The exploitation of a multi-temporal stack of SAR intensity images seems to provide satisfactory results in flood detection problems when different spectral signature in presence of inundation are observed. Moreover, the use of interferometric coherence information can further help in the discrimination process. Besides the remote sensing data, additional information can be used to improve flood detection. We propose a data fusion approach, based on Bayesian Networks (BNs) , to analyze an inundation event, involving the Bradano river in the Basilicata region, Italy. Time series of COSMO-SkyMed stripmap SAR images are available over the area. The following random variables have been considered in the BN scheme: F, that is a discrete variable, consisting of two states: flood and no flood; the n-dimensional i variable, obtained by the SAR intensity imagery; the m-dimensional ? variable, obtained by the InSAR coherence imagery; the shortest distance d of each pixel from river course. The proposed BN approach allows to independently evaluate the conditional probabilities P(iF), P(?F) and P(Fd), and then to join them to infer the value P(F = floodi, ?, d), obtaining the probabilistic flood maps (PFMs). We evaluate these PFMs through comparisons with reference flood maps, obtaining overall accuracies higher than 90%.

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.

Accurate flood mapping is important for both planning activities during emergencies and as a support for the successive assessment of damaged areas. A valuable information source for such a procedure can be remote sensing synthetic aperture radar (SAR) imagery. However, flood scenarios are typical examples of complex situations in which different factors have to be considered to provide accurate and robust interpretation of the situation on the ground. For this reason, a data fusion approach of remote sensing data with ancillary information can be particularly useful. In this paper, a Bayesian network is proposed to integrate remotely sensed data, such as multitemporal SAR intensity images and interferometric-SAR coherence data, with geomorphic and other ground information. The methodology is tested on a case study regarding a flood that occurred in the Basilicata region (Italy) on December 2013, monitored using a time series of COSMO-SkyMed data. It is shown that the synergetic use of different information layers can help to detect more precisely the areas affected by the flood, reducing false alarms and missed identifications which may affect algorithms based on data from a single source. The produced flood maps are compared to data obtained independently from the analysis of optical images; the comparison indicates that the proposed methodology is able to reliably follow the temporal evolution of the phenomenon, assigning high probability to areas most likely to be flooded, in spite of their heterogeneous temporal SAR/InSAR signatures, reaching accuracies of up to 89%.

Multi-sensor, multi-band and multi-temporal remote sensing data can be very useful in precise flood monitoring. In this paper, we describe DAFNE, a Matlab (R)-based, open source toolbox, to produce flood maps from remotely sensed and other ancillary information, through a data fusion approach. DAFNE is based on Bayesian Networks, and is composed of several independent modules, each one performing a different task. Multi-temporal and multi-sensor data can be easily handled, with the possibility of producing time series of output flood maps, and thus follow the evolution of single or recurrent flood events. Here, an application of the toolbox is illustrated to delineate a flood map, close to the peak of inundation occurred in April 2015 on the Strymonas river (Greece), from multi-band optical and SAR data.

Classical applications of the MTInSAR techniques have been carried out in the past on medium resolution data acquired by the ERS, Envisat (ENV) and Radarsat sensors. The new generation of high-resolution X-Band SAR sensors, such as TerraSAR-X (TSX) and the COSMO-SkyMed (CSK) constellation allows acquiring data with spatial resolution reaching metric/submetric values. Thanks to the finer spatial resolution with respect to C-band data, X-band InSAR applications result very promising for monitoring single man-made structures (buildings, bridges, railways and highways), as well as landslides. This is particularly relevant where C-band data show low density of coherent scatterers. Moreover, thanks again to the higher resolution, it is possible to infer reliable estimates of the displacement rates with a number of SAR scenes significantly lower than in C-band within the same time span or by using more images acquired in a narrower time span. We present examples of the application of a Persistent Scatterers Interferometry technique, namely the SPINUA algorithm, to data acquired by ENV, TSX and CSK on selected number of sites. Different cases are considered concerning monitoring of both instable slopes and infrastructure. Results are compared and commented with particular attention paid to the advantages provided by the new generation of X-band high resolution space-borne SAR sensors.

In the Northern part of the Apulia Region, between the Lesina Lagoon and the mouth of the Fortore River, isplaced the Pietre Nere (black stones) Point, a very interesting site and the only outcrop of magmatic rocks in thePuglia region and in the whole Adriatic coast of Italy. The excavation of a canal through this area exposed greymicro- and meso-crystalline gypsum with intercalations of black limestones and marls of Upper Triassic age,mantled by loose sandy Quaternary deposits.The gypsum bedrock shows a high density of cavities, either dissolutional conduits or voids related to gravitationalcollapse processes. Starting from about 1970, a wide new touristic settlement has been built over the area, whichin turn, starting from about 1990, began to suffer for the increasing formation of sinkholes.Several interpretations have been proposed to explain the outcrops of Triassic evaporites that occur in the PietreNere Point area, previously buried by a sequence several kilometres thick of Mesozoic rocks: diapirism; pushingupwards by compressional tectonics; both halokinesis and tectonic deformation.The presence of the sinkholes and of the karst reactivation leads to the demand of a monitoring system, for thedetection of vertical displacements over a large area.Thanks to the ability of radar systems to operate in all weather conditions, day or night, and the possibilityof accurately measuring small surface deformations (changes in altitude of a few millimeters), SAR (syntheticaperture radar) differential interferometry (DInSAR) is an ideal technique for detecting and monitoring grounddeformation phenomena (subsidence, faults, landslides, etc.) over vast areas. As an evolution of DInSAR,persistent scatterers interferometry (PSI) [1] allows to follow millimetric movements of stable objects (mainlybuilding and man-made features) present on the Earth surface through time, studying the interferometric responseof such objects along series of SAR acquisitions.We used data from the ASAR sensor onboard the European Space Agency's ENVISAT satellite, from bothascending (34 acquisitions) and descending (28 acquisitions) geometry, covering a total time interval from May2003 to December 2009.Data were processed with a combination of open-source and in-house developed software [2] in order to extractrelevant information about mean velocities of stable points located on the Lesina Marina area.Relying on the relatively smooth nature of the investigated phenomenon, and assuming negligible north-southmovements, as justified by the overall geometry of the site geomorphological units, information coming fromascending and descending geometries was interpolated over a common georeferenced grid, then combined toobtain vertical and horizontal (east-west) velocity components.We observe PS objects undergoing uplift displacements in both ascending and descending data, with uplift ratesdecreasing in a roughly W-SW direction

Multi-temporal InSAR (MTI) applications pose challenges related to the availability of coherent scattering from the ground surface, the complexity of the ground deformations, the atmospheric artifacts, the visibility problems related to the ground elevation. Nowadays, several satellite missions are available providing interferometric SAR data at different wavelengths, spatial resolutions, and revisit time. A new interesting opportunity is provided by Sentinel-1 mission, which has a spatial resolution comparable to previous ESA C-band missions, and revisit times reduced to up to 6 days. It is envisioned that, by offering regular, global-scale coverage, improved temporal resolution and freely available imagery, Sentinel-1 will guarantee an increasing use of MTI for ground displacement investigations. According to these different SAR space-borne missions, the present work discusses current and future opportunities of MTI applications to ground instability monitoring. Issues related to coherent target detection and mean velocity precision will be addressed through a simple theoretical model assuming backscattering mechanisms related to point scatterers. The paper also presents an example of multi-sensor ground instability investigation over the site of Marina di Lesina, Southern Italy, a village lying over a gypsum diapir, where a hydration process, involving the underlying anhydride, causes a smooth uplift pattern affecting the entire village area, and the formation of scattered sinkholes. More than 20 years of MTI SAR data have been used, coming from both legacy ERS and ENVISAT missions, and last-generation Radarsat-2, COSMO-SkyMed, and Sentinel-1A sensors

Space-borne SAR Differential Interferometry (DInSAR) techniques are attractive for landslide investigations because of their capability to provide regional scale coverage and, under favourable conditions, spatially dense information on small ground surface deformations. In particular, advanced multi-temporal InSAR techniques such as Persistent Scatterer Interferometry (PSI) allow detecting and monitoring, with millimetre precision, displacements occurring on selected radar targets (PS) exhibiting coherent radar backscattering properties. PS targets correspond mainly to man-made structures or to rock outcrops, and their spatial density depends on the ground coverage, and it is maximum over urban areas. The application of multi-temporal InSAR analysis to slope instability monitoring poses challenges related to the complex kinematics of the phenomenon, as well as to the unfavourable settings of the area affected by landslides, often occurring on sites of limited extension, characterized by steep topography and variable vegetation cover. This is the case of the Daunia region, located in the Southern Italian Apennine Mountains, which is characterised by scarce urbanisation (mainly small hill-top towns) and dense vegetation cover. The SPINUA (Stable Point INterferometry over Un-urbanised Areas) PSI multi-temporal processing technique was used in the past years to detect and measure ground displacements over this region. Both C-band medium resolution SAR data from ERS-1/2 and ENVISAT ESA satellites, and X-band high resolution SAR data from the TerraSAR-X (TSX) satellite were used. Results indicate that PSI can be profitably used to investigate slope instability, mainly over the urban and peri-urban areas, and that, on these sites, TSX data result very promising for monitoring areas where ERS/ENVISAT PS density is too low. Nevertheless, the application of PSI for slope instability monitoring still remain problematic or impossible in rural and mountainous areas. This is the case, for instance, of the Municipality of Carlantino, where PS targets detected by both C- and X-band data correspond to urban structures or peri-urban walls and guard rails, while a large landslide, extending for about 2 km from the hilltop down to the valley, is lacking stable coherent targets, due to the vegetation cover. In order to allow stability monitoring through spaceborne SAR interferometry, a network of passive reflectors was designed and deployed on the area of interest. The Corner Reflectors (CR) were designed for TerraSAR-X stripmap acquisitions, and consist of three triangular metal panels welded perpendicular to each others to form a trihedral shape which ensures that the radar signal is scattered back to the sensor. A small size is preferred to minimize the curvature of the side panels, the effect of wind, the exposition to vandalism, and to allow easier transportation and deployment in the harsh terrain setting. To design the CR network, different factors were taken

The application of Persistent Scatterer Interferometry (PSI) to slope instability monitoring poses challenges related to the complex kinematics of the phenomenon, as well as to the unfavourable settings of the area affected by landslides, often occurring on sites of limited extension, characterized by steep topography and variable vegetation cover. New-generation SAR sensors, such as TerraSAR-X (TSX) thanks to their higher spatial resolution, make PSI applications very promising for monitoring areas with low density man-made. Nevertheless, the application of techniques still remains problematic or impossible in rural and mountainous areas. This is the case, for instance, for the Municipality of Carlantino, in Southern Italy. Both C-band medium resolution SAR data from ESA satellites, and X-band high resolution SAR data from the TSX satellite, were processed through the PSI algorithm SPINUA. Despite the higher spatial density of PS from TSX, the landslide body is lacking coherent targets, due to vegetation and variable land cover. To allow stability monitoring, a network of six CRs was designed and deployed over the landslide test site. Twenty-six TSX stripmap images were processed by using both PSI and an ad hoc procedure based on double-difference analysis of DInSAR phase values on the CR pixels, constrained by the accurate CR height measurements provided by DGPS. Despite the residual noise due to the sub-optimal CR network and the strong atmospheric signal, displacement estimation on the CRs allows to propagate the PSI results downslope, proving the stability of the landslide area subjected to consolidation works.

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. Two test sites in Sumatra and Java have been selected according to the availability of archived SAR data, GNSS networks, and geological data. Both COSMO-SkyMed (CSK) and Senitnel-1 data-sets have been processed through MTI algorithms. The derived displacement maps have been interpreted according to the available geological and geophysical information.

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.

We present a case study of a long-term integrated monitoring of a flood event which affected part of the Strymonas dammed river basin, a transboundary river with source in Bulgaria, which flows then through Greece to the Aegean Sea. The event, which affected the floodplain downstream the Kerkini dam, started at the beginning of April 2015, due to heavy rain upstream of the monitored area, and lasted for several months, with some water pools still present at the beginning ofSeptember, due to the peculiar geomorphological conditions of the watershed. We collected a multi-temporal dataset consisting of a high-resolution, X-band COSMO- SkyMed, and several C-band Sentinel-1 SAR and optical Landsat-8 images ofthe area. The results allow following the event in time, sketching amulti-temporal map ofthe post-flood evolution, with relatively high temporal res- olution. We then use hydrological modeling to mimic the dynamics of the flooded area against post event weather patterns and thus explain the observed flood extent evolution. We show how integrating remote sensing-derived maps offlooded areas, geomorphological analyses of the landscape and simplified hydrological modeling allows accurate inference about long-termdynamics offlooded areas, very important in the post event in anthropogenic highlymodified areas, where recovery time after the flood event is considerable, and long term water persistence may lead to large consequences, carrying economic damages and medical emergencies.

High-resolution, remotely sensed images of the Earth surface have been proven to be of help in producing detailed flood maps, thanks to their synoptic overview of the flooded area and frequent revisits. However, flood scenarios can be complex situations, requiring the integration of different data in order to provide accurate and robust flood information. Several processing approaches have been recently proposed to efficiently combine and integrate heterogeneous information sources. In this paper, we introduce DAFNE, a Matlab®-based, open source toolbox, conceived to produce flood maps from remotely sensed and other ancillary information, through a data fusion approach. DAFNE is based on Bayesian Networks, and is composed of several independent modules, each one performing a different task. Multi-temporal and multi-sensor data can be easily handled, with the possibility of following the evolution of an event through multi-temporal output flood maps. Each DAFNE module can be easily modified or upgraded to meet different user needs. The DAFNE suite is presented together with an example of its application.

Monitoring represents the main tool for carrying out evaluation procedures and criteria for spatial and temporallandslide forecast. The forecast of landslide behaviour depends on the possibility to identify either evidences ofactivity (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 positionedand with adequate accuracy, the critical value of displacement and/or acceleration into landslide body. Inmost cases, they do not allow real time warning signs to be generated, due to environmental induced errors, andthe information is related to few points on unstable area. Remote-sensing monitoring instruments are capableof inspecting an unstable slope with high spatial and temporal frequency, but allow solely measurements ofsuperficial displacements and deformations.Among these latest technologies, the satellite Persistent Scatterer SAR Interferometry (PSInSAR) is veryuseful to investigate the unstable area both in terms of space and time. Indeed, this technique allows to analysewide areas, individuate critical unstable areas, not identifiable by means detailed in situ surveys, and study thephenomenon evolution in a long time-scale.Although this technique usually adopts, as first approximation, a linear model to describe the displacementof the detected targets, also non-linear models can be used. However, the satellite revisit time, which defines thetime 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 comparableto the previous ESA missions, but a nominal revisit time reduced to 6 days. By offering regularglobal-scale coverage, better temporal resolution and freely available imagery, Sentinel-1 improves the performanceof PSInSAR for ground displacement investigations.In particular, the short revisit time allows a better time series analysis by improving the temporal samplingand 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 inemergency (post-event) scenarios.In the present work, we propose to match satellite data with numerical analysis techniques appropriate toevidence 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 andnew huge landslides, now close to a live

The recent availability of large amounts of remotely sensed data requires setting up efficient paradigms for the extraction of information from long series of multi-temporal, often multi-sensor, datasets. In this field, monitoring of terrain instabilities is currently performed through algorithms which estimate millimetric displacements of stable (coherent) objects, through analysis of stacks of SAR images acquired in interferometric mode. The result is generally a decomposition of at least part of the complete complex covariance matrix obtained from all possible pairwise combinations of the images in the stack, separating its spatially- and temporally-correlated parts.The same SAR temporal data stacks can be used to apply change detection algorithms, to reveal, over potentially huge spatial scales and with high resolution, terrain surface changes due to e.g. environmental hazards (floods, fires, earthquakes). In this case, again, the temporal covariance matrix contains in practice all the information related to the environmental changes.The covariance matrix, or its normalized version, known as coherence matrix, expresses thus all the information content related to a time series of remotely sensed, coherent data. In the case of SAR data, this kind of representation offers a unified framework for the study of phenomena linked either to the presence of "periods" of persistent scattering characteristics, or to changes of backscattering patterns, hinting to variations in the terrain characteristics.The average operation, involved in the definition of the above-mentioned covariance and coherence matrices, has to be performed necessarily over "homogeneous" pixel sets. This homogeneity criterion can be intended in various ways, including the one connected to the covariance definition itself, thus leading to a sort of recursive estimation process.Moreover, such homogeneity measures are often used as a substitute for the classical Euclidean distance in nonlocal estimate implementation frameworks, used for instance in the design of effective SAR speckle filters.The coherence matrix highlights the role of the interferometric phase. After having suitably modeled various phase contributions, due to topography, atmosphere, etc., it is possible to detect periods in which a target remains stable, and can thus be used as a benchmark for estimating ground deformations or other effects related to the variations of the signal optical path.From the above discussion, it appears that a thorough, physically based modeling of the coherence over such long times series of SAR data constitutes a priority for efficient data exploitation.We illustrate some of the inference which can be made starting from a time series of more than a hundred COSMO-SkyMed (CSK) images acquired in InSAR mode over the Haiti capital of Port-Au-Prince, spanning a period of almost 3 years with short repeat times. Such tight acquisition schedule can be obtained nowadays with latest-generation

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/km2 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.

The Multi-Chromatic Analysis (MCA) uses interferometric pairs of SAR images processed at range sub-bands and explores the phase trend of each pixel as a function of the different central carrier frequencies. The MCA technique introduces the concept of targets exhibiting stable radar returns across the frequency domain (PSfd). In this work we compare this stability along frequencies with the temporal stability which is at the base of persistent scatterers interferometry (PSI) techniques. Different populations of PSfd and "temporal" PS were derived by using COSMOSkyMed SAR data. An ad hoc processing scheme was developed to derive PSI products by processing the same range sub-bandwidth used by the MCA in order to guarantee the same scattering conditions. The populations of PSfd and "temporal" PS were compared and preliminary considerations provided concerning the scattering properties of the targets selected by the two criteria.

In questo lavoro viene presentato il modello SIGNUM acronimo per "Simple Integrated Geomorphological NUmericalModel". Trattasi di un modello numerico di evoluzione del paesaggio basato su TIN e sviluppato in Matlab. SIGNUM è ingrado di simulare l'evoluzione di paesaggi a scala di bacino o catena per intervalli temporali che vanno dalle decine al milionedi anni.

Image alignment is a crucial step in synthetic aperture radar (SAR) interferometry. Interferogram formation requires images to be coregistered with an accuracy of better than a few tenths of a resolution cell to avoid significant loss of phase coherence. In conventional interferometric precise coregistration methods for full-resolution SAR data, a 2-D polynomial of low degree is usually chosen as warp function, and the polynomial parameters are estimated through least squares fit from the shifts measured on image windows. In case of rough topography or long baselines, the polynomial approximation may become inaccurate, leading to local misregistrations. These effects increase with spatial resolution of the sensor. An improved elevation-assisted image-coregistration procedure can be adopted to provide better prediction of the offset vectors. This approach computes pixel by pixel the correspondence between master and slave acquisitions by using the orbital data and a reference digital elevation model (DEM). This paper aims to assess the performance of this procedure w.r.t. the standard one based on polynomial approximation. Analytical relationships and simulations are used to evaluate the improvement of the DEM-assisted procedure w.r.t. the polynomial approximation as well as the impact of the finite vertical accuracy of the DEM on the final coregistration precision for different resolutions and baselines. The two approaches are then evaluated experimentally by processing high-resolution SAR data provided by the COnstellation of small Satellites for the Mediterranean basin Observation (COSMO/SkyMed) and TerraSAR-X missions, acquired over mountainous areas in Italy and Tanzania, respectively. Residual-range pixel offsets and interferometric coherence are used as quality figure. © 2006 IEEE.

Many applications of synthetic aperture radar differential interferometry (DInSAR) lead to a set of sparse phase measurements, e.g. in the processing of long multitemporal stacks of SAR differential interferograms through persistent scatterers interferometry (PSI) techniques. Often, sparse phase data have to be unwrapped, and then interpolated on a regular grid to be useful for subsequent processing steps. This step is necessary for instance in the reconstruction of the so-called APS (Atmospheric Phase Screen). Atmospheric artifacts superimposed on DInSAR measurements have the potential of hindering the accurate estimation of deformation signals. Indeed, sometimes the spatial frequencies of the atmospheric phase contributions can overlap those of deformation signals, so that such artifacts can be misinterpreted as deformation features.For the phase unwrapping stage, the solutions are directly dependent on the PS network density; moreover, phase aliasing, which appears when the signal sampling does not satisfy the Nyquist condition, especially in presence of noise, increases when passing from regular-grid to sparse data. This is because the phase sampling conditions get usually worse.An improvement of the APS estimation step has been proposed, by investigating from the empirical point of view an alternative procedure, which involves an interpolation of the complex field derived from the sparse phase measurements. Unlike traditional approaches, the proposed method allows to bypass the PU step and obtain a regular-grid complex field, from which a wrapped phase field can be extracted. Under general conditions, this smooth phase field can be shown to be a good approximation of the original phase without noise. Moreover, the interpolated, wrapped phase field can be fed to state of the art, regular grid PU algorithms, to obtain a smoother absolute phase field.The performances of this empirical approach are evaluated here over a real dataset, that is composed by 30 ascending SAR X-band COSMO-SkyMed images. The images cover the urban area and outskirts of the capital of Haiti, Port-au-Prince.The accuracy of the reconstructed phase fields is analyzed by the local value of the final inter-image phase coherence (?int), a quality figure related to the residual phase noise after subtraction of all modeled contributions. Its values are taken on points (PS) not used in the interpolation, using different spatial densities and random subsampling patterns in a test area characterized by a strong subsidence bowl.The obtained results may be applied into a broader context than the one specific to the PSI technique, considering the few assumptions on the initial phase field, i.e. its smoothness and good sampling conditions.

We present an example of integration of persistent scatterer interferometry (PSI) and in situ measurements over a landslide in the Bovino hilltop town, in Southern Italy. First, a wide-area analysis of PSI data, derived from legacy ERS and ENVISAT SAR image time series, highlighted the presence of ongoing surface displacements over the known limits of the Pianello landslide, located at the outskirts of the Bovino municipality, in the periods 1995-1999 and 2003-2008, respectively. This prompted local authorities to install borehole inclinometers on suitable locations. Ground data collected by these sensors during the following years were then compared and integrated with more recent PSI datafrom a series of Sentinel-1 images, acquired from March 2014 to October 2016. The integration allows sketching a consistent qualitative model of the landslide spatial and subsurface structure, leading to a coherent interpretation of remotely sensed and ground measurements. The results were possible thanks to the synergistic operation of local authorities and remote sensing specialists, and could represent an example for best practices in environmental management and protection at the regional scale.

The Multi-Chromatic Analysis can be applied to interferometric pairs of SAR images processed at range sub-bands, and consists of exploring the phase trend of each pixel as a function of the different central carrier frequencies. The phase of stable scatterers evolves linearly with the sub-band central wavelength, with a slope proportional to the absolute e. m. path difference. The technique appears optimally suited for the new generation of satellite sensors, which operate with larger bandwidths than previously available instruments, generally limited to few tens of MHz. A first experiment on satellite data was carried out by processing a spotlight interferometric pair of images acquired by TerraSAR-X on the well-known Uluru monolith in Australia. In the present work, we illustrate MCA processing on SAR data acquired over the same site by the COSMO-SkyMed constellation. The topographic profile of the monolith is successfully reconstructed. Furthermore, the results are also compared with those previously derived by processing TerraSAR-X data.

The Multi-Chromatic Analysis (MCA) consists of performing sub-bands splitting in range frequency domain, thus generating chromatic views of lower range resolution, centered at different carrier frequencies. Multi-chromatic interferograms can be then generated by coupling chromatic views coming from an interferometric pair of SAR images. The interferometric phase of spectrally-stable scatterers evolves linearly with the sub-band central frequency, the slope being proportional to the absolute optical path difference. Unlike the standard "monochromatic" InSAR approach, this new technique allows performing spatially independent and absolute phase unwrapping (PU). Potential applications for the study of spectrally-stable targets include topographic measurements, atmospheric research or urban monitoring.The technique appears optimally suited for new-generation, wide-band, high-resolution satellite SAR sensors. This work presents first successful applications of the technique using both TerraSAR-X (TSX) and COSMO/SkyMed (CSK) spotlight data. In particular, we provide results concerning the use of MCA for performing absolute PU as well as for height measurement on a pixel-by-pixel basis. Moreover, the impact of coregistration procedure on the MCA-based inference is investigated.

Applications such as SAR interferometry [1] are increasingly used in "sparse" contexts, in which information about some geophysical parameters (e.g. millimetric terrain deformations) are only available over some of the imaged pixels, corresponding to stable objects [2]. In such cases, it is often necessary to adapt processing algorithms, developed and optimized for regular data grids, to work on sparse samples. One of such algorithms, at the basis of several InSAR processing chains, is the so-called phase unwrapping (PU), consisting of obtaining absolute phase values (i.e. defined over the whole real interval) from the corresponding principal values, i.e. limited to the interval [??, ?[.Recently, a method to reduce the unwrapping problem of a sparse-grid field to one corresponding to a regular grid, has been proposed [3], based on a preliminary nearest-neighbor interpolation step. The solution to the sparse problem is shown to be mathematically equivalent to that of a corresponding regular grid problem, properly derived from the former. The approach allows to employ existing algorithms for regular-grid PU, such as those based on network theory (e.g. the so-called Minimum Cost Flow, or MCF).In this work, stemming from an analysis of the above-mentioned methodology, giving as a solution an absolute phase significant only over the sampled pixels, we propose an alternate procedure, in which the principal phase interpolation step is based on algorithms more advanced than the simple nearest-neighbor scheme. Such interpolation can be performed over the unit-magnitude complex field obtained from the wrapped phase. In this way, the obtained wrapped phase field results more similar to the original, "physical" regular field from which the sparse samples have been obtained.In the case in which this latter field can be assumed to satisfy general conditions of smoothness and homogeneity [4], this allows to exploit at best such characteristics, and to have finally an absolute phase regular matrix more representative of the real data, and then more effective to use in the subsequent processing steps [5].In the paper, several interpolators are considered, such as radial basis functions (RBF), as well as, more generally, Kriging [6], and their performances and application limits are evaluated in simulation, as a function of both the regularity conditions of the original sampled surface, and the sampling density.

Indonesia is periodically affected by severe volcanic eruptions and earthquakes, which are geologically coupled to theconvergence of the Australian tectonic plate beneath the Sunda Plate. Multi-temporal SAR interferometry (MTI) can beused to support studying and modelling of terrain movements. This work is aimed at performing an analysis of grounddisplacements over Indonesian sites through MTI techniques. Test sites have been selected according to the availabilityof archived SAR data, GNSS networks, and geological data. A stack of COSMO-SkyMed data, acquired in stripmapmode between 2011 and 2015, has been selected over the Banda Aceh region in Sumatra island. Geological maps of thetest sites are available, and several GNSS stations from the Continuously Operating Reference Stations Indonesiannetwork are found in the area of interest. Both the SPINUA and the StaMPS MTI algorithms have been used forprocessing the data, and deriving displacement maps. The ground deformations detected on the area are interpretedaccording to the available geological and geophysical information. The MTI results seem to confirm the inactivity of theAceh fault segment, while the lack of coherent targets hinders reliable displacement measurements along the Seulineumsegment. MTI data additionally allowed to identify local, non-tectonic ground instabilities: several areas are affected bysubsidence 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.

Indonesia is periodically affected by severe volcanic eruptions and earthquakes, which are geologically coupledto the convergence of the Australian tectonic plate beneath the Sunda Plate. This work is aimed at performing ananalysis of ground displacements over Indonesian sites through Multi-temporal SAR interferometry (MTI). Twotest sites, in Sumatra and Java, have been selected according to the following requirements: presence of groundinstabilities, possibly related to onshore active faults or volcanoes; good expected interferometric coherence,availability of reliable archived interferometric SAR datasets, availability of ancillary geophysical data.Displacement maps have been obtained by processing COSMO-SkyMed and Sentinel-1 datasets available on thearea, through SPINUA algorithm, which performs Persistent Scattering (PS) analysis. The use of datasets comingfrom two datasets, allows cross-validating final results. The processing of Sentinel-1 data has been more complexw.r.t. that of COSMO-SkyMed data, as standard MTI displacement maps showed strong artifacts, likely due toresidual atmospheric contributions and orbital errors. In order to overcome this problem, an alternative processingscheme has been experimented.The tectonic analysis in Indonesia is difficult because the vegetation cover in the area causes lack of PS along andacross the faults. Our MTI results provided useful information about the ground stability/instability within theselected test sites. In particular, concerning the tectonic activity in Sumatra, the MTI displacement analysis seemsto confirm the inactivity of the Aceh fault segment, as foreseen by geodetic studies. Also, in the Java test site nodisplacement signal was detected related to possible activity of the faults present in the area.Besides the tectonic activity, ground displacements were also identified basically reflecting local effects. Thecauses of these displacements were investigated by using ancillary geological data, and in situ inspections.The subsidence phenomena are mainly related to the presence of unconsolidated coastal/alluvial sediments andgroundwater pumping.An interesting example concerns a coastal area in Banda Aceh, which was overrun and completely destroyedby the 2004 tsunami. Most subsiding PS targets are positioned on port facilities structures and embankments.Extensive rebuilding and new constructions in the area add weight to the unconsolidated sediments. There is alsoan extensive presence of seasonally flooded crops and salt production flats. This suggests that the subsidenceoccurring in the area is probably related to compaction of sediments and/or recent artificial fill.A subsidence has been also revealed in Java over the Yogyakarta urban area. This local displacement is inducedby groundwater exploitation and soft sediment compaction, a result of major urban expansion and human activityduring the last years. The high resolution of COSMO-SkyMed data allows catching

We apply persistent scatterer interferometry (PSI) techniques to synthetic aperture radar (SAR) data from ERS and ENVISAT satellites on the Lesina Marina area, a coastal tourist village in Apulia, Southern Italy, where the excavation of a canal exposed grey micro- and meso-crystalline gypsum which is now showing a high density of cavities and sinkholes due to gravitational collapse processes. We observe PS objects undergoing displacements, along the sensor line of sight, forming the same relatively smooth pattern in all the processed data stacks. Vertical displacement rates, derived through integration of ascending and descending geometries, reach about 4 mm/year on locations adjacent to the canal, gently decreasing towards the western end of the built-up area. High-precision leveling measurements, performed in 1999 and 2010, reveal a substantial agreement with the ENVISAT PSI data, taking into account a small bias due to the choice of the leveling reference point. The dataset, thus validated, suggests the presence of an uplift phenomenon going on steadily for the entire timespan covered by the SAR observations (1992--2009). These observations, supported by petrographic data and in situ investigations, seem only in part compatible with a residual diapirism, and hint instead to more complex processes, such as a combination of diapirism and the hydration of the residual anhydrite in the core of the gypsum mass. These results confirm the importance of the integration between in situ, geologic and geophysical, remotely sensed investigations, as the latter often represent an essential tool to infer whether a given phenomenon, which can be hypothesized by the former, is presently under development.

Competition and synergy between tectonic and erosional processes are recognized as the main factors influencingthe shape of many landscapes.While considerable efforts are dedicated to the explanation of particular landscape forms and features, such asthose found in some parts of the Earth surface, another aspect which is rising interest in the scientific communityis the emergence of similar patterns and regularities in a variety of situations and environmental conditions.Recent investigations, for instance, have been dedicated to the analysis of landscape features such as regular valleyspacing in drainage networks evolving on slopes affected by competing tectonic uplift and terrain erosion.Analysis of digital terrain models reproducing either actual features, or simulated surfaces obtained throughapplication of landscape processes to synthetic terrain, have shown how the emergence and persistence ofconsiderable degrees of regularity in the terrain dissection into parallel river basins is a feature common to bothtypes (real and simulated) of landscapes. Such a regularity has been observed in linear mountain fronts, in differenttypes of tectonic and climatic settings [Hovius 1996, Talling et al. 1997, Castelltort & Simpson 2006].Regular river spacing has been also observed in simulated landscapes obtained through application of numericalmodels [Perron et al. 2009], or indoor scaled reproductions of an orogen subject to erosion by rain-wash[Bonnet 2009]. Several classes of explanations have been proposed for the onset and persistence of such spacingregularities. In particular, one critical aspect is the transient phase of reorganization that involves landscapesundergoing changes in geometry.In this work, we investigate the temporal evolution of mean river basin aspect ratio, R, defined as the ratio betweenmountain front width W and basin outlet spacing S, averaged over a number of basins spanning at least a givenfraction (say, 2/3) ofW. The parameter R is analyzed on simulated landscapes obtained by application of numericalmodels of uplift, hillslope diffusion and fluvial erosion to synthetic surfaces, represented as triangulated irregularnetworks (TINs). The model is completely implemented in Matlab, thus leaving ample access to a number ofavailable terrain analysis and visualization tools.We report some observations about the temporal evolution of the R parameter, an aspect not very well covered inrecent investigations. In particular, we investigate its response to different values of uplift rates and erosion power.We also simulate the response of R to the reorganization of the river network following the setup of a gradient inthe precipitation regime.ReferencesBonnet, S. (2009). Shrinking and splitting of drainage basins in orogenic landscapes from the migration ofthe main drainage divide. Nature Geoscience. 2, 766-771Castelltort S. & Simpson G. (2006) - River spacing and drainage networ

Tra i tanti problemi che affl iggono le costepugliesi, la subsidenza delle piane costiere èquello meno conosciuto, anzi, in diversi casinegato o in qualche caso rimandato a futurimonitoraggi (ad es., AA.VV. 2011). In realtà,studi a riguardo, seppur limitati alla pianacostiera del Golfo di Manfredonia, sono statieseguiti da un certo numero di gruppi di ricerca,con risultati del tutto simili e che indicanouna non trascurabile presenza del fenomeno.Ciò che manca sono approfondimenti cheportino all'individuazione sicura delle causeche hanno determinato un'accelerazione delfenomeno negli ultimi anni.Questo lavoro descrive le attività di ricercae monitoraggio condotte fi nora sull'areacostiera del Tavoliere. Partendo dall'individuazionee da un inquadramento storico delproblema, si passa ad una descrizione deimetodi usati per quantifi care l'entità dellasubsidenza e al tentativo di individuarne lecause. Si descrive infi ne la possibilità di applicarele tecniche InSAR ad altre piane costiere,pugliesi e non solo, in maniera retroattiva,ma soprattutto come prospettiva per unmonitoraggio di dettaglio da effettuarsi nelprossimo futuro, grazie alla disponibilità dinuovi sensori e tecniche.

The use of satellite Synthetic Aperture Radar Interferometry (InSAR) for monitoring ground instability due to landslide events, although advantageous over large spatial scales, still poses challenges related to the recurrently complex kinematics of the phenomena or to the unfavorable settings of the examined areaswith respect to steep topography and vegetated land cover. This paper presents results obtained by usingMulti-temporal InSAR techniques with high resolution TerraSARX (TSX) data formonitoring the Carlantino landslide, located in theDaunian Subapennine (Apulia region, southern Italy) on a slope overlooking a water reservoir, and subjected to several investigations and consolidationworks. The targets detected by using Persistent Scatterer Interferometry (PSI) correspond to urban structures or peri- urban walls and guard rails, while the landslide body is almost completely devoid of stable targets, due to the widespread vegetation and variable land cover. To allowstability monitoring, a network of six Corner Reflectors (CR)was designed and deployed over the landslide test site. The TSX imageswere analyzed by using both the PSI processing and a procedure, based on the double difference analysis of InSAR phase values on the CR pixels. De- spite residual noise and the loss of 2 CRs due to vandalism, the processing allowed verifying the stability of the upper and central part of the landslide body, and relating indirectly the movements at the toe of the landslide to the water level fluctuations of the reservoir. Finally, this experiment suggests some recommendations and guidelines in planning CR deployment in complex landslide sites.©

L'osservazione della Terra da piattaforme spaziali, integrata con misure in situ e con acquisizione da piattaforme aeree, è una tecnologia di riferimento per il monitoraggio di ampie zone del Territorio con una elevata frequenza spaziale. Queste ca-ratteristiche sono essenziali per investigare, da un lato, l'effetto di modifiche indotte da cambiamenti climatici, dall'altro la presenza di situazioni che siano precursori di cambiamenti, in un'ottica di previsione ed allerta. Nel presente lavoro vengono presentati alcuni esempi applicativi in questo scenario.

The multichromatic analysis (MCA) uses interferometric pairs of SAR images processed at range subbands and explores the phase trend of each pixel as a function of the dif- ferent central carrier frequencies to infer absolute optical path difference. This approach allows retrieving unambiguous height information on selected pixels, potentially solving the problem of spatial phase unwrapping, which is instead critical in the stan- dard monochromatic processing. The method, based on concepts originally introduced by Madsen and Zebker, has been developed in previous work both theoretically and through simulations. This paper presents the first MCA experimental validation of the procedure, through application to a wideband SAR single-pass interferometric data set acquired by the AES-1 airborne sensor. An evaluation of the impact of theMCA processing parameters on the height estimation performances is obtained through a para- metric analysis. The results confirm the indications derived by the theoretical analysis, demonstrating the feasibility of the MCA absolute phase measurement, provided that a sufficient bandwidth is available.

The present paper presents the results of the application of Multi Chromatic Analysis (MCA) for height retrieval by processing both AES-1 airborne data and satellite TerraSAR-X data. In particular, a test of the robustness of the MCA technique with respect to total processed bandwidth has been performed through comparison of results from datasets with bandwidths spanning form 100 to 400 MHz.A first validation of the mentioned technique has been carried out by comparing the retrieved heights w.r.t. ground elevation from external SRTM DEM, as well as by verifying the reliability of the fringe classifications based on the integer number of phase cycles computed through MCA.Results are presented and commented by addressing potential and limitation of the technique.

The Multi-Chromatic Analysis, as introduced in [1], uses interferometric pairs of SAR images processed at range sub-bands and explores the phase trend of each pixel as a function of the different central carrier frequencies. The phase of stable scatterers evolves linearly with the sub-band central wavelength, the slope being proportional to the absolute optical path difference. Unlike the standard "monochromatic" InSAR approach, this technique allows performing spatially independent and absolute topographic measurements, if the attention is focused on single targets exhibiting stable phase behaviour across the frequency domain. Potential applications for the study of frequency-stable targets include topographic measurement, atmospheric research, and urban monitoring. Through a simplified model [2], we obtained a first evaluation of the impact of the MCA processing parameters on the height estimation performances. A total bandwidth of at least 300 MHz seems to be required to provide reliable results. Thus, the technique appears optimally suited for the new generation of satellite sensors, which operate with larger bandwidths than previously available instruments, generally limited to few tens of MHz. SAR sensors such as those mounted on TerraSAR-X (TSX) or COSMO-SkyMed (CSK) spacecraft, all pose great expectations on the potential use of multi-chromatic methods.The practical feasibility of the technique was demonstrated in [2] by using a set of SAR data collected by the airborne AES-1 radar interferometer, operating at X-band by multi-channel electronics, which provides a total radar bandwidth of 400 MHz. A first successful application of the technique to satellite data was also shown in [3] by using a spotlight interferometric pair of images acquired by TSX on the well-known Uluru monolith in Australia. In the present work, we illustrate results obtained through MCA processing on spaceborne SAR data acquired by the CSK constellation both on Parkfield in California (USA), and on the Uuluru monolith. A CSK tandem pair acquired on the Uluru test site was used to validate the MCA-based height measurements by using a digital surface model (DSM) derived from optical stereo imagery captured at 15 cm resolution. The same dataset was also processed to validate the theoretical analysis [2] developed to assess the performance of the MCA with respect to the radiometric parameters involved in the processing (total bandwidth, sub-bandwidth, number of sub bands).The MCA technique introduces the concept of frequency-stable targets (PSfd), i.e. objects exhibiting stable radar returns across the frequency domain. This concept is complementary to that of temporal stability, which is at the base of persistent scatterers interferometry (PSI) techniques [4]. In PSI applications, stable targets (PS) are recognized as those exhibiting temporal stability through a stack of tens of SAR images. It is then natural to try to compare the two concepts, examining t

Multi-Chromatic Analysis (MCA) of SAR images relays on exploring sub-band images obtained by processing portions of range spectrum located at different frequency positions. It has been applied to interferometric pairs for phase uwrapping and height computation. This work investigates two promising applications: the comparison between the frequency-persistent scatterers (PSfd) and the temporal-persistent scatterers (PS), and the use of inter-band coherence of a single SAR image for vessel detection. The MCA technique introduces the concept of frequency-stable targets, i.e. objects exhibiting stable radar returns across the frequency domain which is complementary to that of temporal stability at the base of PS interferometry. Both spotlight and stripmap TerraSAR-X images acquired on the Venice Lagoon have been processed to identify PSfd and PS. Different populations have been analyzed to evaluate the respective characteristics and the physical nature of PSfd and PS. Concerning the spectral coherence, it is derived by computing the coherence between sub-images of a single SAR acquisition. In the presence of a random distribution of surface scatterers, spectral coherence must be proportional to sub-band intersection of sub-images. This model is fully verified when observing measured spectral coherence on open see areas. If scatterers distribution departs from this distribution, as for manmade structures, spectral coherence is preserved. We investigated the spectral coherence to perform vessel detection on sea background by using spotlight images acquired on Venice Lagoon. Sea background tends to lead to verylow spectral coherence while this latter is preserved on the targeted vessels, even for very small ones. A first analysis shows that all vessels observable in intensity images are easily detected in the spectral coherence images which can be used as a complementary information channel to constrain vessel detection.

This work investigates the possibility of performing target analysis through the Multi-Chromatic Analysis (MCA), a technique that basically explores the information content of sub-band images obtained by processing portions of the range spectrum of a synthetic aperture radar (SAR) image. According to the behavior of the SAR signal at the different sub-bands, MCA allows target classification. Two strategies have been experimented by processing TerraSAR-X images acquired over the Venice Lagoon, Italy: one exploiting the phase of interferometric sub-band pairs, the other using the spectral coherence derived by computing the coherence between sub-band images of a single SAR acquisition. The first approach introduces the concept of frequency-persistent scatterers (FPS), which is complementary to that of the time-persistent scatterers (PS). FPS and PS populations have been derived and analyzed to evaluate the respective characteristics and the physical nature of the targets. Spectral coherence analysis has been applied to vessel detection, according to the property that, in presence of a random distribution of surface scatterers, as for open sea surfaces, spectral coherence is expected to be proportional to sub-band intersection, while in presence of manmade structures it is preserved anyhow. First results show that spectral coherence is well preserved even for very small vessels, and can be used as a complementary information channel to constrain vessel detection in addition to classical Constant False Alarm Rate techniques based on the sole intensity channel.

The multichromatic analysis (MCA) can be applied to interferometric pairs of synthetic aperture radar (SAR) images processed at range subbands and consists of exploring the phase trend of each pixel as a function of the different central carrier frequencies. The phase of stable scatterers linearly evolves with the subband central frequency, with a slope proportional to the absolute electromagnetic path difference that can be estimated and used for both phase unwrapping and height computation. MCA has been theoretically evaluated and tested on airborne wideband SAR data, appearing optimally suited for the new generation of satellite sensors, which operate with larger bandwidths than previously available instruments, generally limited to few tens of megahertzs. In this letter, we illustrate MCA application to satellite SAR data acquired in spotlight mode over the Uluru monolith in Australia. The topographic measurements derived through MCA on the monolith are compared with those provided by a high-resolution digital elevation model from optical stereo imagery. The theoretical parametric model describing the MCA performances according to the processing parameters is also validated.

Marina di Lesina is a peculiar geological site, affected by sinkhole phenomena, causing instabilities and failures of infrastructures. This tourist village, lying not far from Punta delle Pietre Nere, the only outcrop of magmatic rock in the Mediterranean basin, sits on a diapir made of Triassic gypsum, mantled by Quaternary sandy deposits. The cutting of the artificial Acquarotta canal in 1930, connecting the nearby Lesina lagoon to the Mediterranean Sea, exposed this grey micro and meso-crystalline gypsum with intercalations of black limestones and marls. This event is a likely cause for the formation of dissolutional conduits and cavities, found in the area, leading to the formation of the sinkholes which have been plaguing the site in the last years [1]. This peculiar geological setting, coupled with its relatively high value as a local touristic resort, led to its selection as a test site for precise InSAR displacement monitoring techniques. The monitoring, started with legacy ERS and ENVISAT sensors, is continuing through analysis of higher-resolution data.

The recent availability of wide-bandwidth, high-frequency, high-resolution SAR data is contributing to improved moni-toring capabilities of spaceborne remote sensing instruments. In particular, the new COSMO/SkyMed (CSK) and Ter-raSAR-X (TSX) X-band sensors allow better performances in multitemporal DInSAR and PSI applications than legacy C-band sensors such as ENVISAT ASAR, with respect to both target detection and terrain displacement monitoring ca-pabilities. In this paper we investigate about the possibility of achieving performances of PSI displacement detection comparable to those of C-band sensors, by use of reduced numbers of high-resolution X-band acquisitions. To this end, we develop a simple model for phase and displacement rate measurement accuracies taking into account both target characteristics and sensors acquisition schedule. The model predicts that the generally better resolution and repeat-time characteristics of new-generation X-band sensors allow reaching accuracies comparable to C-band data with a significantly smaller number of X-band acquisitions, provided that the total time span of the acquisitions remains the same. This allows in principle to contain the costs of monitoring campaigns, by using less scenes. Indications are more variable in the case of short-time acquisition schedules, such as those involved in the generation of so-called "rush products" for emergency applications. In this case, the higher uncertainty given by shorter total time spans lowers X-band performances to levels mostly comparable to those of the legacy medium-resolution C-band sensors, so that no significant gain in image number budget are foreseen. These theoretical results are confirmed by comparison of three PSI datasets, acquired by ENVISAT ASAR, CSK and TSX sensors over Assisi (central Italy) and Venice.

In this work we present a numerical framework for simulation of surface processes and landforms. The model is called SIGNUM (Simple Integrated Geomorphological NUmerical Model) and is a Matlab, TIN-based landscape evolution model. We use the model to show a few examples of simulated topographic surfaces evolved through application of mathematical expressions for hillslope and fluvial erosion, channel sediment transport and surface uplift. A particular example is shown to reproduce a topographic feature similar to real landscapes, namely the approximately regular spacing of valleys at linear mountain fronts. Although work in the field of computer simulation of geomorphological processes of landscape evolution is at its beginning, results and insights from models such as the ones we present are gaining more and more attention in the scientific community, justifying and encouraging increasing research efforts.

Sparse phase measurements often need to be interpolated on regular grids, to extend the information to unsampled locations. Typical cases involve the removal of atmospheric phase screen information from Interferometric Synthetic Aperture Radar (InSAR) stacks, or the retrieval of displacement information over extended areas in Persistent Scatterers Interferometry (PSI) applications, when sufficient point densities are available. This operation is usually done after a phase unwrapping (PU) of the sparse measurements to remove the sharp phase discontinuities due to the wrap operation. PU is a difficult and error-prone operation, especially for sparse data. In this work, we investigate from the empirical point of view an alternative procedure, which involves an interpolation of the complex field derived from the sparse phase measurements. Unlike traditional approaches, our method allows to bypass the PU step and obtain a regular-grid complex field from which a wrapped phase field can be extracted. Under general conditions, this can be shown to be a good approximation of the original phase without noise. Moreover, the interpolated, wrapped phase field can be fed to state-of-the-art, regular-grid PU algorithms, to obtain an improved absolute phase field, compared to the canonical method consisting of first unwrapping the sparse-grid data. We evaluate the performance of the method in simulation, comparing it to the classical methodology described above, as well as to an alternative procedure, recently proposed, to reduce a sparse PU problem to a regular-grid one, through a nearest-neighbor interpolation step. Results confirm the increased robustness of the proposed method with respect to the effects of noise and undersampling.

Stochastic models are often used to describe the spatial structure of atmospheric phase delays in differential interferometric synthetic aperture radar (DInSAR) data. Synthetic aperture radar interferograms often exhibit anisotropic atmospheric signals. In view of this, the use of anisotropic models for atmospheric phase estimation is increasingly advocated. However, anisotropic models lead to increased computational complexity in estimating the correlation function parameters with respect to the isotropic case. Moreover, the performance is degraded when dealing with DInSAR techniques involving only a few sparse points usable for computations, as in the case of persistent scatterer interferometry applications, particularly when this estimation has to be done in an automated way on many interferograms. In the present work, we propose some observations about the actual advantage given by anisotropic modeling of atmospheric phase in the case of sparse-grid point-target DInSAR applications. Through analysis of simulated data, we observe that an improvement in the performances of kriging reconstruction approaches can be obtained only when sufficient sampling densities are available. In critical sampling conditions, automated methods with reasonable computational cost may improve their performance if external information on the atmospheric phase screen field is available. © 2006 IEEE.

In order to ensure sub-pixel accuracy of geocoded SAR products, precise estimation and correction of theAtmospheric Path Delay (APD) is needed, in particular for the new generation of high resolution satellite SARsensors (TerraSAR-X, COSMO-SkyMed). The goal of the present study is to assess the performances ofoperational Numerical Weather Models (NWM) as tools for APD mitigation. The Regional AtmosphericModeling System (RAMS) has been selected for this purpose. In order to guarantee an accurate knowledge ofboth the satellite orbit and the target position, TerraSAR-X data and corner reflectors have been used for theexperiment. Differential GPS measurements confirm that NWM are able to estimate APD with an accuracy offew decimeters. Therefore, NWM can be also exploited as tools for providing preliminary indications on theamount of orbital or timing errors. The analysis has been hence extended to COSMO-SkyMed data.

The continuous feedbacks among tectonics, surface processes, and climate are reflected in the distribution of catchments on active mountain ranges. Previous studies have shown a regularity of valley spacing across mountain ranges worldwide, but the origin of this geomorphological feature is currently not well known. In this work, we use a landscape evolution model to investigate the process of fluvial network organization and the evolution of regular ridge-and-valley patterns on simulated mountain ranges. In particular, we investigate the behavior of such patterns when subjected to a perturbation in landscape processes from a previous steady state, resulting from a sudden variation in the pattern of bedrock erodibility, from homogeneous to a gradient. We analyze the time evolution of the mean ratio ë' between the linear spacing of adjacent valleys and the half width of the mountain range. We show how a valley spacing ratio of ~0.5 is first achieved at steady state under uniform bedrock erodibility. After applying the gradient of bedrock erodibility across the landscape, we observe that ë' first increases and then decreases to a new steady-state value that is smaller than the original value. A detailed analysis of the simulations, through observations of surface 'snapshots' at repeated time intervals, allows to gain some insight into the mechanisms governing this fluvial network reorganization process, driven by the migration of the main divide toward the side characterized by lower bedrock erodibility. On both sides of the range the new steady-state valley spacing is obtained through mechanisms of catchment reorganization and competition between adjacent fluvial networks. In particular, catchment reorganization is characterized by the growth of smaller catchments between shrinking larger catchments on the side with lower erodibility, and the growth of larger catchments on the side with higher erodibility.

Multi-temporal InSAR (MTI) applications pose challenges related to the availability of coherent scattering from the ground surface, the complexity of the ground deformations, presence of atmospheric artifacts, and visibility problems related to the ground elevation. Nowadays, several satellite missions are available, providing interferometric SAR data at different wavelengths, spatial resolutions, and revisit times.High-resolution X-Band SAR sensors, such as the COSMO-SkyMed constellation, acquire data with spatial resolution reaching metric values, and revisit time up to a few days, leading to an increase in the density of usable targets, as well as to an improved detection of non linear movements. Medium resolution C-band SAR data have been thoroughly exploited in the last two decades, thanks to the ERS-1/2 and ENVISAT-ASAR missions, and Radarsat-1/2. A new interesting opportunity is provided by the Sentinel-1 mission, which has a spatial resolution comparable to previous ESA C-band missions, and a revisit time reduced to 12 and 6 days, by considering, respectively, one or two satellites. It is envisioned that, by offering regular, global scale coverage, improved temporal resolution and freely available imagery, Sentinel-1 will guarantee an increasing use of MTI for ground displacement investigations.The present work discusses opportunities of MTI applications to ground instability monitoring by assessing the performance of the different available satellite missions, according to acquisition parameters such as wavelength, spatial resolution, revisit time and orbital tube size. This performance analysis allows to foresee the quality of displacement maps estimated through MTI according to mission characteristics, and thus to support SAR data selection. In particular, a comparative analysis is carried out, aimed at addressing specific advantages of different satellite missions in L-, C- and X-band. For instance, high resolution data increase the density of coherent targets, thus improving the monitoring of local scale events. Short (X-band) wavelengths improve the sensitivity to displacements. Short revisit times allow collecting large data stacks in short times, and improve the temporal sampling, thus increasing the chances to catch pre-failure signals (high-rate, nonlinear signals). The precision of the displacement rate detection depends on the number of images and on the phase noise, while the precision of the residual height error estimation depends also on the orbital tube size. Sentinel-1 will provide data for the next years with short revisit time, and it is thus likely to provide reliable displacement estimations at large scale, and in quite limited observation time spans. However, due to its narrow orbital tube size, it has a limited height precision, which leads to poor geo-location quality.An example of multi-sensor ground instability investigation is also presented concerning the site of Marina di Lesina, in Southern Italy, where s

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 variations throughout the whole monitored time-period.

We apply high-resolution, X-band, stripmap COSMO-SkyMed data to the monitoring of flood events in the Basilicata region (Southern Italy), where multitemporal datasets are available with short spatial and temporal baselines, allowing interferometric (InSAR) processing. We show how the use of the interferometric coherence information can help to detect more precisely the areas affected by the flood, reducing false alarms and missed identifications which affect algorithms based on SAR intensity alone. The effectiveness of using the additional InSAR information layer is illustrated by RGB composites of various combinations of intensity and coherence data. Analysis of multitemporal SAR intensity and coherence trends reveals complex behavior of various field types, which we interpret through a Bayesian inference approach, based on a manual identification of representative scattering and coherence signatures of selected homogeneous fields. The approach allows to integrate external, ancillary information to derive a posteriori probabilistic maps of flood inundation accounting for different scattering responses to the presence of water. First results of this semiautomated methodology, using simple assumptions for the SAR signatures and a priori information based on the distance from river courses, show encouraging results, and open a path to improvement through use of more complex hydrologic and topo-hydrographic information.

We apply high-resolution, X-band, stripmap COSMO/SkyMed data to the monitoring of a flood event in Southern Basilicata region (Italy), where a multi-temporal dataset is available, allowing interferometric processing. We show how the use of the interferometric phase information can actually help to detect precisely the areas affected by the flood, using e.g. RGB composites of various information layers derived from the data. We also present results of unsupervised clustering of the multi-temporal data, which allow to shed some light on the physical interpretation of some of the identified clusters.

In precision flood monitoring it is important to follow the temporal evolution of an event. Often, however, sufficient temporal coverage of events spanning several days can be attained only by recurring to multi-sensor data, due to different acquisition characteristics and schedules of different types of sensors. We present an example of a successful fusion of data coming from both SAR (COSMO-SkyMed stripmap, 3-m resolution) and optical (RapidEye, multispectral, 5 mresolution) data, covering a flood event in southern Italy. The data fusion is performed through a Bayesian network approach, a reliable means to infer probabilistic infomation from heterogeneous sources. Results show accordance with independent model-based flood mapsreaching accuracies of up to 96%.

The objective of this study is to illustrate a pre-operational near surface soil moisture (SSM) product derived, at 1 km resolution, from Sentinel-1 data over the Mediterranean basin. The high resolution is crucial in this area characterized by small to medium size watersheds (e.g. from 500 km2 to 5000 km2). Indeed, it may allow to resolve SSM patterns related to the landscape characteristics of the watersheds and link them to their hydrologic response.

Several numerical landscape evolution models (LEMs) have been developed to date, andmany are available as open source codes. Most are written in efficient programming languages such asFortran or C, but often require additional code efforts to plug in to more user-friendly data analysisand/or visualization tools to ease interpretation and scientific insight. In this paper, we present aneffort to port a common core of accepted physicalprinciples governing landscape evolution directly into a high-level language and data analysisenvironment such as Matlab. SIGNUM (acronym for Simple Integrated Geomorphological NumericalModel) is an independent and self-contained Matlab, TIN-based landscape evolution model, built tosimulate topography development at various space and time scales. SIGNUM is presently capable ofsimulating hillslope processes such as linear and nonlinear diffusion, fluvial incision into bedrock,spatially-varying surface uplift which can be used to simulate changes in base level, thrust and faulting,as well as effects of climate changes. Although based on accepted and well-known processes andalgorithms in its present version, it is built with a modular structure, which allows to easily modify andupgrade the simulated physical processes to suite virtually any user needs. The code is conceived as anopen-source project, and is thus an ideal tool for both research and didactic purposes, thanks to thehigh-level nature of the Matlab environment and its popularity among the scientific community. In thepaper the simulation code is presented together with some simple examples of surface evolution, andguidelines for development of new modules and algorithms are proposed.

We report on the InSAR-related results of the National Research Project (PRIN) entitled "Advanced technologiesin the assessment and mitigation of the landslide risk: precursors detection, previsional models and thematicmapping", funded by the Italian Ministry for Scientific Research. In the framework of the project, multi-temporalinterferometric techniques were applied to time series of SAR data, from legacy ERS and ENVISAT, as well ashigh-resolution TerraSAR-X sensors. We report on the final outcomes of the project, which concentrate on twosites of the Apulia Region, representative of terrain instability problems widespread in the area.The fist one is the coastal area near the Lesina Marina tourist village, at the north of the Region, close to theGargano promontory, where the excavation of a canal exposed grey micro- and meso-crystalline gypsum which isnow showing a high density of cavities and sinkholes due to gravitational collapse processes. A slow but steady upliftphenomenon has been detected by processing through persistent scatterers interferometry (PSI) methodologiesERS and ENVISAT data, acquired in both ascending and descending geometries, and spanning a total time intervalfrom 1995 to 2010. The displacement data were validated by comparison with leveling measurements performedin 2000 and 2010. Derived vertical displacement rates exceed 3-4 mm/y on locations adjacent to the canal, gentlydecreasing towards the western end of the built up area. These observations, supported by ancillary data and insitu investigations performed in the past, seem compatible with processes such as diapirism or the hydration of theresidual anhydrite in the core of the gypsum mass.The second site is an inland landslide area close to the municipality of Carlantino, in the Daunia mountains. Here,a relatively large landslide affects the slopes spreading from the town outskirts to the banks of the Occhito lake, anartificial basin formed by a dam on the Fortore river. PS targets detected by both C- and X-band data correspond tourban structures or peri-urban walls and guard rails, while the landslide body is almost completely devoid of stabletargets, due to the vegetation cover. In order to allow stability monitoring through spaceborne SAR interferometry,a network of passive reflectors was designed and deployed on the area of interest. To design the corner reflector(CR) network, different factors were taken into account: the visibility of the CR by the satellite in terms of geometryand radiometry, the accessibility of the location on the ground, and the relative distance between CR. Resultsof the comparison of phase data over the CR with that of surrounding objects are presented.Work supported by the Italian Ministry of Research in the framework of PRIN 2008 research grant "Advancedtechnologies in the assessment and mitigation of the landslide risk: precursors detection, previsional models andthematic mapping". Te

We 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).

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.

In multi-temporal applications of synthetic aperture radar (SAR) interferometry, differential phase contributions due to atmospheric inhomogeneities, estimated over sparse points, have to be interpolated and removed from the regular-grid interferograms in order to highlight the phase stability of more image pixels, which then add to the available data to infer useful information about terrain displacements or other phenomena of interest. Interpolation is usually done on the phase data after a phase unwrapping (PU) operation. In a previous work, we considered the alternative interpolation step applied directly to the complex phasor derived from the wrapped phase, thus bypassing the error-prone sparse PU operation. In this article, the performances of the proposed methodology are evaluated over atmospheric phase screen (APS) data estimated from a previous processing through persistent scatterers interferometry (PSI) methods. The original persistent scatterer (PS) population is reduced by thresholding their inter-image coherence values, and then further subsampled randomly in a rectangle inside a detected subsidence bowl. Both the classical and the proposed interpolation procedures are applied to the subsampled APS phase values. The interpolated fields are then removed from the rest of the PS, and the residual phase values are compared in terms of inter-image coherence. Results confirm that interpolating complex phasors, thus avoiding PU, gives results equivalent to the standard procedure in good sampling conditions. Moreover, when point sparsity induces phase aliasing, thus hindering the PU operation, the proposed method allows to better recover phase information over unsampled pixels, improving the final results of the PSI processing.

The application of multi-temporal differential SAR interferometric analysis to slope instability monitoring poses challenges related to the complex kinematics of the phenomenon, as well as to the unfavourable settings of the area affected by landslides, often occurring on sites of limited extension, characterized by steep topography and variable vegetation cover. The use of passive reflectors allows to extend the stability monitoring on areas lacking natural coherent reflectors. The present work discusses the problematic aspects of design and deployment of a corner reflector network, and presents preliminary results obtained on the Carlantino village in the Daunia Apennines (Italy) by using X-band TerraSAR-X data. © 2012 IEEE.