Database Design and Minimum Coverage Algorithm for Urban Environmental Design Information System

The field of urban environmental design faces increasingly complex data processing and resource management challenges. This study aims to design a state-of-the-art urban environmental design information system database and integrate minimum coverage algorithms to optimize resource allocation in the design decision-making process. The system adopts entity-relationship model to represent entities such as urban areas, buildings, public facilities, etc. and their attributes and relationships, which reduces data redundancy and improves data integrity through normalization theory, and ensures data security through role-based access control. The database architecture design takes into account the special needs of geospatial data and realizes efficient data retrieval and updating. The integrated minimum coverage algorithm adopts a greedy strategy, which gradually constructs the minimum set to realize extensive coverage by prioritizing queues and coverage gain calculation. The experimental results show that the Urban Environmental Design Information System (UEDIS) database excels in query response time, with a maximum query response time of only 572 milliseconds, demonstrating extremely high query speed. The minimum coverage algorithm maintains a coverage rate between 90.1% and 99.9% in the test, proving the efficiency and accuracy of the algorithm in urban environmental design. The highest memory usage of the algorithm is only 1,493KB, showing high efficiency in memory usage. Comprehensive analysis shows that the integration of database and algorithms provides a data management solution for urban environmental design that is both secure and efficient, and is able to support complex query and analysis needs and optimize the allocation and utilization of urban spatial resources.