Ferrentino, Emanuele

This study focuses on a very complex environment, namely the Ionian coast of the Basilicata region, Southern Italy, which includes different kinds of beaches, river mouths and built-up areas. This complex environment is used as a test case to analyze the time variability of the coastline using measurements that were remotely sensed by the satellite European Copernicus Synthetic Aperture Radar (SAR) mission. First, the accuracy of the coastline, extracted by the SAR, is discussed with respect to finer-spatial-resolution drone-based light detection and ranging (LIDAR) measurements. Then, a time series of SAR dual-polarimetric measurements acquired by the European Copernicus mission is used to discuss the time variability of the coastline of the area of interest in a time period spanning from 2015 to 2021. The experimental results show that the accuracy of the SAR-based coastline is better than 15 m, which is reasonably good precision for monitoring the erosion/accretion processes that characterize the area of interest at a moderate scale. The estimated time variability of the extracted coastline suggests a dominant erosion process, which is always within 60 m.

In this study, we discuss the extra-value of polarimetric information in observing the lava flow. Dualpolarimetric Synthetic Aperture Radar (SAR) measurements are processed using a polarimetric change detector that, instead of looking at the variation of the backscatter intensity between a pair of images collected before and after the event, looks at changes in the polarimetric scattering behavior. We demonstrate that the scattering changes detected by the proposed polarimetric approach well-correlate with the footprint of the lava flow provided by external sources. In addition, we also compare the performance of the polarimetric change detector with conventional single-polarization metrics showing that the former one always outperforms the incoherent single-polarization measurements. To further demonstrate the robustness of the polarimetric change detectors, we selected two test cases that refer to vulcanic eruptions calling for completely different environments. The first one, related to the Etna volcano, calls for a lava flow over a vegetation-free environment; the second one is related to the Nyiragongo volcano and calls for a lava flow in a vegetated environment. Experimental results show that the polarimetric change detectors automatically adapt to the changing environment outperforming the single-polarization detectors.

In this work several change detection techniques based on satellite SAR data acquired by Cosmo-SkyMed Second Generation missions have been evaluated aiming at detecting the landslide-mudflow phenomenon triggered by the strong flooding event that hit Ischia Island in November 2022. It severely impacted on Casamicciola Terme area causing damages and collapses of many buildings and unfortunately also casualties. Experimental results show how both Single- (SP) and Dual- (DP) Polarimetric techniques are able to detect the main landslide occurring along the northern flank of Mt. Epomeo and in some cases also connected phenomena such as mud accumulation. Additional analyses have been performed to quantitatively evaluate the performance of all of them showing as in this case DP techniques outperform the SP ones. The outcomes are then discussed taking into account both the features of each technique and the investigated scenario. Detecting and mapping this kind of phenomena is important for the evaluation of the affected area, especially for complex scenarios such as Ischia island, and can be very useful to support both the stakeholders for the first aid and the Civil Protection for the post-crisis management.

The monitoring of ships is of paramount importance for ocean and coastal area surveillance. The synthetic aperture radar is shown to be a key sensor to provide effective and continuous observation of ships due to its unique imaging capabilities. When advanced synthetic aperture radar imaging systems are considered, the full scattering information is available that was demonstrated to be beneficial in developing improved ship detection and classification algorithms. Nonetheless, the capability of polarimetric synthetic aperture radar to observe marine vessels is significantly affected by several imaging and environmental parameters, including the incidence angle. Nonetheless, how changes in the incidence angle affect the scattering of ships still needs to be further investigated since only a sparse analysis, i.e., on different kinds of ships of different sizes observed at multiple incidence angles, has been performed. Hence, in this study, for the first time, the polarimetric scattering of the same ship, i.e., a small fishing trawler, which is imaged multiple times under the same sea state conditions but in a wide range of incidence angles, is analysed. This unique opportunity is provided by a premium L-band UAVSAR airborne dataset that consists of five full-polarimetric synthetic aperture radar scenes collected in the Gulf of Mexico. Experimental results highlight the key role played by the incidence angle on both coherent, i.e., co-polarisation signature and pedestal height, and incoherent, i.e., multi-polarisation and total backscattering power, polarimetric scattering descriptors. Experimental results show that: (1) the polarised scattering component is more sensitive to the incidence angle with respect to the unpolarised one; (2) the co-polarised channel under horizontal polarisation dominated the polarimetric backscattering from the fishing trawler at lower angles of incidence, while both co-polarised channels contribute to the polarimetric backscattering at higher incidence angles; (3) the HV polarisation provides the largest target-to-clutter ratio at lower incidence angles, while the HH polarisation should be preferred at higher angles of incidence.

This study investigates the extra benefit provided by the joint use of synthetic aperture radar (SAR) polarimetric diversity and ascending/descending orbit passes to quantify postearthquake damage that occurred over the area of Amatrice, an Italian city significantly damaged by the 2016 Central Italy earthquake. First, the sensitivity of PolSAR features derived from SAR scenes collected under ascending/descending orbits to the damage is investigated. Then, the damage assessment is performed using a processing chain that consists of extracting dual-polarimetric SAR features to detect damage and, then, applying a fuzzy clustering scheme, to partition the feature outputs into damage levels. This processing chain is first separately applied to Sentinel-1 SAR scenes collected under ascending/descending orbits; then the processing outputs are merged using two different approaches. To discuss the quality of the estimated damage maps, ground information collected by surveys performed by a trained team is used. Experimental results show that the joint use of ascending/descending orbit passes improves the estimation of damage levels (up to 78 % ) with respect to the estimation performed using the orbiting passes separately.

This study analyzes the ability of polarimetric Synthetic Aperture Radar (PolSAR) measurements to quantify post-earthquake damages. To achieve this goal, a twofold task is addressed: on one side a processing chain, which exploits multi-polarization SAR features, and a decision-tree classifier is proposed to quantify the levels of damage in earthquake-affected urbanized areas using dual-polarimetric (DP) SAR imagery. On the other side, a new damage index is developed that allows a fair spatial intercomparison of building-by-building information, collected via ground surveys on the damaged areas, and SAR-derived damage maps. The proposed rationale is showcased using measurements related to the Central-Italy Earthquake occurred in 2016 where both Sentinel-1 DP imagery and ground-based information are available. Experimental results demonstrate the soundness of the proposed approach. The main outcomes can be summarized as follows: a) DP features perform better than single-polarization ones; b) DP features exhibit a larger sensitivity to lower damage grades if compared to the single polarization (SP) feature; c) the accuracy of the estimated damage levels depends on the requested granularity in the damage maps; d) the accuracy obtained using DP features spans from 52% up to 71% when five and two damage classes are considered, respectively.

In this study, the sensitivity of dual-polarization features extracted from dual-polarimetric coherent synthetic aperture radar (SAR) imagery to urban damage due to the earthquake occurred in Central -Italy in 2016 is addressed. First, a conventional singlepolarization feature, based on the coherence between pre- and post-event co-polarized imagery, is analysed using SAR scenes collected by the Copernicus Sentinel-1 mission over the area of Amatrice, an Italian city significantly damaged by the 2016 earthquake that affected Central Italy. Then, the same analysis is undertaken using the cross-polarized channel to point out that the joint use of co- and cross-polarized channels can help in better observing the damaged area. Finally, a coherent dual-polarimetric feature, based on the inter-channel coherence, is proposed. This feature results in a sensitivity to damaged areas comparable to the one provided by conventional single-polarization features. However, the interchannel coherence has the benefit to be based only on two SAR acquisitions, i.e. before and after the earthquake and it is less affected by false alarms. SAR, polarimetry,earthquake, losses.