COSMO-SkyMed Synthetic Aperture Radar Research Articles

Model-based comparisons of near-coincident TerraSAR-X and COSMO-SkyMed VV-polarized SAR measurements over sea surface with and without oil slicks

ABSTRACT This paper contrasts predicted X-band sea surface backscattering from slick-free and oil-covered sea surfaces with actual measurements acquired by the X-band satellite TerraSAR-X and COSMO-SkyMed Synthetic Aperture Radar (SAR) missions. Two SAR scenes were acquired with a temporal difference of about 36 minutes, under similar met-ocean conditions, during the North Sea’s Gannet Alpha oil spill accident. The normalized radar cross section of the slick-free sea surface is predicted using the Advanced Integral Equation Model (AIEM) while the backscatter from the oiled sea surface is predicted by the AIEM augmented with the Model of Local Balance (MLB) to include the damping effect of oil slicks. Experimental results show that X-band co-polarized numerical predictions agree reasonably well with both TSX and CSK actual measurements collected over slick-free sea surfaces. When dealing with oil-covered sea surfaces, the predicted backscattering reasonably agrees with TSX measurements, while it overestimates the CSK ones. This is likely due to the different spreading conditions of the oil imaged by the two satellite missions.

Land subsidence susceptibility mapping in urban settlements using time-series PS-InSAR and random forest model

Land subsidence in urban settlements is globally becoming prevalent and severe due to sea level rise and accelerated construction. However, few studies have analyzed the susceptibility of land subsidence in urban settlements and the subsidence rate thresholds that have a great impact on the reliability of the land subsidence susceptibility map (LSSM). This work aims to provide a novel LSSM framework for decision makers to conduct risk control in regional urban settlements. Herein, the COSMO-SkyMed Synthetic Aperture Radar (SAR) data from July 2016 to June 2021 was acquired for remote sensing interpretation in Wuhan, China. Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technology, combined with geostatistical analysis, was employed to map regional land subsidence rates. A total of 12 impact factors, identified through Pearson correlation coefficient (PCC) and multicollinearity tests, were selected as input features for the machine learning model. The performance of the model was assessed using Receiver Operating Characteristic (ROC) curves, and the segmentation of PS points for land subsidence rate was discussed. Furthermore, the correspondence between the measured ground-level observations and the predicted LSSM was compared. The results demonstrate that the random forest (RF) model outperforms other models in the test set, achieving an Area Under the Curve (AUC) of 0.940. The optimal threshold of −10 mm/year is proposed for segmenting PS points, which exhibits the strongest reliability in the distribution characteristics of the susceptibility index (SI). Combined with a high-performance hybrid model, this work is expected to provide a promising reference for land subsidence susceptibility prediction in similar urban settlements worldwide.

COSMO-SKYMED: A SATELLITE TOOL FOR MONITORING CULTURAL HERITAGE

Abstract. COSMO-SkyMed is the flagship Synthetic Aperture Radar (SAR) satellite constellation of the Italian Space Agency (ASI) that, among the many civilian applications for which it was originally conceived, is nowadays successfully exploited for cultural heritage applications. Current capabilities offered by both the First and Second Generations satellites are reviewed in light of the experience undertaken by ASI through data exploitation initiatives with scientific and commercial users, and more importantly in the framework of institutional projects and cooperation agreements such as those with the Colosseum Archaeological Park and the Italian Ministry of Culture (MiC). The interferometric nature of COSMO-SkyMed SAR acquisitions is the key feature exploited in structural and ground deformation monitoring of monuments and historical buildings, so as the constellation is currently the essential Earth Observation asset supporting MiC’s Extraordinary Plan of Monitoring and Conservation of Immovable Cultural Heritage. Further applications that could be enabled by COSMO-SkyMed data are explored through internal ASI research activity, such as the use of high resolution Digital Elevation Models (DEM) for topographic surveying of archaeological tells and condition assessment to estimate the impact due to natural and anthropogenic threats (e.g. looting, agriculture, destruction). Finally, current perspectives towards operational use and greater user uptake of COSMO-SkyMed for purposes of scientific downstream are opened by the new ASI programme Innovation for Downstream Preparation for Science (I4DP_SCIENCE).

SAR Imaging Distortions Induced by Topography: A Compact Analytical Formulation for Radiometric Calibration

Modeling of synthetic aperture radar (SAR) imaging distortions induced by topography is addressed and a novel radiometric calibration method is proposed in this paper. An analytical formulation of the problem is primarily provided in purely geometrical terms, by adopting the theoretical notions of the differential geometry of surfaces. The novel and conceptually simple formulation relies on a cylindrical coordinate system, whose longitudinal axis corresponds to the sensor flight direction. A 3D representation of the terrain shape is then incorporated into the SAR imaging model by resorting to a suitable parametrization of the observed ground surface. Within this analytical framework, the area-stretching function quantitatively expresses in geometrical terms the inherent local radiometric distortions. This paper establishes its analytical expression in terms of the magnitude of the gradient of the look-angle function uniquely defined in the image domain, thus resulting in being mathematically concise and amenable to a straightforward implementation. The practical relevance of the formulation is also illustrated from a computational perspective, by elucidating its effective discrete implementation. In particular, an inverse cylindrical mapping approach is adopted, thus avoiding the drawback of pixel area fragmentation and integration required in forward-mapping-based approaches. The effectiveness of the proposed SAR radiometric calibration method is experimentally demonstrated by using COSMO-SkyMed SAR data acquired over a mountainous area in Italy.

Regional-Scale Systematic Mapping of Archaeological Mounds and Detection of Looting Using COSMO-SkyMed High Resolution DEM and Satellite Imagery

“Tells” are archaeological mounds formed by deposition of large amounts of anthropogenic material and sediments over thousands of years and are the most important and prominent features in Near and Middle Eastern archaeological landscapes. In the last decade, archaeologists have exploited free-access global digital elevation model (DEM) datasets at medium resolution (i.e., up to 30 m) to map tells on a supra-regional scale and pinpoint tentative tell sites. Instead, the potential of satellite DEMs at higher resolution for this task was yet to be demonstrated. To this purpose, the 3 m resolution imaging capability allowed by the Italian Space Agency’s COSMO-SkyMed Synthetic Aperture Radar (SAR) constellation in StripMap HIMAGE mode was used in this study to generate DEM products of enhanced resolution to undertake, for the first time, a systematic mapping of tells and archaeological deposits. The demonstration is run at regional scale in the Governorate of Wasit in central Iraq, where the literature suggested a high density of sites, despite knowledge gaps about their location and spatial distribution. Accuracy assessment of the COSMO-SkyMed DEM is provided with respect to the most commonly used SRTM and ALOS World 3D DEMs. Owing to the 10 m posting and the consequent enhanced observation capability, the COSMO-SkyMed DEM proves capable to detect both well preserved and levelled or disturbed tells, standing out for more than 4 m from the surrounding landscape. Through the integration with CORONA KH-4B tiles, 1950s Soviet maps and recent Sentinel-2 multispectral images, the expert-led visual identification and manual mapping in the GIS environment led to localization of tens of sites that were not previously mapped, alongside the computation of a figure as up-to-date as February 2019 of the survived tells, with those affected by looting. Finally, this evidence is used to recognize hot-spot areas of potential concern for the conservation of tells. To this purpose, we upgraded the spatial resolution of the observations up to 1 m by using the Enhanced Spotlight mode to collect a bespoke time series. The change detection tests undertaken on selected clusters of disturbed tells prove how a dedicated monitoring activity may allow a regular observation of the impacts due to anthropogenic disturbance (e.g., road and canal constructions or ploughing).

Multithreading Based Parallel Processing for Image Geometric Coregistration in SAR Interferometry

Within the framework of multi-temporal Synthetic Aperture Radar (SAR) interferometric processing, image coregistration is a fundamental operation that might be extremely time-consuming. This paper explores the possibility of addressing fast and accurate SAR image geometric coregistration, with sub-pixel accuracy and in the presence of a complex 3-D object scene, by exploiting the parallelism offered by shared-memory architectures. An efficient and scalable processor is proposed by designing a parallel algorithm incorporating thread-level parallelism for solving the inherent computationally intensive problem. The adopted functional scheme is first mathematically framed and then investigated in detail in terms of its computational structures. Subsequently, a parallel version of the algorithm is designed, according to a fork-join model, by suitably taking into account the granularity of the decomposition, load-balancing, and different scheduling strategies. The developed parallel algorithm implements parallelism at the thread-level by using OpenMP (Open Multi-Processing) and it is specifically targeted at shared-memory multiprocessors. The parallel performance of the implemented multithreading-based SAR image coregistration prototype processor is experimentally investigated and quantitatively assessed by processing high-resolution X-band COSMO-SkyMed SAR data and using two different multicore architectures. The effectiveness of the developed multithreaded prototype solution in fully benefitting from the computing power offered by multicore processors has successfully been demonstrated via a suitable experimental performance analysis conducted in terms of parallel speedup and efficiency. The demonstrated scalable performance and portability of the developed parallel processor confirm its potential for operational use in the interferometric SAR data processing at large scales.

Land Subsidence in Wuhan Revealed Using a Non-Linear PSInSAR Approach with Long Time Series of COSMO-SkyMed SAR Data

Wuhan is an important city in central China, with a rapid development that has led to increasingly serious land subsidence over the last decades. Most of the existing Interferometric Synthetic Aperture Radar (InSAR) subsidence monitoring studies in Wuhan are either short-term investigations—and thus can only detect this process within limited time periods—or combinations of different Synthetic Aperture Radar (SAR) datasets with temporal gaps in between. To overcome these constraints, we exploited nearly 300 high-resolution COSMO-SkyMed StripMap HIMAGE scenes acquired between 2012 and 2019 to monitor the long-term subsidence process affecting Wuhan and to reveal its spatiotemporal variations. The results from the Persistent Scatterer Interferometric SAR (PSInSAR) processing highlight several clearly observable subsidence zones. Three of them (i.e., Houhu, Xinrong, and Guanggu) are affected by serious subsidence rates and non-linear temporal behavior, and are investigated in this paper in more detail. The subsidence in Houhu is caused by soft soil consolidation and compression. Soil mechanics are therefore used to estimate when the subsidence is expected to finish and to calculate the degree of consolidation for each year. The COSMO-SkyMed PSInSAR results indicate that the area has entered the late stage of consolidation and compression and is gradually stabilizing. The subsidence curve found for the area around Xinrong shows that the construction of an underground tract of the subway Line 21 caused large-scale settlement in this area. The temporal granularity of the PSInSAR time series also allows precise detection of a rebound phase following a major flooding event in 2016. In the southern industrial park of Guanggu, newly detected subsidence was found. The combination of the subsidence curve with an optical time-series image analysis indicates that urban construction is the main trigger of deformation in this area. While this study unveils previously unknown characters of land subsidence in Wuhan and clarifies the relationship with the urban causative factors, it also proves the benefits of non-linear PSInSAR in the analysis of the temporal evolution of such processes in dynamic and expanding cities.

Satellite X-band SAR data exploitation trends in the framework of ASI’s COSMO-SkyMed Open Call initiative

Abstract COSMO-SkyMed (Constellation of Small satellites for Mediterranean basin Observation) is an Italian Earth Observation (EO) and Dual-Use (Civilian and Defense) Space System conceived with the aim to establish a worldwide service providing Synthetic Aperture Radar (SAR) data, products and services compliant with well-established international standards and relevant to a wide range of applications, such as emergency and risk management, scientific and commercial applications and defense Applications. Starting from 2007, the Italian Space Agency (ASI) has promoted the COSMO-SkyMed SAR data exploitation through several initiatives such as “Announcement of Opportunity”, “Open Call for Science” and “Open Call for National Small and Medium Enterprises (SMEs)”. This paper is focused on the trends and results observed in the context of the “Open Call for Science”, an initiative completely addressed to the national and international scientific community since 2015. In particular, in this framework, the observed trend and advances in science and applications of SAR imagery and Interferometric SAR (InSAR) are summarized and assessed, also in light of the scientific evidence published in the recent literature by scientific users of ASI’s “Open Call for Science”.

Mapping impact of urbanization in Shahat-Cyrene (Libya) using a big SAR data approach of change detection with COSMO-SkyMed time series

Uncontrolled and unregulated urbanization around the modern town of Shahat, Libya, has been reported by several studies as a pressing issue for the conservation of archaeological heritage in the cultural landscape south of Cyrene UNESCO World Heritage Site (WHS). In this paper, we implemented a big Synthetic Aperture Radar (SAR) data analysis approach on a selection of more than 180 StripMap images that the Italian Space Agency (ASI)’s COSMO-SkyMed constellation has consistently collected at 3-m resolution over Cyrene since 2011, as part of its background acquisition scenario. We prove the accuracy of the method to map the spatial and temporal spread of new building and road blocks using COSMO-SkyMed SAR data, and its complementarity with the mapping based on the full archive of cloud-free Copernicus Sentinel-2 multi-spectral imagery at 10-m resolution (2015-2017). Owing to the higher spatial resolution and half-month frequency of observation of COSMO-SkyMed, we better delineated the new urban features and estimated more precisely when these were developed across the landscape.

The Optimized Small Incidence Angle Setting of a Composite Bragg Scattering Model and its Application to Sea Surface Wind Speed Retrieval

The normalized radar cross section (NRCS) of microwave backscattering from a rough sea surface can be described by a composite Bragg scattering (CBS) model, which is a combination of a two-scale backscatter model and a geometric optics model. For small local radar incidence angles that are smaller than a given angle setting, the two-scale backscattering mechanism of the sea surface is replaced by a geometric optics solution for specular reflection. In this study, an optimized setting of 18 degrees for the small incidence angle is determined by comparing the NRCSs between 52 RADARSAT-2 (R2) synthetic aperture radar (SAR) images and the CBS model with simultaneous sea surface wind derived by meteorological mooring buoys located in the northern South China Sea. By using the CBS model with the optimized incidence angle setting of 18° and the nearly simultaneous wind directions of the Advanced Scatterometer (ASCAT) as the input, sea surface wind speeds are retrieved from 46 R2 SAR images at C-band and from 2 COSMO-SkyMed (CSK) SAR images at X-band for the application study. The average root mean square error of the C-band R2 SAR retrieval results validated against nearly simultaneous measurements of ASCAT is 1.5 m/s, while the same value is 1.6 m/s for the X-band CSK SAR image. The results also indicate that the optimized small incidence angle setting of the CBS model found in this study is relatively reliable under sea surface wind speed conditions less than 14.0 m/s.

Comparison of Tropospheric Path Delay Estimates from GNSS and Space-Borne SAR Interferometry in Alpine Conditions

We compare tropospheric delays from Global Navigation Satellite Systems (GNSS) and Synthetic Aperture Radar (SAR) Interferometry (InSAR) in a challenging mountainous environment in the Swiss Alps, where strong spatial variations of the local tropospheric conditions are often observed. Tropospheric delays are usually considered to be an error for both GNSS and InSAR, and are typically removed. However, recently these delays are also recognized as a signal of interest, for example for assimilation into numerical weather models or climate studies. The GNSS and InSAR are techniques of complementary nature, as one has sparse spatial but high temporal resolution, and the other very dense spatial coverage but repeat pass of only a few days. This raises expectations for a combination of these techniques. For this purpose, a comprehensive comparison between the techniques must be first performed. Due to the relative nature of InSAR estimates, we compare the difference slant tropospheric delays ( d S T D ) retrieved from GNSS with the d S T D s estimated using Persistent Scatterer Interferometry (PSI) of 32 COSMO-SkyMed SAR images taken in a snow-free period from June to October between 2008 and 2013. The GNSS estimates calculated at permanent geodetic stations are interpolated to the locations of persistent scatterers using an in-house developed least-squares collocation software COMEDIE. The Pearson’s correlation coefficient between InSAR and GNSS estimates averaged over all acquisitions is equal to 0.64 and larger than 0.8 for approximately half of the layers. Better agreement is obtained mainly for days with high variability of the troposphere (relative to the tropospheric conditions at the time of the reference acquisition), expressed as standard deviations of the GNSS-based d S T D s. On the other hand, the most common feature for the days with poor agreement is represented by very stable, almost constant GNSS estimates. In addition, there is a weak correlation between the agreement and the water vapor values in the area, as well as with the number of stations in the closest vicinity of the study area. Adding low-cost L-1 only GPS stations located within the area of the study increases the biases for most of the dates, but the standard deviations between InSAR and GNSS decrease for the limited area with low-cost stations.

COSMO-SkyMed SAR for Detection and Monitoring of Archaeological and Cultural Heritage Sites

Synthetic aperture radar (SAR) imagery has long been used in archaeology since the earliest space radar missions in the 1980s. In the current scenario of SAR missions, the Italian Space Agency (ASI)’s COnstellation of small Satellites for Mediterranean basin Observation (COSMO-SkyMed) has peculiar properties that make this mission of potential use by archaeologists and heritage practitioners: high to very high spatial resolution, site revisit of up to one day, and conspicuous image archives over cultural heritage sites across the globe. While recent literature and the number of research projects using COSMO-SkyMed data for science and applied research suggest a growing interest in these data, it is felt that COSMO-SkyMed still needs to be further disseminated across the archaeological remote sensing community. This paper therefore offers a portfolio of use-cases that were developed in the last two years in the Scientific Research Unit of ASI, where COSMO-SkyMed data were analysed to study and monitor cultural landscapes and heritage sites. SAR-based applications in archaeological and cultural heritage sites in Peru, Syria, Italy, and Iraq, provide evidence on how subsurface and buried features can be detected by interpreting SAR backscatter, its spatial and temporal changes, and interferometric coherence, and how SAR-derived digital elevation models (DEM) can be used to survey surface archaeological features. The use-cases also showcase how high temporal revisit SAR time series can support environmental monitoring of land surface processes, and condition assessment of archaeological heritage and landscape disturbance due to anthropogenic impact (e.g., agriculture, mining, looting). For the first time, this paper provides an overview of the capabilities of COSMO-SkyMed imagery in StripMap Himage and Spotlight-2 mode to support archaeological studies, with the aim to encourage remote sensing scientists and archaeologists to search for and exploit these data for their investigations and research activities. Furthermore, some considerations are made with regard to the perspectives opened by the upcoming launch of ASI’s COSMO-SkyMed Second Generation constellation.

COSMO–SkyMed Synthetic Aperture Radar Data to Observe the Deepwater Horizon Oil Spill

Oil spills are adverse events that may be very harmful to ecosystems and the food chain. In particular, large sea oil spills are very dramatic occurrences that may affect sea and coastal areas. Hence, the sustainability of oil rig infrastructures and oil transportation via oil tankers is linked to law enforcement based on proper monitoring techniques, which are also fundamental to mitigate the impact of such pollution. In this study, a showcase referring to the Deepwater Horizon (DWH) oil incident, one of the world’s largest incidental oil pollution event that occurred in the Gulf of Mexico in 2010 affecting a sea area larger than 10,000 km 2 , is analyzed using remotely-sensed information collected by Synthetic Aperture Radar (SAR). Although, operationally, SAR sea oil slick observation is typically accomplished using C-band VV-polarized SAR imagery, during the DWH oil incident, because of their very dense revisit time, even single-polarization X-band COSMO-SkyMed (CSK) SAR measurements were collected. In this study, we exploit, for the first time, incoherent dual co-polarization SAR data collected by the Italian CSK X-band SAR constellation showing the key benefits of HH-VV SAR measurements in observing such a huge oil pollution event, especially in terms of the very dense revisit time offered by the CSK constellation.

Radargrammetric approaches to the flat relief of the amazon coast using COSMO-SkyMed and TerraSAR-X datasets

The Amazonian coast consists of extensive flood plains and plateaus characterized by a high discharge of water and sediment from the Amazon River. This wide landscape occurs under a tropical climate with heavy rains and high cloud cover, making it unsuitable for conventional mapping based on optical images. Additionally, the flat relief and vegetation structure of the Brazilian Amazon coast define an incoherent to partially coherent behavior for the microwave signal, rendering radargrammetric models more suitable for the three-dimensional mapping of its surface. This study aimed to assess the digital surface models (DSMs) provided by Cosmo-SkyMed (CSK) and TerraSAR-X (TSX) Stripmap datasets throughout the radargrammetric models from SARscape and Toutin. The DSMs were generated from SAR (synthetic aperture radar) data with an acquisition geometry that addressed the need for a compromise between the intersection angles and low temporal decorrelation. The radargrammetric SARscape and Toutin’s models were developed from different amounts of stereo ground control points (SGCP). The generated DSMs were evaluated considering a set of 40 independent checkpoints (ICP) measured by GNSS in the field, in their entirety and disaggregated by coastal environment. The vertical accuracy was based on the estimation of the discrepancies, bias and precision (standard deviation and root mean square error – RMSE), and the Taylor and Target diagrams were used for a more comprehensive comparison. In the vertical accuracy analysis using all ICPs measured in situ, the DSM obtained by the SARscape’s model from the CSK SAR data resulted in the lowest RMSE (4.34 m) and mean discrepancy (0.05 m), but Toutin’s model had the lowest standard deviation (2.58 m) of the discrepancies. The Taylor and Target diagrams showed fluctuations in accuracy that alternated the DSMs generated from the two types of SAR data, indicating that TSX produced more stable models and CSK produced better vertical accuracy. The Amazon Coastal Plateau and Fluvial Marine Terrace environments defined three-dimensional representations with lower RMSEs (better than 7.8 and 8.9 m, respectively), regardless of the type of SAR data or the radargrammetric model used. The worst performance, which was for the Fluvial Marine Plain, was influenced by the specific characteristics of this coastal environment, such as the structure of the mangrove vegetation and the shoreline. In general, the high resolution and good ability to revisit the SAR data used, together with the radargrammetric models, allowed for the accurate mapping of the flat relief of the Amazon coastal environments, providing detailed spatial information that can be acquired in severe rainfall conditions in a region of intense morphological dynamics.

Digital Image Correlation (DIC) Analysis of the 3 December 2013 Montescaglioso Landslide (Basilicata, Southern Italy): Results from a Multi-Dataset Investigation

Image correlation remote sensing monitoring techniques are becoming key tools for providing effective qualitative and quantitative information suitable for natural hazard assessments, specifically for landslide investigation and monitoring. In recent years, these techniques have been successfully integrated and shown to be complementary and competitive with more standard remote sensing techniques, such as satellite or terrestrial Synthetic Aperture Radar interferometry. The objective of this article is to apply the proposed in-depth calibration and validation analysis, referred to as the Digital Image Correlation technique, to measure landslide displacement. The availability of a multi-dataset for the 3 December 2013 Montescaglioso landslide, characterized by different types of imagery, such as LANDSAT 8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor), high-resolution airborne optical orthophotos, Digital Terrain Models and COSMO-SkyMed Synthetic Aperture Radar, allows for the retrieval of the actual landslide displacement field at values ranging from a few meters (2–3 m in the north-eastern sector of the landslide) to 20–21 m (local peaks on the central body of the landslide). Furthermore, comprehensive sensitivity analyses and statistics-based processing approaches are used to identify the role of the background noise that affects the whole dataset. This noise has a directly proportional relationship to the different geometric and temporal resolutions of the processed imagery. Moreover, the accuracy of the environmental-instrumental background noise evaluation allowed the actual displacement measurements to be correctly calibrated and validated, thereby leading to a better definition of the threshold values of the maximum Digital Image Correlation sub-pixel accuracy and reliability (ranging from 1/10 to 8/10 pixel) for each processed dataset.

Towards operational SAR-based flood mapping using neuro-fuzzy texture-based approaches

Synthetic Aperture Radar (SAR) data are currently the most reliable resource for flood monitoring, though still subject to various uncertainties, which can be objectively represented with probabilistic flood maps. Moreover, the growing number of SAR satellites has increased the likelihood of observing a flood event from space through at least a single SAR image, but generalized methods for flood classification independent of sensor characteristics need to be developed, to fully utilize these images for disaster management. Consequently, a neuro-fuzzy flood mapping technique is proposed for texture-enhanced single SAR images. Accordingly, any SAR image is first processed to generate second-order statistical textures, which are subsequently optimized using a dimensionality reduction technique. The flood and non-flood classes are then modelled within a fuzzy inference system using Gaussian curves. Parameterization is achieved by training a neural network on the image through user-defined polygons. The results of the optimized texture-based neuro-fuzzy classification were compared against the performance of the SAR image alone and that of SAR enhanced with randomly selected texture features. This approach was tested for a COSMO-SkyMed SAR image at two validation sites, for which high resolution aerial photographs were available. An overall accuracy assessment using reliability diagrams demonstrated a reduction of 54.2% in the Weighted Root Mean Squared Error (WRMSE) values compared to the stand-alone use of SAR. WRMSE values estimated for the proposed method varied from 0.027 to 0.196. A fuzzy validation exercise was also proposed to account for the uncertainty in manual flood identification from aerial photography, resulting in fuzzy spatial similarity values ranging from 0.67 to 0.92, with higher values representing better performance. Results suggest that the proposed approach has demonstrated potential to improve operational SAR-based flood mapping.

Spatial evolution of the December 2013 Metaponto plain (Basilicata, Italy) flood event using multi-source and high-resolution remotely sensed data

ABSTRACTWe present a multi-layer, multi-temporal flood map of the event occurred on December 2013 in Basilicata (southern Italy), documenting the spatial evolution of the inundated areas through time, as well as some ground effects of floodwaters inferred from the imagery. The map, developed within a GIS and consisting of four, 1:20,000 scale, different layers, was prepared using image processing, visual image interpretation and field survey controls. We used two COSMO-SkyMed synthetic aperture radar (SAR) images, acquired during the event, and a Plèiades-1B High-Resolution optical image, acquired at the end of the event. We also used the information derived from the satellite imagery to update some local features of the OpenStreetMap (OSM) geospatial database, and then integrated it within the flood map. A classified multi-temporal dynamic map of inundation and flood effects has been produced in the form of a multi-layer pdf file (Main Map).

Lava delta deformation as a proxy for submarine slope instability

The instability of lava deltas is a recurrent phenomenon affecting volcanic islands, which can potentially cause secondary events such as littoral explosions (due to interactions between hot lava and seawater) and tsunamis. It has been shown that Interferometric Synthetic Aperture Radar (InSAR) is a powerful technique to forecast the collapse of newly emplaced lava deltas. This work goes further, demonstrating that the monitoring of lava deltas is a successful strategy by which to observe the long-term deformation of subaerial–submarine landslide systems on unstable volcanic flanks. In this paper, displacement measurements derived from Synthetic Aperture Radar (SAR) imagery were used to detect lava delta instability at Stromboli volcano (Italy). Recent flank eruptions (2002–2003, 2007 and 2014) affected the Sciara del Fuoco (SdF) depression, created a “stacked” lava delta, which overlies a pre-existing scar produced by a submarine–subaerial tsunamigenic landslide that occurred on 30 December 2002. Space-borne X-band COSMO-SkyMED (CSK) and C-band SENTINEL-1A (SNT) SAR data collected between February 2010 and October 2016 were processed using the SqueeSAR algorithm. The obtained ground displacement maps revealed the differential ground motion of the lava delta in both CSK and SNT datasets, identifying a stable area (characterized by less than 2 mm/y in both datasets) within the northern sector of the SdF and an unstable area (characterized by velocity fields on the order of 30 mm/y and 160 mm/y in the CSK and SNT datasets, respectively) in the central sector of the SdF. The slope stability of the offshore part of the SdF, as reconstructed based on a recently performed multibeam bathymetric survey, was evaluated using a 3D Limit Equilibrium Method (LEM). In all the simulations, Factor of Safety (F) values between 0.9 and 1.1 always characterized the submarine slope between the coastline and −250 m a.s.l. The critical surfaces for all the search volumes corresponded to the 30 December 2002 landslide, which involved the lava delta and its surrounding areas. InSAR data provided the post-effusive deformation field after the 2007 and 2014 flank eruptions, whereas LEM results highlighted that the accumulation of lava flows on the prone-to-failure SdF submarine slope is the main cause of the detected lava delta deformation. Lava delta instability, measured also at Pico Island (Azores) and Kilauea volcano (Hawaii), is evidence of the broader spectrum of instability phenomena that take place in the coastal or submarine area of the flanks of the volcanoes. At Kilauea, past lava deltas have moved faster than the surrounding slope and the recorded movements relate only to the collapses of the deltas themselves, producing rapid mass wasting near the coasts. In contrast, at Stromboli and Pico, lava deltas move at the same velocity as the surrounding slope. In these cases, the displacement at lava deltas can be considered as a proxy for the deformation of submarine slides. There are very few studies dealing with lava delta deformation, thus, the analysis presented in this work will benefit the monitoring of submarine slopes in other prone-to-failure coastal or island volcanic systems which have the potential to generate tsunamis.

Dual-Polarimetric C- and X-Band SAR Data for Coastline Extraction

This study proposes a new metric to process dual-polarimetric coherent and incoherent synthetic aperture radar (SAR) data for coastline extraction purposes. The metric, based on the correlation between co- and cross-polarized channels, allows discriminating land from sea in an unsupervised way. Then, simple image processing is adopted to extract continuous coastline from the binary image. Experiments, undertaken on multipolarization C - (RadarSAT-2 and Sentinel-1) and X -band (Cosmo-SkyMed) SAR data collected in South of Italy together with Global Positioning System ground truth, confirm the soundness of the method which is shown to be both effective (a whole SAR scene is processed in seconds) and accurate (the mean error is less than $5$ and $7$ pixels for RadarSAT-2 and CosmoSkyMed, respectively).

Coastline detection in SAR images using discriminant cuts segmentation

The discriminant cut algorithm is used to detect coastlines in synthetic aperture radar (SAR) images. The proposed approach is a region-based one, which is able to capture and utilize spatial information in the image. The real SAR images, e.g. ALOS-1 PALSAR and COSMO-SkyMed SAR images, together with in-situ GPS data were collected and used to validate the performance of the proposed approach for coastline detection in SAR images. The accuracy is better than 4 times the image resolution. The efficiency is also tested.