Agricultural Monitoring with Polarimetric SAR Time Series

Synthetic Aperture Radars (SAR) are imaging sensors capable of extracting information about the scene reflectivity at microwave frequencies [1]. Contrary to optical sensors, they are active sensors capable of extracting information independently of the day-night cycles and the weather conditions. Furthermore, in Polarimetric SAR (PolSAR) systems, different wave polarizations are applied to transmitted and received radar echoes in order to extract additionall information about the target. SAR Polarimetry has demonstrated, specially during the last decade, its ability to extract biophysical and geophysical information about the scene [2]. Additionally, the presence of space-borne SAR systems has empowered the construction of PolSAR time series datasets. These datasets contain different acquisitions of the scene in the same geometry at different time instants. Time series datasets are relevant since they contain useful information not only about the scene, but also about its temporal evolution. This work deals with the exploitation of PolSAR time series datasets for monitoring agricultural areas