Maria Teresa Chiaradia

Weights determination for minimum cost flow InSAR phase unwrapping

The authors investigate the problem of generating weight masks to be used in conjunction with the minimum cost flow algorithm for InSAR phase unwrapping. Different weight values are automatically assigned to the interferogram pixels through a classification of several features extracted from the dataset. Examples on simulated images show that the approach gives good results, and confirm that less error is committed as more information is taken into account in generating the weights.

Applications of Remote Sensing Techniques for Mapping Posidonia Oceanica Meadows

Posidonia Oceanica is a marine phanerogam characterizing an ultimate succession stage (climax) on sandy bottoms in the Mediterranean Sea. In particular, Posidonia Oceanica ecosystems are an important element in improving the water quality of coastal waters [1],[2]. Producing thematic maps of seagrass communities from remote sensing data is a multistep process. First, a preprocessing phase to correct satellite images. The second step is the classification phase. Subsequently the post-classification phase have to improve the accuracy of the results. In this study, Posidonia Oceanica meadows maps of Taranto Gulf, Ionian Sea, in 2001, 2002, and 2004, are produced from Ikonos, ETM+ and ASTER images. A comparison with ground truth measurements in the Ionian Sea shows the advantages and the limits of each approach.

TerraSAR-X InSAR multipass analysis on Venice (Italy)

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.

Coastal Observation through Cosmo-SkyMed High-Resolution SAR Images

ABSTRACT Bruno, M.F.; Molfetta M.G.; Mossa, M., Nutricato, R., Morea, A., and Chiaradia, M.T., 2016. Coastal observation through Cosmo-SkyMed high-resolution SAR images. In: Vila-Concejo, A.; Bruce, E.; Kennedy, D.M., and McCarroll, R.J. (eds.), Proceedings of the 14th International Coastal Symposium (Sydney, Australia). Journal of Coastal Research, Special Issue, No. 75, pp. 795–799. Coconut Creek (Florida), ISSN 0749-0208. The study deals with the application and further improvement of an advanced Earth Observation system, named COSMO-Beach, developed for semi-automatic shoreline extraction and coastal morphology identification. The system exploits SAR Single-Look-Complex data acquired by the COSMO-SkyMed constellation, which is able to provide X-band images with a short revisiting time. The implemented procedures have been tested over a very popular beach in Apulia Region (Italy), affected by erosion problems induced by human activities. The outcomes of the COSMO-Beach system are presented and discussed.

Persistent Scatterers Interferometry Provides Insight on Slope Deformations and Landslide Activity in the Mountains of Zhouqu, Gansu, China

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 widespread 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. Furthermore, 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.

On the use of COSMO/SkyMed data and Weather Models for interferometric DEM generation

Abstract 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.

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation

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 estimate UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system.

C/X-Band SAR Interferometry Used to Monitor Slope Instability in Daunia, Italy

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.

A Bayesian network for flood detection

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.

Land-cover classification-based persistent scatterers identification for peri-urban applications

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.