Eni G. Njoku
 
Jet Propulsion Laboratory, M/S 300-233
4800 Oak Grove Drive
Pasadena, CA 91109, USA
Tel: 818-354-3693; Fax: 818-354-9476;
E-mail: eni.g.njoku@jpl.nasa.gov


Research has involved theoretical, experimental, and space system studies of microwave emission from land surfaces, focusing on retrieval of soil moisture, vegetation water content, and surface temperature. He was a member of the algorithm development teams for the Scanning Multichannel Microwave Radiometer (SMMR) instruments on the Seasat and Nimbus-7 satellites, and is currently a member of the science team for the Advanced Microwave Scanning Radiometer (AMSR) to be launched on EOS PM and ADEOS-II in late 2000. He is a Principal Investigator for a dual-polarized passive/active L/S-band airborne sensor recently developed for soil moisture and salinity studies.
 

Entekhabi, D., H. Nakamura, and E. G. Njoku, "Solving the inverse problem for soil moisture and temperature profiles by sequential assimilation of multifrequency remotely sensed observations", IEEE Trans. Geosci. Rem. Sens., 32, 438-448, 1994.

Njoku, E. G., "Surface temperature estimation over land using satellite microwave radiometry", in: Passive Microwave Remote Sensing Research Related to Land-Atmosphere Interactions (B. J. Choudhury, Y. H. Kerr, E. G. Njoku, P. Pampaloni, Eds.), VSP Press, The Netherlands, 1995.

Wegmuller, U., C. Matzler, and E. G. Njoku, "Canopy opacity models", in: Passive Microwave Remote Sensing Research Related to Land-Atmosphere Interactions (B. J. Choudhury, Y. H. Kerr, E. G. Njoku, P. Pampaloni, eds.), VSP Press, The Netherlands, 1995.

Njoku, E. G. and D. Entekhabi, "Passive microwave remote sensing of soil moisture", J. Hydrology, 184, 101-129, 1996.

Njoku, E. and L. Li, "Retrieval of land surface parameters using passive microwave measurements at 6 to 18 GHz," IEEE Trans. Geosci. Rem. Sens., (in press).

Role in the SMOS mission:

Improved methods to retrieve soil moisture from the mission's multichannel data will be investigated, including available ancillary data, in an optimal framework. Experiences with the AMSR algorithms and data will be incorporated. Data acquired by the JPL airborne sensor in field campaigns, if succesful, will be made available for algprithm development and valid.