The Research of Collaborative System of Remote Sensing Monitoring Based on Bimodal Cloud

Kaijun Yang, Fan Lei, Li Cao, Jide Wei, Zhe Zhang
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Abstract

Abstract. Cloud service is based on cloud computing, Offering a On-Demand service to every terminal equipment of computing resource pool. This paper designed and developed a coordinated operating system based on bimodal cloud. This system is taken mutual scheduling mechanism into account, which is capable of storing massive amounts of heterogeneous remote sensing data and provides fast indexing of data based on various characteristics, integrated Satellite transit forecast, DOM Produce, coordinated change information extraction and results sharing based on Nginx load balancing, in addition, the system designed two layer security system to ensure the safety of data results.The "YunYao" geographic information service rendering engine built on the dual-state cloud platform significantly outperforms mainstream platforms in the same testing environment. Its rendering speed surpasses ArcGIS Desktop by more than two times, exceeds GeoServer by more than four times, and is over seven times faster than ArcGIS Server. Remote sensing practitioners can quickly and conveniently utilize this system, while providing convenient functionalities that enable remote sensing scientists to independently conduct scientific research and development using this system. Experimentation and practice shows that this system simplified routine work flow, improved work efficiency, has a important reference meaning to remote sensing monitoring.
基于双模云的遥感监测协作系统研究
摘要云服务是以云计算为基础,向每个终端设备提供按需服务的计算资源库。本文设计并开发了一种基于双模云的协调操作系统。基于双态云平台构建的 "云遥 "地理信息服务渲染引擎在相同测试环境下的表现明显优于主流平台。其渲染速度超过 ArcGIS Desktop 2 倍以上,超过 GeoServer 4 倍以上,超过 ArcGIS Server 7 倍以上。遥感工作者可以方便快捷地使用该系统,同时该系统提供的便捷功能使遥感科学家可以利用该系统独立进行科学研究和开发。实验和实践表明,该系统简化了日常工作流程,提高了工作效率,对遥感监测具有重要的借鉴意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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