Observing the world‐wide concentration and distribution of ozone is important for monitoring the evolution of the ozone layer, to derive the amount of UV, to provide ozone and UV forecasts and to improve weather forecasting. Monitoring ozone is the primary function of the Global Ozone Monitoring Experiment. Each day, space missions download, from space to ground, many raw images that are stored in ground stations located all over the world. How to process this data resource in real time — or almost real time — and effectively share spatial information among the remote sensing community is a pressing task. Grid computing can provide access to a globally distributed computing environment via authentication, authorization, negotiation and security. It can create a computational environment handling many PetaBytes of geographically distributed data, tens of thousands of heterogeneous computing resources and thousands of simultaneous users from many research institutions. It can provide a powerful tool for sharing both remote sensing data and processing middleware. This paper introduces the concept of grid computing, followed by its applications for atmospheric ozone retrieval. The special remote sensing data analysis note for the Spatial Information Grid (SIG) is addressed in detail. A series of remotely sensed image processing middleware is shown. Experience shows that near‐real‐time products, such as maps of ozone, from the processing and analysis of remotely sensed data are possible.
Department of Computing, London Metropolitan University, 166–220 Holloway Road, London N7 8DB, UK 2:
Laboratory of Remote Sensing Information Sciences, Institute of Remote Sensing Applications, Chinese Academy of Sciences, P. Box 9718, Beijing 100101, China