Practices in Digitally Applying Databases Developed for the Great Wall
Due to its vast linear span,the Great Wall involves complicated cultural and natural environment,making its con-servation and management extremely difficult.Existing studies on the Great Wall lack the support of holistic data,and more detailed investigations are still to be carried out on architectural heritage.Moreover,due to inadequate communication and lack of resource share,the public have had biased views towards the Great Wall for a long period.In this context,digitalization has become a key element for the protection and utilization of the Great Wall as a heritage.The Key Laboratory of Information Technology for Archi-tectural Cultural Heritage,Ministry of Culture and Tourism,Tianjin University has committed itself to collecting the images of and conducting basic research on the Great Wall as a heritage in the last 20 years,and made progresses in studies in various fields,includ-ing defense system,database development,monitoring of deterioration,damage,hazard and risks,digital cloud platform development,and museum display.Firstly,in the field of theoretical study,the Key Laboratory of Information Technology for Architectural Cultural Heritage investi-gates the structure of the military defense system adopted by the Great Wall,which consisted of seven sub-systems,namely,defensive walls,soldier stations,early warning system,smoke signal system,messenger system,borderland trade,and military farming system.These findings cleared the misunderstanding that the Great Wall is a linear wall to block the border.Secondly,facing the great chal-lenges in the holistic conservation of the Great Wall brought by such a vast system,the Key Laboratory of Information Technology for Architectural Cultural Heritage provides a holistic data-based approach to store,manage,study and apply the information and resourc-es relating to the Great Wall based on modern information technologies by building a temporal and spatial defense system database for the Great Wall and a database for the three-dimension view of the whole Great Wall.In terms of practices in applying the two data-bases,the research group provides accesses to the databases on certain terms and conditions to facilitate their applications in different fields.In the technical field,the Key Laboratory of Information Technology for Architectural Cultural Heritage also carries out regular inspections using drones and compares the images collected to monitor any deterioration,damage,or hazard relating to the Great Wall and provides early warnings so that the precise location of any damage can be identified for repairs and protection can be carried out in a timely manner.At the society level,the Key Laboratory of Information Technology for Architectural Cultural Heritage develops a digital cloud platform online through partnership with Internet enterprises focusing on online tourism of Great Wall.Moreover,it works with museums to host offline exhibitions of the research results obtained by Tianjin University with the theme of"Discovering the Great Wall in Virtual and Real World",providing easily accessible,affordable,and appealing digital experience for the public.This paper systematically reviews the research group's studies and practices relating to the digitalization of the Great Wall and relevant results.The visualization of the Great Wall Defense System and three-dimension data coverage across the whole Great Wall were achieved by the research group.This paper deepens research on the Great Wall as a single building and assists in discovering unknown defense facilities,filling some gaps in certain key knowledge and providing scientific basis for conserving and managing the Great Wall.Moreover,it may facilitate the monitoring of deteriorations,damages,hazards,and risks relating to the Great Wall,and provides access to and shares important resources relating to the Great Wall,improving public's participation in the conservation of the Great Wall.
the Great Walldigitalizationdefense systemdatabaseoverall conservation
万方数据
维普
