Identifying Landscape Character for Large Linear Heritage: A Case Study of the Ming Great Wall in Ji-Town, China

Zhao, Shuang; Yang, Diechuan; Chi, Gao

doi:10.3390/su15032615

Cited by 5 publications

(4 citation statements)

References 38 publications

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“…The variables included two levels: natural landscape and cultural heritage. The selection of the variables at the natural landscape level referred to the common indicators used in the landscape character assessment of the UK [38] and the landscape character assessment of mountainous regions in China [56,57,80]. The natural landscape level was defined by five raster datasets: land cover, elevation, relief amplitude, slope, and soil.…”

Section: Selection Of Variables and Establishment Of Databasementioning

confidence: 99%

Integrating Heritage and Environment: Characterization of Cultural Landscape in Beijing Great Wall Heritage Area

He,

Chen,

Zhang

2024

Land

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The Great Wall, as a globally important large-scale linear cultural heritage asset, is an example of the integration of architecture and landscape, demonstrating the interaction and feedback between heritage and the environment. In the context of advocating the holistic protection of cultural heritage and surroundings, this study utilizes landscape character assessment (LCA) to identify the landscape character of the Great Wall heritage area. Taking the heritage area of the Great Wall in Beijing, China, as an example, principal component analysis (PCA), two-step clustering, and the eCognition software were used to identify and describe the landscape character types, and the interaction mechanism between heritage and the environment was further explored through the reclassification process. A total of 20 landscape character types and 201 landscape character areas were identified in the study area, and a deep coupling relationship between heritage and the environment and cultural landscape spatial patterns were found in the core heritage area. The heritage and environmental character of linear heritage areas should be integrated so as to protect, manage, and plan cultural heritage areas at the landscape level. This study identifies and describes the character of the coupling of heritage and the environment in the Great Wall area for the first time, expands the types and methods of landscape character assessment, and carries out the exploration to combine natural and cultural elements of large-scale linear cultural heritage areas.

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Section: Selection Of Variables and Establishment Of Databasementioning

confidence: 99%

Integrating Heritage and Environment: Characterization of Cultural Landscape in Beijing Great Wall Heritage Area

He,

Chen,

Zhang

2024

Land

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“…However, interest in preservation of historical and cultural trails as opposed to urbanization and mass tourism has only emerged recently. While multiple similar quantitative method approaches have been conducted regarding the tourism value of linear CH in general [9][10][11][12][13], only a few works in the literature demonstrate their value and impact through extensive documentation and spatial analysis tools. The most common and longestablished technology used is the Geographic Information System (GIS).…”

Section: Literature Reviewmentioning

confidence: 99%

Geospatial Tool Development for the Management of Historical Hiking Trails—The Case of the Holy Site of Meteora

Potsiou

Ioannidis

Soile

et al. 2023

Land

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This paper presents a holistic guiding methodology for the development of a geospatial tool to be used for the documentation, planning, smart management and dissemination of a country’s network of historic hiking trails. To deal with the challenges and to ensure the sustainability of a historic site, geospatial documentation merging authoritative and crowdsourced data and a WebGIS-based spatial analysis is necessary. Geospatial data collection should include professional field surveys, professional and crowdsourced photographic documentation and video recording of the existing historic walking/hiking trails. A geodatabase, structured using relational model technology, including vector spatial entities (feature classes), mosaics (raster) and tabulated data (geodatabase tables), should be developed on a commercial or open platform; in this case, the ArcGIS Pro is used. Entities with embedded descriptive information and metadata for the technical, legal, historical, and administrative context may then be created. An object-oriented data model is needed to connect spatial and descriptive information. Spatial and descriptive queries or correlations between attribute fields of spatial entities must be enabled for specialized information retrieval by either experts or users. Next, a web GIS application to present the developed geodatabase in a visually appealing and informative way is created. It should integrate 2D maps with built-in tools and should support advanced functionalities, such as: (i) pop-ups that display brief information and images about specific spots along the trails; (ii) dynamic visualization of the vertical profile of each trail; (iii) multimedia information about landmarks, natural features and scenic viewpoints. Finally, the tool includes a feedback service and continuous efficiency monitoring and assessment, and enables adjustments, if and where needed. The tool is tested and used for 10 historical walking/hiking trails of the archaeological and Holy Site of Meteora, Central Greece. This is a UNESCO World Heritage site. The network, with a total length of 35 km, leads to six monasteries, still active since the 12th century, passing by gigantic rocks and beautiful natural landscapes. The site is famous globally and the greater area is continuously overcrowded with visitors. The tool is anticipated to be used for the documentation and management of the whole walking/hiking historic trail network of Greece in the future.

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“…The Great Wall of all dynasties in China has played a very important defensive role. In 1987, the Great Wall was listed as a world cultural heritage site by UNESCO (Zhao et al, 2023). The existence of the Great Wall was also a spiritual line of defense against invasion for ancient China.…”

mentioning

confidence: 99%

“…This damage must be detected and repaired in a timely manner to prevent further structural damage. The traditional methods of identifying damage faced by brick and stone buildings mainly include on-site artificial observation and instrumental analysis (Sowden, 1990;Flores-Colen et al, 2011;Hulimka et al, 2019;Han et al, 2022;Zhao et al, 2023). This work is carried out by experts (mostly experienced craftsmen or professional workers).…”

mentioning

confidence: 99%

Non-destructive testing research on the surface damage faced by the Shanhaiguan Great Wall based on machine learning

Li,

Zheng,

Chen

et al. 2023

Front. Earth Sci.

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The Shanhaiguan Great Wall is a section of the Great Wall of the Ming Dynasty, which is a UNESCO World Heritage Site. Both sides of its basic structure are composed of rammed earth and gray bricks. The surface gray bricks sustain damage from environmental factors, resulting in a decline in their structural quality and even a threat to their safety. Traditional surface damage detection methods rely primarily on manual identification or manual identification following unmanned aerial vehicle (UAV) aerial photography, which is labor-intensive. This paper applies the YOLOv4 machine learning model to the gray surface bricks of the Plain Great Wall of Shanhaiguan as an illustration. By slicing and labeling the photos, creating a training set, and then training the model, the proposed approach automatically detects four types of damage (chalking, plants, ubiquinol, and cracking) on the surface of the Great Wall. This eliminates the need to expend costly human resources for manual identification following aerial photography, thereby accelerating the work. Through research, it is found that 1) compared with manual detection, this method can quickly and efficiently monitor a large number of wall samples in a short period of time and improve the efficiency of brick wall detection in ancient buildings. 2) Compared with previous approaches, the accuracy of the current method is improved. The identifiable types are increased to include chalking and ubiquinol, and the accuracy rate increases by 0.17% (from 85.70% before to 85.87% now). 3) This method can quickly identify the damaged parts of the wall without damaging the appearance of the historical building structure, enabling timely repair measures.

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Identifying Landscape Character for Large Linear Heritage: A Case Study of the Ming Great Wall in Ji-Town, China

Cited by 5 publications

References 38 publications

Integrating Heritage and Environment: Characterization of Cultural Landscape in Beijing Great Wall Heritage Area

Integrating Heritage and Environment: Characterization of Cultural Landscape in Beijing Great Wall Heritage Area

Geospatial Tool Development for the Management of Historical Hiking Trails—The Case of the Holy Site of Meteora

Non-destructive testing research on the surface damage faced by the Shanhaiguan Great Wall based on machine learning

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