Evaluating Blockchain Efficiency for Large-Scale Geospatial Dataset Distribution

Abstract

The secure and reliable distribution of geospatial datasets is an emerging challenge for a country like Papua New Guinea (PNG), where responsible agencies increasingly depend on satellite imagery, cadastral surveys, and environmental monitoring data for the national development growth. Existing government systems are centralized systems which often encounter bottlenecks, risk of tampering, and outages due to single points of failure, which undermine data trust and availability. This study develops and evaluates a blockchain-driven simulation framework that is customized to the PNG’s geospatial metadata distribution. We used synthetic datasets of varying sizes, model tests transaction creation, metadata logging, consensus validation, and block propagation under different consensus mechanisms. The performances were measured across throughput, latency, energy demand, and resilience against tampering. Results obtained from this simulation highlighted clear trade-offs between scalability and security across Proof of Work, Proof of Stake, Proof of Authority, and PBFT. The findings provide practical benchmarks for agencies such as the National Mapping Bureau, Department of Lands, and climate monitoring bodies in PNG, where transparency, low energy consumption, and efficiency are critical. The findings highlight how blockchain can be applied to build transparent and resilient data-sharing systems for national spatial data infrastructures operating under resource constraints.