Massive remote sensing data processing method and system based on distributed architecture

Abstract

The invention relates to the technical field of massive remote sensing application services, in particular to a massive remote sensing data processing method and system based on a distributed architecture. The method comprises the following steps: S1, acquiring information required to be searched; S2, carrying out massive remote sensing image database retrieval, if a retrieved remote sensing imagefile has no associated map tile service, turning to the step S3, and otherwise, turning to the step S6; S3, constructing a remote sensing image data pyramid online, if remote sensing tile data is selected to be stored and map tile service is issued, executing the step S4, and if remote sensing tile data is selected not to be stored, executing the step S6; S4, synchronously storing the remote sensing tile data; S5, performing remote sensing tile data spatial index storage; and S6, publishing and displaying the map tile service. Through the distributed architecture, the requirements of massiveremote sensing data storage, management, visualization and data service one-stop processing in the big data era are met.

Description

technical field [0001] The invention relates to the technical field of massive remote sensing application services, in particular to a method and system for processing massive remote sensing data based on a distributed architecture. Background technique [0002] With the increase of remote sensing data acquisition methods, remote sensing data gradually presents the characteristics of multi-source, multi-scale, and multi-time equalization. However, the explosive growth of data volume has led to a sharp increase in remote sensing data information that needs to be processed, resulting in scattered and disordered storage of massive remote sensing data. The emergence of problems such as insecure security and difficult data retrieval. Massive remote sensing data mainly composed of raster files cannot be quickly shared and directly used. However, the technology based on commercial software image service publishing has a low degree of automation, untimely service provision, and it i...

AI Technical Summary

Problems solved by technology

For example, the invention patent authorized and announced on June 8, 2016 is "A One-Stop Processing Method for Remote Sensing Data Requirements" and the authorized announcement number is CN 103559327B. It provides an integrated online data service, archived data call, The remote sensing data of data production scheduling and programming data service requires a one-stop processing method, but this method still adopts the traditional technical route, focusing on the rapid distribution of data, and does not consider the management and visualization of massive remote sensing data; on August 10, 2018 The invention name of the authorized announcement is "A Big Data Remote Sensing Satellite Data Processing System Based on Hadoop", and the authorized announcement number is CN 105045856B. It is mainly based on the Hadoop data platform to realize the distributed storage and management of remote sensing satellite data, but Without converting remote sensing data into remote sensing map services, it is impossible to satisfy online visual browsing of massive remote sensing image data; the title of the invention published on December 3, 2019 is "A Method and System for Rapid Publishing and Browsing of Massive Image Services", and the publication number is The invention application of CN 110427446A proposes a set of image service release process, which utilizes server clusters for distributed file storage, distributed clipping and update of raster data, and compresses the data and stores them in distributed databases. The image service release is mainly Visual display is performed by reading distributed databases or direct original data drawing. Since there is no spatial data index, the query and browsing performance is low. In addition, the distributed computing framework is not considered to improve the computing and processing capabilities of image services.

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