In view of the characteristics of wide monitoring area and large number of sensors in large-scale monitoring systems like environment monitoring and power grid ice-disaster monitoring system, a Regional Cluster-based lifetime optimization Strategy for large-scale wireless sensor network (RCS) was proposed to save the network energy consumption and prolong the lifetime of the network. The strategy firstly used AGNES (Agglomerative Nesting) algorithm to divide the network into several subareas based on node location for optimizing the distribution of cluster heads. Secondly, uneven clusters would be conducted after cluster heads were generated, and a time threshold value was set to balance node energy consumption. Finally, for inter-cluster communication, a multi-hop routing was adopted by constructing minimum spanning tree on the basis of calculating network energy cost to balance the energy consumption of the cluster heads. In the simulation, compared with LEACH (Low Energy Adaptive Clustering Hierarchy) and EEUC (Energy-Efficient Uneven Clustering) algorithm, RCS respectively reduced the cluster head nodes' energy consumption by 45.1% and 2.4% on average; and respectively extend the network lifetime by 38% and 3.7%.The simulation results show that RCS can be more efficient to balance the overall network energy consumption, and significantly prolong the network lifetime.