Coupled Modelling of Land Surface Microwave Interactions Using Envisat Asar Data

In the last decades microwave remote sensing has proven its capability to provide valuable information about the land surface. New sensor generations as e.g. ENVISAT ASAR are capable to provide frequent imagery with an high information content. To make use of the multiple imaging capabilities of those sensors, sophisticated parameter inversion and assimilation strategies have to be applied. The objective of the presented work is the analysis and quantitative description of the backscattering processes of vegetated areas by means of microwave backscattering models. The effect of changing imaging geometries is investigated and models for the description of bare soil and vegetation backscattering are developed. Spatially distributed model parameterisation is realized by synergistic coupling of microwave scattering models with a physically based land surface process model. This enables the simulation of realistic SAR images, based on bioand geophysical parameters. The approach is validated using nine ENVISAT ASAR images. A pixelwise comparison between simulated and observed backscattering coefficients revealed a mean deviation of 0.5 dB with a corresponding standard deviation of 2.8 dB.