that is fundamental to numerous environmentally fragile areas of the world, many of which seem to be perennially on the brink of disaster from famine. The project held the promise of developing and testing a set of options and methodologies for monitoring and providing near-real-time information about growing conditions and yield predictions of food grains for the inhabitants of a very large area across sub-Saharan Africa. Unfortunately, inadequate funding made it impossible to provide the kind of crop monitoring and early warning system that was envisioned, although the project was successful in demonstrating the potential benefits of using advanced technologies for such applications.

REFERENCES

LeComte, D.M. 1994. The NOAA/NESDIS impact assessment project for drought early warning in the Sahel. In Crop Modeling and Related Environmental Data: A Focus on Applications for Arid and Semiarid Regions in Developing Countries. P.F. Uhlir and G.C. Carter, eds. CODATA, Paris.

LeComte, D.M., F.N. Kogan, C.A. Steinhorn, and L. Lambert. 1988. Assessment of Crop Conditions in Africa. NOAA Tech. Memo. NESDIS AISC 13. NOAA, Washington, D.C.


McDonald, R.B., and F.G. Hall. 1978. LACIE: An experiment in global crop forecasting. Pp. 17–48 in Proceedings of the LACIE Symposium. JSC-14551. NASA Johnson Space Center, Houston, Tex.

McDonald, R.B., and F.G. Hall. 1980. Global crop forecasting. Science . 208: 670–679.


National Aeronautics and Space Administration (NASA). 1983. Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing (AgRISTARS). Res. Rep. AP-J2-0393. NASA, Washington, D.C.

National Oceanic and Atmospheric Administration (NOAA). 1985. Hydrologic and Land Science Applications of NOAA Polar-orbiting Satellite Data . National Environmental Satellite, Data, and Information Service , Washington, D.C.

National Research Council (NRC). 1987. Final Report: Panel on the National Oceanic and Atmospheric Administration Climate Impact Assessment Program for Africa. Office of International Affairs . National Academy Press, Washington, D.C.


Salby, M.L., H.H. Hindon, K. Woodberry, and K. Tanaka. 1991. Analysis of global cloud energy from multiple satellites. Bull. Am. Meteorol. Soc. 72(4): 467–480.


Tarpley, J.D., S.R. Schneider, and R.L. Money. 1984. Global vegetation indices from the NOAA-7 meteorological satellite. J. Clim. Appl. Meteorol, 23: 491–494.

Tucker, C.J., J.R.G. Townsend, and T.E. Goff. 1985. African land-cover classification using satellite data. Science 227: 369–375.



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