首页> 外文会议>Geoscience and Remote Sensing, 1997. IGARSS '97. Remote Sensing - A Scientific Vision for Sustainable Development., 1997 IEEE International >Visualization of satellite derived time-series datasets using computer graphics and computer animation
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Visualization of satellite derived time-series datasets using computer graphics and computer animation

机译:使用计算机图形和计算机动画可视化卫星衍生的时间序列数据集

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The German Remote Sensing Data Centre (DFD) of the German Aerospace Research Establishment (DLR) is operationally generating remote-sensing based time series datasets. These datasets can be used for example for environmental, climatological and atmospherical research. Bearing in mind the enormous amount of data already generated at DLR from today's missions, even with a comfortable search-engine like ISIS (provided by DLR) it is a major problem to identify those datasets most suitable for a specific research task. Looking into the future, data quantities will increase with new missions like ENVISAT. Therefore, it appears essential to provide the user-community with efficient tools to explore and evaluate these time series-datasets. Visualization forms the most efficient way to explore the contents of vast data quantities and to identify the subsets showing the phenomena of interest in a relatively short time. Synthesis with secondary remote sensing data for visualization offers the possibility of multidimensional data exploration. Finally, visualization is essential for the presentation of a projects purpose and its results. Data gaps in time-series form a problem in visualization as they are prohibitive for stable movement in computer animation. For this reason different interpolation techniques have been developed primarily for atmospheric sensors and now prove to be a valuable tool for interpolation of other remote sensing datasets. A video presentation showing examples of films created at DLR are given.
机译:德国航空航天研究建立(DLR)的德国遥感数据中心(DFD)正在运行地生成基于遥感的时间序列数据集。这些数据集可用于例如环境,气候和大气的研究。考虑到今天的任务中已经在DLR生成的大量数据,即使是ISIS(DLR提供的舒适搜索引擎)也是一个主要问题,可以识别最适合特定研究任务的数据集。展望未来,数据量将随着Envisat等新任务而增加。因此,它似乎是向用户社区提供有效的工具来探索和评估这些时间序列数据集。可视化形成探索庞大数据量的内容的最有效方法,并识别在相对较短的时间内显示兴趣现象的子集。具有用于可视化的辅助遥感数据的合成提供了多维数据探索的可能性。最后,可视化对于呈现项目目的和结果至关重要。数据序列中的数据间隙在可视化中形成了一个问题,因为它们在计算机动画中稳定的运动稳定。因此,已经主要用于大气传感器的不同的插值技术,现在证明是用于插值的其他遥感数据集的宝贵工具。给出了显示在DLR上产生的薄膜的示例的视频介绍。

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