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Multi-temporal SAR interferometry (MTInSAR) provides mean displacement maps and displacement time series over coherent objects on the Earth surface, allowing analysis of wide areas to identify ground deformations, and studying evolution of displacement phenomena over long time scales. MTInSAR techniques have proven very useful for detecting and monitoring also slope instabilities.Nowadays, several satellite missions are available providing InSAR data at different wavelengths, spatial resolutions, and revisit times. The Italian X-Band COSMO-SkyMed constellation acquires data with spatial resolution reaching metric values, and provides revisit times of up to a few days, leading to an increase in the density of the measurable targets, thus improving the monitoring of local scale events as well as the detection of non-linear displacements. The recent Sentinel-1 C-band mission from the European Space Agency (ESA) provides a spatial resolution comparable to previous ESA SAR missions, but a nominal revisit time reduced to 6 days. By offering regular global-scale coverage, better temporal resolution and freely available imagery, Sentinel-1 improves the performance of MTInSAR for ground displacement investigations. In particular, the short revisit time allows a better time series analysis by improving the temporal sampling and thus the chances to catch pre-failure signals characterised by high rate and non-linear behaviour. Moreover, it allows collecting large data stacks in a short time periods, thus improving MTInSAR performance in emergency (post-event) scenarios. These characteristics are very promising for early warning of slope failure events and monitoring subsequent displacements trends. In this work, we present the results obtained by using both COSMO-SkyMed and Sentinel-1 data for investigating the ground stability of hilly villages located in Southern Italian Apennine (Basilicata region). In the area of interest, several landslides occurred in the recent past (e.g. Montescaglioso in 2013) and more recently (e.g. Pomarico in 2019), causing extensive damage to houses, commercial buildings, and infrastructures.SAR datasets acquired by COSMO-SkyMed and Sentinel-1 from both ascending and descending orbits have been processed by using the SPINUA MTInSAR algorithm, in order to exploit the potentials of these two satellite missions to investigate ground displacements related to slope instabilities. Mean velocity maps and displacement time series have been analysed looking, in particular, for non-linear trends that are possibly related to relevant ground instability episodes and, thanks to the high spatial resolution, useful in terms of early warning, in the case of rigid soil masses. Results are presented and discussed in relation to known events occurred in the area of interest.

Multi-temporal SAR interferometry (MTInSAR), by providing both mean displacement maps and displacement time series over coherent objects on the Earth, allows analysing wide areas, identifying critical ground instabilities, and studying the phenomenon evolution in a long time-scale. This technique has been proved to be very useful for detecting and monitoring also slope instabilities. Nowadays, several satellite missions are available providing InSAR data at different wavelengths, spatial resolutions, and revisit time. The high-resolution X-Band COSMO-SkyMed constellation, acquires data with spatial resolution reaching metric values, and provides revisit times of up to a few days, leading to an increase in the density of the measurable targets, thus improving the monitoring of local scale events as well as the detection of non-linear displacements. The recent Sentinel-1 C-band mission from the European Space Agency (ESA), provides a spatial resolution comparable to the previous ESA missions, but a nominal revisit time reduced to 6 days. By offering regular global-scale coverage, better temporal resolution and freely available imagery, Sentinel-1 improves the performance of MTInSAR for ground displacement investigations. In particular, the short revisit time allows a better time series analysis by improving the temporal sampling and the chances to catch pre-failure signals characterised by high rate and non-linear behaviour signals. Moreover, it allows collecting large data stacks in a short time period, thus improving the MTInSAR performance in emergency (post-event) scenarios. These characteristics are very promising for early warning of slope failure events and monitoring subsequent displacements trends. In this work, we present the results obtained by using both COSMO-SkyMed and Sentinel-1 data for investigating the ground stability of hilly villages located in Southern Italian Apennine (Basilicata region). In the area of interest, several landslides occurred in the recent past (e.g. on Montescaglioso in 2013) and also very recently (e.g. on Pomarico in 2019), causing damages to houses, commercial buildings, and infrastructures. SAR datasets acquired by COSMO-SkyMed and Sentinel-1 from both ascending and descending orbits have been processed by using SPINUA MTInSAR algorithm, in order to exploit the potentials of these two satellite missions to investigate ground displacements related to the slope instabilities. Mean velocity maps and displacement time series have been analysed looking, in particular, to non-linear trends that are possibly related to relevant ground instabilities and, thanks to the high spatial resolution, useful in terms of early warning, in the case of rigid soil masses. Results are presented and discussed in relation to the well know events occurred in the area of interest.

Multi-temporal Synthetic Aperture Radar Interferometry (MTInSAR) techniques allow detecting and monitoring millimetric displacements occurring on selected targets exhibiting coherent radar backscattering properties. Because of the bandwidth limitation of Synthetic Aperture Radar images, pulse responses are significantly affected by sidelobes that should be identified and masked out before the selection of coherent targets candidates. In fact, sidelobes often exhibit a coherent backscattering behavior and can be hence erroneously identified as persistent scatterers (PS). These artifacts can be also clearly visible in the images, in case of strong scatterers embedded in a surrounding weak clutter environment, such as the echoes generated by ships or buildings. The actual large amount of Geospatial Big Data fosters the implementation of automatic tools for sidelobe detection and cancelation. A number of algorithms have been proposed in the scientific literature for sidelobe reduction in Single-Look-Complex images, ranging from apodization methods to target extraction techniques. In this study we deal in particular with the Spatially Variant Apodization (SVA), a nonlinear filter based on cosine-on-pedestal weighting functions. This approach is attractive because it is able – in theory – to achieve a total sidelobe cancelation, without degrading the original image resolution, and for its computational efficiency. However, as shown in recent works, SVA suffers from several drawbacks: (i) it modifies the statistics of speckle-dominated areas, (ii) a negative bias is introduced in the reflectivity images over homogeneous areas, (iii) the amplitude and phase of the original images could be distorted by the SVA filtering. In particular, it has been demonstrated that SVA filtering compromise the quality of MTInSAR outcomes. Therefore, recent works propose the use of SVA for just identifying and masking out the radar coordinates of the detected side-lobes in the PS candidates position map. In this work we apply SVA for proper coherent target selection in COSMO-SkyMed STRIPMAP co-polarized interferometric data takes, acquired in onshore and offshore environments. In order to highlight both advantages and limitations of this technique, we analyze the performances of SVA approaches in terms of computational efficiency and robustness to focusing artifacts (responsible of non-ideal pulse responses). In particular, we test the SVA filtering both in simulation and in complex real scenarios, where sidelobes of close strong scatterers are mixed and superimposed upon each other. We show the outcomes of MTInSAR techniques before and after the application of SVA filtering. Acknowledgments The research is partly co-funded by the Italian Space Agency in the framework of the FAST4MAP project (“Fast & Advanced SAR Techniques for Monitoring & Alerting Processes” - ASI Contract n. 2015-020-R.0). CSK® Products© of ASI delivered by ASI under a license to use.

With the increasing quantity and quality of the imagery available from a growing number of SAR satellites and the improved processing algorithms, multi-temporal interferometry (MTI) is expected to be commonly applied in landslide studies. MTI can now provide long-term (years), regular (weekly-monthly), precise (mm) measurements of ground displacements over large areas (thousands of km2), at medium (~20 m) to high (up to 1-3 m) spatial resolutions, combined with the possibility of multi-scale (regional to local) investigations, using the same series of radar images. We focus on the benefits as well as challenges of multisensor and multi-scale investigations by discussing MTI results regarding two landslide prone regions with distinctly different topographic, climatic and vegetation conditions (mountains in Central Albania and Southern Gansu, China), for which C-band (ERS or ENVISAT) and X-band COSMO-SkyMed (CSK) imagery was available (all in Stripmap descending mode). In both cases X-band MTI outperformed C-band MTI by providing more valuable information for the regional to local scale detection of slope deformations and landslide hazard assessment. This is related to the better spatial-temporal resolutions and more suitable incidence angles (40°-30° versus 23°) of CSK data While the use of medium resolution imagery may be appropriate and more cost-effective in reconnaissance or regional scale investigations, high resolution data could be preferentially exploited when focusing on urbanized landslides or potentially unstable slopes in urban/peri-urban areas, and slopes traversed by lifelines and other engineering structures.

We focus on the use of advanced multi-temporal interferometry (MTI) for mapping and monitoring of ground deformations caused by open-cast mining and hydrocarbon production. We also show how MTI can be exploited to monitor the stability of infrastructure in adjacent areas. Open-cast mines represent a good target for MTI, because they are (1) often very large (from few to tens of km(2)); (2) free of or covered by sparse vegetation; (3) require long-term regular monitoring. The operational deformation monitoring via MTI can now rely on free of charge medium-resolution Sentinel-1 data, consistently and regularly acquired by the European Space Agency (ESA) since 2014. To illustrate the application potential of MTI based on Sentinel-1 data, we present the case study of the Belchatow mine (Poland), one of the largest open-cast mines in Europe. We stress that thanks to wide-area coverage; space-borne MTI represents a cost-effective approach to monitoring ground/slope instability hazards in large open pits, as well as the stability of the associated engineering structures and facilities. On-land oil and gas fields are also often huge and ground deformations induced by their exploitations can be profitably targeted by MTI. This is illustrated through an example of MTI application from the Middle East that relies on high-resolution (3m) radar data. The example highlights the possibility of obtaining extremely dense (spatially continuous) information, which is important for monitoring complex ground deformations caused by oil field exploitation.

he new multi-temporal interferometry (MTI) techniques can be profitably used to study land instability hazards. The potential appears great, but the MTI-derived results are yet to be fully explored, especially those based on high spatio-temporal resolution data. Here we focus on the use of MTI for mapping and monitoring of slope and ground instabilities in open-cast mines. They represent a good target for MTI, because they are i) often very large (from few to tens of km2); ii) free of or covered by sparse vegetation; iii) require long-term (years-decades) regular monitoring. Furthermore, given the often large extent of areas affected by surface mining and life span of mines (tens of years), long-term monitoring via traditional in-situ methods can be impractical (economically and technically). However, a review of the recent literature suggests that in comparison to applications to underground mines, MTI has been relatively little exploited to investigate ground instabilities related to surface mining. One reason for this is that some portions of open-cast mines can lack measurable radar targets due to rapid changes of ground surface caused by mining operations (e.g., overburden stripping, waste material damping). We argue that this limitation can now be (in part) mitigated by the higher frequency and regularity of acquisitions provided by the European Space Agency Sentinel-1 (S-1) mission (nominally every 6 days since Oct 2016). Indeed, S-1 medium resolution C-band SAR data acquired at 6 days imply improved time coherence with respect to previous C-band missions, leading to better coverage. We also argue that the initial reconnaissance approaches using S-1 data can be suitably integrated with high spatial resolution MTI (based on e.g., COSMO-SkeyMed or TerraSAR-X imagery) to provide most valuable information for the spatial and temporal analyses of slope deformation and a sound basis for derived products ranging from early slope instability hazard identification to individual landslide monitoring. To illustrate the potential and limitations of MTI for detecting and monitoring ground instabilities induced by surface mining, we present case study examples from two large coal open-cast operations in Europe.

Multi-temporal InSAR (MTI) applications pose challenges related to the availability of coherent scattering from the ground surface, the complexity of the ground deformations, atmospheric artifacts, and visibility problems related to ground elevation. Nowadays, several satellite missions are available providing interferometric SAR data at different wavelengths, spatial resolutions, and revisit time. A new and interesting opportunity is provided by Sentinel-1, which has a spatial resolution comparable to that of previous ESA C-band sensors, and revisit times improved by up to 6 days. According to these different SAR space-borne missions, the present work discusses current and future opportunities of MTI applications in terms of ground instability monitoring. Issues related to coherent target detection, mean velocity precision, and product geo-location are addressed through a simple theoretical model assuming backscattering mechanisms related to point scatterers. The paper also presents an example of a multi-sensor ground instability investigation over Lesina Marina, a village in Southern Italy lying over a gypsum diapir, where a hydration process, involving the underlying anhydride, causes a smooth uplift and the formation of scattered sinkholes. More than 20 years of MTI SAR data have been processed, coming from both legacy ERS and ENVISAT missions, and latest-generation RADARSAT-2, COSMO-SkyMed, and Sentinel-1A sensors. Results confirm the presence of a rather steady uplift process, with limited to null variations throughout the whole monitored time-period.

Advanced remote sensing techniques are now capable of delivering more rapidly high quality information that is sufficiently detailed (and cost-effective) for many engineering applications. Here we focus on synthetic aperture radar (SAR), multi-temporal interferometry (MTI). With radar satellites periodically re-visiting the same area, MTI provides information on distance changes between the on-board radar sensor and the targets on the ground (e.g., human-made structures such as buildings, roads and other infrastructure). The detected distance changes are thus interpreted as evidence of ground and/or structure instability. In settings with limited vegetation cover, MTI can deliver very precise (mm resolution), spatially dense information (from hundreds to thousands measurement points/km 2) on slow (mm-cm/year) deformations affecting the ground and engineering structures. Radar satellites offer wide-area coverage (thousands km 2) and, with the sensors that actively emit electromagnetic radiation and thus can "see'' through the clouds, one can obtain deformation measurements even under bad weather conditions. We illustrate the potential of high resolution MTI and explain what this technique can deliver to assist in infrastructure instability hazard assessment. This is done by presenting selected examples of MTI applied to monitor post-construction behavior of engineering structures. The examples are from Italy and include: an earthfill dam, an off-shore vertical breakwater built to protect an oil terminal, city buildings and a highway. We also stress that the current approach to the assessment of instability hazard can be transformed by capitalizing more on the presently underexploited advantage of the MTI technique, i.e., the capability to provide regularly spatially dense quantitative information for large areas where engineering infrastructure may currently be unaffected by instability, but where the terrain and infrastructure history (e.g., aging) may indicate potential for future failures.

Landslide investigations can now benefit from high quality information obtainable using multi-temporal interferometry (MTI) techniques (e.g., PSInSAR, SBAS) and images acquired by satellite synthetic aperture radars (SAR). MTI is only little affected by bad weather and can provide long-term (years), regular (weekly-monthly), precise (mm) measurements of ground displacements over large areas (thousands of km2), with the possibility of exploiting the same series of radar images for regional to slope-scale investigations. Spatially dense measurements can be obtained (from hundreds to thousands data per km2). Furthermore, by offering regular global-scale coverage, improved temporal resolution (from 12 to 6 days) and free imagery, the new radar satellite mission Sentinel-1 of the European Space Agency (ESA) can now guarantee wider and more efficient application of MTI to landslide investigations. In this work we demonstrate for the first time the excellent potential of MTI based on Sentinel-1 for the detection and monitoring of slope instabilities affecting small hilltop towns in the Apennine Mountains of southern Italy. The is done by comparing the MTI results based on Sentinel-1 images with those based on ENVISAT data (ESA satellite retired few years ago). The comparison shows that by using Sentinel-1 imagery a few times higher density of radar targets (measurement points) can be obtained. Thanks to this and more frequent measurement capability of Sentinel-1, landslide detection and monitoring can be more effective.

Indonesia is periodically affected by severe volcanic eruptions and earthquakes, which are geologically coupled to the convergence of the Australian tectonic plate beneath the Sunda Plate. Multi-temporal SAR interferometry (MTI) can be used to support studying and modelling of terrain movements. This work is aimed at performing an analysis of ground displacements over Indonesian sites through MTI techniques. Test sites have been selected according to the availability of archived SAR data, GNSS networks, and geological data. A stack of COSMO-SkyMed data, acquired in stripmap mode between 2011 and 2015, has been selected over the Banda Aceh region in Sumatra island. Geological maps of the test sites are available, and several GNSS stations from the Continuously Operating Reference Stations Indonesian network are found in the area of interest. Both the SPINUA and the StaMPS MTI algorithms have been used for processing the data, and deriving displacement maps. The ground deformations detected on the area are interpreted according to the available geological and geophysical information. The MTI results seem to confirm the inactivity of the Aceh fault segment, while the lack of coherent targets hinders reliable displacement measurements along the Seulineum segment. MTI data additionally allowed to identify local, non-tectonic ground instabilities: several areas are affected by subsidence due to unconsolidated coastal and alluvial sediments, deserving more investigations by local authorities. Finally, MTI results could be useful to integrate and update data from the existing GPS network.

Monitoring represents the main tool for carrying out evaluation procedures and criteria for spatial and temporal landslide forecast. The forecast of landslide behaviour depends on the possibility to identify either evidences of activity (displacement, velocity, volume of unstable mass, direction of displacement, and their temporal variation) or triggering parameters (rainfalls). Generally, traditional geotechnical landslide monitoring technologies permit to define, if correctly positioned and with adequate accuracy, the critical value of displacement and/or acceleration into landslide body. In most cases, they do not allow real time warning signs to be generated, due to environmental induced errors, and the information is related to few points on unstable area. Remote-sensing monitoring instruments are capable of inspecting an unstable slope with high spatial and temporal frequency, but allow solely measurements of superficial displacements and deformations. Among these latest technologies, the satellite Persistent Scatterer SAR Interferometry (PSInSAR) is very useful to investigate the unstable area both in terms of space and time. Indeed, this technique allows to analyse wide areas, individuate critical unstable areas, not identifiable by means detailed in situ surveys, and study the phenomenon evolution in a long time-scale. Although this technique usually adopts, as first approximation, a linear model to describe the displacement of the detected targets, also non-linear models can be used. However, the satellite revisit time, which defines the time sampling of the detected displacement signal, limits the maximum measurable velocity and acceleration. This makes it difficult to assess in the short time any acceleration indicating a loss of equilibrium and, therefore, a probable reactivation of the landslide. The recent Sentinel-1 mission from the European Space Agency (ESA), provides a spatial resolution comparable to the previous ESA missions, but a nominal revisit time reduced to 6 days. By offering regular global-scale coverage, better temporal resolution and freely available imagery, Sentinel-1 improves the performance of PSInSAR for ground displacement investigations. In particular, the short revisit time allows a better time series analysis by improving the temporal sampling and the chances to catch pre-failure signals characterised by high rate and non-linear behaviour signals. Moreover, it allows collecting large data stacks in a short time period, thus improving the PSInSAR performance in emergency (post-event) scenarios. In the present work, we propose to match satellite data with numerical analysis techniques appropriate to evidence unsteady kinematics and, thanks to the high resolution of satellite data and improved temporal sampling, to detect early stages of land instability phenomena. The test area is situated in a small town in the Southern Apennine, Basilicata region, affected by old and new huge landslides, now close to a lived outskirt.

This work experiments the potentialities of COSMO/SkyMed (CSK) data in providing interferometric Digital Elevation Model (DEM). We processed a stack of CSK data for measuring with meter accuracy the ground elevation on the available coherent targets, and used these values to check the accuracy of DEMs derived from 5 tandem-like CSK pairs. In order to suppress the atmospheric signal we experimented a classical spatial filtering of the differential phase as well as the use of numerical weather prediction (NWP) model RAMS. Tandem-like pairs with normal baselines higher than 300 m allows to derive DEMs fulfilling the HRTI Level 3 specifications on the relative vertical accuracy, while the use of NWP models still seems unfeasible especially for X-band.

High-resolution Synthetic Aperture Radar (SAR) data represent an essential resource for the extraction of Ground Control Points (GCP) with sub-metric accuracy without in situ measurement campaigns. Conceptually, SAR-based GCP extraction consists of the following two steps: (i) identification of the same local feature on more SAR images and determination of their range/azimuth coordinates; (ii) spatial 3D positioning retrieval from the 2D radar coordinates, through spatial triangulation (stereo analysis) and inversion methods. In order to boost the geolocation accuracy, SAR images must be acquired from different line of sights, with intersection angles typically wider than 10 degrees, or even in opposite looking directions. In the present study, we present an algorithm specifically designed for ensuring robustness and accuracy in the fully automatic detection of bright isolated targets (steel light poles or towers) even when dealing with opposite looking data takes. In particular, the popular Harris algorithm has been selected as detector because it is the most stable and robust-to-noise algorithm for corners detection on SAR images. We outline the designed algorithmic solution and discusses the results derived over the urban area of Pisa (Italy), where more than ten COSMO-SkyMed Enhanced Spotlight (ES) stereo images are available, thus resulting an optimal test site for an assessment of the performances of the processing chain. The experimental analysis proofs that, assumed timing has been properly recalibrated, we are capable to automatically extract GCP from CSK ES data takes consisting in a very limited number of images.

Ground Control Points (GCP), automatically extracted from Synthetic Aperture Radar (SAR) images through 3D stereo analysis, can be effectively exploited for an automatic orthorectification of optical imagery if they can be robustly located in the basic optical images. The present study outlines a SAR/Optical cross-matching procedure that allows a robust alignment of radar and optical images, and consequently to derive automatically the corresponding sub-pixel position of the GCPs in the optical image in input, expressed as fractional pixel/line image coordinates. The cross-matching in performed in two subsequent steps, in order to gradually gather a better precision. The first step is based on the Mutual Information (MI) maximization between optical and SAR chips while the last one uses the Normalized Cross-Correlation as similarity metric. This work outlines the designed algorithmic solution and discusses the results derived over the urban area of Pisa (Italy), where more than ten COSMO-SkyMed Enhanced Spotlight stereo images with different beams and passes are available. The experimental analysis involves different satellite images, in order to evaluate the performances of the algorithm w.r.t. the optical spatial resolution. An assessment of the performances of the algorithm has been carried out, and errors are computed by measuring the distance between the GCP pixel/line position in the optical image, automatically estimated by the tool, and the “true” position of the GCP, visually identified by an expert user in the optical images.

Rheticus® is an innovative cloud-based data and services hub able to deliver Earth Observation added-value products through automatic complex processes and, if appropriate, a minimum interaction with human operators. In this paper, we outlines the capabilities of the “Rheticus® Displacement” service, designed for geohazard and infrastructure monitoring through Multi-Temporal SAR Interferometry techniques.

We explore new possibilities offered by the recently available X-band satellite radar sensors for landslide hazard assessments on a detailed scale, with particular reference to the exploitation of Persistent Scatterers Interferometry (PSI) techniques. Special attention is paid to the impact of the improved resolution of new X-band radar imagery on the PSI results, in terms of quality and quantity of useful information. This evaluation is supported by theoretical modelling as well as by the comparison of results from X-band (CSK) and C-band (ENVISAT) PSI for two areas of interest: one in Italy and the other in Switzerland. It is demonstrated that with respect to medium resolution ENVISAT PS processing, fewer CSK high resolution images are sufficient to achieve comparable precision of the mean displacement velocity estimates. This, together with the shorter revisit times provided by the CSK constellation, can be very important when dealing with emergency situations. Furthermore, it is quantified that from about 3 to 11 times greater PS densities are obtained with the higher resolution X-band data. This implies more information about ground surface displacements as well as improved landslide monitoring and slope instability investigation capabilities. Furthermore, ground displacement measurements can be interpreted without local knowledge of the focus area or in situ controls, and, nonetheless, guide single hillslope instability assessments with support of Google Earth and its high resolution optical imagery. This “blind” approach will allow one to monitor remote and poorly known regions at high risk of potentially disastrous slope failures.

This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimated UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system.

Thanks to the technological maturity as well as to the wide availability of SAR data, Multi-temporal SAR Interferometry (MTInSAR) can be used to support systems devoted to environmental monitoring and risk management. In particular, high resolution X-band MTInSAR applications are also suitable for monitoring single man-made structures (buildings, bridges, railways and highways). The paper presents examples concerning the application of MTInSAR techniques and COSMO-SkyMed constellation for instability monitoring of infrastructures and, in particular, harbor docks and railways.

By mapping the concentration of chlorophyll-a (CHL) and the temperature of the sea surface (SST), satellite images reveal the complex dynamics of marine waters and prove to be a very powerful tool when used to detect potential fishing areas, significantly reducing the time of the search, the fuel consumption and the human effort, and simultaneously increasing the CPUE (catch per unit effort). In the present work, various techniques of multi-sensor, multi-resolution and multi-temporal data fusion are applied to multi-spectral satellite image data of MODIS-AQUA, MODIS-TERRA and VIIRS sensors, in order to detect "fronts" of chlorophyll concentration and temperature on the sea surface. According to the physical model of the phenomena, these fronts are generated by the upwelling of cold waters rich of nutrients (phytoplankton) which correspond to areas with a high concentration of pelagic fish and are characterized by high values of local gradients of SST and CHL with anti-parallel orientation. An automatic procedure has been developed to calibrate and validate the production in near-real time of daily maps of expected good fishing grounds to be provided to the FEDERPESCA fleet. The same procedure could be optimized also for other seas.

With the increasing number of radar satellites and improved data processing tools, multi-temporal interferometry (MTI) can considerably enhance our capabilities of monitoring landslide and subsidence hazards. MTI provides long-term (years), regular (weekly-monthly), precise (mm) measurements of ground displacements over large areas (thousands of km2), combined with high spatial resolution (up to 1-3 m) and possibility of multi-scale (regional to site-specific) investigations using the same series of radar images. To highlight the great potential of high resolution MTI we discuss application examples from two seismically active regions prone to land instability: i) Albania, including the large plain area occupied by the city of Tirana and nearby scarcely populated mountains, and ii) Haiti, including the Port-au-Prince metropolitan area, with coastal and mountain zones destabilized by the 2010 Mw 7.0 earthquake. It is shown that MTI can provide very useful results in a wide range of geomorphic, climatic and vegetation environments.

In this work we explored a dataset made by more than 100 images acquired by COSMO-SkyMed (CSK) constellation over the Port-au-Prince (Haiti) metropolitan and surrounding areas that were severely hit by the January 12th, 2010 earthquake. The images were acquired along ascending pass by all the four sensors of the constellation with a mean rate of 1 acquisition/week. This consistent CSK dataset was fully exploited by using the Persistent Scatterer Interferometry algorithm SPINUA with the aim of: i) providing a displacement map of the area; ii) assessing the use of CSK and PSI for ground elevation measurements; iii) exploring the CSK satellite orbital tube in terms of both precision and size. In particular, significant subsidence phenomena were detected affecting river deltas and coastal areas of the Port-au-Prince and Carrefour region, as well as very slow slope movements and local ground instabilities. Ground elevation was also measured on PS targets with resolution of 3m. The density of these measurable targets depends on the ground coverage, and reaches values higher than 4000 PS/km 2 over urban areas, while it drops over vegetated areas or along slopes affected by layover and shadow. Heights values were compared with LIDAR data at 1m of resolution collected soon after the 2010 earthquake. Furthermore, by using geocoding procedures and the precise LIDAR data as reference, the orbital errors affecting CSK records were investigated. The results are in line with other recent studies.

We apply a Bayesian Network (BN) paradigm to the problem of monitoring flood events through synthetic aperture radar (SAR) and interferometric SAR (InSAR) data. BNs are well-founded statistical tools which help formalizing the information coming from heterogeneous sources, such as remotely sensed images, LiDAR data, and topography. The approach is tested on the fluvial floodplains of the Basilicata region (southern Italy), which have been subject to recurrent flooding events in the last years. Results show maps efficiently representing the different scattering/coherence classes with high accuracy, and also allowing separating the multitemporal dimension of the data, where available. The BN approach proves thus helpful to gain insight into the complex phenomena related to floods, possibly also with respect to comparisons with modeling data.

The COSMO-SkyMed (CSK) constellation acquires data from its four SAR X-band satellites in several imaging modes, providing in particular different view angles. The present work investigates the potential of CSK constellation for ground elevation measurement through SAR radargrammetry. We selected an area around Parkfield (California), where several CSK acquisitions are available. We used for radargrammetric processing 2 CSK spotlight image pairs acquired at 1 day of separation, in Same Side Viewing configuration, with baselines of 350 km. Furthermore, a dataset of 33 spotlight images were selected to derive height measurements through both persistent scatterers interferometry(PSI) and interferometric processing of 5 1-day separated pairs included in the dataset. We first predict how the errors in the geometrical parameters and the correlation level between the images impact on the height accuracy. Then, two DEMs were derived by processing the radargrammetric CSK pairs. According to the outcomes of the feasibility analysis, processing parameters were chosen in order to guarantee nominal values of height accuracy within the HRTI Level 3 specifications. The products have a final resolution of 3 m. In order to assess the accuracy of these radargrammetric DEMs, we used the height values provided by the PSI, and an interferometric DEM derived from the CSK tandem-like pairs. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

We present the results of Persistent Scatterers Interferometry (PSI) applied to investigate slope instabilities in a remote high mountain region of Southern Gansu, known to be prone to large magnitude (M7-8) earthquakes and catastrophic slope failures. The PSI processing of high resolution (~3 m) COSMO/SkyMed (CSK) satellite images produced spatially dense information (more than 1,000 PS/km2) on ground surface displacements in the area of Zhouqu, a town located in the Bailong River valley. A substantial portion of the radar targets showed significant displacements (from few to over 50 mm/year), denoting wide- spread occurrence of slope instabilities. In particular, the PSI results provided valuable information on the activity of some very large, apparently slow landslides that represent a persistent hazard to the local population and infrastructure. Monitoring movements of large long-lived landslides is important especially when, as in the case of the Bailong valley, they are known to undergo periods of increased activity resulting in river damming and disastrous flooding. Given the general lack of monitoring data on large landslides at Zhouqu and on other similar major failures that are common in Southern Gansu, the PSI- derived displacements offer unique information, which, following expert judgment, can be used for preliminary wide-area assessments of hazards linked to landslide activity. Fur- thermore, this study shows that with the high resolution CSK data resulting in high radar target density, PSI can also assist in slope/landslide-specific assessments.

The paper investigates the potentialities of the COSMO/SkyMed (CSK) constellation for ground elevation measurement through conventional and multi-temporal SAR Interferometry (InSAR), with particular attention devoted to the impact of the improved spatial resolution with respect to the previous SAR sensors. The Atmospheric Phase Screen (APS) is wellknown to be the main source of errors for accurate topographic mapping through SAR interferometry, in case of monostatic sensors. Different strategies can be adopted to filter out this signal, ranging from the exploitation of the wellknown spatial and temporal statistics of the APS to the estimation of independent APS measurements through Numerical Weather Prediction (NWP) models. Their feasibility and the achievable accuracies are discussed here.

We apply multi-temporal Persistent Scatterer Interferometry (PSI) analysis to investigate slope instability in the Daunia region in the Southern Apennine Mountains. Daunia includes many small hill-top towns affected by landslides and is of particular interest for the Civil Protection – Regione Puglia Authority, one of the end users of the PSI deformation maps. The SPINUA algorithm is used to perform interferometric analysis and detect, with mm precision, the presence of ground surface movements. Consistent results on very slow displacements are obtained using the radar imagery acquired between 2002 and 2010 by the ENVISAT ESA satellite (C-band, medium spatial resolution sensor) and the images acquired between 2010 and 2011 by the X-band high resolution sensor onboard the TerraSAR-X satellite. Thanks to the finer spatial resolution the X-band PSI applications are very promising for monitoring single man-made structures and slope/ground instability in areas where C-band PS density is low.

The present study is aimed at investigating the potentialities of the COSMO/SkyMed (CSK) constellation for ground elevation measurement with particular attention devoted to the impact of the improved spatial resolution wrt the previous SAR sensors. Assuming no movement and successful orbital error removal, the main problem in height computation through InSAR techniques derives from the interferometric phase artifacts related to the interaction between microwave and the lower layers of the atmosphere (APS, Atmospheric Phase Screen). Different strategies can be adopted to filter out this signal, ranging from the exploitation of the well-known spatial and temporal statistics of the APS to the estimation of independent APS measurements through Numerical Weather Prediction (NWP) models. Their feasibility and the achievable accuracies are discussed here.

We present a research project, funded by the Italian Space Agency (ASI), aimed at performing 2D and 3D Focusing of COSMO/SkyMed (CSK) SAR Data. We describe the main objectives of the project, briefly illustrate employed techniques, and finally present the obtained results. The latter show that sub-meter resolution can be achieved in the enhanced spotlight CSK acquisition mode, and that by using 3D focusing it is possible to resolve scatterers at different slant heights within the same range-azimuth resolution cell, even in areas characterized by severe height discontinuities and large thermal dilations effects.

This chapter describes the different design steps needed to go from legacy code to a transformed application that can be efficiently mapped on the hArtes platform.

The Italian Space Agency (ASI Agenzia Spaziale Italiana) funded 27 scientific projects in the framework of COSMO-SkyMed (CSK) program. A subset of them focused on the improvements of the quality and quantity of information which can be extracted from X-SAR data if integrated with other independent techniques (GPS, data and imagery in other bands and wavelengths). The paper summarizes the results obtained from same of these projects and, in particular, regarding: - the use of GPS observations and Numerical Weather Models (NWM) to remove atmospheric artifacts from InSAR imagery so improving the CSK potentialities in the field of topographic mapping; - the integration of SAR data in X, L and C bands to improve snow cover monitoring and glaciers detection; - the use of X-SAR data to retrieve rain precipitation and its validation with C-band radar observations; - the improvements of the focusing techniques.

In the present work we present first results of ground deformation measurements inferred through repeat-pass Synthetic Aperture Radar (SAR) Interferometry (InSAR) in C- and X-band over an Italian Alpine area, in Lombardia region. The activity was carried out in the framework of the MORFEO (MOnitoraggio e Rischio da Frana mediante dati EO) project founded by the Italian Spatial Agency (ASI) and dedicated to landslide risk assessment. A number of areas affected by hydrogeological instabilities have been selected and studied in detail by processing both C- and X-band SAR data through SPINUA, a Persistent Scatterer like algorithm. In particular, two stacks of 30 Ascending ENVISAT SAR images (October 2004 - January 2009) and 32 Descending ENVISAT SAR images (December 2004 - January 2009) have been independently processed to ensures the detection of movements occurring along both west and east facing slopes. Moreover, further deformation measurements have been obtained by processing a set of 12 COSMO-SkyMED ascending HIMAGE interferometric acquisitions (Satellite CSKS1; Beam HI-03; POL: HH; Incidence Angle: 29°) provided by ASI. After a proper tuning of the interferometric algorithmic solutions, even with very high normal baselines, we are able to appreciate the potentials of X-band interferometry. Although the number of COSMO-SkyMED acquisitions is quite limited, spanning a period of only 10 months (August 2008 - June 2009), SPINUA was capable to retrieve preliminary ground displacement patterns that are in good agreement with those previously estimated in C-band. Quite impressive is to realize that, because of the tenfold improved resolution of X-band images, multi-temporal InSAR techniques may be successfully applied for the estimation of the displacement maps with a number of acquisitions much lower than in C-band. InSAR-derived displacements provided on areas of hydrogeological interest are going to be validated in the framework of MORFEO project by the geological partnership thanks to the availability of ground truths. In the present work, we present the results obtained on the towns of Garzeno, Catasco and Germasino which are affected by landslide phenomena. We provide a first validation by comparing the deformation maps derived from ENVISAT C-band data, from COSMO-SkyMED X-band data as well as from ERS and RADARSAT C-band data freely available on the GeoIFFI web-catalogue.

The TerraSAR-X (copyright) mission, launched in 2007, carries a new X-band Synthetic Aperture Radar (SAR) sensor optimally suited for SAR interferometry (InSAR), thus allowing very promising application of InSAR techniques for the risk assessment on areas with hydrogeological instability and especially for multi-temporal analysis, such as Persistent Scatterer Interferometry (PSI) techniques, originally developed at Politecnico di Milano. The SPINUA (Stable Point INterferometry over Unurbanised Areas) technique is a PSI processing methodology which has originally been developed with the aim of detection and monitoring of coherent PS targets in non or scarcely-urbanized areas. The main goal of the present work is to describe successful applications of the SPINUA PSI technique in processing X-band data. Venice has been selected as test site since it is in favorable settings for PSI investigations (urban area containing many potential coherent targets such as buildings) and in view of the availability of a long temporal series of TerraSAR-X stripmap acquisitions (27 scenes in all). The Venice Lagoon is affected by land sinking phenomena, whose origins are both natural and man-induced. The subsidence of Venice has been intensively studied for decades by determining land displacements through traditional monitoring techniques (leveling and GPS) and, recently, by processing stacks of ERS/ENVISAT SAR data. The present work is focused on an independent assessment of application of PSI techniques to TerraSAR-X stripmap data for monitoring the stability of the Venice area. Thanks to its orbital repeat cycle of only 11 days, less than a third of ERS/ENVISAT C-band missions, the maximum displacement rate that can be unambiguously detected along the Line-of-Sight (LOS) with TerraSAR-X SAR data through PSI techniques is expected to be about twice the corresponding value of ESA C-band missions, being directly proportional to the sensor wavelength and inversely proportional to the revisit time. When monitoring displacement phenomena which are known to be within the C-band rate limits, the increased repeat cycle of TerraSAR-X offers the opportunity to decimate the stack of TerraSAR-X data, e.g. by doubling the temporal baseline between subsequent acquisitions. This strategy can be adopted for reducing both economic and computational processing costs. In the present work, the displacement rate maps obtained through SPINUA with and without decimation of the number of Single Look Complex (SLC) acquisitions are compared. In particular, it is shown that with high spatial resolution SAR data, reliable displacement maps could be estimated through PSI techniques with a number of SLCs much lower than in C-band.

Landslides are one of the most serious natural and man induced hazards. The paper presents an innovative system dedicated to the measurement of landslide warning index. The system is based on a geographic information system (GIS) inference engine which properly combine satellite Earth observation (EO) measurements and static geophysical parameters. The system has been developed in the framework of an FP5 European project and it is aimed to provide an operative and flexible tool for public and private entities involved in land management, and in particular in mitigation of both landslide hazard and risk. Particular attention will be devoted to the role that the GIS environment plays as optimal measurement environment since it provides flexible interface between human (both high level geophysical experts and low level end users) and data (heterogeneous data in input to the geophysical model, warning maps in output).

We illustrate, through a sample application to a difficult landslide test site, the use of a novel method to detect potentially stable objects in Persistent Scatterers SAR Interferometry (PSI). Conventional PSI processing involves selecting first-guess potential stable objects, called PS Candidates (PSC), through thresholding of the amplitude dispersion index. This method can lead, in applications to scenes characterized by scarce urbanization, to very low PSC numbers, insufficient for a successful subsequent phase analysis if their spatial distribution is very sparse. Our classification-based approach relies on the proven fact that urban areas are more likely to contain PS pixels than any other land-cover class. Therefore, using pixels belonging to the urban land-cover class as PSC is a convenient way of increasing the number of initial fiducial points while keeping false alarm probabilities to reasonable levels. Results show that PSC belonging to the urban class, selected through simple external classification algorithms, lead to more consistent results for the final PS, both in terms of spatial density, and of reliability of displacement series.

Understanding the temporal dynamic of the biophysical properties of the coastal/shallow waters is a challenging and important task. In the present work Chlorophyll-a concentration in coastal zone shallow waters is obtained by inversion of the MERIS and MODIS level 1 calibrated, geo-located reflectance data. For this purpose, we have used both sensors 1:0 retrieve the chlorophyll concentration, in a scheme of multisensor data assimilation. In fact, the new generation sensor MERIS, on ESA's ENVISAT, with its spatial resolution of 300 meters and 3 days revisitation time, offers a high number of narrow spectral bands in the visible and in the IR. At the same time, MODIS, on NASA's Terra and Aqua Satellites, has a lower space resolution but an higher number of bands in the IR portion of the electromagnetic spectrum and can improve our atmospheric correction algorithms. Due to the high variability of the aerosol (type and concentration) and the water type, an accurate atmospheric correction method based on the 6S radiative transfer code has been performed. The atmospheric data required as input to the 6S code have been retrieved from the MODIS data. The estimated chlorophyll-a concentration has been computed from MERIS and MODIS data using a semi-analytic model, based on the optical properties of water and its components. To validate the inversion procedure, ground measurements have been collected monthly during the year 2003 and have been compared with the values derived from the inversion model.

In the last years, both local and global analysis techniques for the effective processing of interferometric SAR data have been proposed. We developed two local approaches to eliminate inconsistencies in the measured (wrapped) phase field, based on the local configurations of phase gradients in finite windows. The first technique adopts a fixed search strategy which 'cures' isolated residue couples by an appropriate series of corrections determined a priori. A second strategy uses the generalization capabilities of a neural network, trained on a suitable number of simulated target phase fields, to add 2 - (pi) cycles to the proper locations of the interferogram. These approaches, in spite of the high dimensionality of this problem, are able to correctly remove more than half the original number of pointlike inconsistencies on real noisy interferograms. This stems from the observation that phase unwrapping is an ill-posed problem, which has to be solved globally. Hence, a global stochastic method has been implemented, based on the minimization of a functional measuring the regularity of the phase field. The optimization tool used is simulated annealing with constraints. This methodology gives excellent results also in difficult conditions. We will present some of the recent results which aim at integrating the above-mentioned methodologies into powerful processing chains optimized for operating on large IFSAR datasets from real scenes. The effectiveness of such phase retrieving methods allows the application of sophisticated and innovative remote sensing techniques, such as differential interferometry.

2D phase unwrapping, a problem common to signal processing, optics, and interferometric radar topographic applications, consists in retrieving an absolute phase field from principal, noisy measurements. In this paper, we analyze the application of neural networks to this complex mathematical problem, formulating it as a learning-by-examples strategy, by training a multilayer perceptron to associate a proper correction pattern to the principal phase gradient configuration on local window. In spite of the high dimensionality of this problem the proposed MLP, trained on examples from simulated phase surfaces, shows to be able to correctly remove more than half the original number of pointlike inconsistencies on real noisy interferograms. Better efficiencies could be achieved by enlarging the processing window size, so as to exploit a greater amount of information. By pushing further this change of perspective, one passes from a local to a global point of view; problems of this kind are more effectively solved, rather than through learning strategies, by minimization procedures, for which we prose a powerful algorithm, based on a stochastic approach.

Phase unwrapping is one of the toughest problems in interferometric SAR processing. The main difficulties arise from the presence of point-like error sources, called residues, which occur mainly in close couples due to phase noise. We present an assessment of a local approach to the resolution of these problems by means of a neural network. Using a multi-layer perceptron, trained with the back- propagation scheme on a series of simulated phase images, fashion the best pairing strategies for close residue couples. Results show that god efficiencies and accuracies can have been obtained, provided a sufficient number of training examples are supplied. Results show that good efficiencies and accuracies can be obtained, provided a sufficient number of training examples are supplied. The technique is tested also on real SAR ERS-1/2 tandem interferometric images of the Matera test site, showing a good reduction of the residue density. The better results obtained by use of the neural network as far as local criteria are adopted appear justified given the probabilistic nature of the noise process on SAR interferometric phase fields and allows to outline a specifically tailored implementation of the neural network approach as a very fast pre-processing step intended to decrease the residue density and give sufficiently clean images to be processed further by more conventional techniques.

Coordinates in the 3D space of elements in a SAR image can be obtained by the combination of along-track, slant-range and interferometric fringe measurements. In order to evaluate the elevation of a pixel with respect to a slant- range reference plane, its absolute interferometric phase is required and this is typically derived unwrapping a 2D interferometric fringe pattern. Phase inconsistencies in SAR interferograms due to noise and topography determine unwrapping errors which appear as discontinuities in the computed absolute phase field. Phase aliasing arising from rapid phase variations from topography generates 2D unwrapping inconsistencies characterized by phase patterns statistically different from those induced by noise. In this paper, the spatial configurations of the phase field around residues is utilized in the phase unwrapping procedure. The feasibility of a neural network approach for classifying residual complex geometric phase patterns requiring different corrective measures is also presented. In addition, a method based on pseudo-differential interferometry to resolve residual inconsistencies as noise- or topography-generated is explored.