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In the present study, remote sensing of soil moisture is carried out using the Passive and Active L- and S-band airborne sensor (PALS). The data in this paper were taken from five days of overflights near Chickasha, OK during the 1999 Southern Great Plains (SGP99) experiment. Presently, we analyze the collected data to understand the relationships between the observed signals (radiometer brightness temperature and radar backscatter) and surface parameters (surface soil moisture, temperature, vegetation water content, and roughness). In addition, a radiative transfer model and two radar backscatter models are used to simulate the PALS observations. An integration of observations, regression retrievals, and forward modeling is used to derive the best estimates of soil moisture under varying surface conditions.