Khankhoje, Uday K. | Search NASA

NASA NTRS2012

Using Polarimetric SAR Data to Infer Soil Moisture from Surfaces with Varying Subsurface Moisture Profiles

A time-series approach is used to estimate the moisture content-based on polarimetric SAR data. It is found that under the assumption of constant soil moisture, empirically observed relationships between radar backscatter and moisture are only half as sensitive to moisture as compared to actual radar data. A numerical finite element method is used to calculate the radar backscatter for rough soils with arbitrarily varying soil moisture as a function of depth. Several instance of drying and wetting moisture profiles are considered and the radar backscatter is calculated in each case. Radar backscatter is found to crucially depend on the soil moisture variation in the top half wavelength of soil.

subsurface sensing↗

NASA NTRS2011

Normal Incidence for Graded Index Surfaces

A plane wave is incident normally from vacuum (eta(sub 0) = 1) onto a smooth surface. The substrate has three layers; the top most layer has thickness d(sub 1) and permittivity epsilon(sub 1). The corresponding numbers for the next layer are d(sub 2); epsilon(sub 2), while the third layer which is semi-in nite has index eta(sub 3). The Hallikainen model [1] is used to relate volumetric soil moisture to the permittivity. Here, we consider the relation for the real part of the permittivity for a typical loam soil: acute epsilon(mv) = 2.8571 + 3.9678 x mv + 118:85 x mv(sup 2).

plane wave↗