Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 257-263, 2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
27 Nov 2014
INSAT-3D Quality Analysis System (i3dQAS)
D. Jindal1, S. Prakash1, J. Sanghvi2, B. Kartikeyan1, and B. Gopala Krishna1 1Image Analysis and Quality Evaluation Division, SPDCG, SIPA, SAC, ISRO, Satellite, Ahmedabad-380 015, Gujarat, India
2Globaltech (I) Pvt. Ltd., Bodakdev, Ahmedabad-380 054, Gujarat, India
Keywords: DQE, Geometric accuracy, Radiometric Quality, Payload health, Level-0, i3dQAS, Quality Database Abstract. INSAT-3D, an advanced meteorological satellite of ISRO carrying Imager and Sounder payloads is designed for acquiring data required for detailed climatological applications. At established data centres, Raw (L-0) data is processed to generate systematically corrected (Level-1) and geo-physical (Level-2) products which are further disseminated for use in climate related studies. Data quality evaluation (DQE) of basic data products of INSAT-3D is being operationally carried out at MOSDAC, Ahmedabad to monitor in-orbit sensor health, quantify data quality and provide feedback to various missions teams for corrective actions. DQE methodology and quality parameters have been defined keeping in view repeatability of data acquisition and quality requirements of meteorological data. In this paper, we have described INSAT-3D Quality Analysis System (i3dQAS) designed to facilitate effective data quality monitoring through web based portal. Overall context of i3dQAS in a typical data centre set-up, major objectives and design aspects to highlight the architectural and functional view of system are described. Utility of i3dQAS for mission monitoring is described through analysis scenarios for monitoring payload health and geometric accuracy of Imager.
Conference paper (PDF, 1072 KB)

Citation: Jindal, D., Prakash, S., Sanghvi, J., Kartikeyan, B., and Gopala Krishna, B.: INSAT-3D Quality Analysis System (i3dQAS), Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 257-263,, 2014.

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