Abstract: Under the “One Map” initiative,historical cadastral data often contain quality defects that impede refined management.This study aims to develop an efficient and accurate method to detect these data issues.A knowledge graph and a rule-based model were constructed by analyzing the relationships among geographic base map updates,land change surveys,and cadastral operations.Using automated techniques such as high-precision spatial overlay analysis and logical consistency checks,the method systematically identifies timeliness deviations (e.g.,lack of spatial coverage,failure to deregister) and ownership conflicts (e.g.,forest-farmland disputes,unlawful occupation of cultivated land) .Empirical results show that the proposed method significantly improves the efficiency and accuracy of cadastral data issue detection.This approach offers crucial technical support for natural resources management departments to objectively assess cadastral data quality and conduct targeted supplementary surveys,thereby enhancing data reliability.

Key words: cadastral basemap, cadastre, fundamental geospatial information, national land change survey, association matrix, knowledge graph