Thèses sur le sujet « Interferometric Synthetic Aperture Radar (InSAR) »

This work makes an attempt to explain the origin, features and potential applications of the elevation bias of the synthetic aperture radar interferometry (InSAR) datasets over areas covered by vegetation. The rapid development of radar-based remote sensing methods, such as synthetic aperture radar (SAR) and InSAR, has provided an alternative to the photogrammetry and LiDAR for determining the third dimension of topographic surfaces. The InSAR method has proved to be so effective and productive that it allowed, within eleven days of the space shuttle mission, for acquisition of data to develop a three-dimensional model of almost the entire land surface of our planet. This mission is known as the Shuttle Radar Topography Mission (SRTM). Scientists across the geosciences were able to access the great benefits of uniformity, high resolution and the most precise digital elevation model (DEM) of the Earth like never before for their a wide variety of scientific and practical inquiries. Unfortunately, InSAR elevations misrepresent the surface of the Earth in places where there is substantial vegetation cover. This is a systematic error of unknown, yet limited (by the vertical extension of vegetation) magnitude. Up to now, only a limited number of attempts to model this error source have been made. However, none offer a robust remedy, but rather partial or case-based solutions. More work in this area of research is needed as the number of airborne and space-based InSAR elevation models has been steadily increasing over the last few years, despite strong competition from LiDAR and optical methods. From another perspective, however, this elevation bias, termed here as the “biomass impenetrability”, creates a great opportunity to learn about the biomass. This may be achieved due to the fact that the impenetrability can be considered a collective response to a few factors originating in 3D space that encompass the outermost boundaries of vegetation. The biomass, presence in InSAR datasets or simply the biomass impenetrability, is the focus of this research. The report, presented in a sequence of sections, gradually introduces terminology, physical and mathematical fundamentals commonly used in describing the propagation of electromagnetic waves, including the Maxwell equations. The synthetic aperture radar (SAR) and InSAR as active remote sensing methods are summarised. In subsequent steps, the major InSAR data sources and data acquisition systems, past and present, are outlined. Various examples of the InSAR datasets, including the SRTM C- and X-band elevation products and INTERMAP Inc. IFSAR digital terrain/surface models (DTM/DSM), representing diverse test sites in the world are used to demonstrate the presence and/or magnitude of the biomass impenetrability in the context of different types of vegetation – usually forest. Also, results of investigations carried out by selected researchers on the elevation bias in InSAR datasets and their attempts at mathematical modelling are reviewed. In recent years, a few researchers have suggested that the magnitude of the biomass impenetrability is linked to gaps in the vegetation cover. Based on these hints, a mathematical model of the tree and the forest has been developed. Three types of gaps were identified; gaps in the landscape-scale forest areas (Type 1), e.g. forest fire scares and logging areas; a gap between three trees forming a triangle (Type 2), e.g. depending on the shape of tree crowns; and gaps within a tree itself (Type 3). Experiments have demonstrated that Type 1 gaps follow the power-law density distribution function. One of the most useful features of the power-law distributed phenomena is their scale-independent property. This property was also used to model Type 3 gaps (within the tree crown) by assuming that these gaps follow the same distribution as the Type 1 gaps. A hypothesis was formulated regarding the penetration depth of the radar waves within the canopy. It claims that the depth of penetration is simply related to the quantisation level of the radar backscattered signal. A higher level of bits per pixels allows for capturing weaker signals arriving from the lower levels of the tree crown. Assuming certain generic and simplified shapes of tree crowns including cone, paraboloid, sphere and spherical cap, it was possible to model analytically Type 2 gaps. The Monte Carlo simulation method was used to investigate relationships between the impenetrability and various configurations of a modelled forest. One of the most important findings is that impenetrability is largely explainable by the gaps between trees. A much less important role is played by the penetrability into the crown cover. Another important finding is that the impenetrability strongly correlates with the vegetation density. Using this feature, a method for vegetation density mapping called the mean maximum impenetrability (MMI) method is proposed. Unlike the traditional methods of forest inventories, the MMI method allows for a much more realistic inventory of vegetation cover, because it is able to capture an in situ or current situation on the ground, but not for areas that are nominally classified as a “forest-to-be”. The MMI method also allows for the mapping of landscape variation in the forest or vegetation density, which is a novel and exciting feature of the new 3D remote sensing (3DRS) technique. Besides the inventory-type applications, the MMI method can be used as a forest change detection method. For maximum effectiveness of the MMI method, an object-based change detection approach is preferred. A minimum requirement for the MMI method is a time-lapsed reference dataset in the form, for example, of an existing forest map of the area of interest, or a vegetation density map prepared using InSAR datasets. Preliminary tests aimed at finding a degree of correlation between the impenetrability and other types of passive and active remote sensing data sources, including TerraSAR-X, NDVI and PALSAR, proved that the method most sensitive to vegetation density was the Japanese PALSAR - L-band SAR system. Unfortunately, PALSAR backscattered signals become very noisy for impenetrability below 15 m. This means that PALSAR has severe limitations for low loadings of the biomass per unit area. The proposed applications of the InSAR data will remain indispensable wherever cloud cover obscures the sky in a persistent manner, which makes suitable optical data acquisition extremely time-consuming or nearly impossible. A limitation of the MMI method is due to the fact that the impenetrability is calculated using a reference DTM, which must be available beforehand. In many countries around the world, appropriate quality DTMs are still unavailable. A possible solution to this obstacle is to use a DEM that was derived using P-band InSAR elevations or LiDAR. It must be noted, however, that in many cases, two InSAR datasets separated by time of the same area are sufficient for forest change detection or similar applications.

Le tecniche Multi-temporali SAR interferometriche (Mt-InSAR) rappresentano oggigiorno strumenti consolidati per mappare l’evoluzione temporale dei fenomeni di deformazione del suolo Terrestre. Queste tecniche utilizzano congiuntamente sets di interferogrammi SAR differenziali al fine di estrarre la componente legata alla deformazione e produrre così serie storiche di deformazione dei bersagli osservati dal sensore. L'affidabilità delle misure prodotte utilizzando algoritmi Mt-InSAR è strettamente legata alla capacità degli stessi algoritmi nell’isolare esclusivamente i segnali legati alla deformazione dal segnale complessivo interferometrico, e questa operazione diventa sempre più complessa all’aumentare dei livelli di rumore in ciascun interferogramma SAR coinvolto. Le tecniche Mt-InSAR canoniche sono altamente affidabili nel monitorare l'evoluzione dello spostamento dei target che risultano essere ampiamente stabili o coerenti per tutto il periodo di analisi. Diversamente, quando i bersagli sono particolarmente affetti da problemi di decorrelazione, le stime di deformazione ottenute risultano corrotte e inaffidabili. Questo pone le basi per lo sviluppo di processori Mt-InSAR avanzati che possano fornire stime accurate della deformazione del suolo anche in scenari con problemi di decorrelazione più o meno severi. In questo lavoro di tesi affronta dapprima lo studio dello stato dell’arte delle tecniche Mt-InSAR canoniche applicabili sia nel caso di piattaforme satellitare che terrestri, e dopodiché si propongono delle nuove tecniche Mt-InSAR per superare alcune delle criticità riscontrante. In particolare si studiano le tecniche convenzionali Mt-InSAR multigriglia per l'analisi dei target alla griglia di risoluzione spaziale più risoluta, evidenziandone le loro criticità in aree a media e bassa coerenza, e proprio in questo ambito è proposta una tecnica innovativa per meglio operare in ambienti decorrelati. Il metodo proposto si basa su efficienti operazioni con cui viene srotolata la fase (PhU) interferometrica eseguite alle scale spaziali native, ed in particolare, si srotolano dapprima gli interferogrammi alla scala di soluzione mediata (ML) attraverso algoritmi di PhU convenzionali (o avanzati). Successivamente, gli interferogrammi ML srotolati vengono utilizzati per facilitare le operazioni di PhU eseguite alla scala più fine (single-look). In dettaglio, gli interferogrammi multi-look srotolati vengono ricampionati alla griglia single-look e sottratti a modulo modulo-2π agli interferogrammi single-look. Gli interferogrammi epurati dai contributi a bassa frequenza vengono poi srotolati e aggiunti nuovamente agli interferogrammi multilook ricampionati alla griglia di risoluzione più fine. Per realizzare queste operazioni, a differenza dei metodi multigriglia canonici, non si utilizza alcun modello (lineare/non lineare) per recuperare le componenti di deformazione in alta frequenza. Infine, gli interferogrammi single-look srotolati sono opportunamente invertiti al fine di calcolare le serie storiche di deformazione del suolo attraverso un qualsiasi algoritmo a piccola baseline (SB) InSAR multi-temporale. I risultati sperimentali sono stati ottenuti elaborando una serie di dati SAR acquisiti dal sensore COSMO-SkyMed (banda X) sulla zona costiera di Shanghai, in Cina. La tesi prosegue analizzando le tecniche ai minimi quadrati pesate (WLS) e su come sono sfruttate nell’ambito InSAR al fine di migliorare l’operazione con cui si srotola la fase interferometrica e la generazione di serie storiche di deformazione. Proprio in questo contesto, utilizzando gli approcci WLS, si estende l'utilizzabilità dell'algoritmo Mt-InSAR Small BAseline Subset (SBAS) in aree caratterizzate da una coerenza spaziale medio-bassa. In particolare, pixel per pixel, si invertono esclusivamente le fasi interferometriche coerenti utilizzando una metrica a minimi quadrati pesati. Per cui attraverso una selezione adattiva, per ogni pixel si utilizzano ed invertono soltanto le fasi interferometriche coerenti, e tale caratterista può portare a diversi sottoinsiemi disgiunti di dati SAR, che sono poi invertiti sfruttando la Decomposizione a Valori Singolari Pesata (WSVD). Tuttavia, per taluni pixel, l’utilizzo esclusivo delle fasi interferometriche coerenti può portare in alcuni casi allo scarto di acquisizioni SAR particolarmente rumorose, il che si traduce in serie storiche di deformazione affidabili ma con campionamento temporale variabile. I risultati sperimentali sono stati condotti applicando la tecnica sviluppata ad un set di dati SAR acquisiti dai sensori COSMO-SkyMed (CSK) sulla regione Basilicata, nel sud Italia. Il lavoro di tesi continua analizzando le proprietà che ledono alla irrotazionalità delle triplette di fase di interferogrammi SAR multi-look. In particolare, si studiano le conseguenze delle incongruenze temporali di fase dei multi-look sulla generazione delle serie storiche di deformazione del suolo attraverso metodi SB Mt-InSAR. La ricerca condotta mostra come queste incongruenze di fase si possono propagare attraverso una rete temporale ridondante di interferogrammi SB, ed insieme agli errori di PhU, pregiudicano la qualità dei prodotti InSAR generati. In letteratura questo effetto va sotto il nome di bias di fase, il quale può pregiudicare l’affidabilità dei metodi SB quando si impostano delle soglie sulla massima baseline temporale troppo stringenti (nell’ordine di 30 giorni o meno). Proponiamo così, due nuovi metodi per la compensazione di tali fenomeni di bias, i quali metodi sono stati testati utilizzando dati SAR simulati e reali. I dati reali sono stati acquisiti dai sensori Sentinel-1A/B (banda C) sulle aree del Nevada (U.S.), e sulla zona del monte Etna in Sicilia, nel sud Italia. Dopo lo sviluppo di algoritmi per la parte satellitare, il lavoro si sposta sui sensori SAR terrestri (GB-SAR). In questo ambito proponiamo un metodo per stimare e compensare i disturbi introdotti dallo strato atmosferico (APS) in interferogrammi GB-SAR. Un’ambia analisi fisica, statistica e matematica dell'approccio presentato è fornita, discutendo inoltre le potenzialità e i limiti del metodo che a differenza di altri algoritmi, che stimano l'APS dai segnali di fase srotolati, nella metodologia proposta la compensazione avviene direttamente sul dato arrotolato, in modo tale che la stima non è affetta da nessun potenziale errore di PhU. Gli esperimenti eseguiti su dati InSAR GB-SAR simulati e reali confermano la validità della tecnica proposta, confermando inoltre che il metodo è vantaggioso nelle zone caratterizzate da una forte escursione di quota (come ad esempio nelle regioni Alpine e montuose). Infine, viene presentata un'applicazione SAR interferometrica per la stima delle deformazioni della superficie investigata in tre dimensioni (3-D) attraverso l'uso congiunto ed integrato di dati SAR acquisiti da piattaforme satellitari e terrestri. Più precisamente, la catena di combinazione interferometrica sviluppata si compone anche degli innovativi algoritmi Mt-InSAR sviluppati in questo lavoro di tesi, al fine di ottenere mappe di velocità media di deformazione 3-D direttamente alla griglia spaziale più risoluta possibile. Inoltre, in conclusione, vengono menzionate anche alcune interessanti applicazioni SAR satellitari in ambito di prevenzione ed analisi di particolari fenomeni naturali e indotti dall'uomo.
Multi-temporal SAR interferometric (Mt-InSAR) techniques are nowadays mature tools to measure the temporal evolution of the Earth’s surface with millimetric accuracy. The reliability of crustal measurements is closely related to the goodness of the used Mt-InSAR algorithms in isolating the deformation-related signal from the overall signal, and this becomes increasingly complex as the noise levels of each interferogram increase. Canonical techniques are highly reliable in monitoring the displacement evolution of targets that are found to be largely stable or coherent over the entire period of analysis. Otherwise, when the scatterers are particularly affected by decorrelation problems, the obtained deformation estimates turn out to be corrupted and unreliable. Thus, there is a strong demand for new advanced Mt-InSAR processors that can provide accurate estimates of crustal deformation even in scenarios with more or less severe decorrelation problems. This thesis work focuses on the study of multi-temporal InSAR techniques applicable in both satellite and terrestrial case. Specifically, the canonical Mt-InSAR multigrid techniques for analyzing targets at the finest resolution grid will be discussed extensively highlighting their criticality in medium to low coherence areas, and in this context an innovative technique is proposed to better operate in decorrelated environments. The new method relies on efficient phase-unwrapping (PhU) operations performed at the native spatial scales. In particular, a set of multi-look (ML) interferograms is first unwrapped using conventional (or advanced) PhU algorithms at the regional scale. Subsequently, ML unwrapped interferograms are used to facilitate the PhU operations performed at the local scale (single-look). Specifically, the unwrapped multi-look interferograms are resampled to the single-look grid and modulo-2π subtracted to the single-look interferograms. These phase residuals are then unwrapped and added back to the multi-look resampled interferograms. To accomplish these operations, at variance with alternative multiscale methods, no (linear/nonlinear) models are used to fit the spatial high-pass phase residuals. Finally, the unwrapped single-look interferograms are properly inverted to retrieve the ground displacement time series using any small baseline (SB)-oriented multitemporal InSAR tool. Experimental results are performed by processing a set of SAR data acquired by the X-band COSMO-SkyMed sensor over the coastal area of Shanghai, China. Then, the focusing moves on the Weighted Least-squares (WLS) techniques applied within the InSAR framework for improving the performance of the phase unwrapping operations as well as for better conveying the inversion of sequences of unwrapped interferograms to generate ground displacement maps. In both cases, the identification of low-coherent areas, where the standard deviation of the phase is high, is requested. Therefore, a WLS method that extends the usability of the Mt-InSAR Small BAseline Subset (SBAS) algorithm in regions with medium-to-low coherence is presented. In particular, the proposed method relies on the adaptive selection and exploitation, pixel-by-pixel, of the medium-to-high coherent interferograms, only, so as to discard the noisy phase measurements. The selected interferometric phase values are then inverted by solving a WLS optimization problem. Noteworthy, the adopted, pixel-dependent selection of the “good” interferograms to be inverted may lead the available SAR data to be grouped into several disjointed subsets, which are then connected, exploiting the Weighted Singular Value Decomposition (WSVD) method. However, in some critical noisy regions, it may also happen that discarding of the incoherent interferograms may lead to rejecting some SAR acquisitions from the generated ground displacement time-series, at the cost of the reduced temporal sampling of the data measurements. Thus, variable-length ground displacement time-series are generated. The presented experiments have been carried out by applying the developed technique to a SAR dataset acquired by the COSMO-SkyMed (CSK) sensors over the Basilicata region, Southern Italy. In the continuation of the thesis work, the properties characterizing the phase non-closure of multi-look SAR interferograms are explored. Precisely, we study the implications of multi-look phase time incongruences on the generation of ground displacement time-series through SB Mt-InSAR methods. Our research clarifies how these phase inconsistencies can propagate through a time-redundant network of SB interferograms and contribute, along with PhU errors, to the quality of the generated ground displacement products. Moreover, we analyze the effects of short-lived phase bias signals that could happen in sequences of short baseline interferograms and propose a strategy for their mitigation. The developed methods have been tested using both simulated and real SAR data. The latter were collected by the Sentinel-1A/B (C-band) sensors over the study areas of Nevada state, U.S., and Sicily Island, Italy. After the development of algorithms for the satellite part, the work veers to ground-based SAR (GB-SAR) sensors. In this field, we propose a method for estimating and compensating the atmospheric phase screen (APS) in sets of SAR interferograms generated with a GB-SAR instrument. We address the presented approach’s physical, statistical, and mathematical framework by discussing its potential and limitations. In contrast with other existing algorithms that estimate the APS from the unwrapped phase signals, our methodology is based on the straightforward analysis of the wrapped phases, directly. Therefore, the method is not affected by any potential phase unwrapping mistake, and it is suitable for Mt-InSAR applications. The effects of the local topography, the decorrelation noise, and the ground deformation on the APS estimates are deeply studied. Experiments performed on simulated and real GB-SAR InSAR data corroborate the validity of the theory. In particular, the simulated results show that the method is beneficial in zones with medium-to-high topographic slopes (e.g., for Alpine and mountainous regions). Further, an interferometric SAR application for the study of three-dimensional (3-D) deformation through the joint and integrated use of satellite and ground SAR data is presented. More precisely, the interferometric data-combining technique exploits the innovative Mt-InSAR algorithms mentioned above, and allows obtaining 3-D mean displacement velocity maps at the finest spatial grid among the available data. In conclusion, also some interested satellite SAR applications in prevention and analysis of particular natural and human-induced disasters are given.

This thesis considers the use of Interferometric Synthetic Aperture Radar (InSAR) for surveying temporal fluctuations in the velocity of glaciers in the Arctic region. The aim of this thesis is to gain a broader understanding of the manner in which the flow of both land- and marine-terminating glaciers varies over time, and to asses the ability of InSAR to resolve flow changes over timescales which provide useful information about the physical processes that control them. InSAR makes use of the electromagnetic phase difference between successive SAR images to produce interference patterns (interferograms) which contain information on the topography and motion of the Earth's surface in the direction of the radar line-of-sight. We apply established InSAR techniques (Goldstein et al., 1993) to (i) the 925 km2 LangjÖkull Ice Cap (LIC) in Iceland, which terminates on land (ii) the 8 500 km2 Flade Isblink Icecap (FIIC) in Northeast Greenland which has both land- and marine-terminating glaciers and (iii) to a 7 000 km2 land-terminating sector of the Western Greenland Ice Sheet (GrIS). It is found that these three regions exhibit velocity variations over contrasting timescales. At the LIC, we use an existing ice surface elevation model and dual-look SAR data acquired by the European Remote Sensing (ERS) satellite to estimate ice velocity (Joughin et al., 1998) during late-February in 1994. A comparison with direct velocity measurements determined by global positioning system (GPS) sensors during the summer of 2001 shows agreement (r2 = 0.86), suggesting that the LIC exhibits moderate seasonal and inter-annual variations in ice flow. At the FIIC, we difference pairs of interferograms (Kwok and Fahnestock, 1996) formed using ERS SAR data acquired between 15th August 1995 and 3rd February 1996 to estimate ice velocity on four separate days. We observe that the flow of 5 of the 8 outlet glaciers varies in latesummer compared with winter, although flow speeds vary by up to 20 % over a 10 day period in August 1995. At the GrIS, we use InSAR (Joughin et al., 1996) and ERS SAR data to reveal a detailed pattern of seasonal velocity variations, with ice speeds in latesummer up to three times greater than wintertime rates. We show that the degree of seasonal speedup is spatially variable and correlated with modeled runoff, suggesting that seasonal velocity changes are controlled by the routing of water melted at the ice sheet surface. The overall conclusion of this work is that the technique of InSAR can provide useful information on fluctuations in ice speed across a range of timescales. Although some ice masses exhibit little or no temporal flow variability, others show marked inter-annual, seasonal and even daily variations in speed. We observe variations in seasonality in ice flow over distances of ~ 10 km and over time periods of ~10 days during late-summer. With the aid of ancillary meteorological data, we are able to establish that rates of flow in western Greenland are strongly moderated by the degree of surface melting, which varies seasonally and secularly. Although the sampling of our data is insufficiently frequent and spans too brief a period for us to derive a general relationship between climate and seasonality of flow, we show that production of meltwater at the ice surface and its delivery to the ice bed play an important role in the modulation of horizontal flow speeds. We suggest that a similarly detailed investigation of other ice masses is required to reduce the uncertainty in predictions of the future Arctic land-ice contribution to sea level in a warming world.

Information about deformation in an area has become vital not only for safety assessment but also for maintenance of geodetic infrastructures. The latter is necessary to support accurate surveying and mapping applications. This research exploits the complementary features of Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar (InSAR) techniques to assess the long-term deformation in Johor, Malaysia, which can be induced by natural and/or anthropogenic activities. Furthermore, modelling and mitigation of tropospheric effects in GPS and InSAR are addressed to achieve the best possible precision from the two techniques. Indeed, their modelling and mitigation improve the quality of the estimation as well as provide valuable resources for atmospheric studies. The assessment of long-term deformation in Johor is firstly made by analysing the five years (2007 - 2011) point-specific profile at eight Malaysia Real-Time Kinematic GNSS Network (MyRTKnet) stations. Two processing strategies, namely Precise Point Positioning (PPP) and Double-Difference (DD), are employed to assess their capability for deformation monitoring. The latter also make used of the GPS data from 27 IGb08 stations and 7 International GNSS Service (IGS) stations. Analysis of the results revealed deformation that can be explained by plate tectonic movement and earthquakes in the surrounding region. While results from the PPP processing showed a higher correlation with the recorded earthquakes, the results from DD have improved correlation coefficients at about 4% in the East-West and 5% in the Up-Down components. These improvements are valuable when the rate of deformation is the primary interest. In addition to the point-specific profile, the surrounding deformation of Johor has been assessed with the line-of-sight (LOS) velocity maps from the InSAR time-series. Two sets of ERS-1/2 data, consisting a total of 67 images acquired at two descending tracks (i.e. track 75 and 347), are utilised for the generation of the maps. Moreover, the feasibility of Sentinel-1 satellites is also tested, which revealed improved coherence owing to their short revisit cycle. Some part of Johor showed subsidence and uplift trends, which also agreed with the literature. This information cannot be perceived by the GPS alone due to its limited coverage; hence, further attests to the benefit of their joint analysis. Numerous developments have been implemented in the in-house software (i.e. Punnet) such as the implementation of tropospheric correction, outlier’s rejection scheme, statistical analysis to identify the control point for phase unwrapping, and a new method to retrieve temporal evolution of deformation for a rapidly deforming area.

Landslides are one of the biggest natural hazards in Georgia, a mountainous country in the Caucasus. So far, no systematic monitoring and analysis of the dynamics of landslides in Georgia has been made. Especially as landslides are triggered by extrinsic processes, the analysis of landslides together with precipitation and earthquakes is challenging. In this thesis I describe the advantages and limits of remote sensing to detect and better understand the nature of landslide in Georgia. The thesis is written in a cumulative form, composing a general introduction, three manuscripts and a summary and outlook chapter. In the present work, I measure the surface displacement due to active landslides with different interferometric synthetic aperture radar (InSAR) methods. The slow landslides (several cm per year) are well detectable with two-pass interferometry. In same time, the extremely slow landslides (several mm per year) could be detected only with time series InSAR techniques. I exemplify the success of InSAR techniques by showing hitherto unknown landslides, located in the central part of Georgia. Both, the landslide extent and displacement rate is quantified. Further, to determine a possible depth and position of potential sliding planes, inverse models were developed. Inverse modeling searches for parameters of source which can create observed displacement distribution. I also empirically estimate the volume of the investigated landslide using displacement distributions as derived from InSAR combined with morphology from an aerial photography. I adapted a volume formula for our case, and also combined available seismicity and precipitation data to analyze potential triggering factors. A governing question was: What causes landslide acceleration as observed in the InSAR data? The investigated area (central Georgia) is seismically highly active. As an additional product of the InSAR data analysis, a deformation area associated with the 7th September Mw=6.0 earthquake was found. Evidences of surface ruptures directly associated with the earthquake could not be found in the field, however, during and after the earthquake new landslides were observed. The thesis highlights that deformation from InSAR may help to map area prone landslides triggering by earthquake, potentially providing a technique that is of relevance for country wide landslide monitoring, especially as new satellite sensors will emerge in the coming years.
Erdrutsche zählen zu den größten Naturgefahren in Georgien, ein gebirgiges Land im Kaukasus. Eine systematische Überwachung und Analyse der Dynamik von Erdrutschen in Georgien ist bisher nicht vorhanden. Da Erdrutsche durch extrinsische Prozesse ausgelöst werden, wird ihre Analyse zusammen mit Niederschlag und Erdbeben zu einer besonderen Herausforderung. In dieser Dissertation beschreibe ich die Potenziale und Limitierungen der Fernerkundung für die Detektion und das Verständnis von Erdrutschen in Georgien. Die Arbeit ist in einer kumulativen Form geschrieben, und besteht aus einer allgemeinen Einführung, drei Manuskripten sowie einer Zusammenfassung und einem Ausblick. In der vorliegenden Arbeit, Gestimme ich die Oberflächenverschiebung von aktiven Erdrutschen mit Methoden der Radarinterferometrie (InSAR). Die langsamen Erdrutsche (cm pro Jahr) konnten im einfachen Vergleich zeitlich unterschiedlicher Radaraufnahmen (two-pass InSAR), gut nachgewiesen werden. Die extrem langsamen Erdrutsche (mm pro Jahr) konnten hingegen nur mit InSAR Zeitreihentechniken nachgewiesen werden. Der Erfolg der angewandten InSAR Techniken wird durch die erfolgreiche Identifikation von bisher unbekannten Erdrutschen in Zentral Georgien veranschaulicht. Sowohl das Ausmaß als auch die Verschiebungsrate der Erdrutsche wurden quantifiziert. Ferner, um die mögliche Tiefe und Lage von potentiellen Gleitflächen zu bestimmen, wurden inverse Modelle entwickelt. Inverse Modellierung sucht nach Parametern der Quelle, welche die beobachtete Verschiebungsverteilung reproduzieren können. Ferner habe ich anhand der ermittelten Verschiebungsverteilung aus InSAR in Verbindung mit der Morphologie aus Luftaufnahmen das Volumen der untersuchten Erdrutsche empirisch abgeleitet. Ich habe eine Volumenformel für unseren Fall angepasst, und die verfügbaren Datensätze bezüglich Seismizität und Niederschlag kombiniert, um potenzielle auslösende Faktoren zu analysieren. Eine leitende Frage hierbei war: Was sind die Ursachen für die Beschleunigung von Erdrutschen, wie sie in den InSAR Daten beobachtet werden konnte? Das Untersuchungsgebiet in Zentral Georgien ist seismisch sehr aktiv. Als zusätzlichen Produkt der InSAR Datenanalyse wurde ein Deformationsgebiet gefunden, welches im Zusammenhang mit dem Mw=6.0 Erdbeben vom 7. September 2009 zusammenhängt. Beweise für Oberflächenbrüche, die direkt mit dem Erdbeben zusammenhängen, konnten in dem Gebiet nicht gefunden werden, jedoch konnten während und nach dem Erdbeben neue Erdrutsche beobachtet werden. Die Dissertation unterstreicht, dass Verformungsinformationen aus InSAR Analysen helfen können ein Gebiet, welches von Erdbebeninduzierten Erdrutschen gefährdet ist, zu kartieren. Potenziell stellt InSAR eine Technik dar, die von Bedeutung für die landesweite Überwachung von Erdrutschen sein kann, insbesondere im Hinblick auf die neuen Satellitensensoren, die in den kommenden Jahren verfügbar sein werden.

Surface subsidence induced by mining is a source of risk to people, equipment and environment. It may also disrupt mining schedules and increase the cost of mine safety. To provide accurate assessment of the surface subsidence and its level of impact on mine production and environment, it is necessary to develop and introduce comprehensive subsidence monitoring systems. Current techniques for monitoring of surface deformation are usually based on classical survey principles. In general these techniques have disadvantages that limit their applicability: they follow point-by-point data collection techniques, they are relatively time-consuming and costly, they usually cover only a small area, they are not applicable for the monitoring of inaccessible areas and they are not able to collect data continuously.As a complementary or alternative technique, the thesis discusses the applicability of SAR interferometry for monitoring mining induced deformations. InSAR is a remote sensing technique that makes use of Synthetic Aperture Radar (SAR) observations to acquire change in terrain topography. In spite of the widespread application of the technique for monitoring large-scale deformations of the Earth crust, specific modifications are necessary for utilising the technology within a mining context. Limitations, such as difficulty to resolve deformation for a high gradient slope, difficulty to retrieve subsidence for localised highly dynamic ground movements and the unavailability of SAR images with the desired specifications restrict the potential to monitor high rate, localised mine subsidence on day-to-day basis.The secondary aim of the thesis is to present integration of InSAR and GIS in order to propose an optimum methodology for processing of InSAR data to determine mine subsidence. The presented research also involves detailed analysis of InSAR limitations. This in consequence has led to suggestions on how to improve current InSAR capability with respect to the mining needs.The thesis introduces a set of new GIS-based tools and methodologies that are integrated into a conventional InSAR processing technique, to further improve and facilitate application of InSAR in mining. The developed tools and techniques cover the three main stages of data processing (pre-processing, processing and postprocessing). The researcher tried to address InSAR.’s limitations associated with mining related applications and also to provide practical solutions to resolve these issues.

Estimation of biomass has high importance for economic, ecologic and climatic reasons due to the multiple ecosystem services offered by forested landscapes. Measurements that are taken in the field incur personal and economic costs. Nevertheless, biomass surveying based on remote sensing techniques offer efficiency thanks to covering large areas. The European Space Agency (ESA) Sentinel-1 satellite offers promising capabilities for above-ground biomass (AGB) estimation through synthetic aperture radar (SAR) based microwave remote sensing. In this study, experimental AGB estimations based on Sentinel-1 C-band data were produced over the Remingstorp estate (Västergötland County, Sweden) to analyze its performance over boreal productive forests. The obtained measurements were compared against reference values obtained by combining photogrammetric, aerial laser scanning (ALS) and field measurements. Thus, a reference high-resolution canopy height model (CHM) was produced from the difference between photogrammetric digital surface model (DSM) values and ALS digital terrain model (DTM) values. The comparison of CHM observations against diameter at breast height (DBH) field measurements revealed the existence of a vegetation height - vegetation volume relationship for the study species (Pinus Sylvestris and Picea Abbies), which allowed bole volume estimation based on vegetation height values. SAR-based AGB estimates were produced by defining statistical relationships between backscatter intensity and interferometric coherence measurements against reference CHM values. Additionally, evaluation of biomass estimation through interferometric (InSAR) height was possible by comparing against reference photogrammetric DSM. Backscatter signal saturation of C-band at low biomass volumes prevented quantification of biomass but permitted differentiation between forested and non-forested surfaces. Estimation of AGB through interferometric coherence was possible through modeling volumetric decorrelation, which on the contrary prevented biomass retrieval from InSAR height. Due to the given frequency properties at C-band, HV cross-polarized channel was used in all cases for better detection of the canopy layer. Image acquisition under stable conditions was a priority to avoid noise derived from variable dielectric properties, acquisition geometry effects and temporal decorrelation. Hence, image acquisitions under stable hydrometeorological conditions (i. e. stable frozen or dry) and for the lowest repeat-pass interval (i. e. 6-days) were prioritized.

Over the last two decades, Slow Slip Events (SSEs) have been observed across many subduction zones, primarily through continuous GNSS networks. SSEs represent shearing of two tectonic plates, at much slower rates than earthquakes but more rapidly than plate motion. They are not dangerous in themselves, but change the stress field and can potentially trigger devastating earthquakes. While highly valuable, GNSS networks at most locations lack the spatial-resolution required to describe the spatial extent of the slow slip at depth. A better constraint of slow slip at depth in combination with other observations from seismology could be essential in addressing key research questions. These include: “Why do slow slip events occurs in some regions and not others?”, “What drives slow slip events?”, “Do slow slip events delay the occurrence of devastating earthquakes?”, and “Can slow slip events trigger devastating earthquakes?”. Interferometric Synthetic Aperture Radar (InSAR) is an established and attractive technique to study surface displacements at high-spatial resolution. Until now, InSAR has not been fully exploited for the study of SSEs. Here, I provide the necessary InSAR methodology, and further demonstrate the use of InSAR for static and time-dependant slow slip modelling. My developments have a direct benefit for various other applications such as earthquake cycle processes. I Specifically address the following two challenges which limit the wide uptake of InSAR: (1) Decorrelation noise introduced by changing backscattering properties of the surface and a change in satellite acquisition geometry, making it difficult to correctly unwrap meaningful signal. I address this problem by applying existing advanced time-series InSAR processing methods. (2) Atmospheric delays masking the smaller slow slip signal. These are mainly due to spatial and temporal variations in pressure, temperature, and relative humidity in the lower part of the troposphere, which result in an apparent signal in the InSAR data. Different tropospheric correction methods exist, all with their own limitations. Auxiliary data methods often lack the spatial and temporal resolution, while the phase-based methods cannot account for a spatially-varying troposphere. In response, I develop a phase-based power-law representation of tropospheric delay that can be applied in the presence of deformation and which accounts for spatial variation of tropospheric properties. I demonstrate its application over Mexico, where it reduces tropospheric signals both locally (on average by ~0.45 cm for each kilometer of elevation) and the long wavelength components. Moreover, I provide to the research community a Toolbox for Reducing Atmospheric InSAR Noise (TRAIN), which includes all the state-of-the-art correction methods, implemented as opensource matlab routines. When comparing these methods, I find spectrometers give the largest reduction in tropospheric noise, but are limited to cloud-free and daylight acquisitions. I also find that all correction methods perform ~10-20% worse when there is cloud cover. As all methods have their own limitations, future efforts should aim at combining the different correction methods in an optimal manner. Additionally, I apply my InSAR methodology and power-law correction method to the study of the 2006 Guerrero SSE, where I jointly invert cumulative GNSS and InSAR SSE surface displacements. In Guerrero, SSEs have been observed in a “seismic gap”, where no earthquakes have occurred since 1911, accumulating a seismic potential of Mw 8.0-8.4. I find slow slip enters the seismogenic zone and the Guerrero Gap, with ~5 cm slip reaching depths as shallow as 12 km, and where the spatial extent of the slow slip collocates on the interface with a highly coupled inter-SSE region as found from an GNSS study. In addition, slow slip decreased the total accumulated moment since the previous SSE (4.7 years earlier) by ~50% Over time and while accounting for SSEs, the moment deficit in the Guerrero Gap increases each year by Mw ~6.8. Therefore I find that the Guerrero Gap still has the potential for a large earthquake, with a seismic potential of Mw ~8.15 accumulated over the last century. Finally, I show the application to use InSAR for time-dependant slow slip modelling. From a simulation of the 2006 SSE, I demonstrate that InSAR is able to provide valuable information to constrain the spatial extent of the slow slip signal. With a future perspective of continued high repeat acquisitions of various SAR platforms, my expansion of the Network Inversion Filter with InSAR will become a powerful tool for investigating the spatio-temporal correlation between slow slip and other phenomena such as non volcanic tremor. Moreover, this approach can apply to earthquake cycle processes. Studying the broader earthquake cycle will further our knowledge of seismic hazard and increase our resilience to such events.

Australia is one of the leading mineral resource extraction nations in the world. It is one of the world’s top producers of nickel, zinc, uranium, lithium, coal, gold, iron ore and silver. However, the complexity of the environmental issues and the potentially damaging consequences of mining have attracted public attention and political controversy. Other types of underground natural resource exploitation, such as ground water, gas or oil extractions, also cause severe land deformation on different scales in space and time. The subsidence due to underground mining and underground fluid extractions has the potential to impact on surface and near surface infrastructure; as well as water quality and quantity, that in turn has the potential to impact on threatened flora and fauna, and biodiversity conservation. Subsidence can also impact natural and cultural heritage. To date, most of land deformation monitoring is done using conventional surveying techniques, such as total stations, levelling, GPS, etc. These surveying techniques provide high precision in height at millimetre accuracy, but with the drawbacks of inefficiency and costliness (labour intensive and time consuming) when surveying over a large area. Radar interferometry is an imaging technique for measuring geodetic information of terrain. It exploits phase information of the backscattered radar signals from the ground surface to retrieve the altitude or displacements of the objects. It has been successfully applied in the areas of cartography, geodesy, land cover characterisation, mitigation of natural or man-made hazards, etc. The goal of this dissertation was to develop a system which integrated differential interferometric synthetic aperture radar (DInSAR), ground survey data and geographic information systems (GIS) as a whole to provide the land deformation maps for underground mining and water extraction activities. This system aimed to reinforce subsidence assessment processes and avoid or mitigate potential risks to lives, infrastructure and the natural environment. The selection of suitable interferometric pairs is limited to the spatial and temporal separations of the acquired SAR images as well as the characteristics of the site, e.g. slope of terrain, land cover, climate, etc. Interferometric pairs with good coherence were selected for further DInSAR analysis. The coherence analysis of both C- and L-band spaceborne SAR data was studied for sites in the State of New South Wales, Australia. The impact of the quality of the digital elevation models (DEM), used to remove the static topography in 2-pass DInSAR, were also analysed. This dissertation examined the quality of the DEM generated using aerial photogrammetry, InSAR, and airborne laser scanning (ALS) against field survey data. Kinematic and real-time kinematic GPS were introduced here as an efficient surveying method for collecting ground truth data for DEM validation. For mine subsidence monitoring, continuous DInSAR mine subsidence maps were generated using ERS-1/2, Radarsat-1 and JERS-1 data with the assumption of negligible horizontal displacement. One of the significant findings of this study was the results from the ERS-1/2 tandem DInSAR, which showed an immediate mine subsidence of 1cm occurred during a period of 24 hours. It also raised the importance of SAR constellations for disaster mitigation. In order to understand the 3-D displacement vectors of mine deformation, this dissertation also proposed a method using the SAR data acquired at 3 independent incidence angles from both ascending and descending orbits. Another issue of the high phase gradient, induced by the mine subsidence, was also addressed. Phase gradient was clearly overcome by having the L-band ALOS data with an imaging resolution of 10m, which is better than the imaging resolution of 18m of the previous generation of the Japanese L-band SAR satellite, JERS-1. The ground survey data over a similar duration was used for validation. Besides mine subsidence monitoring the land deformation caused by groundwater pumping were also presented. In contrast to mine subsidence, the underground water extraction induced subsidence has the characteristics of a slow rate of change and less predictable location and coverage. Two case studies were presented. One was at the geothermal fields in New Zealand and another was the urban subsidence due to underground water over exploitation in China. Both studies were validated against ground survey data. Finally, SAR intensity analysis for detecting land deformation was demonstrated when DInSAR was not applicable due to strong decorrelation. The region of land surface change, which may be caused by human activities or natural disasters, can be classified. Two cases studies were given. The first study was the surface change detection at an open-cut mine. The second one was the 2004 Asian tsunami damage assessment near Banda Aceh. The results presented in this dissertation showed that the integrated system of DInSAR, GIS and ground surveys has the potential to monitor mine subsidence over a large area. The accuracy of the derived subsidence maps can be further improved by having a shorter revisit cycle and better imaging resolution of the newly launched and planned SAR satellites and constellation missions. The subsidence caused by groundwater pumping can be monitored at an accuracy of millimetre by utilising the technique of persistent scatterer InSAR.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.
Includes bibliographical references (p. 127-130).
In this thesis, we deal primarily with the multi-baseline SAR configuration utilizing three satellites. Two applications of InSAR, multi-baseline height retrieval and multi-baseline compensation of CCD's slope biasing effects, are first examined in details. An optimal baseline-weighted height averaging technique is introduced. Phase averaging, a novel height retrieval technique, combines the multi-baseline phase data into one, such that only one set of heights is retrieved from the three-satellite configuration. This approach outperforms single baseline height retrieval and allows application of the conventional two-satellite height retrieval process on the multi-baseline data, without need for excessive modifications. Slope biasing effects, inherent in multilook coherence estimator, make it difficult to identify if low or medium coherence values are results of an actual scene change or an undulating terrain. This ambiguity can be best resolved by accounting for the topographic phase variations via prior knowledge of the original height profile, whose precise retrieval requires a multi-baseline satellite configuration. The three-satellite setup is then related to a realistic cartwheel configuration, where the resulting errors in the height retrieval and CCD process, due to the constant cartwheel rotation, are analyzed. It is found that baseline-weighted averaging becomes a necessary step for the correct and automated retrieval of heights while change detection works equally well when considering a realistic cartwheel setup, even though its performance becomes dependent on the cartwheel's start position. Lastly, errors in satellite positions are introduced and their impacts on height retrieval and CCD are studied.
(cont.) In CCD, it is shown that the effects of satellite position errors is minimal since in this case, only the local terrain profile rather than the absolute terrain matters. However, in height retrieval, small errors in the positions propagate into unacceptably large misalignments. Attempts to account for these errors without prior knowledge of any ground truths are also made, making use of cost minimization functions.
by Song Liang Chua.
S.M.

Interferometric Synthetic Aperture Radar (InSAR) is an established technique which has been applied to Earth surface displacement analysis and topographic reconstruction. Two complex coherent SAR acquisitions of the same scene are combined to form an interferogram from which surface displacement or terrain measurements are made. The similarities between both SAR signals is captured in the coherence and its magnitude is determined by the spatial separation between acquiring antennas and the changes (if any) to the physical characteristics of the scattering target in the duration between both SAR acquisitions. Both of these products derivable from the interferometric process have been applied in this study with the aim of enhancing monitoring and assessing changes in the coastal environment, with emphasis on the coastal geomorphology. A combination of remote sensing data acquired for Montrose Bay, NE Scotland, has been used to analyze changes to the geomorphology of the beach and dune system in terms of sediment volume analysis, erosion and accretion processes and shoreline changes over a short-term period of 4 years. The interferometric coherence was applied to detect changes to the dune morphology, which have been actively eroding at the southern flank of the Bay. The interferometric analysis presented in this thesis was based on SAR data acquired by the Sentinel-1 SAR antenna and the results demonstrated the limitations of the sensor for terrain mapping and DEM reconstruction. In addition, the significance of the vegetation on the interferometric coherence was demonstrated. However, the results have shown that temporal baseline remained a significant consideration in the application of interferometric coherence in highly dynamic environments such as the coastal environment.

Bibliography: p. 149-155.
This thesis examines the topic of Synthetic Aperture Radar Interferometry in a historical perspective, tracing its development from its beginnings in the 1960s up until May 1994. Applications are listed and airborne and spaceborne implementations reviewed. The underlying theory of interferometry is explained, including a discussion of error sources, and a simulation for point targets is documented to illustrate the interferometric processing steps. The application of the SASAR VHF SAR system to interferometric operation is examined analytically.

Dissertation (Ph.D. in Physical Oceanography)--Naval Postgraduate School, June 1990.
Dissertation supervisor: Thornton, E.B. "June 1990." Description based on title screen as viewed on 19 October 2009. DTIC Identifiers: INSAR (INTERFEROMETRIC SAR). Author(s) subject terms: Interferometric SAR, scene coherence time, 2D wavenumber spectra, surface currents. Includes bibliographical references (p. 192-198). Also available in print.

Approved for public release; distribution is unlimited
Snow accumulation is a significant factor for hydrological planning, flood prediction, trafficability, avalanche control, and numerical weather/climatological modeling. Current snow depth methods fall short of requirements. This research explores a new approach for determining snow depth using airborne interferometric synthetic aperture radar (InSAR). Digital elevation models (DEM) are produced for Snow Off and Snow On cases and differenced to determine elevation change from accumulated snow. Interferograms are produced using Multi-pass Single Look Complex airborne Ku-band SAR. Two approaches were attempted. The first is a classical method similar to spaceborne InSAR and relies on determining the baseline of the interferometric pair. The second used a perturbation method that isolates and compares high frequency terrain phase to elevation to generate a DEM. Manual snow depth measurements were taken to verify the results. The first method failed to obtain a valid baseline and therefore failed. The second method resulted in representative DEMs and average snow depth errors of -8cm, 95cm, -49cm, 176cm, 87cm, and 42cm for six SAR pairs respectively. Furthermore, Ku-band appeared to be a high enough frequency to avoid significant penetration of the snow. Results show that this technique has promise but still requires more research to refine its accuracy.

InSAR was used to remotely prospect for ground deformation and to map lava flows associated with eruptions at Nyamuragira and Nyiragongo volcanoes (DRC). Eleven ERS SAR scenes were obtained. Initial InSAR results revealed excellent interferometric coherence over barren lava surfaces, although coherence was limited over vegetated areas and on the steep upper slopes of the volcanoes. This resulted in isolated patches of coherence, which despite significant modifications to the processing technique, could not be bridged during the unwrapping of the interferograms. However, reliable results were achieved by processing the isolated areas separately. New areas of interferometric coherence enabled lava flows emplaced during the 2002 Nyiragongo, and 1998 and 2001 Nyamuragira eruptions to be identified and mapped in higher detail than was available in existing maps. Based on the mapped flow areas and assumed flow thicknesses, minimum estimates for the erupted volumes were found to be 22 x 10⁶ m³, 71 x 10⁶ m³ and 133 x 10⁶ m³, respectively. Previously undetected deformation signals were found over both long (years) and short (weeks) time-periods. A persistent and generally decreasing subsidence was observed in Nyamuragira’s NE flow field, and was attributed to post-emplacement cooling and densification of pre- 1997 lavas and associated substrate relaxation due to lava loading. Localised inflation and deflation signals were observed on Nyamuragira’s NE flanks and summit caldera, and were interpreted as reflecting the dynamics of shallow magma systems. Maximum deformation rates within Nyamuragira’s summit caldera were about five times greater than those recorded for the NE flanks. Inflation of Nyamuragira’s NW flanks was interpreted as being due to magma accumulation prior to the 2002 eruption.

Thesis (M.S.)--University of Missouri-Columbia, 2008.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on July 8, 2009) Includes bibliographical references.

L'objectif de cette thèse est d'exploiter le radar à ouverture synthétique (SAR) multiligne la caractérisation de la structure forestière et la surveillance de l'affaissement des sols. Dans le cas des zones forestières, les paramètres de la structure de la forêt tropicale sont dérivés par la tomographie SAR (TomoSAR). Pour les zones urbaines, la subsidence des sols est étudiée à l'aide des techniques d'interférométrie SAR (InSAR). TomoSAR et InSAR seront en utilisant des images SAR multi-lignes de base sur différents sites. Avant l'analyse tomographique, un algorithme d'étalonnage de phase est nécessaire pour compenser les résidus de phase qui altèrent les données et influent sur la mise au point des données multi-lignes de base. D'abord, une étude tomographique a été réalisée dans les forêts tropicales, où la caractérisation de la forêt a été évaluée à l'aide de la tomographie SAR en bandes L et P. Deuxièmement, différentes techniques InSAR ont été comparées en ce qui concerne leurs performances en matière de surveillance de la déformation de la surface de la Terre, en prenant le Liban comme étude de cas.La première partie de la thèse présente l'analyse TomoSAR dans la forêt tropicale du Gabon. Un examen des techniques d'étalonnage de phase utilisées sur les données TomoSAR est présenté. La formulation du problème commence par l'étalonnage de phase de la pile de données considérée comme l'entrée principale pour commencer avec les algorithmes de traitement des données SAR. Ainsi, les algorithmes d'étalonnage de phase proposés dans la littérature sont discutés. Deux des approches d'étalonnage de phase les plus importantes sont ensuite décrites et discutées en détail. Le potentiel des données TomoSAR en bande L pour caractériser la structure de la forêt tropicale est évalué. Le défi ici est la courte longueur d'onde des données en bande L (en comparaison à la bande P), et la possibilité de pénétrer dans la forêt tropicale jusqu'au sol. L'analyse tomographique est réalisée à partir des données UAVSAR de la bande L en campagne AfriSAR menée sur le parc Gabonais Lopé en Février 2016. Il a été constaté que TomoSAR en bande L est capable de pénétrer dans et à travers la canopée jusqu'au sol, ce qui a permis de détecter correctement les couches de la canopée et du sol.Ensuite, le suivi de la structure des forêts tropicales est traité à l’aide de la tomographie ROS en bandes L et P. Pour cela, une comparaison des profils TomoSAR en bandes L et P avec des données lidar du capteur (LVIS) est effectuée afin d'évaluer la capacité de TomoSAR à surveiller et à estimer les paramètres de la structure de la forêt tropicale pour une bonne gestion forestière et pour soutenir les missions spatiales sur la biomasse forestière. Les performances des bandes L et P pour la pénétration de la canopée sont évaluées pour déterminer l'emplacement du sol sous-jacent. En outre, les enregistrements 3D pour chaque configuration sont comparés en ce qui concerne leur capacité à dériver la structure verticale de la forêt.La deuxième partie de la thèse aborde l'utilisation des techniques InSAR dans la surveillance de la subsidence. L'idée est de diviser l'estimation des déformations de surface de la terre en deux étapes. La première étape consiste à utiliser la technique du maximum de vraissemblance pour traiter conjointement les diffuseurs permanets et les diffuseurs distribués afin d'obtenir les meilleures estimations possibles des phases interférométriques. Ensuite, la deuxième étape consiste à séparer les contributions aux phases interférométriques dues à la topographie de la scène et au champ de déformation causées par le bruit de décorrélation et les perturbations atmosphériques. Comme cas d'étude, une analyse approfondie des données INSAR est présentée sur le site Libanais. En s'appuyant sur un ensemble de données de 117 données satellitaires Sentinel-1 acquises sur le Liban entre 2015 et 2019, avec une résolution temporelle élevée (6 jours)
The objective of this thesis is to exploit Multi-baseline Synthetic Aperture Radar (SAR) for studying the remote sensing of natural scenarios, such as forest structure characterization and land subsidence monitoring. In the case of forested areas, tropical forest structure parameters are derived by Tomography SAR (TomoSAR) technique. For urban areas, Land subsidence is investigated through Interferometry SAR (InSAR) techniques. TomoSAR and InSAR will be treated by using Multi-baseline SAR images over different sites. Prior to tomographic analysis, a phase calibration algorithm is needed to compensate for phase residuals that corrupt the data and influence the focusing of Multi-baseline data. First, a tomographic study has carried out in tropical forest, where the forest characterization was assessed by using SAR tomography at L and P-band. Second, different InSAR techniques have been compared with respect to their performance in monitoring earth’s surface deformation, taking Lebanon as a case study.The first part of the thesis presents the TomoSAR analysis in the tropical forest. A review of phase calibration techniques employed on TomoSAR data is shown. The problem formulation starts with the phase calibration of the data stack that is considered as the main gate to begin with SAR processing algorithms. Thus, the main phase calibration algorithms proposed in the literature are discussed. Two of the most important phase calibration approaches are then described and discussed in detail. The potential of L-band TomoSAR data to characterize tropical forest structure is evaluated. The challenge here is the short wavelength of L-band data, and whether can penetrate tropical forests down to the ground. Tomographic analysis is carried out using L-band UAVSAR data from the AfriSAR campaign conducted over Gabon Lopé Park in February 2016. It was found that L-band TomoSAR was able to penetrate into and through the canopy down to the ground, and thus the canopy and ground layers were detected correctly. Then, monitoring tropical forest structure using SAR tomography at L- and P-band are treated. For this, a comparison of the P- and L-band TomoSAR profiles, Land Vegetation and Ice Sensor (LVIS), and discrete return LiDAR is provided in order to assess the ability for TomoSAR to monitoring and estimating the tropical forest structure parameters for enhanced forest management and to support biomass missions. The L- and P-band's performances for canopy penetration are assessed to determine the underlying ground locations. Additionally, the 3D records for each configuration are compared regarding their ability to derive forest vertical structure.The second part of the thesis tackle the utilization of InSAR techniques in land subsidence monitoring. The idea is to split the estimation of earth's surface deformations into two steps. The first step is to use Maximum Likelihood technique to jointly process Permanent scaterrers and Distributed scaterrers in order to yield the best estimates of interferometric phases. Then, the second step is to separate the contributions to the interferometric phases due to the scene topography and deformation field from those caused by decorrelation noise and atmospheric disturbances. As a case study, an extensive InSAR analysis of Lebanon site is shown, relying on a data-set of 117 Sentinel-1 satellite data acquired over Lebanon between 2015 and 2019, with high temporal resolution (i.e. 6 days)

Thesis (Ph. D.)--University of Nevada, Reno, 2008.
"August, 2008." Includes bibliographical references (leaves 140-147). Library also has microfilm. Ann Arbor, Mich. : ProQuest Information and Learning Company, [2008]. 1 microfilm reel ; 35 mm. Online version available on the World Wide Web. Library also has electronic version on CD-ROM

Time series analysis of Synthetic Aperture Radar Interferometry (InSAR) data has become an important scientific tool for monitoring and measuring the displacement of Earth’s surface due to a wide range of phenomena, including earthquakes, volcanoes,landslides, changes in ground water levels, and wetlands. Time series analysis is a product of interferometric phase measurements, which become ambiguous when the observed motion is larger than half of the radar wavelength. Thus, phase observations must first be unwrapped in order to obtain physically meaningful results. Persistent Scatterer Interferometry (PSI), Stanford Method for Persistent Scatterers (StaMPS), Short Baselines Interferometry (SBAS) and Small Temporal Baseline Subset (STBAS)algorithms solve for this ambiguity using a series of spatio-temporal unwrapping algorithms and filters. In this dissertation, I improve upon current phase unwrapping algorithms, and apply the PSI method to study subsidence in Mexico City. PSI was used to obtain unwrapped deformation rates in Mexico City (Chapter 3),where ground water withdrawal in excess of natural recharge causes subsurface, clay-rich sediments to compact. This study is based on 23 satellite SAR scenes acquired between January 2004 and July 2006. Time series analysis of the data reveals a maximum line-of-sight subsidence rate of 300mm/yr at a high enough resolution that individual subsidence rates for large buildings can be determined. Differential motion and related structural damage along an elevated metro rail was evident from the results. Comparison of PSI subsidence rates with data from permanent GPS stations indicate root mean square(RMS) agreement of 6.9 mm/yr, about the level expected based on joint data uncertainty.The Mexico City results suggest negligible recharge, implying continuing degradation and loss of the aquifer in the third largest metropolitan area in the world. Chapters 4 and 5 illustrate the link between time series analysis and three-dimensional (3-D) phase unwrapping. Chapter 4 focuses on the unwrapping path.Unwrapping algorithms can be divided into two groups, path-dependent and path-independent algorithms. Path-dependent algorithms use local unwrapping functions applied pixel-by-pixel to the dataset. In contrast, path-independent algorithms use global optimization methods such as least squares, and return a unique solution. However, when aliasing and noise are present, path-independent algorithms can underestimate the signal in some areas due to global fitting criteria. Path-dependent algorithms do not underestimate the signal, but, as the name implies, the unwrapping path can affect the result. Comparison between existing path algorithms and a newly developed algorithm based on Fisher information theory was conducted. Results indicate that Fisher information theory does indeed produce lower misfit results for most tested cases. Chapter 5 presents a new time series analysis method based on 3-D unwrapping of SAR data using extended Kalman filters. Existing methods for time series generation using InSAR data employ special filters to combine two-dimensional (2-D) spatial unwrapping with one-dimensional (1-D) temporal unwrapping results. The new method,however, combines observations in azimuth, range and time for repeat pass interferometry. Due to the pixel-by-pixel characteristic of the filter, the unwrapping path is selected based on a quality map. This unwrapping algorithm is the first application of extended Kalman filters to the 3-D unwrapping problem. Time series analyses of InSAR data are used in a variety of applications with different characteristics. Consequently, it is difficult to develop a single algorithm that can provide optimal results in all cases, given that different algorithms possess a unique set of strengths and weaknesses. Nonetheless, filter-based unwrapping algorithms such as the one presented in this dissertation have the capability of joining multiple observations into a uniform solution, which is becoming an important feature with continuously growing datasets.

Tropical forests are extremely important ecosystems which play a substantial role in the global carbon budget and are increasingly dominated by anthropogenic disturbance through deforestation and forest degradation, contributing to emissions of greenhouse gases to the atmosphere. There is an urgent need for forest monitoring over extensive and inaccessible tropical forest which can be best accomplished using spaceborne satellite data. Currently, two key processes are extremely challenging to monitor: forest degradation and post-disturbance re-growth. The thesis work focuses on these key processes by considering change indicators derived from radar remote sensing signal that arise from changes in forest structure. The problem is tackled by exploiting spaceborne Synthetic Aperture Radar (SAR) and Interferometric SAR (InSAR) observations, which can provide forest structural information while simultaneously being able to collect data independently of cloud cover, haze and daylight conditions which is a great advantage over the tropics. The main principle of the work is that a connection can be established between the forest structure distribution in space and signal variation (spatial statistics) within backscatter and Digital Surface Models (DSMs) provided by SAR. In turn, forest structure spatial characteristics and changes are used to map forest condition (intact or degraded) or disturbance. The innovative approach focuses on looking for textural patterns (and their changes) in radar observations, then connecting these patterns to the forest state through supporting evidence from expert knowledge and auxiliary remote sensing observations (e.g. high resolution optical, aerial photography or LiDAR). These patterns are descriptors of the forest structural characteristics in a statistical sense, but are not estimates of physical properties, such as above-ground biomass or canopy height. The thesis tests and develops methods using novel remote sensing technology (e.g. single-pass spaceborne InSAR) and modern image statistical analysis methods (wavelet-based space-scale analysis). The work is developed on an experimental basis and articulated in three test cases, each addressing a particular observational setting, analytical method and thematic context. The first paper deals with textural backscatter patterns (C-band ENVISAT ASAR and L-band ALOS PALSAR) in semi-deciduous closed forest in Cameroon. Analysis concludes that intact forest and degraded forest (arising from selective logging) are significantly different based on canopy structural properties when measured by wavelet based space-scale analysis. In this case, C-band data are more effective than longer wavelength L-band data. Such a result could be explained by the lower wave penetration into the forest volume at shorter wavelength, with the mechanism driving the differences between the two forest states arising from upper canopy heterogeneity. In the second paper, wavelet based space-scale analysis is also used to provide information on upper canopy structure. A DSM derived from TanDEM-X acquired in 2014 was used to discriminate primary lowland Dipterocarp forest, secondary forest, mixed-scrub and grassland in the Sungai Wain Protection Forest (East Kalimantan, Indonesian Borneo) which was affected by the 1997/1998 El Niño Southern Oscillation (ENSO). The Jeffries- Matusita separability of wavelet spectral measures of InSAR DSMs between primary and secondary forest was in some cases comparable to results achieved by high resolution LiDAR data. The third test case introduces a temporal component, with change detection aimed at detecting forest structure changes provided by differencing TanDEM-X DSMs acquired at two dates separated by one year (2012-2013) in the Republic of Congo. The method enables cancelling out the component due to terrain elevation which is constant between the two dates, and therefore the signal related to the forest structure change is provided. Object-based change detection successfully mapped a gradient of forest volume loss (deforestation/forest degradation) and forest volume gain (post-disturbance re-growth). Results indicate that the combination of InSAR observations and wavelet based space-scale analysis is the most promising way to measure differences in forest structure arising from forest fires. Equally, the process of forest degradation due to shifting cultivation and post-disturbance re-growth can be best detected using multiple InSAR observations. From the experiments conducted, single-pass InSAR appears to be the most promising remote sensing technology to detect forest structure changes, as it provides three-dimensional information and with no temporal decorrelation. This type of information is not available in optical remote sensing and only partially available (through a 2D mapping) in SAR backscatter. It is advised that future research or operational endeavours aimed at mapping and monitoring forest degradation/regrowth should take advantage of the only currently available high resolution spaceborne single-pass InSAR mission (TanDEM-X). Moreover, the results contribute to increase knowledge related to the role of SAR and InSAR for monitoring degraded forest and tracking the process of forest degradation which is a priority but still highly challenging to detect. In the future the techniques developed in the thesis work could be used to some extent to support REDD+ initiatives.

This thesis evaluates the potential for using line of sight returns and return signals from underneath a forest canopy using X-band, airborne synthetic aperture radar (SAR) tomography. Approximately 30% of the Earth’s land surface is covered by vegetation, therefore global digital elevation models (DEMs) contain a signal from the forest canopy and not the ground. By uncovering new techniques to find the ground signals, using data collected from airborne platforms as verification, such procedures could be applied to currently operational and future X-band, spaceborne systems with the aim of resolving much of the vegetation bias on an international scale. Data from three sources is presented; data collected from Selex ES’s SAR systems, the GOTCHA dataset and simulated data. Before carrying out tomography it is shown that SAR interferometry (InSAR) can successfully be applied to X-band, helicopter data. A scatterer defined as a candidate persistent scatterer (CPS) is introduced, where the pixels are stable and coherent over a matter of days. An algorithm for selecting CPSs is developed by exploiting sparsity and a novel choice of hard thresholding operator. Using simulated forestry and SAR information the effects of changing input parameters on the outcome of the tomographic profile is analysed. What is found in this study is that model simulations demonstrate that ground points can be detected if the platform motion is relatively stable and that temporal decorrelation over the forest volume is kept to a minimal. An understory can confuse the tomographic profile since less line of sight observations can be made. By combining line of sight observations alongside new tomography techniques on high resolution SAR data this thesis shows it is possible to detect ground scatterers, even at X-band.

Satellite geodesy plays an important role in earth observation. This dissertation presents three applications of satellite geodesy in environmental and climate change. Three satellite geodesy techniques are used: high-precision Global Positioning System (GPS), the Gravity Recovery and Climate Experiment (GRACE) and Interferometric Synthetic Aperture Radar (InSAR). In the first study, I use coastal uplift observed by GPS to study the annual changes in mass loss of the Greenland ice sheet. The data show both spatial and temporal variations of coastal ice mass loss and suggest that a combination of warm atmospheric and oceanic condition drove these variations. In the second study, I use GRACE monthly gravity change estimates to constrain recent freshwater flux from Greenland. The data show that Arctic freshwater flux started to increase rapidly in the mid-late 1990s, coincident with a decrease in the formation of dense Labrador Sea Water, a key component of the deep southward return flow od the Atlantic Meridional Overturning Circulation (AMOC). Recent freshening of the polar oceans may be reducing formation of Labrador Sea Water and hence may be weakening the AMOC. In the third study, I use InSAR to monitor ground deformation caused by CO2 injection at an enhanced oil recovery site in west Texas. Carbon capture and storage can reduce CO2 emitted from power plants, and is a promising way to mitigate anthropogenic warming. From 2007 to 2011, ~24 million tons of CO2 were sequestered in this field, causing up to 10 MPa pressure buildup in a reservoir at depth, and surface uplift up to 10 cm. This study suggests that surface displacement observed by InSAR is a cost-effective way to estimate reservoir pressure change and monitor the fate of injected fluids at waste disposal and CO2 injection sites.

With the advent of the first satellites for Earth Observation: Landsat-1 in July 1972 and ERS-1 in May 1991, the discipline of environmental remote sensing has become, over time, increasingly fundamental for the study of phenomena characterizing the planet Earth. The goal of environmental remote sensing is to perform detailed analyses and to monitor the temporal evolution of different physical phenomena, exploiting the mechanisms of interaction between the objects that are present in an observed scene and the electromagnetic radiation detected by sensors, placed at a distance from the scene, operating at different frequencies. The analyzed physical phenomena are those related to climate change, weather forecasts, global ocean circulation, greenhouse gas profiling, earthquakes, volcanic eruptions, soil subsidence, and the effects of rapid urbanization processes. Generally, remote sensing sensors are of two primary types: active and passive. Active sensors use their own source of electromagnetic radiation to illuminate and analyze an area of interest. An active sensor emits radiation in the direction of the area to be investigated and then detects and measures the radiation that is backscattered from the objects contained in that area. Passive sensors, on the other hand, detect natural electromagnetic radiation (e.g., from the Sun in the visible band and the Earth in the infrared and microwave bands) emitted or reflected by the object contained in the observed scene. The scientific community has dedicated many resources to developing techniques to estimate, study and analyze Earth’s geophysical parameters. These techniques differ for active and passive sensors because they depend strictly on the type of the measured physical quantity. In my P.h.D. work, inversion techniques for estimating Earth’s surface and atmosphere geophysical parameters will be addressed, emphasizing methods based on machine learning (ML). In particular, the study of cloud microphysics and the characterization of Earth’s surface changes phenomenon are the critical points of this work.

Les systèmes d’imagerie microonde suscitent un grand intérêt actuellement dans le domaine de la recherche, notamment pour des applications de sécurité (scanners corporels, vision à travers les murs, etc). Plusieurs techniques d’acquisition déjà existantes permettent d’optimiser l’ouverture rayonnante afin de garantir une bonne résolution sur l’image finale. Cependant, le verrou actuel des systèmes d’imagerie est de pouvoir atteindre un temps de rafraîchissement temps réel et d’adresser un grand nombre d’antennes. La majorité des systèmes actuels peinent à concilier la rapidité et la résolution, tout en garantissant une bonne sensibilité. Les travaux réalisés dans ce manuscrit visent à proposer une alternative aux systèmes existants en se basant sur des techniques de codage analogique des signaux d’antennes. Globalement, l’objectif est de minimiser le nombre de récepteurs sans affecter les performances. Les architectures proposées sont essentiellement basées sur le concept du Radar MIMO (pour les systèmes actifs) et du radiomètre à synthèse d’ouverture interférométrique ou SAIR (pour les systèmes passifs). Ces deux systèmes permettent de réduire considérablement le nombre d’antennes sans affecter la résolution de l’image, ce qui permet une première levée de contraintes. En sus, des composants compressifs entièrement passifs sont utilisés pour réduire le nombre de récepteurs des systèmes Radar MIMO et SAIR. Ces composants à diversité spatiale et fréquentielle présentent des fonctions de transfert orthogonales. Utilisés en émission, ils permettent un adressage simultané et indépendant des antennes du réseau. En réception, ils permettent de coder les signaux reçus par les antennes vers un nombre de voies RF considérablement réduit. En appliquant des techniques de décodage appropriées, les signaux reçus par chacune des antennes peuvent être estimées afin d’appliquer les algorithmes dédiés à la reconstruction de l’image. Ces composants offrent l’avantage de réduire fortement le nombre de voies RF tout en conservant la même ouverture rayonnante et en autorisant une acquisition simultanée des signaux. Des démonstrateurs laboratoires ont été réalisés en bande S afin de montrer une preuve de faisabilité des alternatives proposées. Enfin, les résultats obtenus ont fait l'objet d'une demande de brevet et un prototype d'imageur radiométrique à ondes millimétriques est en cours de prototypage dans le cadre du projet ANR-PIXEL
Microwave imaging systems are currently attracting great attention in the field of research, especially for security applications (body scanners, vision through walls, etc.). Several acquisition techniques already exist to optimize the antenna aperture in order to guarantee a good resolution on the final image. However, the current lock of imaging systems is to be able to achieve a real-time acquisition and address numerous antennas. Most of the current systems struggle to reconcile fast imaging and resolution while ensuring good sensitivity. The work carried out in this manuscript aims at proposing an alternative to the existing systems based on analog coding techniques of the antenna signals. Overall, the goal is to minimize the number of receivers without affecting performances. The proposed architectures are based essentially on the concept of the MIMO radar (for active systems) and the Synthetic Aperture Interferometric Radiometer or SAIR (for passive systems). These two systems allow a significant reduction of the number of antennas without affecting the resolution of the image, thus enabling a first lifting of constraints. In addition, passive compressive components are used to reduce the number of receivers in the MIMO Radar and the SAIR systems. These components with spatial and frequency diversity exhibit orthogonal transfer functions. Used in transmission, they allow simultaneous and independent addressing of each element of the antenna array. In reception, they allow the signals received by the antennas to be coded into a considerably reduced number of aggregate waveforms. By applying suitable decoding techniques, the signals received by each antenna can be estimated in order to apply imaging algorithms. These components offer the advantage of greatly reducing the number of RF channels while keeping the same number of antennas and allowing simultaneous acquisition of the signals. Laboratory demonstrators were carried out in S-band to demonstrate the feasibility of the proposed alternatives. Finally, the results obtained were the subject of a patent application and a prototype of a millimeter-wave radiometric imager is being developed in the framework of the ANR-PIXEL project

This work makes an attempt to explain the origin, features and potential applications of the elevation bias of the synthetic aperture radar interferometry (InSAR) datasets over areas covered by vegetation. The rapid development of radar-based remote sensing methods, such as synthetic aperture radar (SAR) and InSAR, has provided an alternative to the photogrammetry and LiDAR for determining the third dimension of topographic surfaces. The InSAR method has proved to be so effective and productive that it allowed, within eleven days of the space shuttle mission, for acquisition of data to develop a three-dimensional model of almost the entire land surface of our planet. This mission is known as the Shuttle Radar Topography Mission (SRTM). Scientists across the geosciences were able to access the great benefits of uniformity, high resolution and the most precise digital elevation model (DEM) of the Earth like never before for their a wide variety of scientific and practical inquiries. Unfortunately, InSAR elevations misrepresent the surface of the Earth in places where there is substantial vegetation cover. This is a systematic error of unknown, yet limited (by the vertical extension of vegetation) magnitude. Up to now, only a limited number of attempts to model this error source have been made. However, none offer a robust remedy, but rather partial or case-based solutions. More work in this area of research is needed as the number of airborne and space-based InSAR elevation models has been steadily increasing over the last few years, despite strong competition from LiDAR and optical methods. From another perspective, however, this elevation bias, termed here as the “biomass impenetrability”, creates a great opportunity to learn about the biomass. This may be achieved due to the fact that the impenetrability can be considered a collective response to a few factors originating in 3D space that encompass the outermost boundaries of vegetation. The biomass, presence in InSAR datasets or simply the biomass impenetrability, is the focus of this research. The report, presented in a sequence of sections, gradually introduces terminology, physical and mathematical fundamentals commonly used in describing the propagation of electromagnetic waves, including the Maxwell equations. The synthetic aperture radar (SAR) and InSAR as active remote sensing methods are summarised. In subsequent steps, the major InSAR data sources and data acquisition systems, past and present, are outlined. Various examples of the InSAR datasets, including the SRTM C- and X-band elevation products and INTERMAP Inc. IFSAR digital terrain/surface models (DTM/DSM), representing diverse test sites in the world are used to demonstrate the presence and/or magnitude of the biomass impenetrability in the context of different types of vegetation – usually forest. Also, results of investigations carried out by selected researchers on the elevation bias in InSAR datasets and their attempts at mathematical modelling are reviewed. In recent years, a few researchers have suggested that the magnitude of the biomass impenetrability is linked to gaps in the vegetation cover. Based on these hints, a mathematical model of the tree and the forest has been developed. Three types of gaps were identified; gaps in the landscape-scale forest areas (Type 1), e.g. forest fire scares and logging areas; a gap between three trees forming a triangle (Type 2), e.g. depending on the shape of tree crowns; and gaps within a tree itself (Type 3). Experiments have demonstrated that Type 1 gaps follow the power-law density distribution function. One of the most useful features of the power-law distributed phenomena is their scale-independent property. This property was also used to model Type 3 gaps (within the tree crown) by assuming that these gaps follow the same distribution as the Type 1 gaps. A hypothesis was formulated regarding the penetration depth of the radar waves within the canopy. It claims that the depth of penetration is simply related to the quantisation level of the radar backscattered signal. A higher level of bits per pixels allows for capturing weaker signals arriving from the lower levels of the tree crown. Assuming certain generic and simplified shapes of tree crowns including cone, paraboloid, sphere and spherical cap, it was possible to model analytically Type 2 gaps. The Monte Carlo simulation method was used to investigate relationships between the impenetrability and various configurations of a modelled forest. One of the most important findings is that impenetrability is largely explainable by the gaps between trees. A much less important role is played by the penetrability into the crown cover. Another important finding is that the impenetrability strongly correlates with the vegetation density. Using this feature, a method for vegetation density mapping called the mean maximum impenetrability (MMI) method is proposed. Unlike the traditional methods of forest inventories, the MMI method allows for a much more realistic inventory of vegetation cover, because it is able to capture an in situ or current situation on the ground, but not for areas that are nominally classified as a “forest-to-be”. The MMI method also allows for the mapping of landscape variation in the forest or vegetation density, which is a novel and exciting feature of the new 3D remote sensing (3DRS) technique. Besides the inventory-type applications, the MMI method can be used as a forest change detection method. For maximum effectiveness of the MMI method, an object-based change detection approach is preferred. A minimum requirement for the MMI method is a time-lapsed reference dataset in the form, for example, of an existing forest map of the area of interest, or a vegetation density map prepared using InSAR datasets. Preliminary tests aimed at finding a degree of correlation between the impenetrability and other types of passive and active remote sensing data sources, including TerraSAR-X, NDVI and PALSAR, proved that the method most sensitive to vegetation density was the Japanese PALSAR - L-band SAR system. Unfortunately, PALSAR backscattered signals become very noisy for impenetrability below 15 m. This means that PALSAR has severe limitations for low loadings of the biomass per unit area. The proposed applications of the InSAR data will remain indispensable wherever cloud cover obscures the sky in a persistent manner, which makes suitable optical data acquisition extremely time-consuming or nearly impossible. A limitation of the MMI method is due to the fact that the impenetrability is calculated using a reference DTM, which must be available beforehand. In many countries around the world, appropriate quality DTMs are still unavailable. A possible solution to this obstacle is to use a DEM that was derived using P-band InSAR elevations or LiDAR. It must be noted, however, that in many cases, two InSAR datasets separated by time of the same area are sufficient for forest change detection or similar applications.

天津是中國遭受地面沉降最嚴重的城市之一。由於經濟與城市化的快速發展，新的沉降中心陸續出現在天津的郊區城鎮。本文結合L-和X-波段合成孔徑雷達(Synthetic Aperture Radar, SAR)資料，利用雷達干涉測量(SAR Interferometry, InSAR)時間序列分析，旨在加強天津郊區的沉降監測能力。先進的基於SAR資料的遙感技術，永久散射體干涉測量(Permanent Scatterers, PS)技術被證明是一種有效的，大範圍的，低成本的沉降監測手段。
工作在X波段(波長為3.1cm)的TerraSAR (TSX)衛星可以提供新一代具有高解析度(1米)和短重放週期(11天)的SAR資料，從而能夠更快的獲取適用於干涉的時間序列的資料，並且適用於單個建築物的沉降觀測。然而，利用X-波段在森林或植被覆蓋區域並不能得到有效資訊。ALOS衛星的SAR感測器工作在L波段，由於波長更長(波長為23cm)，穿透力更強，所以在植被覆蓋區域也具有良好的相干性。但是ALOS衛星的SAR資料解析度更低(7米)，重放週期更長(46天)。從這兩個波段的資料特徵來看，他們可以被認為是互補的。所以，結合這兩個波段的資料可以增強沉降監測的能力和提供更為可靠的結果。儘管ALOS衛星於2011年4月22日停止了工作，我們的研究結果仍然可以為結合不同波段的SAR資料進行沉降監測提供普遍適用的結論，並為以後的研究工作提供參考。
在研究中，我們提出了結合L和X波段的InSAR時間序列分析策略。此策略不僅可以作為X波段資料最優化獲取方案，而且可以成為快速，高精度，低成本，多級，大範圍監測策略。
其次，我們基於多時序SAR資料，利用PS和准PS(Quasi-PS, QPS)技術進行了L波段與X波段的沉降監測能力探尋。L波段和X波段的時間序列分析所得到的沉降模式有很好的吻合性，都監測出三個主要的沉降中心，其中包括一個新近發現的沉降中心位於南河鎮。
X波段的PS分析結果顯示出高密度的PS點，證實了它可以用於同時監測星狀分佈的多個城鎮。結果也表明了高解析度TSX資料可以監測到線狀地物如鐵路，高速公路以及電力線的細節資訊和沉降資訊，這些可以成為高解析度PS技術在中國的重要應用。
除此之外，我們利用水準資料驗證了L和X波段的處理結果，並且對地面沉降的過程進行了研究。由於水準資料和PS監測結果在時間和空間維上的採樣差別很大，所以我們對這兩者比較所具有的不確定性進行了詳細分析。結果表明了這兩種監測資料具有很好的一致性。
最後，我們發現在天津抽取地下水是引起地面沉降的一個主要原因。根據PS結果和地質資料，我們發現地質因素可能是另一個用於解釋沉降中心位置和形狀的原因。
The aim of this dissertation is to enhance the capability of monitoring subsidence in Tianjin suburbs by combining L- and X-band Synthetic Aperture Radar (SAR) data with Interferometry (InSAR) time series analysis. Tianjin is located in one of the major subsidence regions in China and several new subsiding centers have been found in the suburbs of Tianjin. Advanced remote sensing technique, Permanent Scatterers (PS) based on SAR data has been found to be a feasible way to detect and monitor wide area ground subsidence at a low cost.
TerraSAR X-band (TSX) of short wavelength (3.1 cm) provides new generation SAR data with high spatial resolution of 1 m and short revisit period of 11 days. It maintains the capability to fast build up interferometric stack, and to measure the subsidence of individual features, while almost no information can be detected with X-band in the forested and vegetated areas. ALOS L-band signal of longer wavelength (23cm) penetrates deeper into the vegetation cover and depicts higher coherence over non-urban areas, while the spatial resolution is relatively lower (7m) and revisit time is longer (46 days). The characteristics of these two bands can be regarded as complementary. Combining L- and X-band can enhance abilities of subsidence monitoring and provide more reliable results. Although ALOS died on April 22, 2011, this research work will provide general answers for combining different bands of SAR data to monitor subsidence, and give suggestions for future research work.
In this research work, we have developed the strategy of combining L- and X-band with InSAR time series analysis. This strategy can not only be an optimized X-band acquisition plan, but also be a multi-level wide area monitoring strategy of subsidence with fast extraction, high precision and low cost.
Moreover, with multi-temporal SAR data, we also investigate monitoring abilities of L- and X-band by exploring PS and Quasi-PS (QPS) techniques. The subsidence patterns derived from L- and X-band InSAR time series analysis are observed to have a good agreement. Three severe land subsidence zones were detected, containing one newly discovered subsiding center located in Nanhe Town.
The X-band PS analysis shows high density of PS points and confirms its strong ability for simultaneously monitoring subsidence over star-like-distributed multiple towns. The results also demonstrate that linear constructions such as railways, highways and power lines can be detected in detail with high resolution TSX SAR data and indicates the deformation monitoring capability for large-scale man-made linear features which is a key application in China.
Furthermore, L- and X-band results were independently validated with leveling data and ground motion processes were studied. The uncertainties were comprehensively analyzed between PS results and ground leveling data, whose densities are very different in both spatial and temporal domains. The overall results show a good agreement with each other.
Finally, we find that underground water extraction is one of the major reasons for ground subsidence in Tianjin. In addition, with the integrated analysis of the PS results and the geological data, we found that lithological characteristics may be another important reason to explain location and shape of the subsiding centers.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Luo, Qingli.
Thesis (Ph.D.)--Chinese University of Hong Kong, 2013.
Includes bibliographical references (leaves 103-112).
Abstract also in Chinese.
Abstract --- p.I
TABLE OF CONTENT --- p.VI
List of Figures --- p.VIII
List of Tables --- p.XI
List of abbreviations --- p.XII
ACKNOWLEDGEMENT --- p.XIV
Chapter 1 --- INTRODUCTION --- p.1
Chapter 1.1 --- Thesis contributions --- p.6
Chapter 1.2 --- Thesis structure --- p.7
Chapter 2 --- BACKGROUND --- p.9
Chapter 2.1 --- Synthetic Aperture Radar (SAR) --- p.9
Chapter 2.1.1 --- SAR imaging geometry --- p.9
Chapter 2.1.2 --- SAR satellites --- p.10
Chapter 2.2 --- Synthetic Aperture Radar Interferometry (InSAR) --- p.13
Chapter 2.2.1 --- Introduction --- p.13
Chapter 2.2.2 --- Principles of InSAR --- p.13
Chapter 2.3 --- Differential Synthetic Aperture Radar Interferometry (D-InSAR) --- p.18
Chapter 2.3.1 --- D-InSAR principle --- p.18
Chapter 2.3.2 --- The advantages and Limits of interferometric measurements --- p.21
Chapter 2.4.3 --- The development of PS technique --- p.22
Chapter 2.4 --- Persistent Scatterers Interferometry (PSI) --- p.24
Chapter 2.4.1 --- Permanent Scatterers (PS) Technique and Advantages --- p.24
Chapter 2.4.2 --- Principle of PS technique --- p.26
Chapter 2.5 --- QPS (Quasi-PS) Interferometry --- p.28
Chapter 3 --- MULTI IMAGES INSAR ANALYSIS OF TIANJIN --- p.31
Chapter 3.1 --- Introduction --- p.32
Chapter 3.2 --- Study area and SAR data --- p.34
Chapter 3.3 --- X-band optimized acquisition planning combing with L-band --- p.38
Chapter 3.3.1 --- The strategy --- p.38
Chapter 3.3.2 --- Experimental results and analyzes --- p.40
Chapter 3.4 --- Estimating deformation maps with L- and X-band --- p.45
Chapter 3.4.1 --- Monitoring subsidence over multiple towns and large man-made linear features with X-band --- p.45
Chapter 3.4.2 --- The L-band QPS Results --- p.56
Chapter 3.5 --- Conclusions --- p.58
Chapter 4 --- VALIDATION AND INTERPRETAION --- p.61
Chapter 4.1 --- Introduction --- p.61
Chapter 4.2 --- Validation --- p.61
Chapter 4.2.1 --- Leveling data --- p.61
Chapter 4.2.2 --- Uncertainties analysis --- p.64
Chapter 4.2.3 --- Average velocity comparison --- p.66
Chapter 4.2.4 --- Annual displacement comparison --- p.68
Chapter 4.2.5 --- Deformation time series: InSAR results and leveling --- p.70
Chapter 4.2.6 --- Average velocity map comparison between InSAR results and leveling --- p.71
Chapter 4.2.7 --- Displacement comparison between InSAR results and GNSS data --- p.73
Chapter 4.2.8 --- Average velocity comparison between ALOS results and leveling --- p.73
Chapter 4.3 --- Geological Interpretation --- p.74
Chapter 4.4 --- Field survey --- p.77
Chapter 4.5 --- QPS points analysis with aerophotograph --- p.81
Chapter 4.6 --- Conclusions --- p.84
Chapter 5 --- VALIDATION ALONG RAILWAY --- p.87
Chapter 5.1 --- Introduction --- p.87
Chapter 5.2 --- Study area --- p.87
Chapter 5.3 --- The validation plan --- p.87
Chapter 5.4 --- Validation with leveling data --- p.89
Chapter 5.4.1 --- Leveling data --- p.89
Chapter 5.4.2 --- The average subsidence rate comparison --- p.91
Chapter 5.4.3 --- The displacement comparison --- p.95
Chapter 5.5 --- Conclusions --- p.97
Chapter 6 --- SUMMARY --- p.98
The Publications --- p.102
REFERENCES --- p.103

Volcanic subsidence, caused by partial emptying of magma in the subsurface reservoir has long been observed by spaceborne radar interferometry. Monitoring long-term crustal deformation at the most notable type of volcanic subsidence, caldera, gives us insights of the spatial and hazard-related information of subsurface reservoir. Several subsiding calderas, such as volcanoes on the Galapagos islands have shown a complex ground deformation pattern, which is often composed of a broad deflation signal affecting the entire edifice and a localized subsidence signal focused within the caldera floor. Although numerical or analytical models with multiple reservoirs are proposed as the interpretation, geologically and geophysically evidenced ring structures in the subsurface are often ignored. Therefore, it is still debatable how deep mechanisms relate to the observed deformation patterns near the surface. We aim to understand what kind of activities can lead to the complex deformation. Using two complementary approaches, we study the three-dimensional geometry and kinematics of deflation processes evolving from initial subsidence to later collapse of calderas. Firstly, the analog experiments analyzed by structure-from-motion photogrammetry (SfM) and particle image velocimetry (PIV) helps us to relate the surface deformation to the in-depth structures. Secondly, the numerical modeling using boundary element method (BEM) simulates the characteristic deformation patterns caused by a sill-like source and a ring-fault. Our results show that the volcano-wide broad deflation is primarily caused by the emptying of the deep magma reservoir, whereas the localized deformation on the caldera floor is related to ring-faulting at a shallower depth. The architecture of the ring-fault to a large extent determines the deformation localization on the surface. Since series evidence for ring-faulting at several volcanoes are provided, we highlight that it is vital to include ring-fault activity in numerical or analytical deformation source formulation. Ignoring the process of ring-faulting in models by using multiple point sources for various magma reservoirs will result in erroneous, thus meaningless estimates of depth and volume change of the magmatic reservoir(s).

碩士
國立交通大學
電機與控制工程學系
86
This thesis proposes some improvement in unwrapping method of weighted least -square(WLS) , which need huge memory size and calculating time . Discussion about the weightings and minimal processing window size will be hold. Besides genetic algorithm (GA) was proposed to fix the inconsistencies of image that was called "residues" in branch-cuts method,so that make whole terrain continuous, and phase unwrapping will easy to go . Three methods:WLS, GA and branch-cuts method using average algorithm to processing bad bits will be examined to make a comparison on simulated terrain . Finally , combine the good of each method and take it to unwrap the whole real terain .

碩士
國立交通大學
控制工程系
85
An extension to the basic concept of correlation detection as a means of INSARimage registration is developed. To achieve sub- pixel accuracy, analysis approaches with different interpolation methods in different terrain relief are proposed. Numerical results from the process of some selected tie points in the INSAR image are included and compared. Then an appropriate mapping function is generated for the whole INSAR image. A sub- pixel resampled image is acquired by using a bilinear interpolation. Finally, conclusions are given to the determination of suitable process method on certain terrain relief.

Airborne SAR interferometry has the potential to provide topographic data with a precision of the order of one meter. However, to generate data accurate to this level it is essential to measure and compensate for the antenna baseline motion. Conventional motion compensation techniques and their errors are analyzed and extended to the two channel simultaneous imaging scenario of InSAR. An evaluation of the modelling is made using point target simulation and real motion and InSAR data. Phase compensation of both channels to the same reference track and compensation to two separate tracks are considered. The single track approach allows track segmentation to follow aircraft drifts without causing discontinuities in the differential phase, but is sensitive to range cell migration effects. The dual track approach is not sensitive to this but suffers from discontinuous differential phase at segmentation boundaries, which complicates the phase unwrapping process. A new formulation for each approach is presented that compensates for unknown terrain coupled with low frequency aircraft motion. In addition, a new approach that uses the dual track approach initially and then converts to a single reference track after compression is proposed. This realizes the benefits of both approaches with only a small increase in computation.

A time-domain backprojection processor for airborne synthetic aperture radar (SAR) has been developed at the University of Massachusetts’ Microwave Remote Sensing Lab (MIRSL). The aim of this work is to produce a SAR processor capable of addressing the motion compensation issues faced by frequency-domain processing algorithms, in order to create well focused SAR imagery suitable for interferometry. The time-domain backprojection algorithm inherently compensates for non-linear platform motion, dependent on the availability of accurate measurements of the motion. The implementation must manage the relatively high computational burden of the backprojection algorithm, which is done using modern graphics processing units (GPUs), programmed with NVIDIA’s CUDA language. An implementation of the Non-Equispaced Fast Fourier Transform (NERFFT) is used to enable efficient and accurate range interpolation as a critical step of the processing. The phase of time- domain processed imagery is dif erent than that of frequency-domain imagery, leading to a potentially different approach to interferometry. This general purpose SAR processor is designed to work with a novel, dual-frequency S- and Ka-band radar system developed at MIRSL as well as the UAVSAR instrument developed by NASA’s Jet Propulsion Laboratory. These instruments represent a wide range of SAR system parameters, ensuring the ability of the processor to work with most any airborne SAR. Results are presented from these two systems, showing good performance of the processor itself.

碩士
國防大學理工學院
空間科學碩士班
104
Radar is an active system to survey the surface of the earth. It means that it can broadcast the signal by itself and receive the reflected One. Therefore, it can work in night in order to overlap the shortage of optical technology. Based on high frequency of radar having great penetration, it can detect the information of the surface of the earth without the effect of atmosphere. In our research, we focus on where without ground control points or is difficult to arrive to build the DEM combined interferometry and data fusion. There provides the images from ALOS satellite which was launched by Japan Aerospace Exploration Agency in our research. The images were captured in the region of Taipei from 2008 to 2011. By thses images, we can do the interferometry synthetic aperture radar technique to make the digital elevation model. Although the temporary baseline, perpendicular baseline, atmosphere cause error, the results are still improved from 17.85m, 51.94m, 27.2m to 9.98m, 15.8m, 12.26m. Including all the fact, the method is developed the precision of digital elevation model without ground control point and overcome the low quality of these images.

Ground-based/terrestrial radar interferometry (GBRI) is a scientific topic of increasing interest in recent years. The GBRI is used in several field as remote sensing technique for monitoring natural environment (landslides, glacier, and mines) or infrastructures (bridges, towers). These sensors provide the displacement of targets by measuring the phase difference between sending and receiving radar signal. If the acquisition rate is enough the GBRI can provide the natural frequency, e.g. by calculating the Fourier transform of displacement. The research activity, presented in this thesis, concerns design and development of some advanced GBRI systems. These systems are related to the following issue: detection of displacement vector, Multiple Input Multiple Output (MIMO) and radars with 3D capability. The conventional GBRI measures only the component of displacement along range direction. A GBRI operating in monostatic and bistatic modality is presented in this thesis. The sensor detects the first component of displacement as the conventional GBRI (monostatic) and an additional component through a transponder (bistatic). The radar has been successfully tested in controlled environment using a basic transponder (two antennas and an amplifier). The transponder has been improved to increase the gain of the amplifier and to solve some issue of the basic version. Finally, the system is used in real application for measuring the natural axis of a telecommunication tower. The most advanced GRBI system can measure the directional of arrival of scattered signal by exploiting the movement of the antenna on an axis (Ground Based Synthetic Aperture Radar - GBSAR). The step between two position on the axis has to be smaller than a quarter of wavelength. The emerging Multiple Input Multiple Output (MIMO) technique can be used to reduce the mechanical movement parts and the problems related to these. Also, for MIMO radar the spacing between two closer phase center has to be smaller than a quarter of wavelength for the Shannon theorem. In this thesis a Compressive Sensing (CS) MIMO radar is described. Indeed, the CS is a technique able to reconstruct signal without the constrain of Shannon theorem. The signal has to be sparse and randomly sampled in order to use the CS. The CS technique can be applied for increase the scan-length of a MIMO system of $40%div50%$. Therefore, by using the same number of antennas, the CS allows to increase the angular resolution of a MIMO radar. A prototype of interferometric CS MIMO radar has been developed and tested on some bridges. The results were compared with a conventional GBRI with a good agreement. The CS MIMO radar was able to discriminate the left-right movement of bridges. Unfortunately, the repetition rate of this prototype was not enough to retrieve the spectra of natural frequency. Since the movement is along a single axis the obtained radar image does not have angular resolution in the plane orthogonal to the scan axis. In other words, if the radar head scans along the x-axis the radar image cannot have resolution in elevation angle. This is not a serious problem when the scenario is a slope, where the elevation (z-axis) can be reasonably considered an unambiguous function of the (x,y) position. Unfortunately, there are cases where the geometry of the structure under test is much more complex, i.e in urban environment. In this thesis two radar systems with three-dimensional resolution are reported. These two systems synthesize the two technique previously described. Indeed, the first sensor uses the bistatic principle by exploiting the movement of an additional antenna in vertical axis for obtaining the resolution in elevation. The second system exploits the movement on a horizontal axis of the CS MIMO with phase center positioned on a vertical axis. In order to test the capability, the two radars were located in an urban scenario in front of a 7-storey building. Both systems were able to provide a 3D image of the building.

This Ph.D. dissertation focuses on optimizing automated decision-making processes involving critical aspects of road management tasks. Specifically, the research aims to define and implement specific strategies for supplying support to decision-makers considering two leading elements: road maintenance and road safety. We propose some novel applications based on the integrated use of high-performance Non-Destructive Techniques (NDTs) and Geographical Information Systems (GISs) in order to obtain a “fully sensed” infrastructure, creating a multi-scale database concerning structural, geometrical, functional, social, and environmental characteristics. The environmental aspect is essential since climate change phenomena and extreme natural events are increasingly linked with infrastructure damage and serviceability; nonetheless, current Pavement Management Systems (PMSs) commonly rely solely on road pavement structural characteristics and surface functional performance. The high amount of collected data serves as input for calibrating different data-driven approaches, such as Machine Learning Algorithms (MLAs) and statistical regressions. Considering the aspect of road monitoring and maintenance, such models allow identifying the environmental factors that have the most significant impact on road damage and serviceability, as well as recognizing road sites with critical health conditions that need to be restored. Moreover, the calibrated MLAs enable decision-makers to determine the road maintenance interventions with higher priority. Considering road safety, the calibrated MLAs allow identifying the sites where serious road crashes can be triggered and estimating the crash count in a specified time frame. Moreover, it is possible to recognize infrastructure-related factors that significantly impact crash likelihood. Road authorities may consider the outcomes of the dissertation as a novel approach for drafting appropriate guidelines and defining more objective management programs.