Experience of remote sensing information modelling with Grid computing

Abstract

In this paper, we focused on the remote sensing information modeling and determination using Grid computing platform. We have underdone the experiments using remotely sensed images for thermal inertial modeling in Condor system that is one of the Grid Projects existed nowadays worldwide. We divided remote sensing data into several parts and run them on Condor pool and on one single machine. From these tests, the relationship among the work efficiency of image processing in Condor system and the number of the separated parts of image and the number of machines in this system is presented. Given a certain number of machines, a most efficient image size is existed among varies sized images. Besides, the possible causes of the longer put-off in this process are given, and some possible methods to resolve this problem are also presented. It is feasible to use Grid computing system such as Condor to process remote sensing data. And if the postpone problem can be resolved, the work efficiency of Grid systems will be high. Even with so many problems, it is a good thing that Grid systems do many things for you during all of us are in sleep. Our next major task will concentrate on realizing an arithmetic that can read and divide remote sensing images based on image size and number of machines in Grid system automatically, and transfer results back to the submitted machine as a whole data file. © Springer-Verlag Berlin Heidelberg 2004.