Thermal Noise Removal From Polarimetric Sentinel-1 Data

This study proposes, for the first time, an approach to remove thermal noise from the wave coherency matrix,
$\mathrm {C_{2}}$
, estimated from single-look complex dual-polarization Interferometric Wide Swath mode Sentinel-1 synthetic aperture radar data. The approach is straightforward; it exploits the ThermalNoiseRemoval module, provided by the European Space Agency (ESA) in its Sentinel Application Platform (SNAP) software, to remove thermal noise from the channel intensities. Then, noise correction on the complex data is applied, in order to estimate the noise-free
$\mathrm {C_{2}}$
matrix. As a further novelty, the proposed approach can be implemented in SNAP, through the use of a processing graph that is here provided. The method is applied on a dense time series of Sentinel-1 data, collected on an agricultural area located near Seville, Spain. The impact of thermal noise on the estimation of the eigendecomposition parameters of
$\mathrm {C_{2}}$
, i.e., entropy (
$H_{2}$
), average alpha angle (
$\overline {\alpha _{2}}$
), and anisotropy (
$A_{2}$
), is assessed for different land-cover types, namely river, rice, forest, and urban areas. Monte Carlo simulations are implemented to assess the performance of the proposed approach in estimating
$H_{2}$
,
$\overline {\alpha _{2}}$
, and
$A_{2}$
. Results show that the proposed noise removal method improves the estimation of these parameters for the considered land-cover classes.