Algorithm science to operations for the National Polar-orbiting Operational Environmental Satellite System (NPOESS) visible/infrared imager/radiometer suite (VIIRS)
The VIIRS sensor provides measurements for 22 environmental data records (EDRs) addressing the atmosphere, ocean surface temperature, ocean color, land parameters, aerosols, imaging for clouds and ice, and more. That is, the VIIRS collects visible and infrared radiometric data of the Earth's atmosphere, ocean, and land surfaces. Data types include atmospheric, clouds, Earth radiation budget, land/water and sea surface temperature, ocean color, and low light imagery. This wide scope of measurements calls for the preparation of a multiplicity of algorithm theoretical basis documents (ATBDs), and, additionally, for intermediate products such as cloud mask, et al. Furthermore, the VIIRS interacts with three or more other sensors. This paper addresses selected and crucial elements of the process being used to convert and test an immense volume of a maturing and changing science code to the initial operational source code in preparation for launch of NPP. The integrity of the original science code is maintained and enhanced via baseline comparisons when re-hosted, in addition to multiple planned code performance reviews.
Science to operations: challenges, rewards, and pitfalls of converting algorithm science code to operational code
The NGST/Raytheon Contractor Team selected to build and operate the system has responsibility for both hardware and algorithms . This paper describes the process being used by the NGST/Raytheon team to convert science-grade algorithm code to operational code. Also discussed are the challenges, rewards, and pitfalls associated with the process of converting an evolving science-grade algorithm code to pre-launch operational code. A major challenge is dealing with two simultaneous feedback loops; one between the NGST and the sensor vendor; another between NGST and its Raytheon partner to convert an evolving and immature science product to an operational product.
DEM generation from new VIR sensors: IKONOS, ASTER and Landsat-7
DEM generation is a living R&D topic since new-launched satellite images can be used to generate stereoscopic images. Using a coplanarity equation model developed at CCRS and an automatic matching method developed at PCI, DEMs are generated with new VIR stereo data. Accuracy of 4.9 m with high-resolution IKONOS images, and 33 m and 101 m with medium-resolution ASTER and Landsat-7 ETM/sup +/ images respectively are obtained. The same matching accuracy of one-pixel is translated into worse results with Landsat due to a small B/H ratio of 0.15.