Unconscious intelligent retrieval method based on remote sensing space big data

Abstract

The invention provides an unconscious intelligent retrieval method based on remote sensing space big data, which comprises the following steps: 1, firstly, performing storage, organization and sharing management on a remote sensing image data entity through an MFS distributed file system, and performing distributed storage on metadata and a thumb graph of a remote sensing image through a PostgreSQL to ensure the security of the data; 2, quickly importing the metadata in the PostgreSQL into an Elasticsearch cluster, creating an index, and building a distributed retrieval service for the remote sensing image metadata through an ES; 3, performing, by a user, space retrieval on the remote sensing image based on a three-dimensional digital earth or a two-dimensional GIS system, providing unconscious intelligent query by the system, specifically, utilizing an Elasticsearch distributed retrieval cluster for carrying out rapid retrieval on the metadata number, such that at the moment, the user does not need to carry out a large amount of operation interaction, and the inquired remote sensing image information result is calculated and returned in real time based on coordinate information of mouse movement or simply drawn retrieval areas.

Description

technical field [0001] The invention relates to the field of remote sensing data retrieval, in particular to an insensitive intelligent retrieval technology based on remote sensing space big data. Background technique [0002] The Elasticsearch (ES) distributed full-text search engine is an open source, highly scalable distributed full-text search engine, which can store and retrieve massive data in real time; at the same time, it has strong scalability and can be extended to Hundreds of servers are used to process PB-level data. The distributed retrieval service cluster is divided into two levels: the first level is the retrieval server group, each retrieval server group can provide retrieval services independently; the second level is the distributed query server and retrieval server within the retrieval server group , the distributed query server sends the retrieval request to each retrieval server in parallel, and collects the results back, and completes the response to...

AI Technical Summary

Problems solved by technology

[0009] In view of the above problems, the present invention takes "the popularization of remote sensing in industrial applications and public applications" as the starting point, and aims to solve the problems of complex remote sensing data acquisition process, high professional threshold and low remote sensing data service efficiency at the technical level. Based on the new generation Information technology (mainly including Elasticsearch distributed search engine and PostGIS spatial analysis engine) to solve the above problems

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