Method and device for establishing space grid system and remote sensing image processing system

By constructing a 3D holographic management framework and microservice architecture, the problem of efficient management and rapid processing of massive high-resolution remote sensing images in traditional remote sensing image processing systems has been solved, achieving efficient storage, rapid processing, and flexible application.

CN121958583APending Publication Date: 2026-05-01北京云游九州空间科技有限公司
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Patent Information

Application Number
CN202610073282.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-01-20
Publication Date
2026-05-01

AI Technical Summary

Technical Problem

Traditional remote sensing image processing systems cannot meet the needs for efficient management and rapid processing of massive amounts of high-resolution remote sensing images.

Method used

A three-dimensional holographic management framework consisting of temporal, spatial, and spectral grids is constructed. A globally segmented grid is adopted and assigned a unique code to achieve pixel-level data scheduling and parallel reading. Combined with real-time memory processing technology, it supports dynamic band combination, stretching enhancement, and uniform light and color processing. It adopts a microservice architecture and cluster deployment and provides an open API interface.

Benefits of technology

It achieves efficient storage and management, improves data storage efficiency and retrieval speed, supports rapid dynamic processing, shortens data release time, enhances system scalability and flexibility, and adapts to various application scenarios.

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Abstract

The invention provides a method and device for establishing a space grid system and a remote sensing image processing system. The method belongs to the technical field of remote sensing images, and carries out unified structured management on remote sensing image data by constructing a three-dimensional holographic management framework composed of a time grid, a space grid and a spectrum grid. The space grids adopt global subdivision grids and are endowed with unique codes, the time grids establish indexes according to years, seasons and months, and the spectrum grids are divided according to professional spectrum segments. The corresponding device comprises a data receiving module, a grid coding module, a storage module, a scheduling module and a processing module. The system supports micro-service cluster deployment, visual low-loss compression and open API integration. According to the method, pixel-level scheduling, dynamic processing and real-time service release of the remote sensing data are realized, the bottlenecks that the traditional file-level management efficiency is low, the preprocessing is tedious, and the instant service demand of massive high-resolution images is difficult to meet are overcome, and the data management, processing and service efficiency is remarkably improved.
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