An Efficient Modeling with GA Approach to Retrieve Soil Texture, Moisture and Roughness from ERS-2 SAR Data

One of the most important functions of radar remote sensing is to retrieve the soil moisture and surface parameters where surface parameters generally includes soil surface roughness and texture of soil (i.e.,% of coarse sand,silt and clay). Variation of soil moisture and surface parameters changes the soil permittivity, and affects the observation of the radar wave scattering (σ 0 ). How to invert the moisture and surface parameters from radar data has been one of the most interesting problems to be resolved. Still,very few reported work is available to retrieve the soil textures with radar data. Therefore,in present paper an attempt has been made to retrieve the soil textures with soil moisture and surface roughness from Synthetic Aperture Radar (SAR) data. In this case number of variables are more and it is difficult to invert and retrieve the various parameters. To overcome this difficulty,an approach based on Genetic Algorithm (GA) with inclusion of empirical modeling has been proposed to retrieve the soil moisture,roughness and soil texture with ERS-2 (European Remote Sensing) SAR (Synthetic Aperture Radar) data of Haridwar region of India. The retrieved surface parameters and moisture content with proposed approach show quite good agreement with observed values of soil moisture and surface parameters. This study infers that modeling with GA has great potential to retrieve several variables simultaneously with good results.