A method for the quality inspection and update of cadastral data based on spatio-temporal knowledge graphs
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摘要: 准确、高效地开展地籍数据质量检测与地籍数据库更新对自然资源监管至关重要。针对当下地籍数据管理质检更新效率低、动态监管需求难以满足、方法适用范围小等问题,基于时空知识图谱提出了一种地籍数据质检与更新方法框架,以地籍数据和遥感影像作为数据源,通过设计时空知识图谱概念层、数据层与推理规则,构建了针对地籍数据质检与更新工作流程的时空知识图谱。最后使用长沙市7块宗地进行实验,解决了质检与更新过程中的常见错误,并证明了相比一般方法本方法在效率上的优势。Abstract: Accurate and efficient quality inspection and database updates of cadastral data are essential for natural resource management. The current cadastral data management faces problems such as the low efficiency of quality inspection and updates, difficulty in meeting the demand for dynamic supervision, and small application scopes of relevant methods. To solve these problems, this study proposed a method framework based on spatio-temporal knowledge graphs. Moreover, with cadastral data and remote sensing images as data sources, this study constructed a spatio-temporal knowledge graph targeting the quality inspection and update workflow of cadastral data by designing conceptual and data layers and inference rules. Finally, experiments on the method proposed in this study were conducted using seven parcels of land in Changsha. As a result, the common errors in the process of quality inspection and updates were solved, and the method proposed in this study was proven to be more efficient than common methods.
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Key words:
- spatio-temporal knowledge graph /
- cadastral data /
- cadastral database
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