Method, system and device for organizing, storing and retrieving multi-source satellite split-view image data

Abstract

The invention relates to a method, system and device for organizing, storing and retrieving the multi-source satellite split-view image data, and relates to the technical field of satellite remote sensing image data processing. The method comprises the steps of during data organization and storage, when satellites corresponding to the satellite split-view image data are stored for the first time, recording the satellite information and the partition information in a satellite image partition registry, and creating an image metadatabase table of each partition of the satellites based on a spatial database; determining a partition corresponding to the satellite split-scene image, and updating the corresponding image metadatabase table; after an entity file of the satellite split-scene image data is stored, updating the storage path information to the corresponding image metadatabase table; during data retrieval, carrying out first-level retrieval on the satellite image partition registry according to the retrieval constraint conditions, and then carrying out second-level retrieval on all image metadatabase tables determined by the first-level retrieval. According to the above data processing mode, the processing of irrelevant data in the data storage and retrieval process can be effectively reduced, and the calculation efficiency of the data storage and retrieval process is improved.

Description

technical field [0001] The invention relates to the technical field of satellite remote sensing image information systems, in particular to a method, system and device for organizing, storing and retrieving multi-source satellite scene image data. Background technique [0002] In the prior art, when the satellite image data is organized and stored, all the metadata information of a satellite is usually stored in an image metadata table, and the organization and management of the satellite image data is realized through the above method. However, with the continuous increase in the number of satellite launches, satellite images covering most of the world are rapidly accumulating, and the data volume of massive satellite image data from multiple sources, multi-temporal, multi-scale, and multi-version has grown from GB to TB, and to the present On the order of PB, the number of image data records acquired by a satellite reaches several million, which also leads to a very large ...

AI Technical Summary

Problems solved by technology

However, with the continuous increase in the number of satellite launches, satellite images covering most of the world are rapidly accumulating, and the data volume of massive satellite image data from multiple sources, multi-temporal, multi-scale, and multi-version has grown from GB to TB, and to the present On the order of PB, the number of image data records acquired by a satellite reaches several million, which also leads to a very large amount of metadata in the image metadata table

Then, when image data is organized and stored and retrieved in the image metadata table according to the retrieval constraints, the amount of calculation will be very large, and the efficiency of data organization, storage and retrieval is low.

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