A NOSOL-based Information Management And Analysis System For Remote Sensing Data

In the information age, information integration and sharing is the main trend of the times. Aimed at information integration and sharing for remote sensing data, this paper shows the design and implementation of a NOSQL-based information management and analysis system for remote sensing data. The system has been put into operation. This paper mainly discusses the three core components of the system: data integration component, data partition component, data statistics and analysis component.The system’s management and analysis is mainly based on metadata. Because of the multi-source, heterogeneous, massive features of remote sensing metadata, the first problem to be solved is the integration of heterogeneous data. This paper presents the design and implementation of the remote sensing metadata integration using a method of loose mode. As the method shows, field management is the basic unit and it does not need to set the global mode strictly, which makes the data integration procedure dynamic and flexible. In addition, considering the characteristics of key-value, mode free, content free of the remote sensing metadata and the platform scalability and query characteristics of diversification, the system uses MongoDB for distributed storage. While the data partition is the foundation of MongoDB distributed storage, combining the characteristics of the spatial data and the business requirement, this paper gives a data partition method based on GeoHash. In this method, the data with similar location characteristics is divided to the same data chunk.It is novel and effective. At last, to meet the demands of data statistics, the data statistics component is designed based on the MongoDB distributed storage and the MapReduce model. It separates the statistical phase and query operation, thus to fulfill both comprehensive and real-time demand.