Massive remote sensing data organization and management method and system based on distributed hbase storage

Abstract

The invention discloses a global massive remote sensing data organization and management method, which comprises the following steps of: segmenting acquired remote sensing image data into tiles with preset sizes, and calculating information of the tiles; calculating a rowkey in the hbase based on the information of the tile, determining a storage position of the tile in the hbase, and storing thetile and the tile information in the hbase; querying a corresponding tile from the hbase based on a calling request through a calling interface; wherein the information of the tiles comprises hierarchical information, time phase information, tile data types and longitude and latitude ranges to which the tiles belong. According to the method, the advantages of distribution and expandability of thehbase database and the hbase index rowkey generation method are utilized, and rapid retrieval and query of massive tile data are achieved.

Description

technical field [0001] The invention relates to the field of data management, in particular to a method and system for organizing and managing massive remote sensing data based on distributed hbase storage. Background technique [0002] With the rapid development of aerospace remote sensing technology and the diversification of image data acquisition equipment, profound changes have taken place in the way of obtaining remote sensing image data, which has led to an explosive growth in the number of remote sensing image data. In this case, how to effectively generate and query remote sensing images plays an important role in the application of remote sensing images in military, exploration, earth observation and other fields. [0003] In the existing technology, the storage and management of remote sensing images mainly use storage methods based on file systems and traditional relational databases. The file-based storage method requires manual organization and arrangement of ...

AI Technical Summary

Problems solved by technology

The file-based storage method requires manual organization and arrangement of storage files. Not only is it not easy to manage, it cannot organize different remote sensing time-phase data well, and it is easy to cause low efficiency in the case of concurrent access by multiple users.

However, based on the traditional relational database storage method, in the face of massive remote sensing data, it is vulnerable to problems such as single node failure, insufficient scalability, and low query efficiency.

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