Author
Listed:
- Zhe Li
(Key Lab of Information Technology for Architectural Cultural Inheritance (Ministry of Cultural and Tourism), Tianjin 300072, China
School of Architecture, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin 300072, China)
- Mingshuai Li
(Key Lab of Information Technology for Architectural Cultural Inheritance (Ministry of Cultural and Tourism), Tianjin 300072, China
School of Architecture, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin 300072, China)
- Yan Li
(Key Lab of Information Technology for Architectural Cultural Inheritance (Ministry of Cultural and Tourism), Tianjin 300072, China
School of Architecture, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin 300072, China)
Abstract
Following the completion of the Great Wall Resource Survey in 2012, numerous landscape heritage resources along the Great Wall remained undiscovered, highlighting the limitations of conventional survey methods. This study aimed to conduct in-depth investigations of Great Wall signal sites through digital fieldwork methods, unveiling a crucial signaling structure—the auxiliary beacon—and presenting genuine historical scenes of the Great Wall signal network. Through the retrieval of the image database of the entire Great Wall and the utilization of UAVs (drones) for low-altitude remote sensing surveys, 252 auxiliary beacon sites were identified in diverse environments (e.g., deserts, mountains, plains) in Xinjiang, Gansu, Inner Mongolia, Qinghai, Ningxia, and other 10 regions. These case studies enable the categorization of layout types and the proposal of reconstruction hypotheses for the signal network of the Great Wall of China. The findings demonstrate that the beacon fire signals are not lit on the beacon tower tops, but through the ignition of various signals by auxiliary beacons, expressing pre-arranged information. Beacon towers and auxiliary beacons together form an efficient signal network along the Great Wall. This study explores how to use digital survey methods to unearth unknown landscape heritage resources of the Great Wall, enhancing the accuracy of observation for cross-regional and large-scale cultural heritage.
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