CiC: EAGER: CCollaborative: GIS Vector Data Overlay Processing on Azure Platform

CiC：EAGER：CCollaborative：Azure 平台上的 GIS 矢量数据叠加处理

• 批准号: 1048200
• 负责人: Sushil Prasad
• 金额: $ 20万
• 依托单位: Georgia State University Research Foundation, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1048200&HistoricalAwards=false
• 关键词: CiC; EAGER; CCollaborative; GIS; Vector

This collaborative project is focused on GIS vector-based spatial data overlay processing through cloud computing. Vector-based processing is considerably more complicated than raster data processing because raster data is based on regular grid-based fixed-size pixels, while vector features have irregular geometric shapes represented by a list of large number of vertices. GIS data files can be very large-scale huge and as such, computational requirements are significant. Cloud platforms such as Azure are appropriate for large-scale computing and storage capabilities. These capabilities combined with accessibility on-demand and other features have made cloud processing very desirable for GIS applications. This exploratory research will attempt to discover distributed algorithms and test their scalable implementations for GIS overlay processing on the Azure platform.

该协作项目的重点是通过云计算基于GIS矢量的空间数据覆盖处理。 基于向量的处理比栅格数据处理要复杂得多，因为栅格数据基于常规的基于网格的固定大小像素，而矢量特征具有不规则的几何形状，由大量顶点列表表示。 GIS数据文件可能非常大，因此计算要求很大。 诸如Azure之类的云平台适合大规模计算和存储功能。 这些功能结合了按需和其他功能的可访问性，使GIS应用程序非常需要云处理。 这项探索性研究将试图发现分布式算法并测试其在Azure平台上为GIS覆盖处理的可扩展实现。