Modeling study demonstrates a privacy-preserving blockchain architecture for geospatial data, highlighting secure sharing and cross-chain integration in smart cities.
Geospatial data is a fundamental production factor for modern urban governance, for smart city governance, emergency response, ecological monitoring, industrial layout optimization and infrastructure coordination. However, geospatial data has the characteristics of high sensitivity (including location privacy and ownership privacy), strong correlation (data fusion is prone to leakage), and multi-party ownership (diverse interests and demands). The traditional centralized sharing model faces structural difficulties such as high risk of privacy leakage, insufficient data credibility, unclear ownership definition, and lack of sharing incentives. The decentralized, tamper proof, and traceable characteristics of blockchain technology provide a new path for privacy protection and secure sharing of geospatial data. Existing blockchain sharing models encounter significant bottlenecks regarding privacy protection granularity, consensus efficiency, and storage overhead when processing high-dimensional and dynamically updated geospatial data. These limitations further hinder cross-chain interoperability and complicate the secure integration of large-scale spatial datasets. The model can support secure sharing of remote-sensing and trajectory data in smart-city geospatial systems.
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Li et al. (2026) studied this question.
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