Evaluation of the Use of Sub-Pixel Offset Tracking Techniques to Monitor Landslides in Densely Vegetated Steeply Sloped Areas

Sub-Pixel Offset Tracking (sPOT) is applied to derive high-resolution centimetre-level landslide rates in the Three Gorges Region of China using TerraSAR-X Hi-resolution Spotlight (TSX HS) space-borne SAR images. These results contrast sharply with previous use of conventional differential Interferometric Synthetic Aperture Radar (DInSAR) techniques in areas with steep slopes, dense vegetation and large variability in water vapour which indicated around 12% phase coherent coverage. By contrast, sPOT is capable of measuring two dimensional deformation of large gradient over steeply sloped areas covered in dense vegetation. Previous applications of sPOT in this region relies on corner reflectors (CRs), (high coherence features) to obtain reliable measurements. However, CRs are expensive and difficult to install, especially in remote areas; and other potential high coherence features comparable with CRs are very few and outside the landslide boundary. The resultant sub-pixel level deformation field can be statistically analysed to yield multi-modal maps of deformation regions. This approach is shown to have a significant impact when compared with previous offset tracking measurements of landslide deformation, as it is demonstrated that sPOT can be applied even in densely vegetated terrain without relying on high-contrast surface features or requiring any de-noising process

Time series analysis of very slow landslides in the three Gorges region through small baseline SAR offset tracking

Sub-pixel offset tracking has been used in various applications, including measurements of glacier movement, earthquakes, landslides, etc., as a complementary method to time series InSAR. In this work, we explore the use of a small baseline subset (SBAS) Offset Tracking approach to monitor very slow landslides with centimetre-level annual displacement rate, and in challenging areas characterized by high humidity, dense vegetation cover, and steep slopes. This approach, herein referred to as SBAS Offset Tracking, is used to minimize temporal and spatial de -correlation in offset pairs, in order to achieve high density of reliable measurements. This approach is applied to a case study of the Tanjiahe landslide in the Three Gorges Region. Using the TerraSAR-X Staring Spotlight (TSX-ST) data, with sufficient density of observations, we estimate the precision of the SBAS offset tracking approach to be 2-3 cm on average. The results demonstrated accord well with corresponding GPS measurements

Evaluating sub-pixel offset techniques as an alternative to D-InSAR for monitoring episodic landslide movements in vegetated terrain

Spaceborne Synthetic Aperture Radar (SAR) sensors obtain regular and frequent radar images from which ground motion can be precisely detected using a variety of different techniques. The ability to measure slope displacements remotely over large regions can have many uses, although the limitations of the most commonplace technique, differential InSAR (D-InSAR), must be considered prior to interpreting the final results. One such limitation is the assumption that different rates of movement over a given distance cannot exceed a threshold value, dependent upon the pixel spacing of the SAR images and the radar wavelength. Characteristic features of landslides (i.e. the sharp boundary between stable/active ground and the range of temporally-variable velocities) can exhibit high spatial displacement gradients, breaking a fundamental assumption for reliable D-InSAR analysis. Areas of low coherence are also known to hinder the exploitation of InSAR data. This study assesses the capability of TerraSAR-X Spotlight, TerraSAR-X Stripmap and Envisat Stripmap images for monitoring the slow-moving Shuping landslide in the densely vegetated Three Gorges region, China. In this case study, the episodic nature of movement is shown to exceed the measurable limit for regular D-InSAR analysis even for the highest resolution 11-day TSX Spotlight interferograms. A Sub-Pixel Offset Time-series technique applied to corner reflectors (SPOT-CR) using only the SAR amplitude information is applied as a robust method of resolving time-varying displacements, with verifiable offset measurements presented from TSX Spotlight and TSX Stripmap imagery. Care should be exercised when measuring potentially episodic landslide movements in densely vegetated areas such as the Three Gorges region and corner reflectors are shown to be highly useful for SPOT techniques even when the assumptions for valid D-InSAR analysis are broken. Finally the capability to derive two-dimensional movements from sub-pixel offsets (in range and along-track directions) can be used to derive estimates of the vertical and northwards movements to help infer the landslide failure mechanism

Analysing landslides in the Three Gorges Region (China) using frequently acquired SAR images

Spaceborne Synthetic Aperture Radar (SAR) sensors obtain regular and frequent radar images from which ground motion can be precisely detected using a variety of different techniques. The ability to remotely measure slope displacements over large regions has many uses and advantages, although the limitations of an increasingly common technique, Differential SAR Interferometry (D-InSAR), must be considered to avoid the misinterpretation of results. Areas of low coherence and the geometrical effects of mountainous terrain in SAR imagery are known to hinder the exploitation of D-InSAR results. A further major limitation for landslide studies is the assumption that variable rates of movement over a given distance cannot exceed a threshold value, dependent upon the SAR image pixel spacing, the radar sensor wavelength and satellite revisit frequency. This study evaluates the use of three SAR image modes from TerraSAR-X and ENVISAT satellites for monitoring slow-moving landslides in the densely vegetated Three Gorges region, China. Low coherence and episodically fast movements are shown to exceed the measureable limit for regular D-InSAR analysis even for the highest resolution, 11-day interferograms. Subsequently, sub-pixel offset time-series techniques applied to corner reflectors and natural targets are developed as a robust method of resolving time-variable displacements. Verifiable offsets are generated with the TerraSAR-X imagery and the precise movement history of landslides is obtained over a period of up to four years. The capability to derive two-dimensional movements from sub-pixel offsets is used to infer a rotational failure mechanism for the most active landslide detected, and a greater understanding of the landslide behaviour is achieved through comparisons with likely triggering factors and 2D limit equilibrium slope stability analysis

Earth Observations for Geohazards: Present and Future Challenges

Earth Observations (EO) encompasses different types of sensors (e.g., Synthetic Aperture Radar, Laser Imaging Detection and Ranging, Optical and multispectral) and platforms (e.g., satellites, aircraft, and Unmanned Aerial Vehicles) and enables us to monitor and model geohazards over regions at different scales in which ground observations may not be possible due to physical and/or political constraints. EO can provide high spatial, temporal and spectral resolution, stereo-mapping and all-weather-imaging capabilities, but not by a single satellite at a time. Improved satellite and sensor technologies, increased frequency of satellite measurements, and easier access and interpretation of EO data have all contributed to the increased demand for satellite EO data. EO, combined with complementary terrestrial observations and with physical models, have been widely used to monitor geohazards, revolutionizing our understanding of how the Earth system works. This Special Issue presents a collection of scientific contributions focusing on innovative EO methods and applications for monitoring and modeling geohazards, consisting of four Sections: (1) earthquake hazards; (2) landslide hazards; (3) land subsidence hazards; and (4) new EO techniques and services.Part of this work was supported by the UK Natural Environmental Research Council (NERC) through the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET, ref.: come30001) and the LICS and CEDRRIC projects (refs. NE/K010794/1 and NE/N012151/1, respectively), European Space Agency through the ESA-MOST DRAGON-4 projects (ref. 32244) and the Spanish Ministry of Economy and Competitiveness and EU FEDER funds under projects TIN2014-55413- C2-2-P and ESP2013-47780-C2-2-R

Characterizing slope instability kinematics by integrating multi-sensor satellite remote sensing observations

Over the past few decades, the occurrence and intensity of geological hazards, such as landslides, have substantially risen due to various factors, including global climate change, seismic events, rapid urbanization and other anthropogenic activities. Landslide disasters pose a significant risk in both urban and rural areas, resulting in fatalities, infrastructure damages, and economic losses. Nevertheless, conventional ground-based monitoring techniques are often costly, time-consuming, and require considerable resources. Moreover, some landslide incidents occur in remote or hazardous locations, making ground-based observation and field investigation challenging or even impossible. Fortunately, the advancements in spaceborne remote sensing technology have led to the availability of large-scale and high-quality imagery, which can be utilized for various landslide-related applications, including identification, monitoring, analysis, and prediction. This efficient and cost-effective technology allows for remote monitoring and assessment of landslide risks and can significantly contribute to disaster management and mitigation efforts. Consequently, spaceborne remote sensing techniques have become vital for geohazard management in many countries, benefiting society by providing reliable downstream services. However, substantial effort is required to ensure that such benefits are provided. For establishing long-term data archives and reliable analyses, it is essential to maintain consistent and continued use of multi-sensor spaceborne remote sensing techniques. This will enable a more thorough understanding of the physical mechanisms responsible for slope instabilities, leading to better decision-making and development of effective mitigation strategies. Ultimately, this can reduce the impact of landslide hazards on the general public. The present dissertation contributes to this effort from the following perspectives: 1. To obtain a comprehensive understanding of spaceborne remote sensing techniques for landslide monitoring, we integrated multi-sensor methods to monitor the entire life cycle of landslide dynamics. We aimed to comprehend the landslide evolution under complex cascading events by utilizing various spaceborne remote sensing techniques, e.g., the precursory deformation before catastrophic failure, co-failure procedures, and post-failure evolution of slope instability. 2. To address the discrepancies between spaceborne optical and radar imagery, we present a methodology that models four-dimensional (4D) post-failure landslide kinematics using a decaying mathematical model. This approach enables us to represent the stress relaxation for the landslide body dynamics after failure. By employing this methodology, we can overcome the weaknesses of the individual sensor in spaceborne optical and radar imaging. 3. We assessed the effectiveness of a newly designed small dihedral corner reflector for landslide monitoring. The reflector is compatible with both ascending and descending satellite orbits, while it is also suitable for applications with both high-resolution and medium-resolution satellite imagery. Furthermore, although its echoes are not as strong as those of conventional reflectors, the cost of the newly designed reflectors is reduced, with more manageable installation and maintenance. To overcome this limitation, we propose a specific selection strategy based on a probability model to identify the reflectors in satellite images

Vulnerability analysis of buildings in areas affected by slow-moving landslides and subsidence phenomena

2015 - 2016Slow-moving landslides and subsidence phenomena yearly induce huge damages both direct (on structures and/or infrastructures with them interacting) and indirect (corresponding to the associated economic losses). For this reason, studies aimed at analyzing and predicting the aforementioned damages are of great interest for Scientific Community and Authorities in charge of identifying the most suitable strategies for the land-use planning and management of urban areas affected by slowmoving landslides and subsidence phenomena. However, carrying out the activities related to the pursuit of those goals is not straightforward since it usually requires high costs due to the great amount of data to be collected for setting up reliable forecasting models as well as the development of proper procedures that take into account i) the identification and quantification of the exposed elements; ii) the definition and estimation of an intensity parameter; iii) the prediction of the damage severity level (generally associated with the attainment of a certain limit state). In this PhD Thesis some original procedures are proposed. In particular, on the basis of empirical and numerical methods, fragility and vulnerability curves are generated in order to predict the damage to buildings in subsidence- and slow-moving landslide-affected areas. The proposed empirical procedures, based on the joint use of DInSAR data (provided from the processing of images acquired by Synthetic Aperture Radar via Differential Interferometric techniques) and information on damages suffered by buildings (recorded and classified during in situ surveys), were tested on case studies in The Netherlands, affected by subsidence phenomena, and in Calabria Region (southern Italy) for slow-moving landslide-affected areas. The procedure based on the adoption of a numerical method was applied on a structural model representative of a single building. With reference to subsidence phenomena, the analyses were carried out for a densely urbanized municipality following a multi-scale approach. In particular, at medium scale, the subsiding areas that are most prone to ground surface settlements along with their spatial distribution and rates, were preliminarily detected. The above ground surface settlements (here considered as subsidence intensity parameter) combined with the results of an extensive damage survey on masonry buildings, allowed first retrieving, at large-scale (on building aggregates) and at detailed scale (on single buildings), the relationships between cause (settlements/differential settlements) and effect (damage severity level); then, empirical fragility curves were generated for structurally independent single buildings. These latter were validated via their comparison with fragility curves generated, with reference to two others densely urbanized municipalities, for buildings with similar structural typology (masonry) and foundation type (shallow or deep). Finally, fragility and vulnerability curves for masonry buildings were generated by using the entire database of damages. As for slow-moving landslides, the analyses were carried out at large scale. In particular, the joint use of DInSAR and damage surveys data allowed analyzing the consequences induced on the buildings (either of masonry or reinforced concrete) with shallow foundations by retrieving the causeeffect relationships and generating empirical fragility and vulnerability curves. Finally, the numerical analyses carried out on a structural model representative of a single masonry building, allowed to go in-depth in the different aspects contributing to the onset and development of building damages as well as to quantify the uncertainties inherent to the addressed issue. The obtained results highlight the huge potential of the fragility and vulnerability curves generated according to the proposed procedures that, once further calibrated/validated and jointly used with a continuous monitoring of the intensity parameter via conventional (e.g., inclinometers, GPS, topographic leveling) and/or innovative (e.g., SAR images processed via DInSAR techniques) systems, can be valuably used as tools for the analysis and prediction of the damage to buildings for land-use planning and urban management purposes in subsidence- and slow-moving landslide-affected areas. [edited by author]Le frane a cinematica lenta e i fenomeni di subsidenza causano annualmente ingenti danni sia diretti (su strutture e/o infrastrutture con essi interagenti) che indiretti (quali si configurano le associate perdite di natura economica). Per tale ragione, gli studi volti ad analizzare e a prevedere i predetti danni sono di indubbio interesse per le Comunità e gli Enti impegnati nella individuazione delle più idonee strategie di pianificazione e di gestione delle aree urbanizzate affette dai suddetti fenomeni. Tuttavia, lo svolgimento delle attività connesse al perseguimento dei predetti obiettivi è tutt’altro che agevole in quanto richiede costi elevati, dovuti alla grande quantità di dati da acquisire per la generazione di modelli previsionali affidabili, nonché lo sviluppo di procedure che contemplino i) l’identificazione e la quantificazione degli elementi esposti, ii) la definizione e la stima di un parametro di intensità e iii) la previsione del livello di severità del danno (generalmente associato al raggiungimento di uno stato limite). La presente Tesi di Dottorato propone alcune procedure originali che, sulla base di metodi empirici e numerici, conducono alla generazione di curve di fragilità e vulnerabilità quali strumenti di previsione del danno a edifici in aree affette da frane a cinematica lenta e fenomeni di subsidenza. Le procedure empiriche proposte, basate sull’integrazione congiunta di dati DInSAR (ovvero derivanti dalla elaborazione di immagini acquisite da radar ad apertura sintetica montati su piattaforme satellitari mediante tecniche interferometriche differenziali) e sul danno subito da edifici (a sua volta classificato sulla base degli esiti di rilievi in sito dei quadri fessurativi esibiti dalle facciate), sono state testate con riferimento a casi di studio dei Paesi Bassi, affetti da fenomeni di subsidenza, e della Regione Calabria (Italia meridionale), interessati da frane a cinematica lenta. La procedura basata sull’impiego di metodi numerici è stata, invece, applicata su un modello strutturale rappresentativo di un edificio singolo. Con riferimento ai fenomeni di subsidenza, le attività svolte con un approccio multi-scalare hanno consentito preliminarmente di rilevare (a media scala) le aree che risultano essere maggiormente predisposte a cedimenti dovuti a fenomeni di subsidenza. La conoscenza della distribuzione spaziale e della entità di tali cedimenti è stata, poi, combinata con i risultati di un esteso rilievo del danno agli edifici in muratura di un’area comunale in modo da i) risalire – sia a grande scala (su aggregati di edifici) che a scala di dettaglio (singoli edifici) – alle relazioni funzionali che si stabiliscono tra causa (cedimenti assoluti/differenziali) ed effetti (livello di severità del danno) e ii) generare per singoli edifici strutturalmente indipendenti curve di fragilità su base empirica. Le curve di fragilità così calibrate sono state, poi, validate operandone un confronto con curve di fragilità generate, con la medesima procedura, per altre due aree comunali caratterizzate dalla presenza di edifici con la stessa tipologia strutturale e fondale (superficiale o profonda). Si è, infine, provveduto alla generazione di curve di fragilità e di vulnerabilità di edifici in muratura utilizzando l’intero campione di dati a disposizione. Per quanto riguarda le frane a cinematica lenta, le analisi sono state svolte esclusivamente a grande scala, dove l’uso congiunto dei dati DInSAR e del rilievo del danno a edifici in cemento armato e in muratura con fondazioni superficiali ha consentito, ancora una volta, di risalire alle relazioni causa-effetto e di generare curve di fragilità e di vulnerabilità su base empirica. Infine, l’analisi numerica effettuata su un modello strutturale rappresentativo di un singolo edificio in muratura con fondazioni superficiali ha consentito di approfondire il ruolo esercitato da alcuni fattori nella generazione e nello sviluppo del danno nonché di quantificare le incertezze che intervengono nel problema esaminato. I risultati ottenuti evidenziano l’enorme potenzialità delle curve di fragilità e vulnerabilità ottenute che, laddove ulteriormente calibrate e validate, possono essere impiegate congiuntamente con tecniche di monitoraggio in continuo dei parametri d’intensità – sia di tipo convenzionale (quali, ad esempio, inclinometri, GPS, livellazione topografica) che innovative (come quelle derivanti dall’elaborazione di immagini satellitari mediante tecniche DInSAR) – per la messa a punto di modelli previsionali utili alla pianificazione territoriale e alla gestione di aree urbane affette da frane a cinematica lenta e fenomeni di subsidenza. [a cura dell'autore]XV n.s

Elevation and Deformation Extraction from TomoSAR

3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM-X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings

Analisi di dati DInSAR in aree urbane affette da subsidenza o frane a cinematica lenta

2012 - 2013Subsidence and slow-moving landslides systematically cause social, economic and environmental impacts all over the world. For this reason studies aimed at both the characterization of subsidence and slow-moving landslides and the analysis of the consequences on the exposed elements interacting with them are of great interest for the scientific and the technical community. These studies, to be useful in land use planning and management, need a huge number of displacement measurements within and on the boundary of the affected areas. Recently the scientific community has shownan increasing interest in the potential of using satellite observation techniques and, in particular, interferometric methods of Synthetic Aperture Radar (DInSAR)image processing. The literature review on DInSAR applications highlights the possibility of further researches pursuing the exploitation of DInSAR potentiality in studies at different scales and the development of procedures for the proper use of interferometric data and their validation with reference to well documented case studies. To this end, this PhD Thesis is aimed at developing original procedures for the analysis of the interferometric measurements specifically devotedto pursue two main objectives: the characterization of the phenomena of interest and the prediction of consequences to buildings interacting with them. The conceived procedures were tested, in sample areas of the Campania region (southern Italy)following a multi-scale approach. With reference to subsidence phenomena, the studies at small-scale involved the entire region and were mainly aimedatdetecting subsiding macro-areas; within these latter, more detailed studies at medium scale were carried out and the most affected municipalities were individuated. At large scale,focusing on one of these municipalities, studies dealing with the analysis of parameters whose variation leadsto the generation of the damage were carried out. Finally, at the scale of the single building the interferometric data were interpretedaccording todamageability criteria adopted in engineering practice. As forslow-moving landslides, the joint use of interferometric measurements and damage surveysallowed the updating of landslide inventory maps at medium scale and the analysis of the consequencesthrough the generation of fragility and vulnerability curves within a test area including 21 municipalities of BeneventoProvince. At large-scale studies were performed on a landslide-affected area within the municipality of Ascea(Salerno Province) in order to follow the evolution - in space and time - of the analyzed phenomenon as well as to deepen its kinematic behavior, in turn useful for zoning purposes. The obtained results highlight that the conceived procedures can valuably integrate the current practice for land use planning and as well as for the selection of the most suitablemanagement strategy.XII n.s

From Regional Landslide Detection to Site-Specific Slope Deformation Monitoring and Modelling Based on Active Remote Sensors

Landslide processes can have direct and indirect consequences affecting human lives and activities. In order to improve landslide risk management procedures, this PhD thesis aims to investigate capabilities of active LiDAR and RaDAR sensors for landslides detection and characterization at regional scales, spatial risk assessment over large areas and slope instabilities monitoring and modelling at site-specific scales. At regional scales, we first demonstrated recent boat-based mobile LiDAR capabilities to model topography of the Normand coastal cliffs. By comparing annual acquisitions, we validated as well our approach to detect surface changes and thus map rock collapses, landslides and toe erosions affecting the shoreline at a county scale. Then, we applied a spaceborne InSAR approach to detect large slope instabilities in Argentina. Based on both phase and amplitude RaDAR signals, we extracted decisive information to detect, characterize and monitor two unknown extremely slow landslides, and to quantify water level variations of an involved close dam reservoir. Finally, advanced investigations on fragmental rockfall risk assessment were conducted along roads of the Val de Bagnes, by improving approaches of the Slope Angle Distribution and the FlowR software. Therefore, both rock-mass-failure susceptibilities and relative frequencies of block propagations were assessed and rockfall hazard and risk maps could be established at the valley scale. At slope-specific scales, in the Swiss Alps, we first integrated ground-based InSAR and terrestrial LiDAR acquisitions to map, monitor and model the Perraire rock slope deformation. By interpreting both methods individually and originally integrated as well, we therefore delimited the rockslide borders, computed volumes and highlighted non-uniform translational displacements along a wedge failure surface. Finally, we studied specific requirements and practical issues experimented on early warning systems of some of the most studied landslides worldwide. As a result, we highlighted valuable key recommendations to design new reliable systems; in addition, we also underlined conceptual issues that must be solved to improve current procedures. To sum up, the diversity of experimented situations brought an extensive experience that revealed the potential and limitations of both methods and highlighted as well the necessity of their complementary and integrated uses