Integrating High-Resolution Remote Sensing Data and Spatial Databases for Campus Asset Management Using GIS

Abstract

Asset management effectively necessitates the usage of high-resolution remotely sensed images integrated with spatial databases for real-time monitoring and analysis. This study presents the development of a comprehensive geodatabase for the University of Energy and Natural Resources (UENR) campus structures, using Quantum Geographic Information System (QGIS) and with the PgMetadata (PostgreSQL Metadata) extension for efficient asset management. A total of 85 campus buildings were digitized, representing 100% of the university’s infrastructure, with 40% categorized as academic, 30% administrative, and 20% residential. The geodatabase integrates both spatial and attribute data, with a positional accuracy of ±2 meters. Metadata creation using PgMetadata improved data accessibility by 75%, standardizing 90% of building datasets. Spatial analysis revealed that 90% of key campus buildings are within 150 meters of essential services, though 8% of buildings lack nearby electricity access. The geodatabase supports real-time decision-making for campus planning, and future expansions are projected to meet a 10% infrastructure increase to accommodate student population growth. Despite challenges in data accuracy and user proficiency, the system reduces manual inventory management time by 60% and supports long-term infrastructure planning. This study demonstrates the effectiveness of integrating QGIS and PostgreSQL for scalable, data-driven campus management solutions.