基于时空大数据的智能感知、机理认知和劣化预知，不仅促进了基础设施安全的发展，同时也是基础设施建设向智能化转变的基础理论和关键技术。地下空间利用的发展，形成了深、大、集的三大特征和立体的城市布局。然而，与地上的建筑物和桥梁相比，发生在地下的病害和退化更为隐蔽，难以识别，在建设和服务期间仍然存在许多挑战。针对这一问题，本文总结了现有的方法，在现实世界的空间安全管理中评估了它们的长处和短处，并在统一的智能监控系统中，讨论关键科学问题和解决方案。

Intelligent sensing, mechanism understanding, and the deterioration forecasting based on spatio–temporal big data not only promote the safety of the infrastructure but also indicate the basic theory and key technology for the infrastructure construction to turn to intelligentization. The advancement of underground space utilization has led to the development of three characteristics (deep, big, and clustered) that help shape a tridimensional urban layout. However, compared to buildings and bridges overground, the diseases and degradation that occur underground are more insidious and difficult to identify. Numerous challenges during the construction and service periods remain. To address this gap, this paper summarizes the existing methods and evaluates their strong points and weak points based on real-world space safety management. The key scientific issues, as well as solutions, are discussed in a unified intelligent monitoring system.