Spatial data processing on high performance computation architectures

D. Gorgan
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引用次数: 1

Abstract

Spatial data models are complex and huge for large geographical area and high resolution. The management, the processing, and the visualization of such extensive models require high performance computation architectures, heterogeneous software platforms, and new methodologies for development and execution of Earth Science applications. The presentation highlights these challenges by exemplifying the gSWAT, GreenLand, and eGLE applications, developed through the enviroGRIDS project, and available in the BSC-OS Portal. It is presented as well the work of other related research projects such as the BIGEARTH project on spatial big data analysis and processing.
基于高性能计算架构的空间数据处理
对于大地理区域和高分辨率的空间数据模型来说,空间数据模型是复杂而庞大的。管理、处理和可视化这些广泛的模型需要高性能的计算架构、异构的软件平台,以及开发和执行地球科学应用程序的新方法。该报告通过举例说明通过enviroGRIDS项目开发的gSWAT、GreenLand和eGLE应用程序,并在BSC-OS门户网站上提供这些应用程序,突出了这些挑战。本文还介绍了空间大数据分析与处理的BIGEARTH项目等相关研究项目的工作。
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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