Massive Spatial Data Processing Model Based on Cloud Computing Model

Dong Cui, Yunlong Wu, Qiang Zhang
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引用次数: 28

Abstract

Cloud computing model can take advantage of the network resources, creating a powerful computing capacity to meet the real-time processing a large amount of spatial data. So this paper showed a cloud computing model based on a large amount of spatial data processing model. It used not only controller to implement the distribution of spatial data processing tasks but cloud computing power to achieve the corresponding supervised classification and unsupervised classification as well as the surface features information extraction, the extraction of NDVI (Normal Differential Vegetation Index), and made it possible to monitor the application and rapid flooding and the realization of real-time monitoring for dust storms. Forest fires can be used in monitoring, timely understanding of the spread of fire, as well as control of key areas. At the same time, in the aspect of environmental protection, the system can be applied to the ozone layer and the monitoring of glacier flow and determine the direction of study. While the ocean remote sensing can provide real-time data processing of marine red tide monitoring data, and propose feasible solutions.
基于云计算模型的海量空间数据处理模型
云计算模型可以利用网络资源,创建强大的计算能力,满足对大量空间数据的实时处理。为此,本文提出了一种基于海量空间数据处理模型的云计算模型。利用控制器实现空间数据处理任务的分配,利用云计算能力实现相应的监督分类和无监督分类,提取地物信息,提取NDVI (Normal Differential Vegetation Index,正常植被差异指数),实现对应用和快速洪水的监测,实现对沙尘暴的实时监测。可用于森林火情监测,及时了解火情蔓延情况,以及对重点区域进行控制。同时,在环境保护方面,该系统可应用于臭氧层和冰川流量的监测,确定研究方向。而海洋遥感可以对海洋赤潮监测数据进行实时数据处理,并提出可行的解决方案。
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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