Physics-Based Modeling for High-Fidelity Radar Retrievals
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Knowledge of soil moisture dynamics on a global scale is crucial for understanding the Earth's terrestrial water, energy, and carbon cycles and allows better flood, weather and climate prediction, drought monitoring, and improved forecast of future water supply and food production. This work is motivated by the need for the retrieval of accurate soil moisture and focuses on the improvement of soil moisture retrieval based on active microwave remote sensing over vegetated areas. It will address three important, but heretofore uninvestigated, aspects in radar imaging: ionospheric effects, effects of multispecies vegetation (heterogeneity at pixel level), and impact of heterogeneity at landscape level on soil moisture retrieval. These contributions are expected to increase the fidelity of soil moisture retrieval based on low-frequency spaceborne radar and have immediate application in current missions such as the NASA EV-1 AirMOSS mission that observes root-zone soil moisture with a P-band radar at fine-scale resolution (100 m and finer), and the NASA SMAP mission, which will assess surface soil moisture with an L-band radar and radiometer at km-scale resolution (3 km).