories and related initiatives and discusses their potential role as hybrid socio-ecological monitoring systems for adaptive territorial governance. The results also highlight the need for clearer analytical frameworks and greater methodological transparency to facilitate comparison and strengthen their contribution to territorial knowledge and governance. Full article

This study evaluates the accuracy of various preprocessing methods applied to scanned archival aerial photographs for reconstructing historical terrain in the Czech Republic. Seven workflows were tested on identical imagery and control points, varying parameters such as resolution unification, brightness normalization, focal length calibration, and AI-based denoising. Accuracy was assessed using GNSS checkpoints and high-resolution LiDAR data. Results show that basic brightness correction reduced the vertical RMSE by 59% (to 5.69 m). In contrast, standalone AI preprocessing was associated with increased geometric instability (RMSE 16.48 m) due to over-smoothing and the loss of essential micro-texture. However, the evaluated “Fusion AI” workflow—combining AI enhancement with strict focal length constraints—successfully mitigated this degradation. By restricting the internal orientation, it stabilized the vertical accuracy at 6.48 m, closely matching the best traditional approaches. Statistical analysis revealed strong spatial autocorrelation and non-normal error distributions, highlighting the need for robust validation. Ultimately, this study confirms that AI can be effectively utilized to enhance visual clarity in data-scarce historical reconstruction without sacrificing spatial reliability, provided it is strictly geometrically constrained. This offers an optimal compromise and a tested, reproducible workflow that supports heritage preservation and long-term environmental analysis. Full article

In the 1930s and 1940s, Kumbum Monastery (Tibetan: sku’ bum byams pa gling) emerged as a significant spatial node in visual culture during the period of war and modern nation-building in the Republic of China (1912–1949). Through photography, painting, and film, a diverse range of visual media depicted the monastery’s architectural layout, inscribed plaques and steles, Cham dance (Tibetan: འཆམ་, Wylie: ’cham) rituals, lamaic prayers, and scenes of temple fairs and marketplaces. These visual representations not only documented historical detail but also constructed a composite space in which sacredness, transcendence, and secularity intersected. Due to its unique geographical location, religious doctrines, historical narratives, and political entanglements, Kumbum functioned as both a spiritual center and a politically charged symbol. Within this visual discourse, cham rituals and collective prayers were imbued with wartime ideological meanings, aligning religious transcendence with the national aspiration for resistance and victory. The inscribed plaques by state officials visually asserted political authority over sacred religious spaces, while the depiction of temple fairs foregrounded the entanglement of religious practices with everyday secular life, becoming key arenas for ethnic integration and political mobilization. Artists and photographers actively engaged with and reproduced both the symbolic and the quotidian landscapes of the monastery. These visual materials contributed to the broader project of narrating the Republic’s frontier and constructing the nation’s image. By examining how both monastic actors and external observers visually constructed Kumbum Monastery’s political and spiritual space, this study illuminates the complex interplay between religion and state power, and shows how visual media articulated ideological meanings and negotiated spatial relationships as collective responses to the site within the conditions of modernity. 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

As public demand for health and well-being continues to rise, rural landscapes are increasingly valued as settings for stress reduction and psycho-physiological restoration. Drawing on five “Beautiful Villages” in Jiangning District, Nanjing (China), this study categorizes rural landscapes into three types—farmland production landscapes, rural settlement landscapes, and rural mountain–water landscapes—based on the proportional dominance of key landscape elements. Audio-visual stimuli were developed from on-site photography and field recordings to construct controlled rural audio-visual environments. Using a combination of physiological indicators and self-reported psychological assessments, we systematically compare restorative responses across modalities (visual, auditory, and audio-visual) and across landscape types, and examine how specific landscape elements relate to restorative outcomes. Results show that (1) auditory stimuli generally produce stronger restorative responses than visual stimuli, and audio-visual interactions are evident; (2) restorative benefits vary significantly across the three rural landscape types; and (3) visually natural and structurally rich elements are associated with greater restoration, while auditory cues can direct visual attention and natural sounds are positively linked to restorative outcomes. These findings advance understanding of multi-sensory restorative processes in rural landscapes and provide evidence for sustainable rural landscape planning and design by supporting healthier, more restorative, and more human-centered rural environments. Full article

In road planning and landscape design, data collection emphasizes existing site conditions, particularly in projects involving modifications rather than new construction, as such data directly inform subsequent planning decisions. Beyond conventional surveying techniques, large-scale street-region digital elevation models can be generated using aerial imagery acquired from unmanned aerial vehicles. The point clouds derived from these aerial photographs provide a basis for constructing spatial models applicable to street landscape and road planning. In this study, aerial data were processed using Pix4D software 4.8.4 to generate the initial spatial model, which was subsequently integrated into a building information modeling-based design framework in Autodesk Revit 2022. This approach enabled rapid and precise design outputs, while the resulting BIM model was further applied to mapping applications to establish a foundational database for regional public works. Full article

Overwintering peat fires are increasingly reported in the boreal regions, where they persist underground through winter and reignite in spring, intensifying greenhouse gas emissions and landscape degradation. This study investigates the conditions that enable peat fires to survive freezing and snow cover, and presents practical methods for their winter detection and suppression. We combined satellite data, UAV-based thermal imaging, time-lapse photography, and ground measurements of temperature, groundwater depth, and peat moisture to identify active overwintering hotspots. Our results show that these fires persist primarily where groundwater levels remain below 60 cm, particularly under tree roots, compacted soil, or elevated terrain that limits moisture recharge. UAV thermal imaging proved the most reliable detection tool, identifying 98% of hotspots. We developed and successfully applied a winter extinguishing method that involves mechanical disruption and dispersion of smoldering peat over frozen ground, allowing rapid cooling without re-ignition. These findings clarify the mechanisms sustaining overwintering fires and provide an effective approach for their mitigation, contributing to reduced emissions and improved management of boreal peatlands vulnerable to climate change. Full article

Indigenous cultures in Taiwan embody rich ecological knowledge and strong environmental conservation values. However, elementary and secondary education often provides limited exposure to these cultures due to geographic constraints and insufficient instructional resources, relying primarily on textbooks and teacher-centered teaching methods. Such approaches restrict experiential learning, which may diminish students’ motivation and depth of understanding. However, 360-degree virtual reality (VR360) enables immersive simulations of authentic environments, increasing the accessibility of cultural and ecological education through smartphones and low-cost Google Cardboard. In addition, drone technology enhances learning by offering multiple perspectives for environmental exploration and data collection. This study examines the effectiveness of integrating a VR360 and virtual drone system into instruction focused on the ecological context of Sun Moon Lake and Thao Indigenous culture. Learning outcomes for Indigenous and non-Indigenous students were compared in terms of learning effectiveness, motivation, cognitive load, and technology acceptance. Ecological and cultural materials were collected through field investigations and drone photography, enabling students to explore landscapes from a first-person perspective and engage with Thao cultural practices and their relationship with local ecology. The findings indicate that the proposed VR-based system significantly enhances learning experiences and demonstrates strong potential for cultural and ecological education, offering valuable guidance for the design of future immersive instructional strategies and learning materials related to Indigenous cultures. Full article

With the ongoing advancement of urbanization, the renewal of old urban areas has emerged as a central front in enhancing urban quality, with street space improvement playing a pivotal role in advancing sustainable urban development. This study focuses on Chengdu, a highly urbanized megacity, employing a combination of multi-point continuous street view photography, spatial mapping, and landscape design interventions to systematically examine human activity patterns, commercial dynamics, and pathways for spatial optimization along the street-facing interfaces of old residential neighborhoods and their adjacent urban streets. The findings reveal that: (1) commercializing the street-facing façades enhances local employment opportunities; (2) window-type fences demonstrate superior adaptability by effectively balancing commercial accessibility with resident safety; and (3) a diverse mix of commercial types sustains the vitality of street-level economies in these areas. These results not only offer actionable spatial strategies for the renovation of old residential zones in Chengdu but also contribute transferable insights for urban regeneration efforts globally. Full article

Ocular Toxoplasmosis (OT), a leading cause of infectious posterior uveitis, presents significant diagnostic challenges in atypical cases due to phenotypic overlap with other retinochoroiditides and a reliance on expert interpretation of multimodal imaging. This scoping review systematically maps the burgeoning application of artificial intelligence (AI), particularly deep learning, in automating OT diagnosis. We synthesized 22 studies to characterize the current evidence, data landscape, and clinical translation readiness. Findings reveal a field in its nascent yet rapidly accelerating phase, dominated by convolutional neural networks (CNNs) applied to fundus photography for binary classification tasks, often reporting high accuracy (87–99.2%). However, development is critically constrained by small, imbalanced, single-center datasets, a near-universal lack of external validation, and insufficient explainable AI (XAI), creating a significant gap between technical promise and clinical utility. While AI demonstrates strong potential to standardize diagnosis and reduce subjectivity, its path to integration is hampered by over-reliance on internal validation, the “black box” nature of models, and an absence of implementation strategies. Future progress hinges on collaborative multi-center data curation, mandatory external and prospective validation, the integration of XAI for transparency, and a focused shift towards developing AI tools that assist in the complex differential diagnosis of posterior uveitis, ultimately bridging the translational chasm to clinical practice. Full article

This article emerges from a researcher-generated longitudinal photography project conducted between 2016 and 2025 situated on the redundant site of the former Middleton Tuberculosis Hospital in North Yorkshire. The research project explored the site’s transformation through an unmanaged rewilding in the context of surrounding dairy farms within the Nidderdale ‘area of outstanding natural beauty’. The hospital site is reimagined as a bucolic ‘island’ stranded in the ideological socio-cultural notions embedded in “Nature”, the countryside, and agricultural landscape under increasing pressure to value biodiversity and nature’s restoration. Employing a reflexive lyrical critical lens informed by ‘resonance theory’, social semiotics, and expressive visual sociological practice, the article contributes to the debates surrounding landscape valorization, the contestation of the ‘countryside’ as a working, and recreational landscape. Researcher-generated photographic practice captures the duration of iterative site visits, the seasonal atmosphere and potential experience of resonance of the site, providing vivid sources for reflections, meaning-making, while proselytizing the axiom of Kress, that: ‘without frame no meaning’. The key research questions are: (1) Why is researcher-generated photography, amid AI image production, an effective epistemological method for re-presenting and understanding the significance of unmanaged landscape rewilding? (2) How do photographic re-presentations and lyrical reflexivity convey the lived resonance of being in places like the Middleton Hospital site? The text rejects illustrative photographic use in academic discourse, favoring an expressive, allusive, and lyrical interpretation of rewilding’s socio-cultural value. Full article

The federally threatened Puritan tiger beetle (Ellipsoptera puritana; PTB) inhabits Upper Chesapeake Bay bluffs, beaches and Connecticut River point bars. This study focuses on Maryland’s Chesapeake Bay population (Calvert County and Sassafras River), where adult PTBs prey on beach arthropods but establish larval habitat on the adjacent bluffs. A combination of panoramic photography, GIS mapping, and field and laboratory measurements of sedimentological and ecological characteristics were measured across 17 high- and low-density Maryland beetle sites to identify the geologic and biological controls on population distribution and abundance. Results indicate that temporal and spatial fluctuations in PTB abundance are governed by bluff face quality, which in turn, is shaped by antecedent geology (medium-compacted, fine-to-medium, well-sorted sands) and bluff dynamics. We present a four-stage, multi-decadal geomorphodynamic conceptual model in which long-term bluff recession and short-term storm-driven colluvium removal periodically expose fresh bluff surfaces required for larval establishment. By integrating geomorphic, geologic, and ecological perspectives, this study highlights the role of sedimentary processes in maintaining critical estuarine habitats and provides a framework for predicting species persistence in dynamic coastal landscapes. Full article

This research presents a comprehensive analysis of the spatial extent and temporal change in benthic habitats within the Puck Lagoon in the southern Baltic Sea, utilizing integrated machine learning classification and multi-sourced remote sensing. Object-based image analysis was integrated with Random Forest, Support Vector Machine, and K-Nearest Neighbors algorithms for benthic habitat classification based on airborne bathymetric LiDAR (ALB), multibeam echosounder (MBES), satellite bathymetry, and high-resolution aerial photography. Ground-truth data collected by 2023 field surveys were supplemented with long temporal datasets (2010–2023) for seagrass meadow analysis. Boruta feature selection showed that geomorphometric variables (aspect, slope, and terrain ruggedness index) and optical features (ALB intensity and spectral bands) were the most significant discriminators in each classification case. Binary classification models were more effective (93.3% accuracy in the presence/absence of Zostera marina) compared to advanced multi-class models (43.3% for EUNIS Level 4/5), which identified the inherent equilibrium between ecological complexity and map validity. Change detection between contemporary and 1957 habitat data revealed extensive Zostera marina loss, with 84.1–99.0% cover reduction across modeling frameworks. Seagrass coverage declined from 61.15% of the study area to just 9.70% or 0.63%, depending on the model. Seasonal mismatch may inflate loss estimates by 5–15%, but even adjusted values (70–94%) indicate severe ecosystem degradation. Spatial exchange components exhibited patterns of habitat change, whereas net losses in total were many orders of magnitude larger than any redistribution in space. These findings recorded the most severe seagrass habitat destruction ever described within Baltic Sea ecosystems and emphasize the imperative for conservation action at the landscape level. The methodology framework provides a reproducible model for analogous change detection analysis in shallow nearshore habitats, creating critical baselines to inform restoration planning and biodiversity conservation activities. It also demonstrated both the capabilities and limitations of automatic techniques for habitat monitoring. Full article

This study introduces the Historic Urban Landscape (HUL) approach into a rural setting and conducts a case study of Huaqiu Village. By integrating spatial analysis techniques, unmanned vehicle aerial photography, field surveys, and multitemporal data from 2000 to 2023, this study analyzed the heritage value of traditional villages and explored a rural-adaptable pathway for HUL implementation. Findings showed: 1. Based on the temporal and spatial evaluation analysis logic of landscapes under the HUL framework, spatial patterns of the village, such as vegetation growth and reduced in water bodies, have been quantitatively identified, revealing the interaction patterns of a complex ecosystem. 2. Following HUL’s holistic understanding of heritage value, the three-dimensional value characteristics of the village (landscape, function, and spirit) are clarified. 3. By implementing the community participation mechanism of HUL, through villager-led inheritance of intangible cultural heritage and joint formulation of conservation conventions, the living continuity of heritage has been realized. The HUL approach shows remarkable adaptability, with prominent achievements in dynamic-layered protection and community participation. This study breaks through the urban bias of the HUL approach, enriches understanding of rural heritage, and provides a practical paradigm for promoting sustainable development of similar villages. Full article

The study of historical monuments within both architectural and literary frameworks reveals a dynamic interplay between scientific observation and artistic interpretation—a vital characteristic of travel writing/the travelogue. This approach, exemplified by British traveler and writer Henry Finnis Blosse Lynch (1862–1913), reflects how factual detail and creative representation are seamlessly integrated in depictions of sites, landscapes, and cultural scenes. This case study highlights Lynch as a pioneering explorer who authored the first comprehensive volume on Armenian architecture and as a writer who vividly portrayed Armenian monuments through both verbal description and photographic imagery, becoming the first traveler to document such sites using photography. Additionally, this paper emphasizes the significance of Lynch’s detailed accounts of architectural monuments, churches, monasteries, cities, villages, populations, religious communities, and educational institutions in vivid language. The careful study of his work can contribute meaningfully to the investigation of the travelogue as a literary genre and to the preservation and protection of the architectural heritage of historical and contemporary Armenia, particularly in regions facing cultural or political threats. Full article