Geometry-Aware CRDTs for Efficient Collaborative Geospatial Editing

Maintaining consistency in real-time multi-user editing of planar geospatial features remains challenging for traditional collaborative editing techniques, which are primarily designed for text documents. When applied to spatial data, these methods often yield inaccurate results and cause information loss, while also overlooking the geospatial and topological properties of such features. Moreover, they fail to differentiate processing priorities due to limited spatial awareness, hindering targeted performance optimization. To address these limitations, we propose a geometry-aware collaborative editing algorithm based on Conflict-Free Replicated Data Types (CRDTs), integrating a spatial–semantic data model with spatio-temporal operation merging strategies. As an extension of CRDTs tailored for spatial data, it leverages geometric vector clocks (GVCs) and minimum bounding rectangles (MBRs) to capture temporal and spatial dependencies among editing operations, detects topological anomalies through geometric constraints, resolves conflicts via spatio-temporal metadata encoded in GVCs, and optimizes performance through MBR-based operation classification. Experimental results show that this approach improves editing accuracy, contributes to preserving topological integrity, and maintains strong performance under collaborative editing workloads, with notable efficiency gains for large-scale datasets and visible features. This work provides a novel geometry-aware framework for scalable, accurate multi-user editing of planar geospatial features that helps preserve topological integrity.