## 2 Materials and Methods
### The Ground Segment
#### 2.2.4 SAR Data Processing Chain
Afterwards, the absolute calibration of such images is achieved by exploiting illuminated targets with known scattering characteristics, such as CRs [60]. As an example, in Figure 8 (bottom image) we report the Sigma Naught map [60] achieved applying the IREA-CNR SAR data processing to X-band MIPS data acquired over the Salerno coastline within the Campania region, southern Italy, in 2021. Figure 8: External radiometric calibration of X-band MIPS data: amplitude of the multi-look complex (MLC) image (**top**) with the corresponding Sigma Nought map (**bottom**). Range pixel spacing: 1.49 m (SLC) and 7.45 m (MLC). Range resolution: 1.49 m (SLC) and 7.45 m (MLC). Azimuth pixel spacing: 1.62 m (SLC) and 16.2 m (MLC). Azimuth resolution: 2 m (SLC) and 16.2 m (MLC). Range extension: 2.8 km. Azimuth extension: 8 km. Similarly to the RC and RFI detection and removal processing steps, a single job on the IREA-CNR IT platform is responsible for the calibration of one entire SLC, whereas to achieve the parallel calibration of different SLCs, different jobs are simultaneously executed on the different WNs and cores available on the platform. 1. Polarimetric Processing  
Proper combinations of SAR data acquired at different polarizations allow us to characterize complex scenarios and to extract key parameters related to both natural and man-made targets [3]. As remarked above, the MIPS system of the IREA-CNR infrastructure can operate with a fully polarimetric configuration in the L-band. Some activities relevant to the polarimetric calibration of MIPS data for the compensation of undesired effects, such as channel imbalances or polarimetric crosstalk [61; 62], are matter of current work. Moreover, MIPS acquisition campaigns in the L-band are planned for the near future, with the aim of collecting polarimetric datasets to be used for the retrieval of ground parameters, such as, for instance, soil moisture. In this regard, the SAR data processing chain available at IREA-CNR already embeds a number of procedural steps applied in the past to multi-polarized SAR data acquired by other aerial sensors [24] to provide either basic or added value products. Specifically, algorithms for the generation of widely employed (e.g., Pauli, Freeman, and Cloude) polarimetric decomposition maps useful for scene classification purposes [3] are included in the IREA-CNR SAR data processing chain. As an example, in Figure 9 we report the Pauli decomposition map (right image) achieved by the IREA-CNR SAR data processing chain with a fully polarimetric set of P-band SAR data acquired by the Italian Space Agency (ASI) helicopter-borne sensor over the Manfredini area of the Apulia region, southern Italy, in 2021. Model based inversion procedures of polarimetric SAR data for the retrieval of surface parameters, such as ground roughness, soil permittivity and soil moisture content are available as well [63; 64; 65]. The implementation of the polarimetric processing on the IREA-CNR IT platform once again exploits the multi-core capability of the platform to process different polarimetric  
Figure 9: Polarimetric processing of P-band data acquired by the ASI helicopter-borne SAR sensor. Amplitude of the MLC image (**left**) with the corresponding Pauli decomposition map (**right**). Range pixel spacing: 0.75 m (SLC) and 18.75 m (MLC). Range resolution: 3.75 m (SLC) and 18.75 m (MLC). Azimuth pixel spacing: 0.725 m (SLC) and 18.12 m (MLC). Azimuth resolution: 2 m (SLC) and 18.12 m (MLC). Range extension: 2.8 Km. Azimuth extension: 4.53 km. datasets relevant to different flight tracks. For this processing step, a single job is responsible for the entire processing of the polarimetric dataset relevant to one flight track. * Interferometric Processing  
The interferometric processing allows for the generation of interferometric products, such as DEMs or surface deformation maps [1; 2; 4], starting from single-pass and/or repeat-pass interferometric pairs of SLCs.