摘要
【目的】行政区划是行政管理、资源配置和社会经济统计的基础单元。频繁调整导致名称、类型、区划代码及空间范围不断变化,增加了跨年度统计分析和历史追溯的难度,对区域规划和政策实施造成挑战。针对这一问题,本文提出面向复杂时空演化的行政区划知识图谱构建方法,旨在实现行政区划演变的统一语义化表达与智能化管理。【方法】为解决传统GIS难以形式化表达复杂沿革关系与动态演变过程的局限性,本文设计了语义一致的行政区划本体模型,并提出“主-谓-宾-时间”四元组表达框架,系统定义行政区划单元的概念、属性和关系。以1949—2023年中国省、市、县级行政区划长时序矢量数据为基础,采用空间叠加与属性匹配的方法,识别名称变更、行政类型调整、区划代码变更、划入、划出及空间范围变化等沿革事件。基于Neo4j图数据库环境,构建行政区划演变知识图谱,实现行政区划演变知识的结构化管理。【结果】构建的知识图谱包含26269个节点和406744个三元组,完整记录1949—2023年省、市、县级行政区划的名称、代码、面积及演变类型等信息。基于图谱共识别出33507次沿革事件,实现了行政区划的时空演变查询、跨时空逻辑推理与知识发现,以及跨年度统计数据矫正等应用。【结论】本研究突破传统GIS难以刻画复杂时空关系的局限,为行政区划的沿革研究提供了新的技术手段,并为其他地理实体的复杂时空知识建模提供了借鉴。
[Objectives]Administrative divisions serve as fundamental units for administrative management,resource allocation,and socioeconomic statistics.Frequent adjustments lead to continual changes in their names,types,codes,and spatial boundaries,which complicate cross-year statistical analysis and historical traceability,posing challenges to regional planning and policy implementation.To address this issue,this paper proposes a method for constructing an administrative division knowledge graph for complex spatiotemporal evolution,aiming to achieve a unified semantic representation and intelligent management of administrative division changes.[Methods]To address the limitations of traditional GIS in formally expressing complex evolutionary relationships and dynamic evolutionary processes,this study designs a semantically consistent ontology model for administrative divisions and proposes a"Subject-Predicate-Object-Time"quadruple framework to systematically define the concepts,attributes,and relationships of administrative division units.Using long time-series vector data of China's provinces,cities,and counties from 1949 to 2023,methods of spatial overlay and attribute matching are employed to identify evolutionary events such as name changes,type adjustments,code changes,mergers,splits,and spatial boundary changes.An administrative division evolution knowledge graph is then constructed in a Neo4j graph database to enable the structured management of this evolutionary knowledge.[Results]The knowledge graph contains 26269 nodes and 406744 triples,comprehensively documenting information on the names,codes,areas,and evolution types of provincial,municipal,and county-level administrative divisions from 1949 to 2023.Based on the graph,33507 evolutionary events were identified,enabling spatiotemporal evolution querying,cross-spatiotemporal logical reasoning for knowledge discovery,and cross-year statistical data correction.[Conclusions]This research overcomes the limitations of traditional GIS in representing complex spatiotemporal relationships,offering a new approach for the study of administrative division evolution and providing a reference for modeling complex spatiotemporal knowledge of other geographical entities.
作者
王春玲
诸云强
王曙
刘纪猛
冯敏
高振记
WANG Chunling;ZHU Yunqiang;WANG Shu;LIU Jimeng;FENG Min;GAO Zhenji(State Key Laboratory of Resources and Environmental Information System,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;University of Chinese Academy of Sciences,Beijing 100049,China;Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing,210023,China;School of Civil Engineering and Geomatics,Shandong University of Technology,Zibo 255000,China;National Tibetan Plateau Data Center,State Key Laboratory of Tibetan Plateau Earth System,Environment and Resources,Institute of Tibetan Plateau Research,Chinese Academy of Sciences,Beijing 100101,China;Integrated Natural Resources Survey Center,CGS,No.55 Yard,Honglian South Road,Xicheng District,Beijing 100055,China)
出处
《地球信息科学学报》
北大核心
2026年第1期89-104,共16页
Journal of Geo-information Science
基金
国家重点研发计划项目(2022YFB3904200)
中国科学院基础与交叉前沿科研先导专项(XDB0740000)
地理信息科学与技术全国重点实验室自主部署项目(KPI009)。
关键词
行政区划
本体模型
知识图谱
时空特征
演变分析
图数据库
administrative division
ontology model
knowledge graph
spatiotemporal characteristics
evolutionary analysis
graph database
