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With the rapid advancement in remote sensing technology and corresponding applications, the Earth Observation Ground Segment has undergone a significant change at NRSA. From dedicated data acquisition and processing systems, we have realized multi-mission data acquisition quick look and browse systems and also multi-mission integrated information management systems. Front end of data reception station has been upgraded to handle wider bandwidth and data rates up to 320 Mbps for near future missions such as the Radar Imaging Satellite (RISAT). Antenna, feed, down converters and RF chain have been upgraded. To cater to multi-mission scenario mission independent, fully configurable demodulator/bit synchs have been deployed. For handling data acquisition in multi-satellite scenario where in data from 5 to 6 remote sensing satellites are to be received almost simultaneously, automation of operations has been incorporated towards station configuration to avoid manual errors. From media-based data handling, there has been a shift towards net centric data handling among the various work centers such as user order processing, data processing systems, special processing systems, data quality evaluation, and product quality control work centers. The turn around time for dissemination of user desired data products has been improved from two weeks to one day. Presently a state of the art integrated environment has been envisaged which will bring down the turn around time for the supply of data products significantly. Automation has been incorporated at both data acquisition and data processing to improve the product throughput. Presently NRSA is catering to a demand of about 30,000 data products per annum and in the next two years it is aimed to reach a level of 50,000 products per annum by realizing the integrated multi-mission ground system for earth observation (IMGEOS). This will significantly modify the entire data production and dissemination chain so that data can be made available to user within 1 h from data acquisition at Shadnagar in some cases. Some of these novel developments planned in the near future will be discussed in this paper.  相似文献   
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Object-based representations of spatial images   总被引:1,自引:0,他引:1  
Object based representations of image data enable new content-related functionalities while facilitating management of large image databases. Developing such representations for multi-date and multi-spectral images is one of the objectives of the second phase of the Alexandria Digital Library (ADL) project at UCSB. Image segmentation and image registration are two of the main issues that are to be addressed in creating localized image representations. We present in this paper some of the recent and current work by the ADL's image processing group on robust image segmentation, registration, and the use of image texture for content representation. Built upon these technologies are techniques for managing large repositories of data. A texture thesaurus assists in creating a semantic classification of image regions. An object-based representation is proposed to facilitate data storage, retrieval, analysis, and navigation.  相似文献   
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