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Geospatial image information management  Mudit Mathur Squadron Leader Indian Air Force India E-mail: mr.mudit@gmail.com With the launch of each remote sensing (RS) satellite, the data is increasing exponentially both in content and usage. This paper also looks at some recent work on Geo-Spatial Data Production System (GSDPS), remote sensing, on-board information management system, photogrammetry and database system capable of managing a huge amount of RS images Today, multiple terrabytes of Remote Sensing data in the form of images and metadata are being collected by majority of nations across the globe, from diverse and complex space borne platform. It raises question how to process, manage, archive and make best use of the RS information, and share such a vast amount of RS images and value added data, which can benefit to the public at large, developmental projects besides stimulating the concepts and research developments. The need of the hour is mainly to provide an effective and efficient "connection" between the image providers, archivers and the image users, besides 'value adding ' (knowledge-base) to data downloaded and link them directly with the "demand and supply cycle" for optimum utilisation. During the past decade, the satellites have acquired large volume of data using sensors operating in different bands of spectrum, namely, Optical, microwave (synthetic aperture radar (SAR)) and other sensors, that have been systematically collected, processed and stored. The best available state of art systems provides queries mainly in the geospatial coordinates, time of acquisition and the scene types. This information is generally less relevant when compared to the context of the scene, such as pattern, tone, objects, structure, geometric, dielectric properties and scattering parameters etc.. Thus the comprehensive query of an image database is not carried out and lot of valuable contextual data is lost. It is understood after research and experience over the years that the data handling of imageries is different to any other file data handling due to the context-content knowledge-based associated with images. Today, there is a need to emphasise on the development of on-board geo-data base management system for the future EOS enabling end user to directly downlink satellite imagery for their specific area of interest in their work (Campbell et. al 2000, Prescoll et. al 1999, Zhou 2001, Zetocha 2000). One of the key challenges in this area is how to undertake on-board data distribution with autonomous distribution of data, and automatically retrieve other knowledge based information from the data sets of database and how these data sets will be updated and maintained automatically. The answer to these key issues lie in the philosophy of artificial intelligence, data mining algorithms and the concept of neural network along with the advantages of telecommunications.
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