## 2 Materials and Methods
### Methods  
#### 2.2.1 GEO-LEO Satellites Cooperation Scheme  
The overall scheme of using the cloud cover information provided by the GEO meteorological satellites to guide the mission planning of the LEO optical imaging satellites consists of an operational workflow and a GEO-LEO satellites cooperation scheme framework, as shown in Figures 2 and 3, respectively.  
In this strategy, the ground control center develops a 24-h satellite observation schedule based on the imaging requirements and transforms it into payload commands, and then the ground stations upload the commands to the GEO meteorological and LEO optical imaging satellites. During the execution of the observation schedule by the LEO optical imaging  
Figure 3: Framework of GEO–LEO satellites cooperation scheme.  
Figure 2: Operational workflow strategy of GEO–LEO satellites.  
satellites, the GEO meteorological satellite performs autonomous mission planning for the LEO satellites based on the acquired cloud cover information dynamically.  
In the above framework, satellites should have different levels of intelligent and autonomous capabilities. The concept of satellite intelligence was considered initially by [PERSON] et al. (2003) [PERSON] et al. (2003). They performed comparisons on different levels of satellite intelligence. Four levels of satellite intelligence have been identified.  
1. \(I_{1}\) represents the most \"intelligent\" agent. Here the \"agent\" means one intelligent satellite in the satellite system composed by single satellite or multiple satellites. The primary difference between \(I_{1}\) and the other satellite agents is that it is capable of monitoring all satellite agents in the system and planning for the system as a whole;
2. \(I_{2}\) can interact with other satellite agents in the system. This usually requires the agent to have at least partial knowledge of the full agent-based system;
3. \(I_{3}\) has local planning functionalities onboard. \"Local\" means the agent is capable of generating and executing only plans related to its own tasks; and
4. \(I_{4}\) represents the most \"unintelligent\" agent. It can only receive commands and tasks from other satellite agents in the system, or from the ground, and execute them.  
Based on the identification of the satellite intelligence levels, we define a GEO meteorological satellite as \(I_{1}\) level, and LEO optical imaging satellites as \(I_{3}\) level in the GEO-LEO satellites cooperation scheme. The GEO meteorological satellite has a strong computing and autonomous capability, and the onboard data contains orbital data of LEO satellites, as well as a multi-satellite cooperation mission planning capability. The LEO satellites are defined as a partially autonomous capability satellite, which can report their own status data to the GEO meteorological satellite, and also receive mission commands from the GEO meteorological satellite and execute action sequences autonomously.  
The ways of coordination architectures for multiple satellites include top-down coordination, centralized coordination, distributed coordination, and fully distributed coordination. The top-down coordination architecture includes only one single (highly intelligent) \(I_{1}\) level agent, and the other satellite are (unintelligent) \(I_{4}\) agents. The centralized coordination architecture requires at least local planning and, possibly, interaction capabilities between satellite, requiring \(I_{3}\) or \(I_{2}\) agents. The distributed coordination architecture consists of several parallel hierarchical decision-making structures, each of which is commanded by an \(I_{1}\) intelligent agent. In the case of a fully distributed coordination architecture, each satellite in the system represents an \(I_{1}\) level agent, resulting in a totally flat system [33]. In the GEO-LEO satellites cooperation scheme, we define the coordination way between satellites as centralized coordination.