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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.