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Real-time Dynamic Visualization Techniques for Massive Geospatial Data

机译:海量地理空间数据的实时动态可视化技术

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Visualization is a research hotspot in Digital Earth. Available Digital Earth platforms, such as Google Earth and World Wind could only display the prebuilt tiles of geospatial data statically, due to inability to deal with massive geospatial data (especially the remotely sensed imagery) and to adapt for diversified configurations of visualization in real time. In this paper, we propose a complete technical solution for real-time dynamic visualization of massive geospatial data, and mainly focus on the following aspects: a) On the rendering nodes, we build a pyramid model-'Fish File' to store a single remotely sensed imagery, to improve imagery reading efficiency, b) On the visualization server, we adopt a 'distributed storage, centralized management' strategy to organize and manage massive geospatial data, and further introduce a 'data-performance-consistent' schedule scheme to speed the response of servers, c) On the clients, the slicing cache storage and cache update mechanism are proposed for rapid switchover of map layers and geospatial analysis. Following the solution, we constructed a visualization platform. And we compare the performance of our platform with that of the state-of-the-art in rendering of nodes, in response of servers, and in efficiency of platforms, and show screenshots of real-time dynamic visualization.
机译:可视化是数字地球的研究热点。由于无法处理大量的地理空间数据(尤其是遥感图像),并且无法实时适应多样化的可视化配置,因此可用的Digital Earth平台(例如Google Earth和World Wind)只能静态显示地理空间数据的预制图块。在本文中,我们为海量地理空间数据的实时动态可视化提供了一个完整的技术解决方案,主要集中在以下几个方面:a)在渲染节点上,我们构建金字塔模型“鱼文件”来存储单个遥感图像,以提高图像读取效率,b)在可视化服务器上​​,我们采用“分布式存储,集中管理”策略来组织和管理海量地理空间数据,并进一步引入“数据性能一致”的计划方案以加快服务器的响应速度; c)在客户端上,提出了切片缓存存储和缓存更新机制,用于地图层的快速切换和地理空间分析。根据解决方案,我们构建了可视化平台。然后,我们将我们的平台性能与最新技术在节点渲染,服务器响应以及平台效率方面进行了比较,并显示了实时动态可视化的屏幕截图。

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