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Estimation of soil moisture and surface roughness parameters from backscattering coefficient

Journal Article · · IEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers); (United States)
DOI:https://doi.org/10.1109/36.263781· OSTI ID:5289790
;  [1];  [2]
  1. NASA, Greenbelt, MD (United States). Goddard Space Flight Center
  2. CSRE, Indian Inst. of Tech., Bombay (India)

A statistical inversion technique was implemented to estimate soil moisture and surface roughness parameters from the remotely sensed multifrequency backscattering coefficients. Both two- and three-frequency approaches were examined and tested in detail for the inversion technique. Initially the technique was tested with a simulated data set generated from various scattering models. Later it was applied to an experimental data set that provided, for a wide range of surface roughness and soil moisture, backscattering coefficients at many incidence angles and frequencies. It was found that, in general, the three-frequency approach produce more accurate results. However, under a favorable combination of frequencies and incidence angles, both approaches give results with a comparable accuracy. There is a potential that soil moisture could be estimated to an accuracy of about 2%. In the mean time the surface roughness parameters could be estimated to an accuracy of better than 10%.

OSTI ID:
5289790
Journal Information:
IEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers); (United States), Journal Name: IEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers); (United States) Vol. 31:5; ISSN IGRSD2; ISSN 0196-2892
Country of Publication:
United States
Language:
English

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