Terrain Displacements Research Articles

An object-based region-growing phase unwrapping method for mapping vertical displacement in permafrost landscapes

Terrain displacement due to the seasonal thaw of the active layer above permafrost can be sensitive to climate change; however, its accurate characterization remains a challenge. This study aimed to improve the measurement of the subsidence or vertical ground surface displacement using differential synthetic aperture radar interferometry (InSAR). Existing methods for reliable phase unwrapping are hindered by the decorrelation between time-series of SAR acquisitions that can result due to the heterogeneity and structural sensitivity of permafrost landscapes to external conditions. In this study, an advanced phase unwrapping method was proposed, in which three types of regions, namely non-residue, sparse residue, and dense residue objects, were obtained from wrapped interferogram and residue map using a segmentation method. Two variants of Polynomial-Based Region Growing Phase Unwrapping (PBRGPU) were developed, which are sparse-residue Object-based PBRGPU(SOP) and dense-residue Object-based PBRGPU(DOP). The results demonstrated that the proposed method outperformed the existing phase unwrapping methods by partially suppressing the decorrelation phase and enhancing robustness for complex terrain deformation in the absence of measured field data. Both the PBRGPU variants and segmentation strategies compose the object-based unwrapping method for permafrost, and also provide a new framework by combining the segmentations and scenarios for phase unwrapping for permafrost regions.

A Study of Tropospheric and Ionospheric Propagation Conditions during Differential Interferometric SAR Measurements Applied on Zagreb 22 March 2020 Earthquake

The differential interferometric synthetic aperture radar (DInSAR) method is based on phase variation between the complex value of pixels of timely separated scenes in interferometric SAR pairs. This phase variation has five components: surface topography, curvature of planet’s surface, terrain displacement, volume scatterers, and atmospheric propagation effects. The terrain displacement is the main product of the DInSAR method, while the last two effects are unpredictable and bring inaccuracy into the terrain displacement measurements. In this work, the propagation conditions in the troposphere and ionosphere were studied during two DInSAR measurements examining the Zagreb 22 March 2020 earthquake, with terrain raising of up to +3 cm at the epicenter. For the troposphere, the vertical profile of the modified refraction index, which incorporates local curvature change with height, was reconstructed using aerological balloon probing data. Ionospheric conditions were determined based on total electron content (TEC) calculated from the Croatian positioning system (CROPOS) and global navigation satellite system (GNSS) reference stations’ measurements. One of the DInSAR measurements was conducted in unfavorable tropospheric refractive conditions, which resulted in an overall bias of −2 cm. The variability of propagation conditions indicates the need for examining the atmospheric propagation effects when calculating terrain displacements using the DInSAR method. The results of DInSAR indicate slight displacements, comparable with the amplitude of atmospheric variations, and should therefore be approached with caution.

Interferometric Synthetic Aperture Radar (InSAR) applications for mapping of terrain displacement in mineral deposits

The Interferometric Synthetic Aperture Radar (InSAR) applications for mapping of terrain displacement have been tested on the Vlaykov Vruh and Tsar Assen porphyry-copper deposits to test terrain displacements and possible fault movements. Time series for each area have been prepared to display the evolution of displacement over time, for a given point for both Cu-porphyry outcrops.

Msplit Estimation Approach to Modeling Vertical Terrain Displacement from TLS Data Disturbed by Outliers

Terrestrial laser scanning (TLS) is a modern measurement technique that provides a point cloud in a relatively short time. TLS data are usually processed using different methods in order to obtain the final result (infrastructure or terrain models). Msplit estimation is a modern method successfully applied for such a purpose. This paper addresses the possible application of the method in processing TLS data from two different epochs to model a vertical displacement of terrain resulting, for example, from landslides or mining damages. Msplit estimation can be performed in two variants (the squared or absolute method) and two scenarios (two point clouds or one combined point cloud). One should understand that point clouds usually contain outliers of different origins. Therefore, this paper considers the contamination of TLS data by positive or/and negative outliers. The results based on simulated data prove that absolute Msplit estimation provides better results and overperforms conventional estimation methods (least-squares or robust M-estimation). In practice, the processing of point clouds separately seems to be a better option. This paper proved that Msplit estimation is a compelling alternative to conventional methods, as it can be applied to process TLS data disturbed by outliers of different types.

IGS-CMAES: A Two-Stage Optimization for Ground Deformation and DEM Error Estimation in Time Series InSAR Data

Interferometric synthetic aperture radar (InSAR) has become an increasingly recognized remote sensing technology for earth surface monitoring. Slow and subtle terrain displacements can be estimated using time-series InSAR (TSInSAR) data. However, a substantial increase in the availability of exclusive time series data necessitates the development of more efficient and effective algorithms. Research in these areas is usually carried out by solving complicated optimization problems, which is very computationally expensive and time-consuming. This work proposes a two-stage black-box optimization framework to jointly estimate the average ground deformation rate and terrain digital elevation model (DEM) error. The method performs an iterative grid search (IGS) to acquire coarse candidate solutions, and then a covariance matrix adaptive evolution strategy (CMAES) is adopted to obtain the final local results. The performance of our method is evaluated using both simulated and real datasets. Both quantitative and qualitative comparisons using different optimizers support the reliability and effectiveness of our work. The proposed IGS-CMAES achieves higher accuracy with a significantly fewer number of objective function evaluations than other established algorithms. It offers the possibility for wide-area monitoring, where high precision and real-time processing is essential.

USING TAILORED GRAPHICAL TOOLS TO IMPROVE THE QUALITY OF DISPLACEMENT MAPS AT CTTC: THE VETOOLS

Abstract. The Geomatics Division of the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) has been producing terrain displacement maps for more than 15 years using the PSIG software chain, developed entirely by the members of the aforesaid group. PSIG has reached a high level of maturity, being highly automated but also offering the user the possibility to fine-tune the set of critical parameters controlling the process. However, large areas with a high level of diversity often pose problems in finding a good quality solution using a single set of parameters. Improving the quality of the final terrain displacement map means being able to process very local and critical areas using specific sets of parameters; however, identifying such areas is a difficult process without suitable analysis tools. The VETools, a new software project still under development, but very close to its completion, target this problem. With the VETools it is possible to visualize the results produced by a previous PSIG global processing, analysing their quality, thus making possible to identify the local, critical areas, allowing the user to interactively experiment with specific sets of parameters for these areas, reprocessing them and reviewing the local results as many times as desired and, finally, merging all of them in a single, unique solution whose level of quality is appropriate for the whole area of interest. This work presents the current state of development of the VETools, describing their features and the challenges overcome.

Recent advancements in multi-temporal methods applied to new generation SAR systems and applications in South America

Detection and continuous monitoring of Earth's ground surface changes, triggered by natural phenomena or induced by human activities, is nowadays possible using Earth Observation (EO) technologies. Indeed, the exploitation of remotely sensed data collected by constellations of new-generation satellite platforms, complemented with in-situ measurements and ground-based observation systems, represents a well-established practice to get valuable information on Earth's crust and subsurface dynamics. The effects of extreme natural or man-induced events (e.g., earthquakes, volcanic eruptions, flooding phenomena, sea-level rise, big fires, etc.) have severe societal and economic impacts. In particular, the technologies based on the use of Synthetic Aperture Radar (SAR) images reached significant improvements in the last decade due to the growing availability of vast amounts of data collected by multiple-satellite sensors operating at different frequency bands and with complementary viewing angles, polarization and acquisition modes. Accordingly, to process a large amount of SAR data in a timely fashion, up-to-date high-performance computing (HPC) methods and tools are required. This paper addresses the state-of-the-art of SAR technologies for the analysis of long sequences of multiple sets of SAR images and provides a perspective on the forthcoming improvements of these technologies. In particular, the emphasis is placed on novel interferometric SAR and change detection methods, giving an overview of how those processing techniques have been used for investigating sites located in South and Central America. Moreover, an overview of the new generation of SAR sensors' observational capability, especially in the field of ground deformation analysis for mitigating the risk associated with natural and human-induced hazards, is provided. COSMO-SkyMed, ALOS, Sentinel-1, and SAOCOM data are exploited to show how natural and human-induced terrain displacement phenomena can be detected and investigated in different portions (X-, L- and C-band) of the microwave spectrum using SAR technologies.

Chasing a complete understanding of the failure mechanisms and potential hazards of the slow moving Liangshuijing landslide

Landslides in the vicinity of reservoirs are prone to generate deadly waves as in the infamous Vajont case. There are more than 3800 landslides in the Three Gorges Reservoir area through detailed geological investigations, which constitutes a serious tsunami threat to the population and properties nearby. The Liangshuijing landslide, a very large creeping landslide located in the region and characterized by a complex morphology of multiple time varying failure mechanisms, is here investigated. Currently comprehensive measurements taken by ground monitoring network, inclinometric readings, in situ and laboratory geotechnical tests were analyzed to build a conceptual model for the landslide's drivers and its kinematics. The cumulative displacement time series were decomposed into trend and periodic components to reliably establish the relationship between displacements and reservoir behavior. A series of numerical slope stability analyses employing finite element limit analysis was performed to identify the material properties compatible with the observed landslide kinematics. Our results shed light on how reservoir behaviors drive landslide development, on how the identified failure mechanisms affect the observed terrain displacements and on which failure mechanism turns out to be dominant as reservoir conditions change. Our findings provide new insight for hazard assessment and mitigation of landslides near reservoirs: considerably smaller local failure mechanisms may cause a tsunami almost severe. Therefore, a single stability analysis may not be adequate but a full suite of analyses probing the range of possible conditions is required.

Application of Remote Sensing, GIS and Machine Learning with Geographically Weighted Regression in Assessing the Impact of Hard Coal Mining on the Natural Environment

Mining operations cause negative changes in the environment. Therefore, such areas require constant monitoring, which can benefit from remote sensing data. In this article, research was carried out on the environmental impact of underground hard coal mining in the Bogdanka mine, located in the southeastern Poland. For this purpose, spectral indexes, satellite radar interferometry, Geographic Information System (GIS) tools and machine learning algorithms were utilized. Based on optical, radar, geological, hydrological and meteorological data, a spatial model was developed to determine the statistical significance of the selected factors’ individual impact on the occurrence of wetlands. Obtained results show that Normalized Difference Vegetation Index (NDVI) change, terrain height, groundwater level and terrain displacement had a considerable influence on the occurrence of wetlands in the research area. Moreover, the machine learning model developed using the Random Forest algorithm allowed for an efficient determination of potential flooding zones based on a set of spatial variables, correctly detecting 76% area of wetlands. Finally, the GWR (Geographically Weighted Regression (GWR) modelling enabled identification of local anomalies of selected factors’ influence on the occurrence of wetlands, which in turn helped to understand the causes of wetland formation.

Early estimation of ground displacements and building damage after seismic events using SAR and LiDAR data: The case of the Amatrice earthquake in central Italy, on 24th August 2016

The increasing accessibility of Synthetic Aperture Radar (SAR) and Light Detection and Ranging (LiDAR) data, grants the opportunity to experiment new methods to support disaster risk management. However, while SAR analyses are becoming extremely popular, thanks, in particular, to the availability of open source satellite images such as those from the Copernicus project, LiDAR analyses are still less common because of the scarce availability of this type of data over significant time frequencies.In this paper we propose an innovative procedure based on the use of SAR and LiDAR data to rapidly assess seismic damage in the early post-emergency phases. The methodology was applied to the case study of the town of Amatrice (Central Italy), which was hit by a strong earthquake swarm that started in August 2016. Specifically, SAR data is used for a large-scale analysis of terrain displacements following the seismic event, while LiDAR reliefs are used to carry out a change detection and to identify the level of damage at a building-scale in the urban settlement of Amatrice. Results will show how the proposed approach can be extremely effective both in the non-emergency phases to monitor seismic-affected areas and support emergency planning, as well as during the immediate post-earthquake phases to assess the damage it has caused and to support first aid dispositions.

Persistent Scatterer Interferometry in the post-event monitoring of the Idukki Landslides

The monitoring of pre-failure movements and their evolution over time is necessary to assess the predisposing and triggering factors. This research focusses on assessing terrain displacements in the Idukki district (Kerala, India) over a year before the deadly disaster, which occurred in August 2018; this disaster was claimed to be a dreadful one as it took off hundreds of human lives and properties. The post-event Persistent Scatterers interferometric analysis on a stack of 20 Sentinel-1 images was performed to analyse the precursory deformations of the landslides. From the results obtained, the study region is estimated to have undergone a displacement of -26 to +19 mm/year, which indicates the instability of the terrain. Also it is evident that the occurrence of the landslides in August 2018, has been due to the effect of the torrential rainfall and the increase in the pore water inducing instability, thereby causing displacement in the region.

Application of Total Station for Structure and Terrain Displacement Monitoring

Application of Total Station for Structure and Terrain Displacement Monitoring

Stochastic model and GIS spatial analysis of the coal mine subsidence

The occurrence of subsidence caused by the underground coal mining may be a complex process that causes damage to the environment. In the last century, there was a significant development in prediction methods for calculating the surface subsidence. In this paper, a new prediction method has been developed to calculate subsidence by combining a stochastic model of the ground movements and Geographical Information System (GIS). All the subsidence calculations are implemented by an original program package MITSOUKO, where the components of the GIS are used to fulfil the spatial analysis. This subsidence prediction technique has been applied to calculate the ground movements resulting from excavating 21 mining panels that are mined successively in the coal mine ''Rembas''-Resavica, Serbia. Details of movement were sequentially predicted and simulated in terms of years exploitation. Predictive calculation of the undermined terrain displacement parameters by the stochastic method and integration into the GIS is a powerful risk management tool.

Polarimetric Analysis of Natural Terrain Observed With a Ku-Band Terrestrial Radar

Terrestrial radar interferometers (TRI) are complimentary to spaceborne synthetic aperture radar systems for deformation monitoring in natural terrain: they permit shorter revisit times and greater flexibility in acquisition mode and timing. The additional diversity offered by polarimetric data can also be beneficial for TRI observations because polarized waves are sensitive to the dielectric and geometrical properties of the scatterers. Polarimetric data helps to distinguish different scattering mechanisms in a resolution cell while at the same time estimating terrain displacements. However, the polarimetric scattering signatures of natural surfaces at Ku-Band are not as well characterized as the ones at longer wavelengths, owing to relative rarity of full polarimetric systems operating in Ku-band. This band is often employed in TRI to obtain a fine azimuth resolution with a limited aperture size. This article aims at assessing the potential of polarimetric measurements in Ku-band TRI through an experimental study of polarimetric scattering signatures of natural surfaces using two datasets acquired over a glacier and in an agricultural and urban scene. The main finding of this analysis is that the Cloude-Pottier entropy is high for all land cover types; it is only observed to be less than 0.5 for scatterers with a large radar cross section. Several plausible hypotheses for this observation are formulated and tested, the most likely assumes a combination of depolarizing scattering from natural surfaces and the effect of the large ratio of wavelength to resolution cell size.

Ground‐based deformation measurement radar configured with multiple‐input multiple‐output antennas

The application of ground-based radar to monitor the terrain displacement has attracted more and more attentions recently. Most of the existing ground-based radars utilise a linear horizontal rail where the antennas move to generate the image of the test site. Here, the authors present a topology of antenna array with which the digital elevation model of the observed scene can also be generated besides the 2-D image. Several field experiments have been carried out to evaluate the performance of authors’ developed ground-based differential interferometry radar (GB-DInR) configured with this multiple-input multiple-output (MIMO) antenna array. The results demonstrate that authors’ developed MIMO GB-DInR is able to achieve a sub-millimetre precision of displacement measurement and derive the elevation information of target with an error of <0.1 m at a distance of around 100 m.

The worsening impacts of land reclamation assessed with Sentinel-1: The Rize (Turkey) test case

Massive amounts of land are being reclaimed to build airports, new cities, ports, and highways. Hundreds of kilometers are added each year, as coastlines are extended further out to the sea. In this paper, this urbanization approach is monitored by Persistent Scatterer Interferometry (PSI) technique with Sentinel-1 SAR data. The study aims to explore this technology in order to support local authorities to detect and evaluate subtle terrain displacements. For this purpose, a large 3-years Sentinel-1 stack composed by 92 images acquired between 07/01/2015 to 27/01/2018 is employed and stacking techniques are chosen to assess ground motion. The test site of this study, Rize, Turkey, has been declared at high risk of collapse and radical solutions such as the relocation of the entire city in another area are been taken into consideration. A media fact-checking approach, i.e. evaluating national and international press releases on the test site, is considered for the paper and this work presents many findings in different areas of the city. For instance, alerts are confirmed by inspecting several buildings reported by the press. Critical infrastructures are monitored as well. Portions of the harbor show high displacement rates, up to 1 cm/year, proving reported warnings. Rural villages belonging to the same municipality are also investigated and a mountainous village affected by landslide is considered in the study. Sentinel-1 is demonstrated to be a suitable system to detect and monitor small changes or buildings and infrastructures for these scenarios. These changes may be highly indicative of imminent damage which can lead to the loss of the structural integrity and subsequent failure of the structure in the long-term. In Rize, only a few known motion-critical structures are monitored daily with in-situ technologies. SAR interferometry can assist to save expensive inspection and monitoring services, especially in highly critical cases such as the one studied in this paper.

Linking Paleogene Rifting and Inversion in the Northern Song Hong and Beibuwan Basins, Vietnam, With Left‐Lateral Motion on the Ailao Shan‐Red River Shear Zone

AbstractExtrusion tectonics forced by plate collisions shape continents not only through lateral terrain displacement and mountain building but also through massive rifting and basin development. The rift system underneath the Gulf of Tonkin, Vietnam, constitutes a world‐class example of how extrusion tectonics drives continental rifting and transtensional basin development. Rifting and the Song Hong and Beibuwan Basin evolution are compared with the development of the Ailao Shan‐Red River Shear Zone (ASRRSZ) that accommodated the extrusion of Indochina forced by the Indian‐Eurasia collision. Rifting occurred during later Eocene‐Late Oligocene time forced by ASRRSZ left‐lateral shearing. Latest Oligocene‐earliest Miocene transpression and inversion brought rifting to a halt, after which left‐lateral shearing decreased. Paleogene rift systems extended along the trail of the ASRRSZ now outlined by lower to midcrustal metamorphic core complexes. Most of these rift systems were probably inverted and removed during the latest Oligocene‐earliest Miocene, however. The metamorphic core complexes are suggested to represent the lower to midcrustal roots of these transtensional rift basins exhumed by inversion. Rift termination in the northern Gulf of Tonkin and exhumation of the metamorphic core complexes coincided with cessation of Paleogene rifting along the western South China Sea, and a common causal mechanism is speculated.

Evolution of urban monitoring with radar interferometry in Madrid City: performance of ERS-1/ERS-2, ENVISAT, COSMO-SkyMed, and Sentinel-1 products

ABSTRACTDuring the last decades, synthetic aperture radar (SAR) image exploitation has matured with the launch of different satellite missions and the development of different techniques, which allow exploiting the capabilities of the radar images. Among these techniques, persistent scatterer interferometry (PSI) has proven to be a powerful tool to derive terrain deformations over urban areas. It is based on the use of a large number of images over wide areas in order to obtain terrain displacements time series. The imagery from the different SAR missions has led to an archive with data that covers up to 30 years in the past. Moreover, different methods and algorithms have been proposed in order to perform this complex task. In this line, this work aims at identifying if data from different missions and processed by different techniques can be combined in order to study the evolution of urban monitoring. Three different PSI techniques are used in order to process data from four SAR missions: European Remote Sensing (ERS)-1/2, Environmental Satellite, COSMO-SkyMed, and the recent Sentinel-1 A/B. The rapidly evolving urban area of Madrid, where numerous undergrounding works have been carried out in the last decade, has been chosen as the testing environment. The density of persistent scatterers, the deformation accuracy validated with GPS displacements and deformation trends are used as the key performance items for the assessment.

Unwrapping-free interpolation of sparse DInSAR phase data: experimental validation

ABSTRACTIn 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.

Geodetic mass balance of surge‐type Black Rapids Glacier, Alaska, 1980–2001–2010, including role of rockslide deposition and earthquake displacement

AbstractWe determine the geodetic mass balance of surge‐type Black Rapids Glacier, Alaska, for the time periods 1980–2001 and 2001–2010 by combining modern interferometric synthetic aperture radar (InSAR)‐derived digital elevation models (DEMs), DEMs derived from archival aerial imagery, laser altimetry data, and in situ surface elevation measurements. Our analysis accounts for both the large rockslides and terrain displacements caused by the 2002 M7.9 earthquake on the Denali fault, which runs through Black Rapids Glacier. To estimate uncertainties, we apply Monte Carlo simulations. For the earthquake‐triggered rockslides we find a volume of 56.62 ± 2.86 × 106 m3, equivalent to an average debris thickness of 4.44 ± 0.24 m across the 11.7 km2 deposit area on the glacier. Terrain displacement due to the earthquake corresponds to an apparent glacier volume change of −53.1 × 106 m3, which would cause an apparent specific mass balance of −0.19 meter water equivalent (mwe) if not taken into account. The geodetic mass balance of Black Rapids Glacier is −0.48 ± 0.07 mwe a−1 for the entire 30 year period, but more negative for the period 2001–2010 (−0.64 ± 0.11 mwe a−1) than the period 1980–2001 (−0.42 ± 0.11 mwe a−1), in agreement with trends indicated by in situ mass balance measurements. Elevation data indicate no net thickening of the surge reservoir between 1980 and 2010, in contrast to what is expected during the quiescent phase. A surge of Black Rapids Glacier in the near future is thus considered unlikely.