Distributed High Performance Computation for Remote Sensing

We describe distributed and parallel algorithms for processing remotely sensed data such as geostationary satellite imagery. We have built a distributed data repository based around the client-server computing model across wide-area ATM networks, with embedded parallel and high performance processing modules. We focus on algorithms for classification, georectification, correlation and histogram analysis of the data. We consider characteristics of image data collected from the Japanese GMS5 geostationary meteorological satellite, and some analysis techniques we have applied to it. As well as providing a browsing interface to our data collection, our system provides processing and analysis services on-demand.