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MU Internet 2/vBNS Projects

Joint University of Missouri-Columbia/NASA Regional Validation Center

Project Leaders: K. Palaniappan, CECS; J. Engel, Geological Sciences; C. Fulcher, Center for Agricultural Resources;
T. Haithcoat, Geo. Resource Center; D. Diamond, MoRAP


The MU Regional Validation Center will consist of ground station hardware for receiving both GOES-8 and GOES-9 environmental satellite GVAR data using real-time direct readout systems. The system consists of a 12' Paraclipse satellite dish, with Integrated Feed/Downconverters, ISA bus-based BPSK receiver, ISA bus-based Bit Frame Synchronizer and Frame Formatter. Processing of the GVAR data stream signal at approximately one gigabyte per hour is accomplished using a Quorum GVAR Data Server based on an Intel Advanced ZE Minitower 166 MHz Pentium computer.

This high volume data stream will be shared via high speed networks such as 100BaseT and ATM with other research groups on campus and in the vicinity including the Departments of Computer Engineering and Computer Science, Electrical Engineering, Soil and Atmospheric Science, Center for Agricultural Resources Environmental Systems (CARES) in the Department of Agricultural Economics, Geographic Resources Center (GRC) in the Department of Geography, Geology, Missouri Resources Assessment Project (MORAP), Agronomy, and others. The real-time GOES satellite data will also be shared with collaborators on joint projects at other institutions such as NASA Goddard Space Flight Center, University of Wisconsin-Madison, University of Washington-Seattle, University of Arizona-Tucson, and the University of Tennessee.

Instrumentation in terms of GOES-8 and GOES-9 satellite GVAR data receiving systems, supercomputer class computational servers and visualization platforms will be used to explore new computational techniques for: (1) processing real-time remote sensing data, (2) distributed client-server visualization of extremely large remote sensing datasets (such as digital terrain elevation data) with automatic level-of-detail management using multiresolution and graph theoretic dynamic contraction methods, (3) fusion of measured satellite observations with model data, (4) information visualization of multidimensional time varying datasets, (5) data exploration and learning tasks applied to intercomparison of remote sensing data, and (6) ground and in-situ based validation of automatic cloud height and cloud motion vector estimation for input to numerical weather modeling and improving short range forecasting. Many of these analysis algorithms require access to supercomputers at NASA GSFC and JPL for timely processing of real-time data.

Science areas that can be investigated include: (1) impact of urbanization on watersheds, (2) improving short term forecasting of severe weather such as tornadoes and flooding potential using MM5 assimilated satellite observations, (3) predicting surface skin temperature and heat stress index using MM5 model forecasts with assimilated satellite observations for application to energy demand modeling by power utility companies and livestock management (such as effect on milk production) by agribusinesses, (4) correlating field measurements of plant health and crop stress with GOES remote sensing data similar to the AVHRR-based NDVI ratio at the state and regional scale, (5) linking remote sensing observations with economic impact and decision support tools for application to commodity pricing, etc., (6) combining multiresolution, multi-source datasets with automatic pixel classification for natural resource assessment and conservation, (7) estimating soil moisture at the regional scale for assessing environmental deterioration due to soil erosion and flooding, and (8) intelligent management of state transportation facilities through integration with real-time weather data.

The MU Regional Validation Center will be an ideal test bed for developing innovative teaching and educational curricula related to remote sensing and real-time satellite data handling in the environmental and computational science and engineering fields. The Regional Validation Center test bed can also be used as a training center in real-time satellite data processing by state and national agencies and consortia such as MORAP.

The campus wide ATM backbone and vBNS connection will provide fast network access to the real-time satellite data acquired by the direct-readout data system. In addition, the real-time data will also be routinely made available for wide area access using Web protocols via the Internet. All of these activities require high bandwidth and low latency capabilities. Without such capabilities, this project would not be feasible.


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