Mass remote sensing image data distributed storage method and system suitable for quick browsing

Abstract

The invention relates to a mass remote sensing image data distributed storage method suitable for quick browsing. The method comprises the following steps: storing remote sensing image data into a database; metadata extraction: extracting metadata information of the original remote sensing image data; storing a metadata extraction result; storing original remote sensing image data; layering and blocking the data: carrying out layering processing on the original remote sensing image data, carrying out blocking processing on the layered image, and obtaining the layered and blocked data; and layered and partitioned data storage. The invention further discloses a mass remote sensing image data distributed storage system suitable for quick browsing. A management mode of combining a distributed file system and a database management mode is adopted, so that the normalization of data management is ensured, the expandability of the capacity during mass data storage is also ensured, and the limitation of hardware is solved; according to the method, time-consuming waiting of large-data-volume real-time sampling is avoided, and the problems of storage and quick reading and browsing of massive remote sensing image data are solved.

Description

technical field [0001] The invention relates to the technical field of data management, in particular to a distributed storage method and system for mass remote sensing image data suitable for quick browsing. Background technique [0002] Data storage technology is an important component and branch in the field of data processing. Data storage technology has gone through three stages: manual management, file management, and database management. At present, more and more remote sensing image data are generated in various projects, and a single file of remote sensing image data is relatively large, which can easily reach the scale of GB. This puts forward higher requirements for storage medium capacity and data retrieval speed. Currently, the hard disk storage method can no longer meet the needs of users, and is also not suitable for the management of a single relational database. [0003] However, the traditional SAN (Storage Arew Network) or NAS (Network Attached Storage) s...

AI Technical Summary

Problems solved by technology

This puts forward higher requirements for storage medium capacity and data retrieval speed. The current hard disk storage method can no longer meet the needs of users, and it is also not suitable for the management of a single relational database.

[0003] However, the traditional SAN (Storage Arew Network) or NAS (Network Attached Storage) storage technology has bottlenecks in storage capacity and scalability, and there are also certain restrictions on the number of hardware devices deployed, which makes the cost of upgrading the system for users greatly increase

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