Integration of remote sensing intelligent processing algorithm using container cloud technology

Zhitao ZHAO; Lijun ZHAO; Zheng ZHANG; Ping TANG

doi:10.11959/j.issn.2096-0271.2022015

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Integration of remote sensing intelligent processing algorithm using container cloud technology

TOPOC: AEROSPACE BIG DATA | 更新时间：2024-06-03

- Integration of remote sensing intelligent processing algorithm using container cloud technology
- Big data research Vol. 8, Issue 2, Pages: 58-74(2022)
- 作者机构：
  
  1. 中国科学院空天信息创新研究院，北京 100094
  2. 中国科学院大学资源与环境学院，北京 100049
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2022015
  CLC： TP75
- Online First：2022-03，
  
  Published：15 March 2022
- 稿件说明：
移动端阅览
Zhitao ZHAO, Lijun ZHAO, Zheng ZHANG, et al. Integration of remote sensing intelligent processing algorithm using container cloud technology[J]. Big data research, 2022, 8(2): 58-74.
DOI：

Zhitao ZHAO, Lijun ZHAO, Zheng ZHANG, et al. Integration of remote sensing intelligent processing algorithm using container cloud technology[J]. Big data research, 2022, 8(2): 58-74. DOI： 10.11959/j.issn.2096-0271.2022015.

摘要

针对当前航天遥感信息处理向云计算发展的趋势，将容器云技术应用于遥感数据的智能处理，通过在计算集群中部署遥感解译算法镜像与分布式存储服务，屏蔽复杂的环境依赖问题，并通过配置文件进行流程管理，形成了从开发到部署的整体技术路线，为遥感智能解译技术的集成提供了高效可靠的新思路。以几种典型的遥感智能解译算法为例，证明了该方案在智能解译模型的集成化开发部署上的高效性，为遥感智能解译技术的新型云端模式探索了可行性方案。

Abstract

With the development of cloud computing technology in remote sensing data processing

container cloud technology was applied to remote sensing data processing

remote sensing intelligent processing algorithm image was deployed and storage services were distributed in the computing cluster

shielding complex environmental dependence problems.And management through configuration files was processed forming an overall technical route from development to deployment

which provides an efficient and reliable new scheme for the integration of remote sensing intelligent processing algorithms.Taking several typical remote sensing intelligent algorithms as examples

the efficiency of the scheme in the integrated development and deployment was proved

and the feasibility of the new cloud mode of remote sensing intelligent technology was explored.

关键词

Keywords

references

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