Publication Date:
2019-07-13
Description:
In the past the effect of soil roughness was often considered secondary within the determination of soil moisture from remote sensing data. Several studies showed that accurate determination of soil roughness leads to an improved estimation of soil moisture. Two default parameters to describe the surface roughness are the standard deviation of the surface height variation and the surface correlation length with its corresponding autocorrelation function. Both parameters (,) affect the emissivity measured by radiometers as well as the backscattering observed by radars. In this study, we develop a physics-based approach to retrieve and by combining both microwave signals based on active-passive microwave covariation. To test the approach, containing a forward model and a retrieval algorithm, we used active/passive microwave data measured with the ComRAD truck-based SMAP simulator at L-band. Results and validations with corresponding field measurements on ground show that and can be estimated simultaneously when using this approach. The physics-based retrieval algorithm works robustly for two investigated test fields having an RMS-Error of 0.68 cm and 0.69 cm between the microwave-based and field-measured -values, and of 3.13 cm and 3.04 cm for -values. The first validation of the results reveals that the influence of the autocorrelation function, needed within the retrieval, is distinct.
Keywords:
Earth Resources and Remote Sensing
Type:
GSFC-E-DAA-TN58403
,
International Geoscience and Remote Sensing Symposium (IGARSS 2018); Jul 22, 2018 - Jul 27, 2018; Valencia; Spain
Format:
application/pdf
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