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Surface subsidence is a dominant component of the displacement vector triggered by underground mining. Over the last few decades, Differential Interferometry Synthetic Aperture Radar (DInSAR) has been used to efficiently monitor this phenomenon with great spatial and temporal coverage. More advanced multi-temporal DInSAR (MTInSAR) algorithms have been proposed to overcome some of the limitations of conventional DInSAR. However, advanced MTInSAR approaches are also not perfect in terms of measuring mining subsidence (e.g., temporal decorrelation, ambiguity, nonlinearity). For this reason, we propose a fusion of the Persistent Scatterer Interferometry (PSInSAR) and DInSAR results. By combining these complementary techniques, the atmospheric errors in PSInSAR data are reduced and larger deformation rates could have been detected more accurately (thanks to DInSAR) than by an approach solely based on PS-InSAR. This allows to measure areas with fast-moving subsidence (1 m/year) due to ongoing underground coal exploitation. Data from ascending and descending orbits of Sentinel-1A\B were used to obtain the vertical deformation component. The resulting integrated vertical deformation map was compared with the results from levelling benchmarks. The Root Mean Square Error (RMSE) calculated based on this comparison was 22 mm. Moreover, the maximal vertical cumulative subsidence detected in the study area was 1.05 m/year.

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&mdash, the Koytash and Tektonik landslides&mdash, 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.

The repeat-pass Synthetic Aperture Radio Detection and Ranging (RADAR) Interferometry (InSAR) has been a widely used geodetic technique for observing the Earth’s surface, especially for mapping the Earth’s topography and deformations. However, InSAR measurements are prone to atmospheric errors. RADAR waves traverse the Earth’s atmosphere twice and experience a delay due to atmospheric refraction. The two major layers of the atmosphere (troposphere and ionosphere) are mainly responsible for this delay in the propagating RADAR wave. Previous studies have shown that water vapour and clouds present in the troposphere and the Total Electron Content (TEC) of the ionosphere are responsible for the additional path delay in the RADAR wave. The tropospheric refractivity is mainly dependent on pressure, temperature and partial pressure of water vapour. The tropospheric refractivity leads to an increase in the observed range. These induced propagation delays affect the quality of phase measurement and introduce errors in the topography and deformation fields. The effect of this delay was studied on a differential interferogram (DInSAR). To calculate the amount of tropospheric delay occurred, the meteorological data collected from the Spanish Agencia Estatal de Meteorología (AEMET) and MODIS were used. The interferograms generated from Sentinel-1 carrying C-band Synthetic Aperture RADAR Single Look Complex (SLC) images acquired on the study area are used. The study area consists of different types of scatterers exhibiting different coherence. The existing Saastamoinen model was used to perform a quantitative evaluation of the phase changes caused by pressure, temperature and humidity of the troposphere during the study. Unless the phase values due to atmospheric disturbances are not corrected, it is difficult to obtain accurate measurements. Thus, the atmospheric error correction is essential for all practical applications of DInSAR to avoid inaccurate height and deformation measurements.

Ground-based synthetic aperture radar interferometry (GB-InSAR) enables the continuous monitoring of areal deformation and can thus provide near-real-time control of the overall deformation state of dam surfaces. In the continuous small-scale deformation monitoring of a reservoir dam structure by GB-InSAR, the ground-based synthetic aperture radar (GB-SAR) image acquisition may be interrupted by multiple interfering factors, such as severe changes in the meteorological conditions of the monitoring area and radar equipment failures. As a result, the observed phases before and after the interruption cannot be directly connected, and the original spatiotemporal datum for the deformation measurement is lost, making the follow-up monitoring results unreliable. In this study, a multi-threshold strategy was first adopted to select coherent point targets (CPTs) by using successive GB-SAR image sequences. Then, we developed differential GB-InSAR with image subsets based on the CPTs to solve the dam surface deformation before and after aberrant interruptions. Finally, a deformation monitoring experiment was performed on an actual large reservoir dam. The effectiveness and accuracy of the abovementioned method were verified by comparing the results with measurements by a reversed pendulum monitoring system.

Приведены результаты исследования возможности применения поляриметрических и интерферометрических данных X-иL-диапазонов TanDEM-X и ALOS-2 PALSAR-2 для мониторинга криогенных рельефообразующих процессов полуострова Ямал. Выполнен статистический анализ сезонных изменений интенсивности и параметров поляриметрической Н - А - α -декомпозиции на участках с оползнями, активно растущими и пассивными термоцирками научного полигона Васькины дачи., The article presents the results of the developed methods for thermal-degradation processes detection and monitoring based on the X- and L-bands radar data. The research objects are developing thermocircuits and collapsing slopes in the coastal zone of ten lakes of “Vaskiny Dachi” polygon (Central Yamal, 70∘15′N, 69∘05′E). To detect the formed and active cryogenic formations TanDEM-X and ALOS-2 PALSAR-2 interferometric and polarimetric data (VV, VH) of 2015-2016 were used. The research was carried out in three directions: 1) digital terrain models (DTM) with high resolution construction using differential interferometry methods and the cryogenic formations topographical features identification, temporal changes in DTMs observation; 2) comparative statistical analysis of the total intensity and the polarimetric Н-А-α -decomposition components for cryogenic formations and adjacent stable sites; 3) development of a technique for express detection of such formations on the basis of total intensity and polarimetric Н-А-α -decomposition components images texture. It is established that the intensity, polarimetric characteristics, topography parameters and textures of radar images significantly differ from those for neighbouring stable regions (more than 3 σ ) for active thermocircuits. Intensity variations are most significant, but the localization of cryogenic formations can be limited by the radar survey geometric conditions. For passive thermocircuits, landslides in the coastal zone, deviation of intensity and polarimetric characteristics from background ∼ σ , therefore as an indicator a set of polarimetric Н-А-α -decomposition parameters should be used. Combining parameters α and H can be the basis for express diagnostics of the occurrence and activation of cryogenic processes in the area of the present study., №4(23) (2018)

In this work, a dual-band photonics-based radar system is described for precise displacement measures in a multi-target scenario. The radar has been designed for application of monitoring and prevention of possible structural failures of buildings and landslides. The radar system exploits the Stepped Frequency Continuous Wave (SFCW) signal modulation and differential phase measurements are carried out on each range bin to evaluate target displacements. The system effectiveness has been already demonstrated in presence of a single target. Here we present a numerical and experimental evaluation of the displacement estimation accuracy in the case of a multi-target scenario. Our study is focused to understand how the presence of multiple targets impacts on their displacement estimates. Simulation results show a typical accuracy of less than 0.2 mm for distances up to 400 m. These results are confirmed by preliminary experimental outcomes, which take into account different operative conditions in a first measure campaign with multiple targets. Finally, concluding remarks and perspectives draw the agenda for our future investigations.

In recent years, differential interferometry using spaceborne synthetic aperture radar (SAR) sensors has become an established technique for detecting and monitoring centimetre-scale deformations of the Earth's surface, as well as glacier flows and landslides. Although often very efficient, the use of spaceborne SAR data has several drawbacks, namely phase artifacts caused by atmospheric effects and very low coherence due to long data acquisition intervals and the short radar wavelength of the sensor. Most important, current spaceborne sensors are not able to ensure flexible monitoring of critical regions. Airborne sensors may overcome most of the problems mentioned above, but up to now, the operational use of airborne differential SAR interferometry has been prevented by insufficiently accurate motion compensation of the platform. In this letter, first results of airborne differential interferometry using the German Aerospace Center (DLR) experimental SAR system (E-SAR) in the interferometric repeat-pass mode are addressed. This includes an analysis of long-term decorrelation behavior in L-band and, particularly, the correction of residual motion errors in heavily decorrelated interferograms. A first differential interferogram of agricultural and forested areas is presented and analyzed.

Interest is growing in the application of coherent processing of synthetic aperture radar (SAR) data to the monitoring of complex urban or infrastructure areas. However, such scenarios are characterized by the layover phenomenon, in the presence of which conventional interferometric SAR techniques degrade or cannot operate. As a consequence, to monitor reliably a high number of ground structures, the identification, i.e., the detection and height and deformation velocity estimation, of both single and multiple scatterers interfering in the same SAR cell can be a key step. This issue is addressed here by means of differential tomography (Diff-Tomo), a recent multibaseline�multitemporal generalized interferometric framework which allows to resolve multiple moving scatterers at different heights in the same cell. In particular, superresolution adaptive Diff-Tomo is extensively tested and augmented with a new information extraction algorithm for the automated identification of the multiple scatterers. Experiments have been carried out with real C-band spaceborne data over urban areas; corresponding results are shown and discussed.

This paper presents a comprehensive overview of the surface deformation retrieval capability of the Differential Synthetic Aperture Radar Interferometry (DInSAR) algorithm, referred to as Small BAseline Subset (SBAS) technique, in the context of active volcanic areas. In particular, after a brief description of the algorithm some experiments relevant to three selected case-study areas are presented. First, we concentrate on the application of the SBAS algorithm to a single-orbit scenario, thus considering a set of SAR data composed by images acquired on descending orbits by the European Remote Sensing (ERS) radar sensors and relevant to the Long Valley caldera (eastern California) area. Subsequently, we address the capability of the SBAS technique in a multipleorbit context by referring to Mt. Etna volcano (southern Italy) test site, with respect to which two different ERS data set, composed by images acquired both on ascending and descending orbits, are available. Finally, we take advantage of the capability of the algorithm to work in a multi-platform scenario by jointly exploiting two different sets of SAR images collected by the ERS and the Environment Satellite (ENVISAT) radar sensors in the Campi Flegrei caldera (southern Italy) area. The presented results demonstrate the effectiveness of the algorithm to investigate the deformation field in active volcanic areas and the potential of the DInSAR methodologies within routine surveillance scenario.

The application of conventional SAR Interferometry (InSAR) together with the two techniques of subcentimeter accuracy, the Stacking and the Permanent Scatterers (PS) Interferometry, were used to study the ground deformation in the broader area of Athens for the period 1992 to 2002. Using the Stacking interferometric method, 55 ERS-1&2 SAR scenes, between 1992 and 2002, were acquired producing 264 differential interferograms. Among these only 60 were finally selected as fulfilling certain criteria. The co-seismic deformation associated with the Athens Earthquake (Mw = 5.9, September 7, 1999) was excluded from the analytical procedure in an attempt to present results of only aseismic character. In total ground subsidence results of about 12 mm in the southern suburbs of Athens, but higher value of about 40 mm in the northern ones for the period 1992–2002. Based on the PS technique, a precise average annual deformation rate-map was generated for the period 1992–1999, ending just before the Athens earthquake event. Both circular and elongated-shape areas of subsidence are recognizable especially in the northern part of the Athens Basin (3–4 mm/yr), as well as at its southern part (1–3 mm/yr). In addition, a rate of 2–3 mm/yr is also yielded for some part of the Athens city center. Subsidence rates of 1–2 mm/yr are measured at the western part of the basin over an area of old mining activities, and around the newly built Syntagma Metro Station. The correlation of the observed deformation patterns with respect to the spatial distribution of water pumping, older mining activities, metro line tunneling and other local geological parameters is examined and discussed.

The authors are presenting a new method to unwrap the phase from irregularly sampled differential SAR interferograms. Often such interferograms are used to observe land surface deformation in the order of centimeters over long time intervals, say up to years. However, in vegetated regions, the surface tends to decorrelate within this time frame and complicates a quantitative long term analysis. This is especially true for the short C-band wavelength of the space borne sensor ERS, the primary data source for radar interferometry. The authors are presenting a variation of Costantini's minimum cost flow method, that avoids low coherence areas and uses isolated man made or natural point scattering objects instead in order to derive the deformation parameters of large scale land surface changes. The method implies automatic selection of stable targets, analysis of their quality, unwrapping of the target phases. The paper focuses on the phase unwrapping method, an adapted version of the minimum cost flow approach. Results are presented both from simulation and from a sample data set over a land subsidence area.