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As the rapid increasing of the number of the satellites, the number of facilities of the satellite ground stations is becoming insufficient and the conflicts of serving satellite data missions exist. To make full use of the facilities of the China Remote Sensing Satellite Ground Station (RSGS), scheduling optimization of these facilities was studied in this paper, which was not well-solved by the original method in the operation system of RSGS. The problem is formulated as a continuous time-based mixed integer linear programming (MILP) model. A decomposition optimization algorithm is proposed to solve the large-scale problem, which is difficult to solve using traditional methods. In the first step, the particle swarm optimization (PSO) algorithm is used to optimize the multi-ground station relay tasks, and the multi-ground station optimization problem is transformed into several single ground station optimization problems. Next, in two additional steps, optimization of the facilities at a single ground station is performed to further reduce the size of the model. The proposed method has been applied to operations systems of RSGS, and the approach presented in this article has demonstrated stable performance and sufficient efficiency online, resulting in the automation of facility scheduling. [ABSTRACT FROM AUTHOR]

China is one of the most disaster-prone countries in the world. Currently, the disaster prevention and relief mechanism in China is mainly based on single disaster types and is implemented by different ministries and divisions in single administrative regions. Subsequently, the available resources, including data, services, materials, and human resources, cannot be shared and used effectively. Based on the idea of an observation system of systems and a business system of systems, this paper presents an integrated framework for a Chinese National Disaster Reduction System of Systems (CNDRSS) to address this issue. The CNDRSS framework aims to achieve data sharing and collaboration among different disaster-related ministries/institutions by providing one-stop services for all phases of disaster management and linking together existing and planned disaster-related business systems and observation systems. The key technologies use federated databases and a web service to integrate multiple disaster management systems among different ministries/institutions and a sensor web to integrate airborne, space-borne, andin-situobservations through the web service. These event-driven focused-services connecting the various observations, processing, and mapping processes can meet the requirements for complex disaster-chain systems. [ABSTRACT FROM AUTHOR]