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基于众包的古琴名人时空信息采集与移动轨迹时空分析
引用本文:刘菊,陈璨,许珺.基于众包的古琴名人时空信息采集与移动轨迹时空分析[J].地球信息科学,2019,21(6):844-853.
作者姓名:刘菊  陈璨  许珺
作者单位:1. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 1001012. 中国科学院大学资源与环境学院, 北京 1000493. 清华大学艺术教育中心,北京 100084
基金项目:国家自然科学基金项目(41771477);资源与环境信息系统国家重点实验室自主创新项目(O88RA20BYA)
摘    要:古琴是中华民族的古老乐器,知名的古琴名人流传至今,但是由于古代历史书籍匮乏、记录不完整性以及古今地名歧义性等原因,导致无法收集完整的古琴名人移动轨迹数据。本文基于众包思想,构建基于WebGIS的古琴名人时空信息采集系统,着重解决古琴名人轨迹数据库和知识数据库的构建。基于众包数据,古琴名人时空信息采集系统对古琴名人轨迹进行可视化查询,动态展示古琴名人的二维与三维轨迹,并结合古琴知识图谱,实现古琴名人相关信息的智能化查询。古琴名人轨迹点时空核密度分析结果显示古琴名人移动轨迹与中国历史人口迁移趋势一致,且古琴名人倾向于停留在具有浓厚文化气息的历史名城与山水之地,从而有利于古琴文化的传承与发展。本文所采用的方法不仅可用于古琴名人,同样适用于其他历史名人或移动物体的轨迹采集。

关 键 词:古琴  众包  GIS  可视化  时空轨迹  知识图谱  核密度分析  
收稿时间:2018-11-12

Spatiotemporal Analysis of the Trajectories of Guqin Celebrities based on Crowdsourcing Data
Ju LIU,Can CHEN,Jun XU.Spatiotemporal Analysis of the Trajectories of Guqin Celebrities based on Crowdsourcing Data[J].Geo-information Science,2019,21(6):844-853.
Authors:Ju LIU  Can CHEN  Jun XU
Institution:1. State Key laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China3. Center of Art Education, Tsinghua University, Beijing 100084, China
Abstract:Guqin is the most classical Chinese musical instrument. In its more than 3000-year history, guqin has developed many genres with specific characteristics in different regions of China, with each genre having its representative players. If the lifeline trajectories of guqin celebrities in history can be collected, the spatiotemporal distribution of each genre can be analyzed which will help to know the development and evolution of this ancient art. Due to the lack of specialized historic literature of guqin and that the information of guqin are scattered in other literature, it is difficult to collect all the information efficiently. With the rapid development of network technology and the increasing number of internet users, more and more volunteers on the Internet are willing to participate in crowdsourcing. A spatiotemporal trajectory collection and retrieval system of guqin celebrities was built by combining Chinese guqin art, crowdsourcing, and GIS. Representations and the databases of the trajectory data and knowledge data were presented in this study. There are three modules of the system, a data collection module, a knowledge base module, and a spatial retrieval and visualization module. The data collection module collects crowdsourcing input data. The knowledge base module is used to store and retrieve knowledge of guqin. There are complex relations between genres, places, and people, so the graph database Neo4j is used to represent guqin knowledge and the rich relationships among guqin players. The spatial retrieval and visualization module displays trajectories in 2 or 3 dimensions. With the collected trajectories, the spatiotemporal distribution of locations on the trajectories was analyzed. Results show that the trajectories of guqin celebrities were consistent with the trend of population migration in China's history, and that guqin celebrities tended to stay in historically famous cities and landscapes, which were conducive to spreading the guqin culture and creating guqin music.
Keywords:guqin  crowdsourcing  GIS  visualization  spatiotemporal trajectory  knowledge graph  kernel density  
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