Leonardo Daniel Euillades

SBAS-Based Satellite Orbit Correction for the Generation of DInSAR Time-Series: Application to RADARSAT-1 Data

We present an algorithm aimed at correcting satellite orbit information for the generation of differential SAR interferometry (DInSAR) deformation time-series. Our approach exploits small baseline differential interferograms, to preserve their spatial coherence, and is directly compatible with the Small BAseline Subset (SBAS) DInSAR technique. In particular, the algorithm investigates the differential phase gradient directly computed from the wrapped interferograms, and is focused on the estimation of the perpendicular baseline and of the parallel baseline azimuth rate components, separately performed along the range and azimuth directions, respectively. Starting from the estimations carried out on the interferograms, we then retrieve the orbit correction associated with each SAR acquisition of our time-series by solving a system of linear equations via the SVD method, extending the SBAS inversion concept also to the orbit estimation problem. Key application of this technique is the generation of deformation time-series from interferometric sequences of RADARSAT-1 SAR acquisitions which are available for several areas in the world, but are characterized by significantly low accuracy of the or bit information. The presented results, obtained by processing a data set consisting of 33 RADARSAT-1 images of Big Island at Hawaii, show that we may retrieve DInSAR time-series with sub centimeter accuracy, thus confirming the effectiveness of the pro posed technique.

NETVOLC: An algorithm for automatic delimitation of volcano edifice boundaries using DEMs

Abstract Accurately delimiting boundaries is required for characterizing landforms through measurement of their geomorphometric parameters. Volcanism produces a wide range of landforms, from symmetric cones to very irregular massifs, that can gradually merge with the surroundings and contain other elements, thus complicating landform delimitation. Most morphometric studies of volcanoes delimit landforms manually, with the inconvenience of being time-consuming and subjective. Here we propose an algorithm, NETVOLC, for automatic volcano landform delimitation based on the premise that edifices are bounded by concave breaks in slope. NETVOLC applies minimum cost flow (MCF) networks for computing the best possible edifice outline using a DEM and its first- and second-order derivatives. The main cost function considers only profile convexity and aspect; three alternative functions (useful in complex cases) also consider slope, elevation and/or radial distance. NETVOLC performance is tested by processing the Mauna Kea pyroclastic cone field. Results using the main cost function compare favorably to manually delineated outlines in 2/3rds of cases, whereas for the remaining 1/3rd of cases an alternative cost function is needed, introducing some degree of subjectivity. Our algorithm provides a flexible, objective and time-saving tool for automatically delineating volcanic edifices. Furthermore, it could be used for delineating other landforms with concave breaks in slope boundaries. Finally, straightforward modifications can be implemented to extend the algorithm capabilities for delimiting landforms bounded by convex breaks in slope, such as summit craters and calderas.

New Advances of the Extended Minimum Cost Flow Phase Unwrapping Algorithm for SBAS-DInSAR Analysis at Full Spatial Resolution

We present an efficient space-time phase unwrapping (PhU) algorithm that allows us to process sequences of multitemporal full resolution differential synthetic aperture radar (SAR) interferograms for the generation of deformation time-series. The core of the proposed technique, dealing with sparse data grids, is represented by the extended minimum cost flow (MCF) (EMCF) PhU algorithm that was originally developed for the analysis of sequences of multilook interferograms. In particular, our method relies on the joint analysis of the spatial and temporal relationships among a set of properly selected multitemporal differential interferograms, which are compatible with the Small BAseline subset (SBAS) deformation time-series technique. The key point of the approach is the idea to split the complex MCF network problem, representing the overall PhU operation, into that of simpler subnetworks. More precisely, we start by identifying and solving a primary network that involves a proper selection of coherent pixels of the computed interferograms, representing the backbone structure of the overall network. Subsequently, this result is applied for constraining the solution of the subnetworks connected to the primary one, involving the entire set of analyzed pixels. To achieve this task, we solve a constrained optimization problem based on the computation of a constrained Delaunay triangulation in the azimuth/range domain. The overall procedure is implemented through two successive processing steps that are both carried out by using the EMCF PhU technique, which has been slightly modified to take into account the Doppler centroid differences of the exploited interferometric SAR data pairs. The experimental results, achieved by applying the proposed approach to a data set consisting of European Remote Sensing (ERS) SAR data acquired from June 1992 to August 2007 over the Napoli (Italy) bay area, confirm the effectiveness of the proposed PhU approach.

Ground Deformation Between 2002 and 2013 from InSAR Observations

Ground deformation is one of the main geophysical methods for volcano monitoring. Surface deformation patterns can provide important insights into the structure, plumbing system, and state of restless volcanoes. Copahue volcano is one of the most active eruptive centers in Argentina, and a major risk factor for the nearby towns of Caviahue and Copahue. Historic eruptive activity involved low intensity phreatic and phreatomagmatic events in 1992, 1995 and 2000. A new eruptive cycle is ongoing since June 2012, with several phreatic explosions and one phreatomagmatic—magmatic eruption on December 22nd, 2012. In this work, the Small Baseline Subsets (SBAS) DInSAR-based technique is successfully applied to compute surface displacements using the ENVISAT ASAR radar imagery during quiescent and pre-eruptive periods. Our purpose is to investigate possible sources of ground deformation to better understand the system behavior. Analytical models are used to interpret geodetic data and to constrain the parameters that characterize the source responsible for the observed deformation.

On the Generation of Late ERS Deformation Time Series Through Small Doppler and Baseline Subsets Differential SAR Interferograms

In this letter, we investigate the potential of the small baseline subset (SBAS) differential synthetic aperture radar interferometry (DInSAR) technique to produce consistent deformation time series by using data sets of SAR images with high Doppler centroid (DC) frequencies. To cope with this issue properly, we exploited an archive of SAR scenes acquired by the European Remote Sensing 2 (ERS-2) sensor after the February 2000 three-gyroscope navigation mode failure. Our approach is oriented toward the long-term investigation of large-scale displacements with low spatial resolution (about 100 × 100 m) by processing sets of SAR images without discarding scenes depending on their DC values. Our analysis involves a set of descending SAR data frames from 1992 to 2007 relevant to the Napoli (Italy) bay area. Comparison with contemporaneous Global Positioning System measurements clearly confirms the effectiveness of the proposed approach.

RADARSAT-1 deformation time-series analysis based on the SBAS-DInSAR algorithm

We extend the Small BAseline Subset (SBAS) algorithm to generate deformation time-series from SAR data acquired by the Canadian Space Agency (CSA) RADARSAT-1 sensor. The proposed approach is mostly oriented to the investigation of large scale deformation events with relatively low spatial resolutions (of about 100}100 m), and is based on the use of conventional multi-look interferograms with small temporal and spatial baseline separations. With respect to the original SBAS approach, several improvements are required to take into account the inaccuracies on the knowledge of the RADARSAT-1 orbital parameters, and of the significant fluctuations of the dop-pler centroid values over each single SAR scene. This work is aimed to present the first results achieved by applying the implemented RADARSAT-1 SBAS processing chain to an archive of SAR scenes, acquired in the time interval from 2000 to 2003 over, and relevant to the Hawaii Island area. The presented results markedly confirm the effectiveness of the implemented RADARSAT-1 SBAS processing chain.

RADARSAT-1 deformation time-series generation by using the SBAS-DInSAR algorithm

We have extended the deformation time-series generation capability of the Small BAseline Subset (SBAS) DInSAR algorithm to the SAR data collected by the RADARSAT-1 sensor. The selected SBAS algorithm relies on conventional multi-look interferograms characterized by small temporal and spatial baseline values. We present in this work the first results achieved by exploiting the implemented RADARSAT-1 SBAS-DInSAR processing chain. The investigated test site is the area of New Orleans and its surroundings, for which a RADARSAT-1 archive of 27 acquisitions, spanning the time interval between December 2004 and March 2007, has been processed. The presented results demonstrate the effectiveness of the RADARSAT-1 SBAS-DInSAR processing chain.