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Proceedings Paper

Microwave remote sensing of soil moisture with vegetation effect
Author(s): Teferi D. Tsegaye; Ramarao Inguva; Roger H. Lang; Peggy E. O'Neill; Ahmed Fahsi; Tommy L. Coleman; Wubishet Tadesse; Narayan B. Rajbhandari; Sunnie A. Aburemie; Paolo de Matthaeis
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Paper Abstract

The objectives of this study were: to examine the sensitivity of radar backscatter, to estimate soil moisture under a corn plot and to evaluate the effectiveness and sensitivity of a Radiative Transfer Model (RTM), adapted from the earlier work of Njoku and Kong, (1977) in predicting brightness temperature from a grass plot. Microwave radar measurements were collected from plots of different vegetation cover types, vegetation density, and moisture conditions during the Huntsville 1998 field experiment. A large amount of ground data on brightness temperatures, soil moisture, and vegetation characteristics (e.g., biomass, and water content) were collected. The experiments were conducted at Alabama A&M University's, Winfred Thomas Agricultural Research Station, located near Hazel Green, Alabama. Six plots, one 50 X 60 m smooth bare plot, one 50 X 60 m grass plot, and four 30 X 50 m corn plots at full, 2/3, 1/2, and 1/3 densities were used. Radar backscatter data were obtained from a ground based truck mounted radar operating at L, C, and X bands (1.6, 4.75, and 10 GHz) with four linear polarization HH, HV, VV, and VH and two incidence angles (15 and 45 degrees). Soil moisture values were determined using Water Content Reflectometry (WCR). Three types of soil temperature sensors (Infrared Thermometer, Thermistor, and a 4-sensor averaging thermocouple probes) were used. A discrete backscatter approach model and RTM were evaluated. Comparisons between model prediction and experimental observation for HH polarization indicated good agreement for a corn full plot. The direct-reflected scattering coefficient is found to be the most dominant term for both polarization and the backscatter is also highly sensitive to soil moisture. The trends in time variation of brightness temperature are in agreement with the experimental results and the numerical results are within a few percent of the experimental results. The vegetation corrections as estimated by the Jackson and Schmugge method are very small. Detailed examination of the vegetation canopy contribution including the geometry of the canopy, the various absorption and scattering mechanisms are necessary.

Paper Details

Date Published: 17 December 1999
PDF: 12 pages
Proc. SPIE 3868, Remote Sensing for Earth Science, Ocean, and Sea Ice Applications, (17 December 1999); doi: 10.1117/12.373132
Show Author Affiliations
Teferi D. Tsegaye, Alabama A&M Univ. (United States)
Ramarao Inguva, East West Enterprise, Inc. (United States)
Roger H. Lang, George Washington Univ. (United States)
Peggy E. O'Neill, NASA Goddard Space Flight Ctr. (United States)
Ahmed Fahsi, Alabama A&M Univ. (United States)
Tommy L. Coleman, Alabama A&M Univ. (United States)
Wubishet Tadesse, Alabama A&M Univ. (United States)
Narayan B. Rajbhandari, Alabama A&M Univ. (United States)
Sunnie A. Aburemie, Clark Atlanta Univ. (United States)
Paolo de Matthaeis, George Washington Univ. (United States)


Published in SPIE Proceedings Vol. 3868:
Remote Sensing for Earth Science, Ocean, and Sea Ice Applications
Giovanna Cecchi; Edwin T. Engman; Eugenio Zilioli, Editor(s)

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