DocumentCode :
3312166
Title :
Massive Spatial Data Processing Model Based on Cloud Computing Model
Author :
Cui, Dong ; Wu, Yunlong ; Zhang, Qiang
Author_Institution :
Sch. of Inf. & Electron. Eng., Hebei Univ. of Eng., Handan, China
Volume :
2
fYear :
2010
fDate :
28-31 May 2010
Firstpage :
347
Lastpage :
350
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.
Keywords :
Internet; data mining; geophysics computing; remote sensing; spatial data structures; NDVI; cloud computing model; dust storms; information extraction; massive spatial data processing model; network resources; normal differential vegetation index; real-time monitoring; real-time processing; supervised classification; unsupervised classification; Cloud computing; Computer networks; Data mining; Data processing; Feature extraction; Fires; Floods; Remote monitoring; Sea surface; Vegetation mapping; cloud computing; distributed computing; mass data storage; remote sensing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Science and Optimization (CSO), 2010 Third International Joint Conference on
Conference_Location :
Huangshan, Anhui
Print_ISBN :
978-1-4244-6812-6
Electronic_ISBN :
978-1-4244-6813-3
Type :
conf
DOI :
10.1109/CSO.2010.168
Filename :
5532992
Link To Document :
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