Spatial Blockchain: Enhancing Spatial Queries and Applications through Integrating Blockchain and Spatial Database Technologies

Abstract

The fusion of spatial data with blockchain technologies presents an innovative approach towards a decentralized, secure, and trustworthy framework for spatial information management. This integration brings spatial representation to the forefront of blockchain, opening avenues for various sectorial applications. However, challenges like slow processing times, restricted query capabilities, and consistency issues have been identified within the blockchain system. Addressing these challenges, we propose an optimized method for spatial queries by leveraging the high-performance capabilities of spatial databases. Unlike conventional off-chain query techniques, our approach synergistically combines hyperledger fabric with a specialized spatial database. This fusion facilitates distributed spatial queries within blockchain framework, incorporating spatial operation functionalities into smart contracts while preserving the distributed nature of nodes and spatial databases. Enhancing system security, we incorporate a dual-stage verification mechanism alongside a salt-hash storage strategy to counteract potential unauthorized alterations. Initial results validate the efficacy of our methodology in terms of performance and security. Building on this foundation, we introduce a rental transaction system that effectively merges spatial data with blockchain, demonstrating the feasibility and potential of integrating spatial information into the blockchain, especially in the realm of real estate.

Yi Bao

Postdoctoral Researcher
2023 - present
PhD Student
2018 - 2023

My research interests include Geographical Information Systems, Remote Sensing, Urban Data Mining, Deep Learning

Zhou Huang

Associate professor

Associate professor of GIScience