The inconsistency of multi-source geographic data in scale, geometric position, and attribute cause difficult data fusion and update. This study proposed a fusion and update method for geographic data based on geometric and attribute matching. First, the candidate set was acquired using the generalized Voronoi diagram, thus effectively improving the acquisition efficiency and reducing the impact of unrelated targets on the candidate set. Then, the matching analysis of point, line, and plane data was made using key techniques such as geometric and attribute matching. Finally, based on the matching results, the incremental data were extracted from the reference geographic information data, followed by fusion and update of target data. The experimental results show that the method proposed in this study can efficiently identify and extract incremental data and serves as a reference for the innovative exploration into the update mode of monitoring data.
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