A Co-Designed High-Performance Computing and Visualization Framework for Near-Real-Time Sustainable Land Governance Decisions

Sustainable land governance requires timely and accurate monitoring of land-use change to balance ecological, agricultural, and urban demands. Yet policymakers rarely receive actionable insights fast enough, because large-scale geospatial computation and rapid delivery remain disconnected. To close this gap, we introduce a Computational-Visualization Co-design (CVC) framework that welds a distributed high-performance computing engine to a real-time, preprocessing-free visualization system. Our approach represents a system-level innovation. It co-designs computational shards as visualization units, eliminating intermediate data reorganization. This co-design paradigm makes analytical results immediately visible. CVC processes a 20 TB imagery dataset and overlays millions of parcels 5–9 times faster than conventional engines. Map service publishing plummets from 168 h to just 7—a 24-fold speed-up—while client-side performance stays robust. The framework directly supports sustainable land management. It enables proactive monitoring, rapid impact assessment, and evidence-based policy formulation. Our work thus contributes to key Sustainable Development Goals related to land and cities. Validated with national survey data from China, the system merges analysis with instantaneous visual feedback, offering a practical route to sustainable land governance.