Influence of speckle filtering on the assessment of agricultural surface parameters

Retrieval information about soil moisture and roughness from remotely sensed data is of great interest for agricultural soil management. In fact, these two physical parameters are crucial for predicting erosion rates within agricultural watersheds during the rainfall season. In this context, there exists a strong interest to assess the potential of SAR (synthetic aperture radar) images to provide information regarding to these two physical surface parameters with periodic acquisitions. Nevertheless, one major source of error in the quantitative estimate of these parameters is the presence of the speckle within the scene registered by SAR instruments. To overcome this difficulty many filtering techniques have been developed for reducing this multiplicative noise. However, as to the authors' knowledge, no study has analysed the sensitivity of these speckle filtering approaches on the estimates of soil moisture and roughness. Consequently, the authors propose in this paper to quantify the influence of several speckle filtering methods on the assessment of these agricultural soil parameters.