DINSAR

—Recently some experiments demonstrated that reliable DInSAR measurements can be achieved at any band and that further time-series analyses can be applied to airborne data. However , most of the airborne DInSAR results, including the time-series , published so far have focused on short-term analyses (base-lines within hours or few days). This paper presents the first long-term airborne DInSAR survey at P-and X-band with temporal baselines of 1 year and 3 months. The survey was performed by the OrbiSAR system of OrbiSat under contract with Petrobras (PROTRAN), as part of a project to investigate the potential of DInSAR technique to identify, prior to structural damage, geohaz-ards threats to the oil/gas pipelines in São Sebastião—SP, Brazil. After 1 year and 3 months, the P-band data have interferometric coherence equal or greater than 0.3 for approximately 80% of the imaged dense vegetated areas. At X-band, we achieved coherence equal or greater than 0.3 in the urban area. After removing all residual motion errors with proper up-to-date processing, we derived , for the P-band data, land movements with absolute accuracy in the order of centimeters. For X-band we derived land movement measurements with absolute accuracy in the order of millimeters. Through field work evidences, the paper analyses the causes of these centimeter to millimeter land movements, and how they are related to geodynamic processes and geohazard risks. A comparison between the DInSAR and in-loco inclinometer measurements is presented. The paper suggests some possible operational scenarios and discusses on the potential of the airborne DInSAR for geohazard risk monitoring.

We investigate the surface deformation of the May–July 2015 Wolf volcano (Galápagos) eruption, retrieved through space-borne differential synthetic aperture radar interferometry (DInSAR) measurements. To do this, we first examine the ENVISAT SAR acquisitions which imaged the volcano during the 2004–2010 time period, in order to retrieve the pre-eruptive deformations through the Small BAseline Subset (SBAS) DInSAR approach. These measurements allow us to focus on the recent volcano dynamics and to constrain the geometry and characteristics of the main deformation source. In particular, our analytic modelling results suggest that a sill-like source, 2.5 km long, 2.0 km wide and located at depth of about 1.5 km from the caldera floor, fits the observed uplift and E-W pattern, in good agreement with other studies that highlight the existence of a flat-topped shallow source. Subsequently, by considering that the main source maintains similar geometrical and kinematical characteristics over time, we analyse the deformation patterns related to the 2015 eruption. In this case, we invert two Sentinel 1-A DInSAR maps encompassing the May–July 2015 eruption. The observed deformation can be attributed to a magmatic system with pressure change in a single shallow magma body (sill-like source), and the formation of a circumferential dike feeding the eruptive fissure on the SE rim of the summit caldera. This work provides new insights on the caldera dynamics of Wolf volcano and confirms the importance of remote sensing data to improve our knowledge of remote volcanic areas.

The faults are universal in the petroleum reservoirs. Some of them are Semipermeable Filtration Barriers (SPFBs) such that an SPFB can change its permeability performance during production from “permeable” to “sealing,” or vice versa. This may cause sudden changes in reservoir structures and, eventually, result in negative impacts on production. This article  deals with early SPFB detection and characterization. We  consider some case studies of reservoirs with SPFBs, and present a new methodology for SPFB detection that is aimed at investigation of the “green fields.” This includes SAR interferometry and surface geochemical survey as the basic methods for mapping the surface responses to deep geodynamic and fluid-dynamic events, and some techniques for separation of SPFBs from other dislocations. The methodology implementation is demonstrated with the case study of underground gas storage.

Central Asian mountain regions are prone to multiple types of natural hazards, often causing damage due to the impact of mass movements. In spring 2017, Kyrgyzstan suffered significant losses from a massive landslide activation event, during which also two of the largest deep-seated mass movements of the former mining area of Mailuu-Suu—the Koytash and Tektonik landslides—were reactivated. This study consists of the use of optical and radar satellite data to highlight deformation zones and identify displacements prior to the collapse of Koytash and to the more superficial deformation on Tektonik. Especially for the first one, the comparison of Digital Elevation Models of 2011 and 2017 (respectively, satellite and unmanned aerial vehicle (UAV) imagery-based) highlights areas of depletion and accumulation, in the scarp and near the toe, respectively. The Differential Synthetic Aperture Radar Interferometry analysis identified slow displacements during the months preceding the reactiva...

Central Asian mountain regions are prone to multiple types of natural hazards, often causing damage due to the impact of mass movements. In spring 2017, Kyrgyzstan suffered significant losses from a massive landslide activation event, during which also two of the largest deep-seated mass movements of the former mining area of Mailuu-Suu-the Koytash and Tektonik landslides-were reactivated. This study consists of the use of optical and radar satellite data to highlight deformation zones and identify displacements prior to the collapse of Koytash and to the more superficial deformation on Tektonik. Especially for the first one, the comparison of Digital Elevation Models of 2011 and 2017 (respectively, satellite and unmanned aerial vehicle (UAV) imagery-based) highlights areas of depletion and accumulation, in the scarp and near the toe, respectively. The Differential Synthetic Aperture Radar Interferometry analysis identified slow displacements during the months preceding the reactivation in April 2017, indicating the long-term sliding activity of Koytash and Tektonik. This was confirmed by the computation of deformation time series, showing a positive velocity anomaly on the upper part of both landslides. Furthermore, the analysis of the Normalized Difference Vegetation Index revealed land cover changes associated with the sliding process between June 2016 and October 2017. In addition, in situ data from a local meteorological station highlighted the important contribution of precipitation as a trigger of the collapse. The multidirectional approach used in this study demonstrated the efficiency of applying multiple remote sensing techniques, combined with a meteorological analysis, to identify triggering factors and monitor the activity of landslides.