Estimate relative soil moisture change with multi-temporal L-band radar measurements

Abstract

In this study, we evaluate the effect of the surface roughness on estimation of the relative soil moisture change in repeat-pass L-band radar measurements. It has found the surface roughness has a significant impact and a correction technique has been developed. I. INTRODUCTION During recent years, theoretical modeling and field experiments have established the fundamentals of active microwave remote sensing as an important tool in determining physical properties of soil. In attempt to use active microwave remote sensors in estimation of soil moisture, we are mainly facing two major problems: effects of surface roughness and vegetation cover. There are several algorithms developed for measurement of bare soil moisture quantitatively using dual or three polarization L-band SAR image data. A common idea beyond these algorithms is to separate the effects of the surface dielectric and roughness properties on the backscattering signals to present the model, which the inversion was based on, as a product of a dielectric function and a roughness function. They are first-order statistical inversion models. Depending on the data source, the selection of the surface roughness parameters and the backscattering measurements of the different polarizations or their linear combinations, the models have a great difference in terms of both the dielectric and roughness functions. The temporal variability of surface roughness is generally at much longer time scale than that of soil moisture, unless there was a human activity. Commonly, we can reasonably assume that the surface roughness is same at certain time interval. The change in SAR measurements between the repeat-passes, therefore, is resulted from the change of ground dielectric properties or soil moisture. Therefore, the repeat-pass measurements provide additional relative surface soil moisture change information and make it possible to directly estimate the relative moisture change and improving the accuracy of estimating the bare surface soil moisture. However, there has no quantitative algorithm being developed to estimate the relative soil moisture change using repeat-pass measurements. In this study, we evaluate 1) the effects of surface roughness in L-band repeat-pass measurements using IEM simulated data, 2) developing a quantitative algorithm to estimate relative soil moisture change, and 3) validating this technique with JPL/AIRSAR 92's experiment data over the little Washita test site.