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利用知识图谱的国土资源数据管理与检索研究
引用本文:张永军,程鑫,李彦胜,王飞,刘晓健,吴文品.利用知识图谱的国土资源数据管理与检索研究[J].武汉大学学报(信息科学版),2022,47(8):1165-1175.
作者姓名:张永军  程鑫  李彦胜  王飞  刘晓健  吴文品
作者单位:1.武汉大学遥感信息工程学院,湖北 武汉,430079
基金项目:国家自然科学基金42030102国家自然科学基金41971284湖北省自然科学基金创新群体2020CFA003
摘    要:针对国土资源不同数据产品间难以进行有效管理与快速应用的问题,研究利用图数据库对GlobaLand30、FROM-GLC10_2017、GLC_FCS30_2020等公开土地覆盖数据集进行语义层面的结构化存储,建立中国国土资源知识图谱。构建以行政区划为单位进行土地覆盖数据产品管理、知识提取以及数据获取与更新的新型应用框架,利用基于图的异常数据检索算法探究不同产品间的一致性,提出了一种基于知识图谱的感兴趣图节点快速检索算法。通过引入知识图谱,形成了具有447 817个节点、447 816条关系,且可动态更新的中国国土资源知识图谱,并发现了在覆盖全国的2 875个行政单元中有92个区域单元的产品数据一致性不足60%,区域产品精度可能存在较大误差。充分利用了多源土地覆盖数据产品间的信息,缩短了数据预处理的时间,为中国国土资源的知识化管理与应用提供了新思路。

关 键 词:国土资源管理    知识图谱    土地覆盖数据产品    异常数据检索    感兴趣图节点
收稿时间:2021-12-19

Research on Land and Resources Management and Retrieval Using Knowledge Graph
Affiliation:1.School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Abstract:  Objectives  Aiming at the problem of difficult effective management and rapid application between different data products of land and resources, the study uses the graph database to store the public land cover datasets, including GlobaLand30, FROM-GLC10_2017, GLC_FCS30_2020, etc., on the semantic level to establish a knowledge graph of land resources. It provides a new processing framework for the management, rapid application, and data quality assessment of land and resources data.  Methods  A new application framework for land cover data product management, knowledge extraction, and data acquisition and update based on administrative divisions is proposed. Anomaly data retrieval algorithms based on graphs are used to explore the consistency of different products, and a knowledge-based fast retrieval algorithm for graph nodes of interest (GNOI) in the graph.  Results  Through the introduction of the knowledge graph, a dynamically updateable nationwide land resource knowledge graph containing 447 817 nodes and 447 816 relationships has been formed, and it is found that the data accuracy of 92 units may have large errors in the 2 875 administrative units covering the whole country.  Conclusions  The research has greatly improved the utilization rate of multi-source land cover data products, shortened the time of data preprocessing for researchers, and provided new ideas for the knowledge management and application of land resources.
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