Pecora 16 "Global Priorities in Land Remote Sensing" October 23-27, 2005 * Sioux Falls, South Dakota ASSESSING LAND SURFACE DYNAMICS ACROSS THE NEBRASKA SAND HILLS USING ADVANCED MICROWAVE SCANNING RADIOMETER (AMSR-E) DATA PRODUCTS

ABSTRACT The Nebraska Sand Hills is the largest sand dune area in the Western hemisphere, and one of the largest grassstabilized dune regions in the world. It had been suggested that the Sand Hills dunes were active as recently as 900 years ago. To understand the persistence of dune stability, it is important to investigate land surface linkages with the hydrometeorological and biogeophysical processes. Synoptic views of surficial soil moisture and vegetation water content at 25 km spatial resolution have recently become available as standard data products from the multifrequency Advanced Microwave Scanning Radiometer (AMSR-E) on Aqua. In this paper we illustrate the diel, seasonal, and interannual patterns in AMSR-E vegetation water content product using data from 2003 and 2004. Using 14-day maximum AVHRR NDVI composites to capture land surface phenology, we find a strong spatiotemporal correspondence between the vegetation water content product and NDVI

The effects of scene heterogeneity on soil moisture retrieval from passive microwave data

The s–x model of microwave emission from soil and vegetation layers is widely used to estimate soil moisture content from passive microwave observations. Its application to prospective satellite-based observations aggregating several thousand square kilometres requires understanding of the effects of scene heterogeneity. The effects of heterogeneity in soil surface roughness, soil moisture, water area and vegetation density on the retrieval of soil moisture from simulated single- and multi-angle observing systems were tested. Uncertainty in water area proved the most serious problem for both systems, causing errors of a few percent in soil moisture retrieval. Single-angle retrieval was largely unaffected by the other factors studied here. Multiple-angle retrievals errors around one percent arose from heterogeneity in either soil roughness or soil moisture. Errors of a few percent were caused by vegetation heterogeneity. A simple extension of the model vegetation representation was shown to reduce this error substantially for scenes containing a range of vegetation types

Physics-based Modeling for High-fidelity Radar Retrievals.

Knowledge of soil moisture on a global scale is crucial for understanding the Earth's water, energy, and carbon cycles. This dissertation is motivated by the need for accurate soil moisture estimates and focuses on the improvement of soil moisture retrieval based on active remote sensing over vegetated areas. It addresses important, but often neglected, aspects in radar imaging: effects related to the ionosphere, multispecies vegetation (heterogeneity at pixel level), and heterogeneity at landscape level. The first contribution is the development of a generalized radar scattering model as an advancement of current radar modeling techniques for vegetated areas at fine-scale pixel level. It consists of realistic representations of multispecies and subsurface soil layer modeling, and includes terrain topography. This modeling improvement allows greater applicability to different land cover types and higher soil moisture retrieval accuracy. Most coarse-scale satellite pixels (km-scale or coarser) contain highly heterogeneous scenes with fine-scale (100 m or finer) variability of soil moisture, soil texture, topography, and vegetation cover. The second contribution is the development of spatial scaling techniques to investigate effects of landscape-level heterogeneity on radar scattering signatures. Using the above radar forward scattering model, which assumes homogeneity over fine scales, tailor-made models are derived for the contribution of fine-scale heterogeneity to the coarse-scale satellite pixel for effective soil moisture retrieval. Finally, the third contribution is the development of a self-contained calibration technique based on an end-to-end radar system model. The model includes ionospheric effects allowing the use of spaceborne radar signals for accurate soil moisture retrieval from lower frequencies, such as L- and P-band. These combined contributions will greatly increase the usability of low-frequency spaceborne radar data for soil moisture retrieval: ionospheric effects are mitigated, landscape level heterogeneity is resolved, and fine-scale scenes are better modeled. These contributions ultimately allow improved fidelity in soil moisture retrieval and are immediately applicable in current missions such as the ongoing AirMOSS mission that observes root-zone soil moisture with a P-band radar at fine-scale resolution (100 m), and NASA's upcoming SMAP spaceborne mission, which will assess surface soil moisture with an L-band radar and radiometer at km-scale resolution (3 km).PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107290/1/mburgin_1.pd