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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Microwave vegetation indices derived from satellite microwave radiometers

Authors
item Jackson, Thomas
item Shi, J - UNIV CA SANTA BARBARA
item Tao, J - BEIJING NORMAL UNIV

Submitted to: Proceedings of SPIE
Publication Type: Proceedings
Publication Acceptance Date: November 8, 2008
Publication Date: December 15, 2008
Citation: Jackson, T.J., Shi, J., Tao, J. 2008. Microwave vegetation indices derived from satellite microwave radiometers. In: Proceedings of the International Society of Optical Engineering, August 2-6, 2008, San Diego, California. p. 1-6.

Technical Abstract: Vegetation indices are valuable in many fields of geosciences. Conventional, visible-near infrared, indices are often limited by the effects of atmosphere, background soil conditions, and saturation at high levels of vegetation. In this study, the theoretical basis for a new type of passive microwave vegetation indices (MVIs) based on data from the Advanced Microwave Scanning Radiometer (AMSR-E) on the Aqua satellite is developed. Numerical simulation results were used to establish relationships of bare soil surface emissivities at different frequencies. Using a radiative transfer model, a linear relationship between the brightness temperatures observed at two adjacent radiometer frequencies can be derived. The intercept and slope of this linear function depend only on the vegetation properties and can be used as vegetation indices. These can be derived from the dual-frequency and dual-polarization satellite measurements under the assumption that there is no significant impact of the polarization dependence on the vegetation signals. To demonstrate the potential of the new microwave vegetation indices, we compared them with the Normalized Difference of Vegetation Index (NDVI) derived using MODIS at continental and global scales. The results indicate that the MVIs provide a complementary dataset for monitoring global short vegetation and seasonal phenology from space.

Last Modified: 8/1/2014
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