SCALING ANALYSIS OF HETEROGNEITY IN SUPPORT OF SOIL MOISTURE RETRIEVAL AT LANDSCAPE LEVEL FOR LOW-FREQUENCY RADARS

Most traditional radar retrieval techniques utilize radar forward models that assume or require homogeneous scenes. NASA's upcoming Soil Moisture Active Passive (SMAP) mission launching in October 2014 will carry an L-band radar delivering a pixel size of 3 km x 3 km. Even though this resolution is finer than the SMAP 36 km radiometer pixels, it is still coarse enough that modeling such pixels assuming homogeneous scenes is not realistic. This highlights the need to develop spatial aggregation and disaggregation techniques using radar forward scattering models that assume homogeneity over fine-scale sub-pixels and derive tailor-made models for their contribution to the coarse-scale satellite pixel for successful soil moisture retrieval. For radar based soil moisture retrieval to be a strong candidate for future products, this uncertainty has to be successfully mitigated. To study the heterogeneity at landscape level, high-resolution P-band data from the Earth Venture 1 (EV-1) Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission is used as its pixel resolution is fine enough to assume homogeneity over a pixel. In this work, a sampling area over a well-known AirMOSS study site is chosen, an aggregation study based on landcover type is carried out and a coarse resolution radar backscatter function over the sampling area is found to be a weighted linear average of the contributions of the fine-scale pixels.