海量遥感影像数据集的高效管理与调度

Jiankun Zhu, Zhen Zhang, Fei Zhao, Haoran Su, Zhengnan Gu, Leilei Wang
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引用次数: 0

摘要

随着遥感图像传感器技术的快速发展,可用图像数据呈指数级增长。千兆级图像的实时调度以及海量图像数据集的存储和管理对于当前的硬件、网络和存储系统来说都是极具挑战性的。本文设计了环缓存、多线程和块预取机制三种新策略,从图像检索、传输和可视化的角度对遥感图像调度过程进行了综合优化。以这三种策略为核心算法,以PostgreSQL数据库和HDFS分布式文件系统为底层存储系统,采用多层Hilbert空间索引和图像块金字塔对海量遥感图像数据集进行组织,设计了一种新型的遥感图像管理与调度系统(RSIMSS)。测试结果表明,RSIMSS提供了高效稳定的图像存储性能,并支持实时图像调度和视图漫游。
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Efficient Management and Scheduling of Massive Remote Sensing Image Datasets
The rapid development of remote sensing image sensor technology has led to exponential increases in available image data. The real-time scheduling of gigabyte-level images and the storage and management of massive image datasets are incredibly challenging for current hardware, networking and storage systems. This paper’s three novel strategies (ring caching, multi-threading and tile-prefetching mechanisms) are designed to comprehensively optimize the remote sensing image scheduling process from image retrieval, transmission and visualization perspectives. A novel remote sensing image management and scheduling system (RSIMSS) is designed using these three strategies as its core algorithm, the PostgreSQL database and HDFS distributed file system as its underlying storage system, and the multilayer Hilbert spatial index and image tile pyramid to organize massive remote sensing image datasets. Test results show that the RSIMSS provides efficient and stable image storage performance and allows real-time image scheduling and view roaming.
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