基于NoSQL的高分高光谱遥感影像存储模型设计与实现

王晓蕊; 杨强根; 陈凤敏; 马维峰; 唐湘丹; 谭兴; 张时忠

doi:10.3799/dqkx.2015.128

Volume 40 Issue 8

Aug. 2015

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Article Navigation > Earth Science > 2015 > 40(8): 1420-1426

Wang Xiaorui, Yang Qianggen, Chen Fengmin, Ma Weifeng, Tang Xiangdan, Tan Xing, Zhang Shizhong, 2015. Storage Model Design and Implementation of High Resolution and Hyperspectral Remote Sensing Image Based on NoSQL. Earth Science, 40(8): 1420-1426. doi: 10.3799/dqkx.2015.128

Citation:

Wang Xiaorui, Yang Qianggen, Chen Fengmin, Ma Weifeng, Tang Xiangdan, Tan Xing, Zhang Shizhong, 2015. Storage Model Design and Implementation of High Resolution and Hyperspectral Remote Sensing Image Based on NoSQL. Earth Science, 40(8): 1420-1426. doi: 10.3799/dqkx.2015.128

Citation:

Wang Xiaorui, Yang Qianggen, Chen Fengmin, Ma Weifeng, Tang Xiangdan, Tan Xing, Zhang Shizhong, 2015. Storage Model Design and Implementation of High Resolution and Hyperspectral Remote Sensing Image Based on NoSQL. Earth Science, 40(8): 1420-1426. doi: 10.3799/dqkx.2015.128

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Storage Model Design and Implementation of High Resolution and Hyperspectral Remote Sensing Image Based on NoSQL

doi: 10.3799/dqkx.2015.128

1.
Faculty of Earth Resources, China University of Geosciences, Wuhan 430074, China
2.
Network and Educational Technologies Center, China University of Geosciences, Wuhan 430074, China
3.
Wuhan InfoEarth Information Co. Ltd., Wuhan 430074, China
4.
College of Computer Science, China University of Geosciences, Wuhan 430074, China

Received Date: 2015-03-25
Publish Date: 2015-08-01

Abstract

Abstract

It is an issue to be addressed as how to efficiently store and manage massive data that in high resolution and high spectral remote sensing images, and achieve rapid processing, retrieval and visualization of remote sensing data is the problem to be solved. Using non-relational database technology, we designed massive image storage model consists of remote sensing metadata database, image database and image pyramid; set up the remote sensing image storage middleware that consists of the hardware support layer, data layer, data service layer, and application layer. Experiment verifies the remote sensing image data storage model and middleware that based on non-relational database is superior to relational database for video data read and write. Research results prove have great practical value for efficiently storage and management of massive remote sensing image data.
- remote sensing image,
- not only structured query language(NoSQL),
- metadata,
- pyramid

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References(24)

References

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Storage Model Design and Implementation of High Resolution and Hyperspectral Remote Sensing Image Based on NoSQL

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