[1910]'s elastic rebound model of the earthquake cycle (modified from [START_REF] Wright | Remote monitoring of the earthquake cycle using satellite radar interferometry[END_REF]). a) Map view of area spanning a hypothetical fault, in the instant after the last earthquake. b) The same area, in 250 years. The profile A-A', straight at the beginning of the cycle, has become curved. This is known as interseismic strain accumulation. c) The same area, 20 s later, after an earthquake. A-A' is once more a straight line, but this time with a 5 m step at the fault. B-B', straight immediately before the earthquake, is now curved with an offset of 5 m at the fault, decaying with large distances from the fault. ........... 4 Figure 2.1 : Phase simulations from [START_REF] Hooper | Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos[END_REF] measurements (blue squares [START_REF] Mimouni | Pollutions des eaux de la région d'Alger, leurs impacts sur l'environnement et les risques majeurs[END_REF]) in the study area. February 2004 Al Hoceima earthquakes [START_REF] Calvert | An integrated geophysical investigation of recent seismicity in the Al-Hoceima region of North Morocco[END_REF][START_REF] Bezzeghoud | Source parameters of the 1992 Melilla (Spain, Mw 4.8). 1994 Al Hoceima (Morocco, Mw 5.8) and 1994 Mascara (Algeria, Mw 5.7) earthquakes and seismotectonic implications[END_REF], whose epicenters are indicated by gray and black stars, respectively. Small black circles are M > 4 aftershocks from IGN with focal mechanism solutions from [START_REF] Buforn | Seismic sources on the Iberia-African plate boundary and their tectonic implications[END_REF] and [START_REF] Stich | Source analysis of the Mw 6.3 2004 Al Hoceima earthquake (Morocco) using regional apparent source time functions[END_REF]. Dashed rectangles are the frames of the Envisat radar images with arrows showing the flight direction of the satellite. The convergent plate boundary between Africa and Eurasia is depicted with a thick gray line in the inset map with arrows illustrating the direction and estimated rate (min. and max.) of convergence [START_REF] Nocquet | Geodetic measurements of crustal deformation in the Western Mediterranean and Europe[END_REF]. Red arrows indicate the recent GPS measurements [START_REF] Koulali | New GPS constraints on active deformation along the Africa-Iberia plate boundary[END_REF] [START_REF] Calvert | An integrated geophysical investigation of recent seismicity in the Al-Hoceima region of North Morocco[END_REF]Ait Brahim, Tadili, et al., 2004) with surface cracks and fissures observed after the 2004 event (redrawn from Ait Brahim, Nakhcha, et al., 2004). Thick white line is the surface trace of the modeled fault plane. . Figure 5.1 : a) Tectonic map of Turkey and surrounding regions with GPS vectors in a Eurasia fixed reference frame [START_REF] Reilinger | GPS constraints on continental deformation in the Africa-Arabia-Eurasia continental collision zone and implications for the dynamics of plate interactions[END_REF]. Rectangle shows the location of Figure 5.1b. b) Shaded SRTM topography map along the North Anatolian fault zone in northwestern Turkey with the recent rupture segments of large earthquakes [START_REF] Barka | Strike-slip fault geometry in Turkey and its influence on earthquake activity[END_REF][START_REF] Şaroğlu | Active Fault Map of Turkey, General Directorate of Mineral Research and Exploration[END_REF]. The dashed rectangles are the Envisat image frames with track numbers used in this study. ............................ Chapter I :

INTRODUCTION 2 1. INTRODUCTION
Understanding the mechanics of active faults is important for building reliable seismic hazard evaluations and better understanding of the earthquake physics and earthquake deformation cycle. The simplest form of the earthquake cycle was conceptualized by [START_REF] Reid | The mechanics of the earthquake: the California earthquake of 18 April, 1906[END_REF] and is referred to as elastic rebound theory (Figure 1.1), which was the first attempt on the earthquake surface deformation based on observations and field measurements. The idea was based on the cyclic buildup and release of elastic strain around faults, which is complemented by transient deformation at the Earth's surface. The earthquake cycle is typically split into three phases: rapid displacement that occurs during an earthquake is referred to as coseismic; it is followed by postseismic transient movements for years to decades, which is finally decays to a steady-state interseismic deformation for typically hundreds to thousands of years [e.g. [START_REF] Thatcher | A model for the earthquake cycle in underthrust zones[END_REF][START_REF] Wright | Remote monitoring of the earthquake cycle using satellite radar interferometry[END_REF][START_REF] Feigl | Geodetic observations of post-seismic transients in the context of the earthquake deformation cycle[END_REF]. In order to understand the fault behaviors and driving mechanisms behind the earthquakes and the interaction between them, it is necessary to examine the spatial and temporal evolution of the crustal deformation along active faults. Although, we do not have deformation observations with modern instruments spanning a complete earthquake cycle because of the long interseismic-event time in many fault zones, we can observe deformation around faults at different stages of the cycle by looking globally [START_REF] Wright | Earthquake cycle deformation and the Moho: Implications for the rheology of continental lithosphere[END_REF].

Crustal deformation observations by satellite geodesy have contributed significantly to our understanding of tectonics and earthquakes. Measurements of surface deformation are routinely used to constrain the subsurface geometry of active faults and the spatial distribution of coseismic, postseismic and aseismic slip. Recent advances in satellite geodesy, particularly in InSAR, have led to a dramatic improvement in the quantity and quality of deformation measurements of the earthquake cycle [e.g. [START_REF] Wright | Remote monitoring of the earthquake cycle using satellite radar interferometry[END_REF][START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF][START_REF] Peyret | Present-day interseismic surface deformation along the Longitudinal Valley, eastern Taiwan, from a PS-InSAR analysis of the ERS satellite archives[END_REF]Cakir et al., 2012]. Since its application to the 1992 Landers earthquake [START_REF] Massonet | The displacement field of the Landers earthquake mapped by radar interferometry[END_REF], the InSAR technique has been widely used for measuring the coseismic displacements associated with continental earthquakes [e.g. [START_REF] Cakir | Coseismic and early post-seismic slip associated with the 1999 Izmit earthquake (Turkey). from SAR interferometry and tectonic field observations[END_REF][START_REF] Sudhaus | Source model for the 1997 Zirkuh earthquake (MW=7.2) in Iran derived from JERS and ERS InSAR observations[END_REF], but also particularly valuable for examining and constraining postseismic [e.g. [START_REF] Ryder | Post-seismic motion following the 1997 Manyi (Tibet) earthquake: InSAR observations and modeling[END_REF][START_REF] Biggs | The postseismic response to the 2002 M 7.9 Denali Fault earthquake: constraints from InSAR 2003-2005[END_REF], interseismic [e.g. [START_REF] Wang | Interseismic slip rate of the northwestern Xianshuihe fault from InSAR data[END_REF]Cavalie et al., 2012] and asesmic slip [e.g. [START_REF] Cakir | Creeping along the Ismetpaşa section of the North Anatolian Fault (Western Turkey: Rate and extent from InSAR[END_REF][START_REF] Cakir | Onset of aseismic creep on major strike-slip faults[END_REF][START_REF] Champenois | Monitoring of active tectonic deformations in the Longitudinal Valley (Eastern Taiwan) using Persistent Scatterer InSAR method with ALOS PALSAR data[END_REF] deformation in several cases. The surface deformation associated with moderate-to-large size earthquakes (M > 6) is, however, very often hardly visible in the field since deformation occur on blind faults that do not produce a visible rupture on the earth surface (e.g., Al

Hoceima 2004, Mw 6.4 [START_REF] Cakir | Surface deformation associated with the Mw 6.4, 24 February 2004 Al Hoceima, Morocco, earthquake deduced from InSAR: implications for the active tectonics along North Africa[END_REF]; Ain Temouchent 1999, Mw 5.7 [Belabbes et al., 2009b]) or hidden faults beneath Quaternary deposits or offshore faults along the coastlines (e.g., Zemmouri 2003; Mw 6.8 [Belabbes et al., 2009],

Bam 2003, Mw 6.6 [START_REF] Funning | Surface displacements and source parameters of the 2003 Bam (Iran) earthquake from Envisat advanced synthetic aperture radar imagery[END_REF]). One of the utmost advantages of InSAR is its capability to monitor such tectonically complex zones and provide the surface field displacement (to the subtle scale) and related seismic rupture parameters.

Recent advanced InSAR techniques that can measure displacements with millimeterlevel accuracy reveal transient signals in the deformation fields produced by both moderate and large earthquakes.

Postseismic transient signals exhibit characteristic time scales ranging from

weeks to decades and distance scales from hundreds of meters to hundreds of kilometers. Geodetic measurements following numerous large earthquakes show that amplitudes of postseismic deformation are in general an order of magnitude smaller than coseismic deformation and decreases exponentially with time over a period of years to decades [START_REF] Schwartz | Slow slip events and seismic tremor at Circum-Pacific subduction zones[END_REF]. However, the postseismic contribution following moderate sized earthquakes has been inferred to exceed in some cases the coseismic deformation (e.g. M 6.0, 2004 Parkfield earthquake [START_REF] Freed | Afterslip (and only afterslip) following the 2004 Parkfield, California, earthquake[END_REF]). There are three mechanisms that have been proposed and widely used to explain postseismic deformation, which are (1) afterslip on the coseismic rupture plane [START_REF] Smith | Displacement on the San Andreas fault subsequent to the 1966 Parkfield earthquake[END_REF], (2) visco-elastic relaxation in the lower crust/upper mantle [START_REF] Pollitz | Mobility of continental mantle: Evidence from postseismic geodetic observations following the 1992 Landers earthquake[END_REF], and (3) poro-elastic rebound [START_REF] Peltzer | Poro-elastic rebound along the Landers 1992 earthquake surface rupture[END_REF].

While in same cases only one mechanism is claimed to have operated [START_REF] Freed | Afterslip (and only afterslip) following the 2004 Parkfield, California, earthquake[END_REF],

several mechanisms are thought to contribute to postseismic deformation in others [START_REF] Hearn | Izmit earthquake postseismic deformation and dynamics of the North Anatolian Fault Zone[END_REF].

Fault creep, or aseismic slip on a fault plane, is thought to be an important component of the earthquake cycle [e.g. [START_REF] Tse | Crustal earthquake instability in relation to the depth variation of frictional slip properties[END_REF]. Although, the majority of active faults may be locked, accumulating strain over a long period of time (e.g., up to 300 years along a single segment of the North Anatolian fault; [START_REF] Barka | Slip distribution along the North Anatolian fault associated with the large earthquakes of the period 1939-1967[END_REF])

and releasing it abruptly during moderate-to-large earthquakes (Mw > 6), some faults slip freely, accumulating little or no strain and generating no significant earthquakes [START_REF] Steinbrugge | Creep on the San Andreas fault[END_REF][START_REF] Thatcher | Systematic inversion of geodetic data in central California[END_REF][START_REF] Burford | Slip on the San Andreas fault in central California from alignment array surveys[END_REF]Bürgmann et al., 2000]. Faults that exhibit surface creep can appear to be locked at shallow or mid crustal depths, but nevertheless episodically produce moderate earthquakes.

Examples of such partially locked faults include the Hayward fault [START_REF] Savage | Inferred depth of creep on the Hayward fault, central California[END_REF][START_REF] Schmidt | Distribution of aseismic slip-rate on the Hayward fault inferred from seismic and geodetic data[END_REF], the Superstition Hills fault [START_REF] Bilham | Surface slip subsequent to the 24 November 1987 Superstition Hills, California, earthquake monitored by digital creepmeters[END_REF][START_REF] Wei | A silent M4.8 event of October 3-6, 2006, on the Superstition Hills Fault, Southern California[END_REF], the Longitudinal Valley fault [START_REF] Champenois | Monitoring of active tectonic deformations in the Longitudinal Valley (Eastern Taiwan) using Persistent Scatterer InSAR method with ALOS PALSAR data[END_REF][START_REF] Thomas | Spatio temporal evolution of seismic and aseismic slip on the Longitudinal Valley Fault, Taiwan[END_REF] and the Ismetpaşa segment of the North Anatolian Fault [START_REF] Ambraseys | Some characteristic features of the Anatolian fault zone[END_REF][START_REF] Cakir | Creeping along the Ismetpaşa section of the North Anatolian Fault (Western Turkey: Rate and extent from InSAR[END_REF]. Knowledge of the extent and rate of aseismic creep on the fault plane is therefore critical for reliable assessment of seismic hazard as it effectively reduces the fault surface area capable of rupture in earthquakes. Its spatiotemporal variation along faults has also important implications for forecasting the timing, locations, and potential sizes of future earthquakes and for understanding the fault behavior [Bürgmann et al., 2000].

The possibility to study the spatial and temporal evolution of these slow crustal motions is a key issue with important implications in the understanding of the dynamics of the deformation phenomena. An effective way to study the temporal behavior is the generation of deformation time series. Recent InSAR time series approaches [e.g. [START_REF] Ferretti | Nonlinear subsidence rate estimation using Permanent Scatterers in Differential SAR Interferometry[END_REF][START_REF] Hooper | A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches[END_REF] are capable of mapping slow surface deformation, such as postseismic and aseismic slip, over time. These approaches have been successfully used to reveal slow crustal motions in several cases; for instance, postseismic deformation following the L'Aquila 2009, Mw 6.3, earthquake (Italy) [START_REF] Lanari | Surface displacements associated with the L'Aquila 2009 Mw 6.3 earthquake (central Italy): New evidence from SBAS-DInSAR time series analysis[END_REF], interseismic strain accumulation across the Gazikoy-Saros segment of the NAF (Turkey) [START_REF] Motagh | Strain accumulation across the Gazikoy-Saros segment of the North Anatolian Fault inferred from Persistent Scatterer Interferometry and GPS measurements[END_REF], and slow surface creep on NAF faults [START_REF] Cakir | InSAR velocity field across the North Anatolian Fault (eastern Turkey): Implications for the loading and release of interseismic strain accumulation[END_REF].

Due to aforementioned reasons throughout this dissertation study, the InSAR Chapter II :

METHODOLOGY 2. METHODOLOGY
InSAR is a powerful technique for measuring surface deformation because of the high spatial resolution achieved and the ability to acquire the data remotely.

While ground displacement due to many geophysical processes are now routinely calculated with conventional InSAR, mapping the subtle and slow surface deformation such as aseismic processes requires more sophisticated approaches than the classical differential InSAR method which is often limited by atmospheric errors and signal decorrelation. Advanced techniques increase the number of locations where a deformation signal can be extracted and reduce the associated error with regard to involve the simultaneous processing of multiple SAR acquisitions in time [START_REF] Ferretti | Nonlinear subsidence rate estimation using Permanent Scatterers in Differential SAR Interferometry[END_REF][START_REF] Ferretti | Permanent scatterers in SAR interferometry[END_REF]. Such advanced techniques are able to reduce the effects of noise and signal decorrelation due to atmospheric effects, digital elevation model (DEM) errors, and orbital inaccuracies [START_REF] Hooper | Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos[END_REF]. Compared to conventional InSAR, the advanced techniques generate time series of ground deformations for individual targets using multi-temporal stacks of SAR images with regard to these targets that have a constant echo over the time and that are called persistent scatterers (PS) [START_REF] Ferretti | Nonlinear subsidence rate estimation using Permanent Scatterers in Differential SAR Interferometry[END_REF][START_REF] Hooper | A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers[END_REF][START_REF] Kampes | Displacement parameter estimation using permanent scatterer interferometry[END_REF].

Currently there are two broad categories of algorithms for processing multiple acquisitions, persistent scatterer and small baseline approaches, which are optimized for different models of scattering. In this dissertation, ground displacements have been calculated using the StaMPS (Stanford Method for Persistent Scatterers) [START_REF] Hooper | Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos[END_REF][START_REF] Hooper | A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches[END_REF] software package. The StaMPS uses ROI_pac software [START_REF] Rosen | Updated repeat orbit interferometry package released[END_REF] for focusing the raw images, and DORIS software [START_REF] Kampes | Doris: the delft object-oriented radar interferometric software[END_REF] for calculating interferograms. The topographic phase contribution in the interferograms is removed using the SRTM 90m DEM data [START_REF] Farr | The Shuttle Radar Topography Mission[END_REF]. In this chapter, persistent scatterer (PSI) and small baseline (SBI) algorithms that have been applied in this dissertation will be generally described.

Persistent Scatterer InSAR (PSI)

The PSI method is an extension to the conventional InSAR techniques, which addresses both decorrelation and atmospheric problems. The decorrelation degree of radar signals depends on the distribution of scattering centers on the ground that contributes to a pixel. In a radar image, the reflected wave from a resolution element is the coherent sum of individual wavelets scattered by many discrete scatterers on the ground (Figure 2.1). If these scatterers move with respect to each other between satellite passes, the phase of the returning radar echo will vary in a random manner which leads to decorrelation (Figure 2.1a). In contrast, if one of the scatterers contributing to the pixel is much brighter than the background scatterers, the variance in the phase of the radar echo due to relative movement of the background scatterers will be reduced, and may be small enough to enable extraction of the underlying deformation signal (Figure 2.1b). The approach in which these pixels are identified and isolated, was first achieved for InSAR applications by [START_REF] Ferretti | Nonlinear subsidence rate estimation using Permanent Scatterers in Differential SAR Interferometry[END_REF][START_REF] Ferretti | Permanent scatterers in SAR interferometry[END_REF], with further improvements by [START_REF] Colesanti | SAR monitoring of progressive and seasonal ground deformation using the permanent scatterers technique[END_REF], and is referred to as Permanent Scatterers

Technique™ in their patented method. There are various PSI approaches that have since been developed [e.g., [START_REF] Adam | The development of a scientific permanent scatterer system[END_REF][START_REF] Crosetto | Deformation monitoring using remotely sensed radar interferometric data[END_REF][START_REF] Lyons | Fault creep along the southern San Andreas from interferometric synthetic aperture radar, permanent scat-terers, and stacking[END_REF][START_REF] Werner | Interferometric point target analysis for deformation mapping[END_REF][START_REF] Kampes | Displacement parameter estimation using permanent scatterer interferometry[END_REF][START_REF] Hooper | Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos[END_REF]Ketelaar et al., 2008]. In comparison, PS selection algorithms and deformation estimation methods are different in between these approaches. For many of these algorithms, initial sets of PS pixels are identified by analysis of their amplitude scintillations in a series of interferograms. Furthermore, these methods consider not only a PS pixel is characterized by a certain phase stability over time, but also its phase history must match an assumed model of how displacement varies with time [START_REF] Ferretti | Nonlinear subsidence rate estimation using Permanent Scatterers in Differential SAR Interferometry[END_REF][START_REF] Ferretti | Permanent scatterers in SAR interferometry[END_REF][START_REF] Adam | The development of a scientific permanent scatterer system[END_REF][START_REF] Lyons | Fault creep along the southern San Andreas from interferometric synthetic aperture radar, permanent scat-terers, and stacking[END_REF][START_REF] Werner | Interferometric point target analysis for deformation mapping[END_REF][START_REF] Kampes | Displacement parameter estimation using permanent scatterer interferometry[END_REF]. These algorithms have been very successful for urban areas that contain large numbers of man-made structures that tend to produce very efficient reflectors that dominate background scattering. Since these methods use a functional temporal model to identify PS pixels, approximate knowledge of how the deformation varies with time is required a priori. Commonly, deformation is assumed to be steady-state or periodic in nature, whereas the temporal nature of the deformation is usually one of the phenomena that we wish to detect. In comparison to these approaches, the StaMPS persistent scatterer approach is applicable in areas undergoing non-steady deformation, such as most volcanoes and aseismic slip, with no prior knowledge of the variations in deformation rate since it does not use any temporal deformation model in the PS identification step [START_REF] Hooper | Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos[END_REF]. It has been successfully used to reveal slow surface creep along the Longitudinal Valley (Eastern Taiwan) [START_REF] Champenois | Monitoring of active tectonic deformations in the Longitudinal Valley (Eastern Taiwan) using Persistent Scatterer InSAR method with ALOS PALSAR data[END_REF], and along the North Anatolian Fault (Turkey) at Izmit [START_REF] Cakir | Onset of aseismic creep on major strike-slip faults[END_REF] and Ismetpaşa [Cetin et al., 2014a].

There are four parts in StaMPS; interferogram formation, PS identification, PS selection and displacement estimation.

Interferogram formation:

In order to select PS pixels with StaMPS, 12 interferograms are usually sufficient instead of the least 25 interferograms relying on functional temporal model algorithms [START_REF] Colesanti | SAR monitoring of progressive and seasonal ground deformation using the permanent scatterers technique[END_REF]]. Suppose we form N single-look interferograms from N+1 images, all with respect to one "master" image (Figure 2.2a), which minimizes the sum decorrelation that is a product of four terms, dependent on temporal baseline (T), spatial perpendicular baseline ( ), Doppler centroid baseline (F DC ) and thermal noise [START_REF] Zebker | Decorrelation in interferometric radar echoes[END_REF]. The critical values are dependent on the data set, but typical values for the ERS satellites acquired in arid regions are = 5 years, = 1100 m and = 1380 Hz. We choose the master that maximizes total correlation, assuming a constant value for thermal correlation.

PS identification algorithm does not actually require that all interferograms are formed with respect to one master, only that all are coregistered to one master [START_REF] Hooper | Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos[END_REF]. Squint angle error is commonly avoided in conventional InSAR by processing both images to a common squint angle [START_REF] Hooper | Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos[END_REF].

Eventually, the position of every pixel is estimated in a geocoded reference frame using the orbital parameters and the DEM. Theoretically, our estimates of position could be improved using various parameters estimated during processing, but positional accuracy to within several meters is usually sufficient for the most deformation modeling purposes [START_REF] Hooper | Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos[END_REF].

PS identification:

We use both amplitude and phase analysis to estimate the PS probability for each pixel in the series of interferograms that we have formed. Although a PS pixel is defined by phase stability, there is a statistical relationship between amplitude stability and phase stability. For phase analysis, an initial selection of candidate pixels is made based on amplitude analysis using amplitude dispersion, , which is the ratio of the standard deviation of the amplitude over its mean defined by [START_REF] Ferretti | Permanent scatterers in SAR interferometry[END_REF]. For StaMPS, the threshold value of ≤ 0.4 reduces the data by an order of magnitude and includes most of the PS. Then the PS probability is refined using phase analysis in an iterative process. Finally, the PS probability is estimated for those PS pixels not included in the initial selection [START_REF] Hooper | Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos[END_REF].

PS selection:

We select PS candidates on the basis of their phase characteristics since PS are defined by phase stability. Current methods for selecting PS candidates rely on thresholding pixel amplitude dispersion with time [START_REF] Ferretti | Permanent scatterers in SAR interferometry[END_REF]. If signal to noise ratio (SNR) is high (>10), amplitude dispersion is an accurate proxy for phase standard deviation, which leads to pick bright PS, e.g., certain man-made structures.

However, the simple relationship between amplitude dispersion and phase stability breaks down for low SNR scatterers, and the method is no longer successful.

The StaMPS approach is to form interferograms and remove most of the topographic phase signature using a digital elevation model (DEM). The residual phase, , of the xth pixel in the ith topographically corrected interferogram can be written as the sum of 5 terms, where is the phase change due to movement of the pixel in the satellite line-ofsight (LOS) direction, is the phase equivalent of the difference in atmospheric retardation between passes, is the phase due to orbit inaccuracies, is the residual topographic phase due to error in the DEM and is the noise term due to variability in scattering from the pixel, thermal noise and coregistration errors. PS is defined as pixels where is small enough that it does not completely obscure the signal [START_REF] Hooper | A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers[END_REF]. Assuming values are small, is a measure of the phase stability of the pixel and hence an indicator of whether the pixel is a PS. Statistically, however, pixels with higher are more likely to be PS.

The final step is to select PS based on the calculated values of (2.4). Any pixel with random phase has a finite chance of having high and therefore we can only select in a probabilistic fashion. Therefore, [START_REF] Hooper | A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers[END_REF] described a threshold value that maximizes the number of real PS selected while keeping the fraction of random phase pixels selected (false positives) below a specified value, q. The probability density function (PDF) of for the data, , is a weighted sum of the PDF for the random phase pixels, , and the PDF for the non-random phase (PS) pixels, i.e.,

We want to find such that where , and are unknown. For low values (< 0.3), .

Assuming then that allows a conservative value of to be estimated and hence we can calculate .

Since the risk of false positives increases with increasing amplitude dispersion, the number of PS selected further by calculating is refined as a function of amplitude dispersion. For each PS candidate, the value of is used that corresponds to the amplitude dispersion of the candidate as the threshold value.

In order to exclude sideslopes, adjacent selected pixels are assumed to be dominated by the same scatterer, and discard all but the pixel with the highest value [START_REF] Hooper | Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos[END_REF].

Displacement estimation:

Once the most likely PS pixels are selected, their phase is corrected for DEM error by subtracting the estimated values of , where is the residual DEM error term due to uncertainty in our estimate of , including any spatially correlated DEM error.

In order to retrieve the phase due to deformation, , the phase must be unwrapped. In this analysis, the three-dimensional unwrapping algorithm described by [START_REF] Hooper | Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos[END_REF], two in space and one in time, is used to have more reliable results.

After unwrapping, several terms remain in equation (2.8), which mask .

Unlike

, the spatially correlated portion of these terms is assumed to be uncorrelated temporally. Thus, by high-pass filtering the unwrapped data in time then low-pass filtering in space, we are able to estimate the spatially correlated error (similar to [START_REF] Ferretti | Permanent scatterers in SAR interferometry[END_REF]). Subtracting this signal from the equation (2.8) leaves just and spatially uncorrelated error terms that can be modeled as noise.

The detailed processing procedure of PSI can be found at Hooper et al.

[ 2004, and 2007].

Small Baseline Processing (SBI)

The targets of SB methods are those pixels whose phases when filtered decorrelate little over short time intervals, referring to as slowly-decorrelating filtered phase (SDFP) pixels by [START_REF] Hooper | A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches[END_REF]. Standard SB approaches [START_REF] Berardino | A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms[END_REF][START_REF] Schmidt | Time dependent land uplift and subsidence in the Santa Clara valley, California, from a large interferometric synthetic aperture radar data set[END_REF] work with multi-looked and individually phase-unwrapped interferograms, which does not take advantage of two potential benefits provided by processing multiple acquisitions together. The first is the potential to process the data at the highest possible resolution, which enable identification of isolated SDFP pixels surrounded by completely decorrelated pixels.

The second is the ability to unwrap the phase more robustly in three dimensions.

StaMPS SBI approach operates on single-look images to identify single-look SDFP pixels directly, and uses a new statistical algorithm proposed by [START_REF] Hooper | A statistical-cost approach to unwrapping the phase of InSAR time series[END_REF] for three-dimensional unwrapping that is applicable to single-or multiple-master time series.

Small Baseline interferograms

In order to maximize the correlation of the produced interferograms, small baseline methods seek to minimize the perpendicular, temporal and Doppler baselines, which will limit spatial decorrelation effects and increase the number of observable ground points [START_REF] Berardino | A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms[END_REF][START_REF] Hooper | A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches[END_REF]. The data pairs used to produce interferograms are characterized by a small perpendicular baseline, while

ensuring that no isolated clusters are present in the network of image pairs (Figure 2.2b). In SBI analysis minimum 5 images are required, however, in practice typically more are necessary to provide the minimum correlation requirements. The recombination of the resampled SLC images from the PS processing are used to generate the interferograms by filtering in azimuth to exclude non-overlapping Doppler spectrum, and in range to reduce the effects of geometric decorrelation.

Geometric phase is estimated by orbital ephemerides and a DEM, and subtracted [START_REF] Hooper | A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches[END_REF].

SDFP pixel selection

An initial subset of pixels expecting to include almost all SDFP pixels is selected through amplitudes analysis. For Gaussian scatterer pixels, an indication of the phase stability is given by the amplitude difference dispersion, , which is the ratio of the standard deviation of the difference in amplitude between master and slave over the mean amplitude. This is similar to the amplitude dispersion index derived by [START_REF] Ferretti | Permanent scatterers in SAR interferometry[END_REF] for point scatterers. However, is a better estimate of phase stability in the case where spectral filtering has been applied. Note that although the same algorithm [START_REF] Hooper | Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos[END_REF] is used to select both PS and SDFP pixels, different sets of pixels are chosen as the algorithm is applied to different sets of interferograms i.e. single master with no spectral filtering vs.

multiple masters with spectral filtering. Details of processing procedure of SBI technique can be found at Hooper [2008].

Concluding Remarks

The advanced InSAR time series algorithms offer many advantages with respect to conventional InSAR regardless of the selected approach. First of all, atmospheric artifacts can be detected and filtered out due to their different space-time behavior with respect to the deformation signal [START_REF] Ferretti | Nonlinear subsidence rate estimation using Permanent Scatterers in Differential SAR Interferometry[END_REF][START_REF] Berardino | A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms[END_REF]. Second, topographic artifacts and unwrapping errors can be diminished using space-time data redundancy [START_REF] Pepe | On the extension of the minimum cost flow algorithm for phase unwrapping of multitemporal differential SAR interferograms[END_REF][START_REF] Hooper | Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos[END_REF]. Moreover, possible orbital errors can be effectively compensated using the measurements of a limited number of GPS stations [START_REF] Gourmelen | Interferometric synthetic aperture radar-GPS integration: Interseismic strain accumulation across the Hunter Mountain fault in the eastern California shear zone[END_REF]and references therein]. All these characteristics contribute to improve the measurement final precision up to about 1 mm/yr and 5 mm for determination of velocity maps and time series displacements, respectively [START_REF] Casu | A quantitative assessment of the SBAS algorithm performance for surface deformation retrieval from DInSAR data[END_REF][START_REF] Lanari | Application of the SBAS-DInSAR technique to fault creep: A case study of the Hayward fault, California, Remote Sens[END_REF].

On the other hand, there are limitations to the PSI method. StaMPS approach is the improved version of the method, which addresses these limitations and includes other minor adjustments to the method. The first limitation is the step to estimate spatially correlated terms depends on the assumed length scale of the correlation, which is fixed with a band-pass filtering method that adapts to any phase gradient present in the data itself. The second limitation is the phase unwrapping is implemented as a series of two-dimensional (2-D) problems, leading to artifacts in the unwrapped phase. Two algorithms are developed to solve the problem, the first being a true three-dimensional (3-D) algorithm and the second being a pseudo-3-D algorithm. The 3-D algorithm is only applicable where there are no multiple-cycle phase discontinuities and no 2-D closed-loop discontinuities. For other cases, the pseudo-3-D algorithm is applicable [START_REF] Hooper | Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcan Alcedo, Galapagos[END_REF][START_REF] Hooper | A statistical-cost approach to unwrapping the phase of InSAR time series[END_REF].

Regarding the main limitations of the SBI technique, the unwrapping errors and the unfiltered atmospheric artifacts characterize the main error sources in the deformation retrieval process. Indeed, they may affect the accuracy and the coherent pixel density of the obtained results. In addition, there are limitations related to the InSAR technology that is essentially based on SAR sensors operating at C-band. In this case, the coherence is essentially maintained only in urbanized and rocky areas.

The next generation sensors such as the ALOS-PALSAR system that operate at lower frequencies of the electromagnetic spectrum and in particular within the Lband (1.27 GHz frequency corresponding to a 23.6 cm wavelength) can play a key role in this context. Although, a sensitivity reduction in the displacement detection will be caused by the wavelength increase, a significant improvement of the coherence characteristics is also expected in the generated differential InSAR interferograms [START_REF] Lanari | Application of the SBAS-DInSAR technique to fault creep: A case study of the Hayward fault, California, Remote Sens[END_REF]. Furthermore, another promising element is the development of SAR sensor constellations such as the COSMO-SKYMED, TerraSAR-X and Sentinel that should allow a significant reduction in the SAR sensor revisit time with a drastic and positive impact on the temporal decorrelation phonemena.

In the following, through the analysis of a number of selected case studies within the African-Eurasian convergence zone, we use these advanced InSAR techniques to monitor and characterize the field displacements associated with the small-scale deformation along seismogenic faults. events. This seismic event is the largest continental thrust-slip earthquake of the last decade that can be studied with space geodesy in the Tell Atlas of northern Algeria.

POSTSEISMIC DEFORMATION FOLLOWING

Coseismic studies using InSAR, teleseismic data, coastal uplift and GPS measurements, combined with the mainshock and aftershock seismicity distribution revealed a N60º-65º trending fault rupture, dipping 40º to 50º SE and located offshore about 8-13 km from the coastline [START_REF] Delouis | Slip distribution of the 2003 Boumerdes-Zemmouri earthquake, Algeria, from teleseismic, GPS, and coastal uplift data[END_REF][START_REF] Meghraoui | Coastal uplift and thrust faulting associated with the Mw= 6.8 Zemmouri (Algeria) earthquake of 21 May, 2003[END_REF][START_REF] Ayadi | Zemmouri earthquake rupture zone (Mw 6.8, Algeria): Aftershocks sequence relocation and 3D velocity model[END_REF][START_REF] Mahsas | Shallow afterslip following the 2003 May 21, Mw= 6.9 Boumerdes earthquake, Algeria[END_REF]Belabbes et al., 2009].

Following the 2003 Zemmouri earthquake, the study of continuous GPS (CGPS) measurements at 6 benchmarks gave evidence of < 1 cm/yr postseismic deformation during 2.5 years [START_REF] Mahsas | Shallow afterslip following the 2003 May 21, Mw= 6.9 Boumerdes earthquake, Algeria[END_REF]. The CGPS data can be best explained with shallow rupture patches (<7.5-km-depth) with up to 30 cm afterslip, inferring Mw 6.3 cumulative seismic moment. In this study, in order to obtain a better picture of the postseismic surface deformation during a longer period of time

Seismotectonic Setting

The Tell Atlas of northern Algeria is the source of frequent large and moderate seismic events mostly with thrust fault mechanisms (Table 3.1), including

Zemmouri earthquake of 2003 revealed a comparable pattern of active deformation in agreement with the NNW-SSE to NW-SE convergence and transpressive tectonics along the Africa-Eurasia plate boundary [START_REF] Morel | Goringe-Alboran-Tell tectonic zone: A transpression system along the Africa-Eurasia plate boundary[END_REF][START_REF] Meghraoui | Active faulting and transpression tectonics along the plate boundary in North Africa[END_REF]. These seismogenic structures described with the E-W to NE-SW trending folds and en-echelon thrust faults results from 2 to 3 mm/yr shortening across the Tell Atlas during the late Quaternary [START_REF] Meghraoui | Earthquake-induced flooding and paleoseismicity of the El Asnam, Algeria, fault-related fold[END_REF],

which is comparable to the 4 to 6 mm/yr present day rate of convergence between Africa and Eurasia obtained from NUVEL-1A and global GPS solutions [START_REF] Nocquet | Geodetic measurements of crustal deformation in the Western Mediterranean and Europe[END_REF][START_REF] Serpelloni | Kinematics of the western Africa-Eurasia plate boundary from focal mechanisms and GPS data[END_REF]. In north-central Algeria, the dominant active tectonic structures are NE-SW to E-W trending Blida thrust and fold system to the south and ENE-WSW trending Sahel anticline to the north, which form the edges of the Mitidja Basin (Figure 3.1) [START_REF] Maouche | Active coastal thrusting and folding, and uplift rate of the Sahel Anticline and Zemmouri earthquake area (Tell Atlas, Algeria)[END_REF]. As illustrated by the mainshock rupture and aftershocks, the Zemmouri earthquake affected ~55 km-long shoreline and ~15 km-thick upper crustal structure of the eastern part of the Mitidja Basin and related Blida thrust and fold system [START_REF] Ayadi | Zemmouri earthquake rupture zone (Mw 6.8, Algeria): Aftershocks sequence relocation and 3D velocity model[END_REF]. A detailed study of the mainshock relocation [START_REF] Bounif | The 21 May 2003 Zemmouri (Algeria) earthquake Mw 6.8; relocation and aftershock sequence analysis[END_REF] and aftershock distribution using the tomography analysis reveals a NE-SW trending and 40º SE dipping fault rupture with two seismicity patches [START_REF] Ayadi | Zemmouri earthquake rupture zone (Mw 6.8, Algeria): Aftershocks sequence relocation and 3D velocity model[END_REF]. Analysis of body and surface waves of teleseismic records denotes 2.86 x 10 19 N m seismic moment and a ~15 s fault rupture with ~1 m surface slip, and 2.1 m maximum slip at depth with bilateral rupture propagation along two patches [START_REF] Delouis | Slip distribution of the 2003 Boumerdes-Zemmouri earthquake, Algeria, from teleseismic, GPS, and coastal uplift data[END_REF]. Also, the source models from body wave inversion suggest similar results pointing out the bilateral rupture propagation on a 60-km-long fault with two patches and 2.3 m maximum slip at depth [START_REF] Yagi | Source process of large and significant earthquakes in 2003[END_REF]. The geodetic studies (coastal uplift, GPS and InSAR) also point out two patches with up to 1 m of surface slip at SW of the earthquake rupture [START_REF] Semmane | Fault location and source process of the Boumerdes, Algeria, earthquake inferred from geodetic and strong motion data[END_REF][START_REF] Mahsas | Shallow afterslip following the 2003 May 21, Mw= 6.9 Boumerdes earthquake, Algeria[END_REF]Belabbes et al., 2009]. Seismic moment, mainshock location at depth and field observations suggest that the earthquake rupture did not reach to the surface along the coastline but likely offshore at the seafloor. Measurements of uplifted marine terraces along a 55-km-long coastline reveal an average ~0.5 m uplift with a max 0.75 m east of Boumerdes and a minimum of almost zero near Cap Djenet [START_REF] Meghraoui | Coastal uplift and thrust faulting associated with the Mw= 6.8 Zemmouri (Algeria) earthquake of 21 May, 2003[END_REF][START_REF] Maouche | Active coastal thrusting and folding, and uplift rate of the Sahel Anticline and Zemmouri earthquake area (Tell Atlas, Algeria)[END_REF]. The coastal deformation and rupture history associated with the aftershock distribution (Figure 3.1), representing a clear concentration on the SW patch suggest, however, a complex fault rupture likely resulting from several asperities along fault strike. Initial geodetic and seismicity studies [START_REF] Bounif | The 21 May 2003 Zemmouri (Algeria) earthquake Mw 6.8; relocation and aftershock sequence analysis[END_REF][START_REF] Meghraoui | Coastal uplift and thrust faulting associated with the Mw= 6.8 Zemmouri (Algeria) earthquake of 21 May, 2003[END_REF][START_REF] Delouis | Slip distribution of the 2003 Boumerdes-Zemmouri earthquake, Algeria, from teleseismic, GPS, and coastal uplift data[END_REF][START_REF] Yelles | Coseismic deformation of the Algerian Atlas mountains-Evidence from aftershocks of the 1980 El Asnam earthquake[END_REF][START_REF] Semmane | Fault location and source process of the Boumerdes, Algeria, earthquake inferred from geodetic and strong motion data[END_REF][START_REF] Alasset | The tsunami induced by the 2003 Zemmouri earthquake (Mw 6.9, Algeria); modeling and results[END_REF] imply the existence of a N54°-N70° striking and 40° to 50° SE dipping fault rupture with surface slip at 5 to 15 km offshore. The high-resolution swath bathymetry and seismic profiles of the continental slope offshore the 2003 earthquake area identify outcropping thrust fault and scarps located at ~20 and 32 km from the shoreline and infer a flat and ramp rupture geometry [Devercheres et al., 2005]. The moment tensor analysis obtained from broadband seismic records indicates a 25° SE dipping rupture suggesting a fault surface trace at 15 to 20 km offshore limited to the SW by a NNE trending transform fault and forms a step over with the Blida thrust system [Braunmiller and Bernardi, 2005].

InSAR Observations

A map of cumulative line-of-sight (LOS) deformation between 12-July-2003 and 18-September-2010 is obtained from a mean LOS velocity field calculated from 31 descending ENVISAT images covering the earthquake region and the Bay of [2008]. Afterslip taking place on the sections of high coseismic slip would otherwise produce uplift, and thus LOS range decrease, instead of LOS range increase observed in the earthquake region.

Modeling

Afterslip

In order to investigate to what extent a model of afterslip can explain the InSAR LOS velocity field together with the CGPS measurements of Mahsas et al.

[2008], inverse modeling has been performed utilizing the boundary element software, Poly3Dinv [START_REF] Thomas | Poly3D: A three-dimensional, polygonal element, displacement discontinuity boundary element computer program with applications[END_REF][START_REF] Maerten | Inverting for slip on three dimensional fault surfaces using angular dislocations[END_REF] that predicts surface displacements due to angular dislocations on triangular faults buried in a linearelastic and homogeneous, isotropic half-space with a damped least square minimization. Triangular boundary elements allows to reconstruct of a surface of any desired tipline shape fault models that better approximate 3D planar surfaces, avoiding gaps and overlaps that are inevitably encountered when modeling curved or segmented faults of varying strike with rectangular planes commonly used to model geodetic observations [START_REF] Maerten | Effects of local stress perturbation on secondary fault development[END_REF].

In our inversions, we use the model fault deduced by Belabbes et al. [2009] from coseismic SAR, GPS data, and coastal uplift measurements. It is a curved The estimated moment released for 7 years (2003 -2010) is 4.1 x 10 18 Nm (Mw = 6.34), ~28% higher than that estimated during the first 2.5 years [START_REF] Mahsas | Shallow afterslip following the 2003 May 21, Mw= 6.9 Boumerdes earthquake, Algeria[END_REF]. It increases to 4.6 x 10 18 Nm (Mw = 6.38), in the case of 0.3 smoothing factor. These estimates suggest that the cumulative postseismic moment release during 7 years is around 15 to 25% of the coseismic moment release estimated from seismology and geodesy [START_REF] Delouis | Slip distribution of the 2003 Boumerdes-Zemmouri earthquake, Algeria, from teleseismic, GPS, and coastal uplift data[END_REF]Belabbes et al., 2009].

Visco-elastic

A possibly noteworthy controlling factor of the postseismic deformation transients is the inelastic response of the Earth by time, since it consists of an elastic brittle upper crust and ductile visco-elastic lower crust and upper mantle. The theory of viscoelasticity assumes that the deformation initiates in elastic upper crust and expands to ductile lower crust up to upper mantle [START_REF] Nur | Postseismic viscoelastic rebound[END_REF][START_REF] Savage | Equivalent strike-slip earthquake cycles in half-space and lithosphere-asthenosphere earth models[END_REF]. In order to compute the visco-elastic relaxation, we used the numerical code developed by [START_REF] Wang | PSGRN/PSCMP-a new code for calculating co-and post-seismic deformation, geoid and gravity changes based on the viscoelastic-gravitational dislocation theory[END_REF]

Poro-elastic

Poro-elastic approaches estimate the near field pore pressure change that earthquake loads. In order to evaluate poro-elastic deformation, we computed the poro-elastic rebound signal by calculating the difference between the elastic deformation induced by the earthquake in undrained and drained crustal rocks. We used the coseismic model of the Belabbes et al., [2009] with the Poisson's ratio values for undrained (0.31) and drained (0.27) elastic parameters as suggested by [START_REF] Peltzer | Poro-elastic rebound along the Landers 1992 earthquake surface rupture[END_REF] for the 1992 Landers earthquake. The observed two-lobe pattern has been successfully reproduced by the poro-elastic model but with a much lower value of subsidence (i.e., maximum 5 mm) on the coastline. In the attempt of [START_REF] Lin | Stress transfer among en echelon and opposing thrusts and tear faults: Triggering caused by the 2003 Mw=6.9 Zemmouri, Algeria, earthquake[END_REF]. This also changes our perception of the seismic cycle characterization and suggests longer recurrence intervals for large earthquakes in the Algiers region.

The afterslip distribution is well constrained and appears to be the most significant mechanism of the postseismic deformation following the 2003 Zemmouri thrust earthquake since all the models with different factors of smoothing and weighting predict afterslip mostly at shallow depths. On the other hand, part of the postseismic deformation can be due to poro-elastic and/or visco-elastic relaxation in the lithosphere. Postseismic deformation of the Chi-Chi thrust earthquake (Mw 7.7) obtained from GPS measurements over a 15-month period are better explained by afterslip than viscoelastic relaxation [START_REF] Hsu | Temporal and spatial variations of post-seismic deformation following the 1999 Chi-Chi, Taiwan earthquake[END_REF]. In the Zemmouri earthquake, the visco-elastic relaxation model predicts the subsidence observed in the InSAR results. The model however fails to explain the horizontal motions observed with GPS and the two-lobe pattern observed by SBI. The visco-elastic contribution to the observed surface deformation remains unclear (Figure 3.9). On the other hand, the poro-elastic rebound is a fairly rapid response [START_REF] Riva | Viscoelastic relaxation and long-lasting after-slip following the 1997 Umbria-Marche (Central Italy) earthquakes[END_REF], and its contribution is likely to be small since the first SAR image was taken ~6 weeks after the earthquake (Figure 3.10).

Comparing the high-resolution of SBI time series and water level change measurements in the Mitidja basin shows that both are consistently decreasing with time, suggesting the subsidence is controlled by water level changes (Figure 3.4).

Although, the subsidence may be partly due to tectonic ground movements, their distinction is difficult due to the resolution and error range of the water level fluctuations. While the postseismic deformation in the Mitidja basin should be trivial since coseismic surface deformation was absent or negligible there [Belabbes et al., 2009], strong shaking during the coseismic activity may cause pre-existing fractures to open and rock sediments to dilate leading to a step like decrease in water level [START_REF] Wang | Earthquakes and Water[END_REF]. Moreover, precipitation, stream flows or human activities may add to the postseismic ground deformation in the alluvial basin.

Published paper from this chapter can be found in Appendix C. [START_REF] Bezzeghoud | Source parameters of the 1992 Melilla (Spain, Mw 4.8). 1994 Al Hoceima (Morocco, Mw 5.8) and 1994 Mascara (Algeria, Mw 5.7) earthquakes and seismotectonic implications[END_REF][START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF]. Although, several geophysical and geodetic studies have been performed since the earthquake [START_REF] Buforn | Seismic sources on the Iberia-African plate boundary and their tectonic implications[END_REF][START_REF] Stich | Source analysis of the Mw 6.3 2004 Al Hoceima earthquake (Morocco) using regional apparent source time functions[END_REF][START_REF] Cakir | Surface deformation associated with the Mw 6.4, 24 February 2004 Al Hoceima, Morocco, earthquake deduced from InSAR: implications for the active tectonics along North Africa[END_REF][START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF][START_REF] Biggs | Fault identification for buried strike-slip earthquakes using InSAR: The 1994 and 2004 Al Hoceima, Morocco earthquakes[END_REF][START_REF] Tahayt | The Al Hoceima (Morocco) earthquake of 24 February 2004, analysis and interpretation of data from ENVISAT ASAR and SPOT5 validated by ground-based observations[END_REF][START_REF] Van Der Woerd | The Al Hoceima Mw 6.4 earthquake of 24 February 2004 and its aftershocks sequence[END_REF], the source of the 2004 earthquake remains debated

COSEISMIC AND POSTSEISMIC

including key parameters such as fault geometry (e.g. number and location of broken fault segments), maximum slip and depth. Models of the 2004 earthquake based on InSAR data suggest different fault ruptures with mainly NW-SE trending planar or curved shaped right-lateral strike-slip fault [START_REF] Cakir | Surface deformation associated with the Mw 6.4, 24 February 2004 Al Hoceima, Morocco, earthquake deduced from InSAR: implications for the active tectonics along North Africa[END_REF][START_REF] Biggs | Fault identification for buried strike-slip earthquakes using InSAR: The 1994 and 2004 Al Hoceima, Morocco earthquakes[END_REF][START_REF] Tahayt | The Al Hoceima (Morocco) earthquake of 24 February 2004, analysis and interpretation of data from ENVISAT ASAR and SPOT5 validated by ground-based observations[END_REF], consistent with the aftershocks distribution on surface and at depth [START_REF] Tahayt | The Al Hoceima (Morocco) earthquake of 24 February 2004, analysis and interpretation of data from ENVISAT ASAR and SPOT5 validated by ground-based observations[END_REF][START_REF] Van Der Woerd | The Al Hoceima Mw 6.4 earthquake of 24 February 2004 and its aftershocks sequence[END_REF].

In this study, we analyze both the co-and post-seismic deformation associated with the 2004 earthquake on the Al Hoceima region using the InSAR technique.

InSAR time series calculated from Envisat ASAR images using small baseline approach by means of the Stanford Method of Persistent Scatterers (StaMPS) [START_REF] Hooper | A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches[END_REF] reveal the subtle ground movements between 2004 and 2010 in the same area where we observe the remarkable coseismic displacements. The SBI analysis shows up to 4 cm cumulative line-of-sight movement, towards and away from the satellite, in the same region of coseismic surface deformation, which is in good agreement with the right-lateral strike-slip motion. The spatial pattern of the postseismic deformation suggests that a revision of the coseismic fault model of [START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF] is necessary in the southern tip of the fault. On the basis of these new observations the coseismic model has been revised using the same data set (one ascending and one descending interferogram) used by [START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF]. We calculate various models to better understand the relationships between the coseismic and postseismic deformation, and to constrain the earthquake rupture geometry and related slip at depth. February 2004 Al Hoceima earthquakes [START_REF] Calvert | An integrated geophysical investigation of recent seismicity in the Al-Hoceima region of North Morocco[END_REF][START_REF] Bezzeghoud | Source parameters of the 1992 Melilla (Spain, Mw 4.8). 1994 Al Hoceima (Morocco, Mw 5.8) and 1994 Mascara (Algeria, Mw 5.7) earthquakes and seismotectonic implications[END_REF], whose epicenters are indicated by gray and black stars, respectively. Small black circles are M > 4 aftershocks from IGN with focal mechanism solutions from [START_REF] Buforn | Seismic sources on the Iberia-African plate boundary and their tectonic implications[END_REF] and [START_REF] Stich | Source analysis of the Mw 6.3 2004 Al Hoceima earthquake (Morocco) using regional apparent source time functions[END_REF]. Dashed rectangles are the frames of the Envisat radar images with arrows showing the flight direction of the satellite. The convergent plate boundary between Africa and Eurasia is depicted with a thick gray line in the inset map with arrows illustrating the direction and estimated rate (min. and max.) of convergence [START_REF] Nocquet | Geodetic measurements of crustal deformation in the Western Mediterranean and Europe[END_REF]. Red arrows indicate the recent GPS measurements [START_REF] Koulali | New GPS constraints on active deformation along the Africa-Iberia plate boundary[END_REF].

Seismotectonic Settings

The Rif Mountain range belongs to the E-W trending thrust-and-fold system of North Africa that results mainly from the convergent movements of Africa toward Eurasia (Iberia) during the Tertiary [START_REF] Morel | Goringe-Alboran-Tell tectonic zone: A transpression system along the Africa-Eurasia plate boundary[END_REF] [START_REF] Demets | Effects of recent revisions to the geomagnetic reversal time scale on estimates of current plate motions[END_REF][START_REF] Nocquet | Geodetic measurements of crustal deformation in the Western Mediterranean and Europe[END_REF]. Besides, recent GPS observations confirm the WNW-ESE oblique convergence between Africa and Iberia and associated rate in the Strait of Gibraltar (4.3±0.5 mm/yr along the N116ºE±6º direction) [Mc Clusky et al., 2003;[START_REF] Fernandes | Surface velocity field of the Ibero-Magrebian segment of the Eurasia-Nubia Plate boundary[END_REF][START_REF] Serpelloni | Strain accumulation across the Messina Straits and kinematics of Sicily and Calabria from GPS data and dislocation modeling[END_REF][START_REF] Vernant | Geodetic constraints on active tectonics of the Western Mediterranean: Implications for the kinematics and dynamics of the Nubia-Eurasia plate boundary zone[END_REF]. This oblique convergence is the driving force for the active deformation along the plate boundary;

however, the seismicity is considerably complex and varies significantly from east to west. Although the rate of seismicity might be correlated with the long-term rate (several ka) of convergence along the plate boundary, it is not evident to determine this rate only with short period of instrumental seismic records. While the 1994-2004

Al Hoceima seismic sequence and the recent seismicity imply that the Rif Mountain range is being deformed under a strike-slip tectonic regime [START_REF] Bezzeghoud | Source parameters of the 1992 Melilla (Spain, Mw 4.8). 1994 Al Hoceima (Morocco, Mw 5.8) and 1994 Mascara (Algeria, Mw 5.7) earthquakes and seismotectonic implications[END_REF], adjacent regions in Gulf of Cadiz to the west and northern Algeria to the east are subject to thrust faulting deformation [START_REF] Grimison | The Azores-Gibraltar plate boundary: focal mechanisms, depths of earthquakes and their tectonic implications[END_REF][START_REF] Morel | Goringe-Alboran-Tell tectonic zone: A transpression system along the Africa-Eurasia plate boundary[END_REF]. According to the kinematic model of transpression and block rotation in North Africa, the discrepancy between the shortening and convergence directions might reflect the oblique tectonics with interactions between thrust-related folding and strike-slip faulting along the plate boundary [START_REF] Meghraoui | Active faulting and transpression tectonics along the plate boundary in North Africa[END_REF]. Local and regional seismotectonic studies in North Africa have suggested that the active thrusts and strike-slip faulting are coeval, and that contractional tectonics are accompanied by right-lateral en echelon fold axes, basal decollements and dipslip geometries with imbricated structures in the upper crust [START_REF] Yielding | Active tectonics of the Algerian Atlas Mountains, evidence from aftershocks of the 1980 El Asnam earthquake[END_REF][START_REF] Meghraoui | Earthquake-induced flooding and paleoseismicity of the El Asnam, Algeria, fault-related fold[END_REF][START_REF] Meghraoui | Active faulting and transpression tectonics along the plate boundary in North Africa[END_REF]. Although trending clearly in NW-SE direction between Iberia and the Tell Atlas of Algeria, the recent GPS velocities (Figure 4.1 inset) illustrate a southwestward motion of the Rif and Betic domains relative to Nubia and Eurasia respectively [START_REF] Fernandes | Surface velocity field of the Ibero-Magrebian segment of the Eurasia-Nubia Plate boundary[END_REF][START_REF] Serpelloni | Strain accumulation across the Messina Straits and kinematics of Sicily and Calabria from GPS data and dislocation modeling[END_REF][START_REF] Pérouse | Active surface deformation and sub-lithospheric processes in the western Mediterranean constrained by numerical models[END_REF][START_REF] Koulali | New GPS constraints on active deformation along the Africa-Iberia plate boundary[END_REF]. They hypothesize that the unexpected velocity field in the Rif-Betic zone is the result of the combined effects of long-term northwest-southeast oblique convergence between the Eurasian and the Nubian plates; low rigidity of the Alboran Sea domain [START_REF] Ammar | The tectonic structure of the Alboran Margin of Morocco[END_REF];

and a south-southwest-directed horizontal traction applied beneath the External Rif which is due to the rollback of the delaminated African continental lithospheric mantle pulled by the sinking oceanic Western Mediterranean slab [START_REF] Fadil | Active tectonics of the western Mediterranean: Geodetic evidence for rollback of a delaminated subcontinental lithospheric slab beneath the Rif Mountains, Morocco[END_REF]. trending planar or curved shaped right-lateral strike-slip fault [START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF][START_REF] Cakir | Surface deformation associated with the Mw 6.4, 24 February 2004 Al Hoceima, Morocco, earthquake deduced from InSAR: implications for the active tectonics along North Africa[END_REF][START_REF] Biggs | Fault identification for buried strike-slip earthquakes using InSAR: The 1994 and 2004 Al Hoceima, Morocco earthquakes[END_REF]. On the contrary, [START_REF] Tahayt | The Al Hoceima (Morocco) earthquake of 24 February 2004, analysis and interpretation of data from ENVISAT ASAR and SPOT5 validated by ground-based observations[END_REF] et al., 1997;Ait Brahim, Tadili, et al., 2004) with surface cracks and fissures observed after the 2004 event (redrawn from Ait Brahim, Nakhcha, et al., 2004). Thick white line is the surface trace of the modeled fault plane. is approximately east-west motion (Figure D.1d). These simple components are not exact because the incidence angle varies across the swath, but the changes are gradual and have little effect on the short wavelength [START_REF] Fielding | Surface ruptures and building damage of the 2003 Bam, Iran, earthquake mapped by satellite synthetic aperture radar interferometric correlation[END_REF].

Neotectonic features of the

Consequently, the surface displacement in the Al Hoceima region where there is a common lobe between the ascending and descending interferograms must be overwhelmingly vertical (i.e., subsidence as is it shows range increase).

Postseismic InSAR data

Two sets of SAR data were used to analyze postseismic surface deformation using a time series approach, as applied to reveal slow surface creep along the North Anatolian Fault at Izmit (Turkey) faults [START_REF] Cakir | Onset of aseismic creep on major strike-slip faults[END_REF], postseismic deformation following the May 21, 2003 Zemmouri (Algeria) earthquake [START_REF] Cetin | Seven years of postseismic deformation following the 2003 Mw=6.8 Zemmouri earthquake (Algeria) from InSAR Time Series[END_REF], and interseismic surface deformation along the North Tabriz Fault [START_REF] Karimzadeh | Interseismic strain accumulation across the North Tabriz Fault (NW Iran) deduced from InSAR time series[END_REF]. InSAR time series calculated from Envisat ASAR images acquired in the ascending and descending modes using StaMPS software [START_REF] Hooper | A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches[END_REF], which reveal the subtle surface deformation in the Al Hoceima region associated with the 2004 earthquake. Orbital errors are estimated and removed from the mean line-ofsight velocity field with a best-fit bilinear ramp instead of using the StaMPS orbital error estimations. The detailed processing procedure for SBI technique can be found in Chapter 2.2.

We have analyzed 15 Envisat ASAR images on descending track (T280) between 06-June-2004 and 31-January-2010 covering the earthquake region (Figure 4.5). A map of cumulative line-of-sight deformation is obtained from a mean LOS velocity field calculated from 33 interferograms using SBI technique (Figure 4.5).

The time series of displacements on ascending track (T230) were calculated by [START_REF] Gonzalez | Study of the present-day tectonics and seismogenic sources of the Al-Hoceima region (Morocco) using GPS and MTInSAR[END_REF], using 33 differential interferograms from 15 Envisat ASAR images between 01-October-2003 and 01-August-2007 (Figure 4.5). The analysis of time series displacements on ascending track is based on adopted approach to [START_REF] Atzori | Postseismic displacement of the 1999 Athens earthquake retrieved by the Differential Interferometry by Synthetic Aperture Radar time series[END_REF] to minimize the effect of temporal smoothing and also the erroneous propagation of the coseismic signal over the pre-and post-seismic periods. Firstly, all SAR images have been co-registered to a common reference image (master image), and then all possible interferograms with small baselines (less than 300 meters) have been generated. Then, StaMPS/MTI [START_REF] Hooper | A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches[END_REF] has been run to solve for the unwrapped differential phases and to invert for the time series displacements (Figure D.1). Prior to that point, all parameters related to temporal smoothing have been selected below the maximum temporal sampling rate (typically, 35 days for Envisat and ERS). Once the time series of displacements has been generated, temporal filtering has been applied by splitting the time series into two subsets (pre-and post-earthquake), and temporally low-pass filtering with the same Gaussian type (sigma = 0.75 yr). No coseismic signal is allowed to propagate to pre-and post-seismic periods through this approach.

Modeling

In order to estimate what kind of fault geometry and slip distribution can explain both the co-and post-seismic LOS velocity fields, inverse modeling has been performed utilizing the boundary element software Poly3Dinv [START_REF] Thomas | Poly3D: A three-dimensional, polygonal element, displacement discontinuity boundary element computer program with applications[END_REF][START_REF] Maerten | Inverting for slip on three dimensional fault surfaces using angular dislocations[END_REF].

Modeling of coseismic deformation

The analysis of coseismic interferograms, benefiting from aftershocks and postseismic InSAR time series, provides significant information on the main characteristics and location of the 2004 earthquake rupture, which requires a revision in the southern tip of the fault according to these new observations. Since the modeled main fault must not crosscut the visible fringes [START_REF] Cakir | Surface deformation associated with the Mw 6.4, 24 February 2004 Al Hoceima, Morocco, earthquake deduced from InSAR: implications for the active tectonics along North Africa[END_REF] The slip distribution predicted by the model with a right-lateral slip is shown in Figure 4.9. It shows predominantly right-lateral displacements up to 2.2 m localized mostly at depths between 4 and 7 km on the southern section around the fault bend, similar to that of [START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF]. The southern section of the fault rupture is supplemented by reverse slip due to the restraining bend on the fault.

Furthermore, northern section of the fault suggests right-lateral slip with normal faulting, which is in good agreement with extensional faults seen in the region and aftershocks focal mechanisms. The inferred 5 x 10 18 Nm (equivalent of Mw 6.4) inversion also presents shallow afterslip mainly from 1-8 km depth complementing the coseismic slip. Figure 4.12 illustrates the residuals obtained after these inversions. Although models after inverting two data sets separately explain the main features of the postseismic displacement fields, the predicted slip distribution is rather different in the earthquake region. Furthermore, these models do not show a satisfactory fit to the data as they result in significant residuals in near field along the fault rupture, which might be probably due to triggered postseismic splay fault on the northern section of the fault as suggested previously by [START_REF] Cetin | Coseismic and postseismic deformation associated with the Mw=6.4 February 24, 2004 Al Hoceima earthquake (Morocco) from InSAR: Evidence for triggered postseismic slip on neighboring faults[END_REF] that is connected to the main rupture around the fault bend. Consequently, inversions with joint data sets show quite deteriorated residuals. Therefore, the two data sets are rather inconsistent with each other, which is evident in the velocity maps shown in

Discussion and Conclusion

Postseismic deformation associated with the 2004 Al Hoceima earthquake is documented using Envisat ASAR data from 2004 to 2010 in descending geometry and from 2004 to 2007 in ascending geometry. InSAR time series analysis has revealed postseismic LOS displacements up to 4 cm uplift and subsidence where a remarkable coseismic displacement was observed after the earthquake. The spatial pattern of the postseismic displacement fields and aftershocks distribution however required a revision in the southern tip of the fault of the coseismic fault rupture models proposed by previous studies [START_REF] Cakir | Surface deformation associated with the Mw 6.4, 24 February 2004 Al Hoceima, Morocco, earthquake deduced from InSAR: implications for the active tectonics along North Africa[END_REF][START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF][START_REF] Biggs | Fault identification for buried strike-slip earthquakes using InSAR: The 1994 and 2004 Al Hoceima, Morocco earthquakes[END_REF][START_REF] Gonzalez | Study of the present-day tectonics and seismogenic sources of the Al-Hoceima region (Morocco) using GPS and MTInSAR[END_REF]. The coseismic fault model has been revised using the same data set (one ascending and one descending interferogram) used in Cakir et al. [2006]. Remodeling of the coseismic interferograms suggests a fault geometry same as that of [START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF] in the northern section that is well constrained according to ascending interferogram, except its southernmost section where the postseismic surface deformation and aftershocks distribution require a bend or step to the left and a NW-SE trending planar segment after the bend. The model is predominated by right-lateral slip with normal faulting on main branches of the fault that is similar to that of [START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF], which is in good agreement with extensional faults seen in the region and aftershocks focal mechanisms [i.e., van der Woerd et al., 2014], and reverse faulting around the fault bend that is consistent with the restraining bend. Remodeling of the coseismic interferograms indicates a geodetic moment of 5 x 10 18 Nm (equivalent of Mw 6.4), which is in good agreement with those obtained from seismological observations [Ait Brahim et al., 2004a;[START_REF] Stich | Source analysis of the Mw 6.3 2004 Al Hoceima earthquake (Morocco) using regional apparent source time functions[END_REF], and InSAR studies [START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF][START_REF] Biggs | Fault identification for buried strike-slip earthquakes using InSAR: The 1994 and 2004 Al Hoceima, Morocco earthquakes[END_REF][START_REF] Cakir | Surface deformation associated with the Mw 6.4, 24 February 2004 Al Hoceima, Morocco, earthquake deduced from InSAR: implications for the active tectonics along North Africa[END_REF].

The elastic dislocation modeling of the postseismic LOS displacements indicates that postseismic deformation can be explained by shallow (< 8 km) afterslip with up to 0.3 m displacement mainly above the high slip patches of the coseismic slip as with 5.0 x 10 17 Nm (Mw 5.73) cumulative moment release. Afterslip can occur either up-dip or down-dip of the ruptured zone [START_REF] Smith | Displacement on the San Andreas fault subsequent to the 1966 Parkfield earthquake[END_REF][START_REF] Marone | On the mechanics of earthquake afterslip[END_REF][START_REF] Zweck | Three-dimensional elastic dislocation modeling of the postseismic response to the 1964 Alaska earthquake[END_REF][START_REF] Hsu | Frictional afterslip following the 2005 Nias-Simeulue earthquake, Sumatra[END_REF]. The coseismic slip deficit at the uppermost sections of the fault appears to be filled by the postseismic afterslip, inferring a complementary coseismic and postseismic slip as commonly observed for other moderate-large earthquakes [START_REF] Reilinger | Coseismic and Postseismic Fault Slip for the 17 August 1999, M=7.5, Izmit, Turkey Earthquake[END_REF][START_REF] Cetin | Seven years of postseismic deformation following the 2003 Mw=6.8 Zemmouri earthquake (Algeria) from InSAR Time Series[END_REF].

Additionally, the postseismic deformation requires further studies to explain the remaining residuals in the near field by the afterslip modeling, which might possibly be related with a triggered postseismic splay fault. Shallow moderate-to-large earthquakes in the Rif Mountain of northern Morocco expose postseismic deformation that may constitute a significant part in the earthquake cycle.

Aftershocks and postseismic deformation are the most common manifestations of stress relaxation following moderate-large earthquakes. Identifying the relation between aftershocks and postseismic deformation remains unclear. In some cases of large thrust earthquakes, it has been observed that the aftershocks and geodetic deformation follow the same temporal evolution [START_REF] Perfettini | Postseismic relaxation driven by brittle creep: A possible mechanism to reconcile geodetic measurements and the decay rate of aftershocks, application to the Chi-Chi earthquake, Taiwan[END_REF][START_REF] Perfettini | Geodetic displacements and aftershocks following the 2001 Mw = 8.4 Peru earthquake: Implications for the mechanics of the earthquake cycle along subduction zones[END_REF][START_REF] Hsu | Frictional afterslip following the 2005 Nias-Simeulue earthquake, Sumatra[END_REF]. This observation seems to hold also for the Mw 6.4, 2004 Al Hoceima earthquake (Figure 4.3). The Rif is subject to distributed strike-slip deformation via northeast-southwest and northwest-southeasttrending conjugate faults that is supported by strike-slip earthquakes and related aftershocks with left-and right-lateral kinematics. These conjugate faults including the 1994-2004 earthquake ruptures crosscut the thrust faults of the Rif illustrate that Quaternary strike-slip tectonics superimposed on Tertiary thrust-and -fold tectonics [START_REF] Meghraoui | Earthquake-induced flooding and paleoseismicity of the El Asnam, Algeria, fault-related fold[END_REF]. That active tectonics and related geomorphological features associated with strike-slip faults are not well developed on the landscape suggests that the Rif neotectonic regime is probably on its early stages, which can be interpreted as fragmentation of the Rif Mountain range result from a westward escape tectonics in the frame of the Africa-Eurasia (Iberia) collision tectonics.

In this study we present an interseismic velocity field mapped using the PSI time series technique [START_REF] Ferretti | Permanent scatterers in SAR interferometry[END_REF][START_REF] Hooper | A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers[END_REF] between 2003 and 2010 on two overlapping descending tracks of Envisat ASAR (C-band) satellite covering the NAF between 32.1°E and 34.3°E (Figure 5.1). We use the surface velocity field and provide for the first time a model of aseismic slip distribution on the fault using elastic half-space dislocations. Finally, we discuss the mechanism of aseismic creep, its initiation and the potential causes for its along-strike variation on the basis of creep rate variation and lithology along the fault.

InSAR Observations

We present interseismic velocity fields obtained from PSI analysis [START_REF] Hooper | A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers[END_REF], which has been successfully used to reveal slow surface creep along the Longitudinal Valley (Eastern Taiwan) [START_REF] Champenois | Monitoring of active tectonic deformations in the Longitudinal Valley (Eastern Taiwan) using Persistent Scatterer InSAR method with ALOS PALSAR data[END_REF] and the NAF faults [START_REF] Cakir | InSAR velocity field across the North Anatolian Fault (eastern Turkey): Implications for the loading and release of interseismic strain accumulation[END_REF]. Orbital errors are estimated and removed from the mean line-ofsight velocity field with a best-fit bilinear ramp. Velocity standard deviation maps, calculated by StaMPS using bootstrapping, reach a maximum of 2.4 mm/yr for two individual overlapping tracks (Figure E.1). The detailed processing procedure can be found in Chapter 2.1.

Surface velocity

We have analyzed 55 Envisat ASAR images on two descending and overlapping tracks (T479 and T207;

Estimation of creep rate and extent

In order to determine the surface creep rate and its variations along the fault, we first subtract from the velocity field an interseismic model as explained in the modeling section below. Subsequently, profiles of residual velocities perpendicular to the fault are extracted at every ~1 km along the fault. Along 3 km on each side of the fault, we find a best-fitting line to the profiles, and compute the creep rate as an offset of the intercepts of these two lines at the fault trace (Figure 5.5) [START_REF] Burford | Slip on the San Andreas fault in central California from alignment array surveys[END_REF] studies [START_REF] Deniz | Determination of crustal movement in Turkey by terrestrial geodetic methods[END_REF][START_REF] Cakir | Creeping along the Ismetpaşa section of the North Anatolian Fault (Western Turkey: Rate and extent from InSAR[END_REF][START_REF] Karabacak | Monitoring aseismic creep along the North Anatolian Fault (Turkey) using ground-based LIDAR[END_REF][START_REF] Ozener | Quantifying aseismic creep on the Ismetpaşa segment of the North Anatolian Fault Zone (Turkey) by 6 years of GPS observations[END_REF][START_REF] Kaneko | Interseismic deformation and creep along the central section of the North Anatolian fault (Turkey): InSAR observations and implications for rate-andstate friction properties[END_REF]. The InSAR LOS time series are in good agreement with LOS-projected GPS time series at Ismetpaşa and show linear decays with time

(

Modeling

To estimate the aseismic slip distribution on the Ismetpaşa segment, we model the LOS displacements using the Poly3Dinv software [START_REF] Maerten | Inverting for slip on three dimensional fault surfaces using angular dislocations[END_REF] that uses the boundary element approach (see details in Chapter 3.4.1). To infer the aseismic slip distribution on the fault, we first model and remove from the LOS velocity field the long wavelength signal due to the interseismic strain assuming that the regional deformation due to the secular loading arises from buried displacement below the NAF. To model this secular loading, we use the far field (> 20 km away from the fault) LOS velocity field data (with the Orta earthquake region being masked). We invert for a right-lateral sense of slip on a single fault patch buried below 10 km to infinity (900 km) and obtain ~25 mm/yr of interseismic slip rate.

However, the model does not entirely account for the long wavelength signal in the velocity field, implying the presence of unwrapping and unmodeled atmospheric errors, and orbital residuals in the data. We therefore obtain a variable interseismic slip model using multiple fault patches (12 triangles) to flatten the far field velocity field required for modeling the distribution of shallow creep on the fault (Figure E.2). We subtract this inverted interseismic model from the LOS velocity field and obtain a residual LOS velocity field that is considered as a creep signal in vicinity of the fault (Figure 5.8). The residual LOS velocities show a sharp color contrast across the fault that can also be seen in the profiles shown in Figure 5.8b. Some of the remaining velocities, which are on the corner of the tracks with ±2-3 mm/yr, in the velocity field are, however, most probably due to atmospheric artifacts or unmodeled orbital errors but these don't affect offset at fault. In addition, the postseismic surface deformation associated with the 2000 Orta earthquake [START_REF] Cakir | Synthetic aperture radar interferometry observations of the M=6.0 Orta earthquake of 6 June 2000 (NW Turkey): Reactivation of a listric fault[END_REF] becomes more prominent and appears as circular area of range decrease ~30 km across anomaly with a blue color. To model the creep on the fault surface, we formed a vertical fault from surface to a depth of 10 km, using quadrangles of about 5 km long along the fault strike. The width of the quadrangles increases from 1 to 3 km in the down dip direction (Figures 5.8 and 5.9). To evaluate the uncertainty of slip distribution, we first estimate a 1-D covariance function for each data set by radially averaging a 2-D autocorrelation function calculated using the power spectrum of the data in the far field where there are no orbital ramps or deformation signal due to aseismic creep [START_REF] Hanssen | Radar interferometry: data interpretation and error analysis[END_REF]. We then fit a colored noise model [START_REF] Lennon | Red-shifts and red herrings in geographical ecology[END_REF] to the 1-D covariance function. Using the procedures in [START_REF] Fukushima | Laboratory study on scattering characteristics in rock samples[END_REF], for each data set on the two tracks we construct 200 simulations of spatially correlated random noise that matches the colored noise model. We use them to perturb each of our original data sets [START_REF] Funning | Surface displacements and source parameters of the 2003 Bam (Iran) earthquake from Envisat advanced synthetic aperture radar imagery[END_REF], which are then inverted for pure right-lateral strike slip (locked on the fault edges, except at its top) using a scale-dependent umbrella-smoothing operator to avoid any unphysical oscillatory slip distribution. A smoothing factor of 0.5 is used since lower values predict slip rates much higher than the interseismic slip rates estimated from the GPS measurements (24.2±0.2 mm/yr) by [START_REF] Reilinger | GPS constraints on continental deformation in the Africa-Arabia-Eurasia continental collision zone and implications for the dynamics of plate interactions[END_REF] and from InSAR (25±1.5 mm/yr) in this study. After calculating the mean slip, we estimate 95% confidence intervals from its distribution on each triangular patch. The results show a shallow creeping depth (mostly above 5 km) and an intermittent slip distribution with a highest rate of 20±2 mm/yr on several patches along the fault, similar to that inferred along the Hayward fault [START_REF] Schmidt | Distribution of aseismic slip-rate on the Hayward fault inferred from seismic and geodetic data[END_REF] (Figure 5.9). Although the surface creep deduced from offsets of bestfitting lines correlates to some extent with the creep inferred with Poly3Dinv modeling at depth, the largest patch located ~40 km east of Ismetpaşa is not obvious in the surface creep rate curves.

Discussion

The mechanical behavior of active fault zones can vary from continuous aseismic creep to sudden rupture during earthquakes, and the same fault zone may evolve either laterally or at depth from seismic to aseismic deformation [START_REF] Freed | Afterslip (and only afterslip) following the 2004 Parkfield, California, earthquake[END_REF][START_REF] Gratier | Geological control of the partitioning between seismic and aseismic sliding behaviours in active faults: Evidence from the Western Alps, France[END_REF]. It is therefore important to determine whether this transition is geologically and tectonically controlled since some types of rocks are more prone to seismic failure while the others are more likely to exhibit aseismic creep [START_REF] Gratier | Geological control of the partitioning between seismic and aseismic sliding behaviours in active faults: Evidence from the Western Alps, France[END_REF]. If the fault zone rocks are weaker than the surrounding rocks and do not heal after the rupture, they may exhibit stable sliding friction behavior, so called velocity-strengthening conditions [START_REF] Carpenter | Weakness of the San Andreas Fault revealed by samples from the active fault zone[END_REF].

Inherited tectonic structures, the presence of weak rocks or the thickness of the gouge zone may control the distribution of surface creep. Serpentines [START_REF] Allen | The tectonic environments of seismically active and inactive areas along the San Andreas fault system[END_REF] and clay rich lithology [START_REF] Warr | Clay mineral transformations and weakening mechanisms along the Alpine Fault, New Zealand[END_REF] have long been identified as zones of structural characteristics with phyllosilicate foliations resulting into fault weakening [START_REF] Collettini | Fault zone fabric and fault weakness[END_REF]. Similarly, calcareous rocks with phyllosilicates are able to creep in the upper crust by pressure solution [START_REF] Gratier | Geological control of the partitioning between seismic and aseismic sliding behaviours in active faults: Evidence from the Western Alps, France[END_REF].

The analysis of geological maps reveals that the aseismic surface creep can be, to some extent, correlated with the geology along the North Anatolian Fault (Figure 5.10). The major surface creep in the shallow depths of the western part of the creeping segment, overlapping with 1944 earthquake rupture is correlated with the Upper Jurassic-Lower Cretaceous limestone unit, probably due to pressure solution. In the eastern part of the creeping segment, which overlaps with the 1943 earthquake rupture, aseismic slip is possibly related to the serpentinite bodies marked in the geology map as Mesozoic ophiolotic mélange along the fault zone (Figure

5.10a

). There appears to be no correlation, however, between the variation of creep rate and surface lithology along the fault (Figure 5.10).

The downward-circulation of meteoric fluids may also contribute to the creep in the weaker upper crust as shown by the numerous hot springs along the Alpine active fault zone in New Zealand [START_REF] Allis | New insights to temperature and pressure beneath the central Southern Alps, New Zealand[END_REF], and in particular in the western and central-western segments of the North Anatolian fault zone. In fact, Paleozoic metamorphic rocks, along with Mesozoic limestone and flysch, comprise the basement rocks in the geothermal fields along the North Anatolian fault zone [START_REF] Erisen | Türkiye jeotermal envanteri, General Directorate of Mineral Research and Exploration (MTA)[END_REF]. Therefore both the geology and the downward circulation of meteoric fluids might have a control on the aseismic slip of the Ismetpaşa segment.

Although it is not known whether or not the fault was creeping before the 1944 earthquake, postseismic measurements at Ismetpaşa reveals an exponential decay in creep rate that appears to have graded into a steady-state slip over the last decades or so (Figure 5.11). This suggests that aseismic slip may continue for decades, and plausibly during the entire earthquake cycle (~200-300 yr). Change in the creep rate with time is fitted to an exponential relaxation function that suggests Newtonian behavior of creep in a ductile shear zone [START_REF] Savage | Postseismic relaxation and transient creep[END_REF]. Using fully dynamic models of earthquake cycles, [START_REF] Kaneko | Interseismic deformation and creep along the central section of the North Anatolian fault (Turkey): InSAR observations and implications for rate-andstate friction properties[END_REF] inferred that the friction behavior of Ismetpaşa creeping segment is velocity strengthening at shallow depths, changing to velocity weakening at 3 to 6 km-depth. Our models suggest that these properties may vary in space along the fault.

Conclusions

We The three-dimensional elastic dislocation modeling suggests that surface creep occurs along a 100-km long section since the easternmost 20 km creeping section estimated with best fitting linear approximations (Figure 5.6b) is not detected with the 3-D elastic dislocation modeling (Figure 5.9) probably due to high level of noise in this section. The creeping section extends at least 30 km further east compared to the previous studies [START_REF] Cakir | Creeping along the Ismetpaşa section of the North Anatolian Fault (Western Turkey: Rate and extent from InSAR[END_REF][START_REF] Kaneko | Interseismic deformation and creep along the central section of the North Anatolian fault (Turkey): InSAR observations and implications for rate-andstate friction properties[END_REF]. Modeling results indicate a shallow creeping depth, mostly less than 5 km, in good agreement with the velocity-strengthening at shallow depths deduced from dynamic models by [START_REF] Kaneko | Interseismic deformation and creep along the central section of the North Anatolian fault (Turkey): InSAR observations and implications for rate-andstate friction properties[END_REF] and elastic dislocation models by [START_REF] Cakir | Creeping along the Ismetpaşa section of the North Anatolian Fault (Western Turkey: Rate and extent from InSAR[END_REF]. Thus, the Ismetpaşa segment appears to be locked with a higher stressing rate at the lower seismogenic crust, which is able to generate strain release during moderate-large earthquakes such as those that occurred in the 1943, 1944 and 1951 earthquakes. An analysis of the geological structures suggests that aseismic slip along the Ismetpaşa creeping segment is mainly controlled by the limestone and serpentine bodies.

Published paper from this chapter can be found in Appendix F. supporting the previous inferences that the earthquake was associated with two rupture segments. Inverse modeling using dislocations on triangular faults in an elastic and homogeneous half-space suggest that subsidence in the area of high coseismic uplift can be explained by afterslip on the shallow sections (< 5 km) of the fault above the areas of coseismic slip, in agreement with previous estimates based on GPS observations. The impact of earthquake sequence on soft sediments and ground water table southwest of the earthquake area, allow us to characterize a ground deformation of non-tectonic origin. The cumulative postseismic moment due to afterslip during 7 years following the 2003 mainshock is equivalent to an Mw 6.3 earthquake. Therefore, the postseismic deformation and stress buildup has significant implications on the earthquake cycle models and recurrence intervals of large earthquakes in the Algiers area.

The coseismic and postseismic surface deformation associated with the February 24, 2004 Al Hoceima earthquake (Mw 6.4) in the Rif Mountains of Northern Morocco has been analyzed using Envisat ASAR data acquired in both ascending and descending modes. Due the absence of clear coseismic faulting and related features in the field, the exact location of the earthquake rupture location was not known before the previous InSAR studies [START_REF] Cakir | Surface deformation associated with the Mw 6.4, 24 February 2004 Al Hoceima, Morocco, earthquake deduced from InSAR: implications for the active tectonics along North Africa[END_REF][START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF][START_REF] Biggs | Fault identification for buried strike-slip earthquakes using InSAR: The 1994 and 2004 Al Hoceima, Morocco earthquakes[END_REF]. These studies showed that the earthquake must be associated with a NW-SE trending right-lateral, apparently blind strike-slip fault. In this study we remodel the coseismic interferograms in light of postseismic deformation field to refine the coseismic model of [START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF]. The InSAR time series of postseismic deformation and aftershocks distribution allow us to better constrain the southeastern end of the earthquake rupture. This fault geometry is similar to that of [START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF] in the northern section, which is well constrained due to narrow distance in between the fringes of zero LOS deformation in the ascending interferograms. To the south, the rupture displays a left bend or step, instead of a curvature proposed by [START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF], and a planar and parallel fault plane after the bend. Postseismic displacement field is remarkably prominent and quite high considering the size of the main shock (Mw 6.4). Modeling of 3.3-year postseismic deformation suggests that it is most likely due to shallow (< 8 km) afterslip on the coseismic fault mainly above the high slip patches of the coseismic slip as with 5.0 x 10 17 Nm (Mw 5.73) cumulative moment release. Modeling results suggest a complementary coseismic and postseismic slip as commonly observed for other moderate-large earthquakes [START_REF] Reilinger | Coseismic and Postseismic Fault Slip for the 17 August 1999, M=7.5, Izmit, Turkey Earthquake[END_REF][START_REF] Cetin | Seven years of postseismic deformation following the 2003 Mw=6.8 Zemmouri earthquake (Algeria) from InSAR Time Series[END_REF]. Shallow Consequently, afterslip however appears to be a dominant postseismic deformation mechanism produced by both moderate and large earthquakes, deep visco-elastic and/or poro-elastic relaxation might contribute to cumulative surface deformation in some cases. Yet, this is rather puzzling to apply the precise approach to combine them together and requires more detailed analysis to avoid unreliable results. For instance, visco-elastic and poro-elastic contributions to the postseismic relaxation were however analyzed in the Zemmouri postseismic deformation; InSAR data did not provide adequate horizontal motions information since it captures line-of-sight displacements. Furthermore, the cumulative moment release of postseismic afterslip may commonly reach to 30% of a moderate or large-sized earthquake moment release. On the other hand, smaller earthquakes (M < 6) may exceptionally have a higher postseismic afterslip relative to coseismic moment release that reach to 70% of coseismic moment release, which is observed following the 2007 Ghazaband (M 5.5, Balochistan, Pakistan) fault earthquake [START_REF] Fattahi | Coseismic and postseismic deformation due to the 2007 M5. 5 Ghazaband fault earthquake, Balochistan, Pakistan[END_REF]. Besides, surface creep may initiate as a postseismic afterslip and continue for a long time as shown in the Ismetpaşa case.

The inverse modeling using elastic dislocations on triangular faults with a nonlinear minimization procedure based on simulating algorithm has been utilized to obtain slip distribution associated with the surface deformation. Modeling results indicate that afterslip and/or aseismic slip is mostly confined to superficial depths (< 5km) as shown in the three case studies, which is in good agreement with several locales worldwide. The shallower depth of afterslip and aseismic slip is consistent with inferred velocity-strengthening behavior along the shallow parts of faults related to zone of weaker rocks than the surrounding rocks. In addition, this study confirms again that afterslip generally surrounds the high-slip patches of the coseismic rupture as shown in the Zemmouri and Al Hoceima cases.

In perspective, in order to build reliable seismic hazard evaluations, it is important to understand the earthquake cycle, fault behaviors, driving mechanisms behind the earthquakes and interaction between them. The earthquake cycle is simply conceptualized on cyclic build up and release of elastic strain around faults, which is complemented by transient deformation. Realistic seismic hazard analysis must accurately explore numerous seismic cycles and include the strain build-up via plate motions, dynamic stress changes during rupture, and postseismic transient deformation. Such seismic hazard analysis must be able to explain the interaction of aseismic and seismic slip, the segmentation of faults, and the strong spatial variations in the intensity of strong shaking [START_REF] Bakun | Implications for prediction and hazard assessment from the 2004 Parkfield earthquake[END_REF]. Consequently, improved seismic hazard assessments require up-close and detailed observations, and complementary data from in situ studies of the Earth's crust. Therefore, satellite geodesy observations, particularly InSAR, have contributed significantly to our understanding of earthquake cycle and build reliable hazard assessments.

This study shows once again that InSAR is a remarkably useful and powerful tool in detecting crustal deformation due to earthquakes and aseismic surface or deep fault creep as a result of plate motions. We show here that the InSAR time series contribution to analyze slow surface deformations is satisfactory for active tectonic studies. This work also demonstrates that the contribution of postseismic displacement maps combined with aftershocks distribution is useful to determine the fault geometry if there is no clear surface faulting (e.g. the case of 2004 Al Hoceima earthquake). Also, it is noteworthy using both ascending and descending acquisition modes of satellite to estimate the reliable slip distributions associated with the coseismic and postseismic deformations. Besides, GPS data were beneficial as a supplementary data to determine the related parameters with the deformation (e.g. La zone de convergence de plaques Afrique -Eurasie comporte des failles capables de générer de forts séismes destructeurs. L'objectif de cette thèse est une meilleure compréhension du comportement de ces failles, et du cycle sismique associé, par l'analyse des déformations co-, postet inter-sismiques enregistrées en surface, dans la zone de convergence. Une attention particulière est portée aux déformations lentes et à leur part dans le cycle sismique, mesurées en surface et analysées à l'aide des techniques InSAR (Synthetic Aperture Radar Interferometry), et modélisées par les méthodes de la dislocation élastique.

Résumé en anglais

This Ph.D. thesis is conducted in the frame of the "co-tutelle" scholarship (EOST-ITU) provided by French Embassy in Ankara. In addition, a 10-month scholarship « Bourse excellence Eiffel », and 8-month scholarship « TUBITAK 2214B -joint Ph.D. » were other sources of support for the preparation of this thesis.

The convergence between African and Eurasian plates is at the origin of active tectonic structures that generate large and destructive earthquakes. This thesis aims to improve our understanding of fault behavior and the earthquake cycle by analyzing surface deformation along selected active faults during the periods of co-, post-and inter-seismic deformation within the Africa-Eurasia convergence zone. In this context, slow deformation observed at the surface and associated with the earthquake cycle is analyzed using Synthetic Aperture Radar Interferometry (InSAR) time series technique, and modeled with elastic dislocation methods. §

  Figure 1.1 : Schematic of Reid [1910]'s elastic rebound model of the earthquake cycle (modified from Wright [2002]). a) Map view of area spanning a hypothetical fault, in the instant after the last earthquake. b) The same area, in 250 years. The profile A-A', straight at the beginning of the cycle, has become curved. This is known as interseismic strain accumulation. c) The same area, 20 s later, after an earthquake. A-A' is once more a straight line, but this time with a 5 m step at the fault. B-B', straight immediately before the earthquake, is now curved with an offset of 5 m at the fault, decaying with large distances from the fault. ........... 4 Figure 2.1 : Phase simulations from Hooper et al. [2007] for (a) a distributed scatterer pixel and (b) a persistent scatterer pixel. The cartoons above represent the scatterers contributing to the phase of one pixel in an image and the plots below show simulations of the phase for 100 iterations, with the smaller scatterers moving randomly between each iteration. The brighter scatterer in (b) is three times brighter than the sum of the smaller scatterers. ................................................................. 10 Figure 2.2 : Sketch of the interferometric data pairs (green lines) selection for a) single (PSI) and b) multiple master (SBI) image (red circles) configurations. The SAR dataset is relevant to the Envisat ASAR acquisitions carried out from 12-July-2003 to 18-September-2010 covering the 2003 Zemmouri earthquake region. ................................. 12 Figure 3.1 : Tectonics and seismicity of the Zemmouri-Boumerdes region shown with SRTM shaded topography. Focal mechanisms are from Global CMT project. Two destructive earthquakes and related aftershocks (Tipaza 1989 and Zemmouri 2003, green and yellow circles, respectively) limit the Mitidja-Algiers active zone (black lines are thrust faults [Maouche et al., 2011]). Dashed box is the Envisat images frame (Track 65). Black box in inset map shows the study region. ................. 25 Figure 3.2 : The baseline plot showing the interferogram pairs (green lines) between radar images (red circles). ..................................................................... 26 Figure 3.3 : Seven-year postseismic cumulative LOS range change following the 2003 Zemmouri earthquake. Movements away from the satellite are shown with yellow to red colors and, those towards the satellite with yellow to blue. The black arrows with 95% confidence ellipses are 2.5year cumulative postseismic GPS displacements from Mahsas et al. [2008]. Red line is the trace of the modeled fault on the sea floor. Numbers show the locations of time series plotted in Figure 1.4. ........ 27 Figure 3.4 : Time series of InSAR data (red circles) and groundwater tablemeasurements (blue squares[START_REF] Mimouni | Pollutions des eaux de la région d'Alger, leurs impacts sur l'environnement et les risques majeurs[END_REF]) in the study area. Note the strong correlation between water level fluctuations and InSAR phase

  Figure 1.1 : Schematic of Reid [1910]'s elastic rebound model of the earthquake cycle (modified from Wright [2002]). a) Map view of area spanning a hypothetical fault, in the instant after the last earthquake. b) The same area, in 250 years. The profile A-A', straight at the beginning of the cycle, has become curved. This is known as interseismic strain accumulation. c) The same area, 20 s later, after an earthquake. A-A' is once more a straight line, but this time with a 5 m step at the fault. B-B', straight immediately before the earthquake, is now curved with an offset of 5 m at the fault, decaying with large distances from the fault. ........... 4 Figure 2.1 : Phase simulations from Hooper et al. [2007] for (a) a distributed scatterer pixel and (b) a persistent scatterer pixel. The cartoons above represent the scatterers contributing to the phase of one pixel in an image and the plots below show simulations of the phase for 100 iterations, with the smaller scatterers moving randomly between each iteration. The brighter scatterer in (b) is three times brighter than the sum of the smaller scatterers. ................................................................. 10 Figure 2.2 : Sketch of the interferometric data pairs (green lines) selection for a) single (PSI) and b) multiple master (SBI) image (red circles) configurations. The SAR dataset is relevant to the Envisat ASAR acquisitions carried out from 12-July-2003 to 18-September-2010 covering the 2003 Zemmouri earthquake region. ................................. 12 Figure 3.1 : Tectonics and seismicity of the Zemmouri-Boumerdes region shown with SRTM shaded topography. Focal mechanisms are from Global CMT project. Two destructive earthquakes and related aftershocks (Tipaza 1989 and Zemmouri 2003, green and yellow circles, respectively) limit the Mitidja-Algiers active zone (black lines are thrust faults [Maouche et al., 2011]). Dashed box is the Envisat images frame (Track 65). Black box in inset map shows the study region. ................. 25 Figure 3.2 : The baseline plot showing the interferogram pairs (green lines) between radar images (red circles). ..................................................................... 26 Figure 3.3 : Seven-year postseismic cumulative LOS range change following the 2003 Zemmouri earthquake. Movements away from the satellite are shown with yellow to red colors and, those towards the satellite with yellow to blue. The black arrows with 95% confidence ellipses are 2.5year cumulative postseismic GPS displacements from Mahsas et al. [2008]. Red line is the trace of the modeled fault on the sea floor. Numbers show the locations of time series plotted in Figure 1.4. ........ 27 Figure 3.4 : Time series of InSAR data (red circles) and groundwater tablemeasurements (blue squares[START_REF] Mimouni | Pollutions des eaux de la région d'Alger, leurs impacts sur l'environnement et les risques majeurs[END_REF]) in the study area. Note the strong correlation between water level fluctuations and InSAR phase

  . ..................................................................................................... 40 Figure 4.2 : Tectonic map of the Al Hoceima region (compiled from

  .................................................................................................... 43 Figure 4.3 : Aftershocks distribution of the 2004 earthquake obtained from Tahayt et al. [2009] and van der Woerd et al. [2014] in the Al Hoceima region. Blue lines show the mapped thrust and nappe structures in the mountains and normal faults that limit the Al Hoceima Quaternary Basin. Thick white line is the surface projection of our modeled xvii coseismic fault. Dashed lines show the perpendicular profiles to the fault (see profiles on the right). Cross sections of the aftershocks are shown on the right panel with profile numbers at the right bottom. Topographic profiles are shown as black lines on the top of sections. Blue arrows indicate the tip of our modeled coseismic blind fault location. ................................................................................................. 44 Figure 4.4 : Coseismic interferograms of the February 24, 2004 Al Hoceima earthquake. Each fringe shows 2.83 cm of surface displacement along the radar line-of-sight. Dashed lines are digitized fringes used in modeling of the interferograms. Blue line is the best model fault. Inactive thrust faults are shown to facilitate comparison of the interferograms. The gray and black arrows indicate the satellite flight direction and line-of-sight direction (right looking), respectively. ....... 46 Figure 4.5 : Baseline plot showing the interferogram pairs (green lines) between descending (T280) and ascending (T230) radar images (red circles). .. 48 Figure 4.6 : Cumulative LOS range change (a) between 2004 and 2010 deduced from SBI time series on descending track and (b) between 2004 and mid-2007 deduced from StaMPS/MTI time series on the ascending track in the Al Hoceima region. Movements away from the satellite are shown with warm colors and those towards the satellite with cool colors, which is consistent with right-lateral sense of motion. Thick black line is the best model fault. The gray and black arrows indicate the satellite flight direction and line-of-sight direction (right looking), respectively.Numbers show the locations of time series plotted in Figure 4.7. ......................................................................................................... 49 Figure 4.7 : Time series of InSAR data (blue circles for descending and red circles for ascending). Postseismic deformation in the earthquake region is manifested by linear change in descending time series due to lack of four months data just after the earthquake and similarly linear change in ascending time series after sudden change due to the earthquake. ....... 50 Figure 4.8 : a, b) Synthetic interferograms predicted by a right-lateral strike-slip c, d) residual interferograms obtained after subtracting the synthetic interferograms from the observed data (shown in Figure 4.4). Dashed lines are digitized fringes used in modeling of the interferograms. Blue line is the best model fault. .................................................................... 52 Figure 4.9 : Color-coded postseismic strike-slip distribution (right-lateral) on the 2004 Al Hoceima earthquake rupture with a reverse slip component (black dashed lines), which coincides with the step or/and bend of the earthquake rupture, and a normal slip component located on the main branches of the fault. ............................................................................. 53 Figure 4.10 : a) Ascending and b) descending cumulative LOS data sets during ~3.3 years used in inversions. Thick black line is modeled coseismic fault. The pink line shows the model fault tested to improve the model fit to LOS data change. The blue line indicates a fault suggested by the NE-SW trending aftershocks distribution. ................................................... 55 Figure 4.11 : Color-coded postseismic right-lateral strike-slip afterslip distribution on the Al Hoceima earthquake rupture. The afterslip distributions inverted from ascending data show patches of slip (up to 35 cm) along mostly the upper sections of the fault (<5-km-depth) complementing the coseismic slip (black dashed lines) at deeper fault sections. Descending xviii data on the other hand predicts a deep slip on the southern side of the fault similar to the coseismic model. ..................................................... Figure 4.12 : Residual maps obtained after subtracting the synthetic InSAR data (Figure D.2) from the observed data (shown in Figure 4.10). Residuals after inversion of (a) the ascending and (b) the descending data alone, and (c, d) jointly with a lower weighting for the descending data. Black line is the top of the coseismic model fault, and the dashed black line is the bottom of the coseismic model fault. ...............................................

Figure 5 . 2 :

 52 Figure D.1 : (a-b) Since InSAR measures surface change in 1-D (i.e. between surface and the radar) the surface deformation due to a right-lateral strike-slip fault on the ground will be recorded differently from ascending and descending orbits. The model fault used in the figure trends approximately NE-SW and has a dip of about 80º to the NE. The uniform slip observed on the fault surface is 50 cm. (c) The sum of the two phases of ascending and descending interferograms is largely vertical motion, and (d) the difference between two phases (descending minus ascending) is approximately east-west motion. ........................ 111 Figure D.2 : Time series of ascending LOS for Al Hoceima region between 2003 and 2007. Each image represents the incremental displacement towards the satellite since the time of the previous image, relative to pixels in the northwest corner. ................................................................................. 112 Figure D.3 : Model of 3.3-year cumulative LOS postseismic surface deformation predicted by the modeled slip distribution shown in Figure 4.11. Black lines show the top of the modeled fault. White dashed lines show the bottom of the modeled fault. ............................................................... 113 Figure D.4 : Model of 3.3-year cumulative LOS postseismic surface deformation predicted by the two fault rupture inversions according to aftershocks distribution. Black line shows the main modeled fault. Blue line indicates the fault branch obtained using aftershocks distribution. ..... 114 Figure D.5 : Residual maps obtained after subtracting the synthetic InSAR data (Figure D.3) from the observed data (shown in Figure 4.10). Residuals after inversion of (a) the ascending and (b) the descending data alone, and (c, d) jointly with a lower weighting for the descending data. Black line shows the main coseismic model fault, and blue line is the secondary fault branch. ........................................................................ 115 Figure D.6 : Model of 3.3-year cumulative LOS postseismic surface deformation predicted by the two fault rupture inversions according to PS LOS change in the southern section of the fault. Black line shows the main modeled fault. Pink line indicates the fault branch obtained using PS LOS displacement fields...................................................................... 116 Figure D.7 : Residual maps obtained after subtracting the synthetic InSAR data (Figure D.5) from the observed data (shown in Figure 4.10). Residuals after inversion of (a) the ascending and (b) the descending data alone, and (c, d) jointly with a lower weighting for the descending data. Black line shows the main coseismic model fault, and pink line is the secondary fault branch. ........................................................................ 117 Figure D.8 : Resolution test using checker-box approach with 0.10 m slip at different depths for each cell. .............................................................. 117 Figure E.1 : Velocity standard deviation maps calculated by StaMPS using bootstrapping. ....................................................................................... 118 Figure E.2 : Variable interseismic slip model using multiple fault patches to flatten the far field velocity field. ................................................................... 118 Figure E.3 : Residual LOS velocity field. ............................................................... 119 Figure E.4 : Resolution test using checker-box approach with 0.10 m slip at different depths for each cell. .............................................................. 119

  divers signaux sur les processus de déplacement visible en surface. Dans le cas de la faille inverse, les signaux cosismiques et postsismiques sont en opposition, alors que dans le cas de la faille en décrochement dextre les signaux cosismiques et postsismiques de la déformation sont comparables (même mécanisme de faille dextre). Le troisième exemple étudié montre un cas de déformation asismique lente (en creep) qui suggère une initiation des déplacements postsismiques depuis environ 70 ans, en liaison avec les deux séismes majeursde Mw 7.3 (1944) etde Mw 6.9 (1951). Bien-que la répétition de l'acquisition des images radar nécessite 35 jours, l'utilisation des images Envisat SAR a permis l'étude des déformation cosismique et postsismique pour des séismes modérés à forts. La perspective de l'utilisation de nouvelles générations d'images SAR (TerraSAR-X, et Sentinel qui permettent une acquisition tous les 3 à 12 jours) offrent la possibilité d'augmenter la résolution des images, et une réduction importante des effets de la décorrelation temporelle. Par conséquent, les nouvelles générations de constellations et capteurs d'image SAR en multi-fréquences avec réduction des temps d'acquisition, semblent très prometteurs pour l'étude spatio-temporelle de la déformation crustale. Au cours de cette thèse, nous avons distingué quatre mécanismes de déformation possibles (visco-elastique, poro-elastique, « afterslip » et zone de faille en effondrement ou bien zone de faille scellée) liés aux déplacements en surface, aux abords de la rupture et mesurables par les techniques géodésiques. La prépondérance xxx des mécanismes de déformation postsismique suggère le développement d'un système analytique dédié aux mécanismes de déformation postsismique. L'apport de chaque mécanisme au modèle de déformation observé peut-être déduit de la longueur d'onde et du temps écoulé de l'amplitude des déplacements. Par conséquent, le mécanisme de « l'afterslip » apparait comme dominant pour les déformations postsismiques liées aux séismes modérés ou forts, aux processus visco-élastique profonds et/ou à la relaxation poro-élastiques, pouvant parfois contribuer aux déformations de surface cumulées. Cependant, on ne peut ignorer l'aspect complexe de la combinaison des méthodes d'analyse des mécanismes de déformation qui requièrent des traitements robustes pour éviter les résultats peut fiables. Par exemple, malgré l'apport des processus visco-élastiques et poro-élastiques à la relaxation postsismique dans le cas du séisme de Zemmouri, les résultats InSAR ne permettent pas la caractérisation des déplacements horizontaux, car restreints à la déformation suivant le LOS. Le moment cumulé des déplacements postsismiques en « afterslip » peuvent atteindre 30% de la deformation totale cosismique liée à un fort séisme (M ≥ 6) ; les séismes faibles à modérés (M < 6) peuvent exceptionnellement montrer de forts déplacements en « afterslip » qui peuvent atteindre 70% du moment cosismique. Par ailleurs, les déplacements lents asismiques (creep) peuvent s'initier lors des déplacements en « afterslip » et se continuer durant plusieurs années tels qu'illustrés par l'exemple d'Ismetpaşa le long de la faille nord anatolienne. La modélisation en problème inverse utilisant la dislocation élastique sur des failles triangulaires avec une procédure de minimisation non-linéaire basée sur des algorithmes de simulation, a été utilisée pour obtenir la répartition des déplacements liée à une surface de rupture. Les résultats de la modélisation obtenus lors des différents cas d'étude de notre thèse indiquent que « l'afterslip » ou la déformation asismique sont le plus souvent confinés dans la partie superficielle de la croute supérieure (< 5 km), ce qui est en bon accord avec d'autres études de zones de faille actives. Les profondeurs superficielles de « l'afterslip » et des mouvements asismiques le long des zones de rupture sont cohérents avec les caractéristiques physiques de la déformation (velocity-strengthening behavior) et des roches fragiles par rapport à un substratum plus solides. Par ailleurs, notre étude confirme encore une fois que les déplacements « afterslip » sont complémentaires et entourent généralement les zones de rupture cosismique avec de grands déplacements, comme xxxi c'est le cas pour le séisme de Zemmouri (chapitre III) et dans une moindre mesure pour le séisme de Al Hoceima (chapitre IV). En perspective, et pour pouvoir développer des évaluations fiables de l'aléa sismique, il est important de mieux comprendre les caractéristiques du cycle sismique, des comportements de faille, des mécanismes générant les séismes et de leur interaction. Le cycle sismique est ici conceptualisé par le biais de l'accumulation et du relâchement des déformations élastiques sur les failles, en complément de la déformation transitoire. Une analyse réaliste de l'aléa sismique doit explorer les nombreuses possibilités de percevoir le mode de cycle sismique, en incluant l'accumulation des déformations liées au mouvement des plaques tectoniques, des changements de contrainte dynamiques durant les ruptures et de la déformation postsismique transitoire. Cette analyse de l'aléa sismique doit pouvoir expliquer la relation entre les déplacements sismiques et asismiques, la segmentation des failles et les variations spatiales importantes de l'intensité des vibrations sismiques. Le développement de l'évaluation de l'aléa sismique nécessite des observations détaillées en champ proche, associées à des données complémentaires « in-situe » de la déformation de la croute terrestre. Par conséquent, les études géodésiques par satellite en général, et de l'InSAR en particulier, contribuent significativement à une meilleure compréhension du cycle sismique et au développement d'une évaluation réaliste de l'aléa sismique d'une zone sismogène. Notre étude montre l'utilité et le rendement des méthodes InSAR pour l'identification et la caractérisation de la déformation crustale liée aux séismes, ainsi qu'à la déformation asismique, ou bien à la déformation lente en profondeur associée aux mouvements des plaques tectoniques. Nous montrons par ce travail la contribution des séries temporelles à l'étude des déformations lentes de surface liée à la tectonique active. Nous démontrons également qu'en l'absence de la rupture en surface, la contribution des déplacements cosismiques combinée aux répliques des séismes aide à une meilleure définition de la géométrie d'une faille sismique (e.g. voir le cas du séisme de 2004 à Al Hoceima, chapitre IV). Il est également utile de noter l'importance de l'utilisation des deux modes d'acquisition ascendantes et descendantes des images radar satellite afin de contraindre la déformation cosismique et postsismique. Par ailleurs, les données GPS sont souvent bien utiles et complémentaires aux données InSAR pour déterminer les paramètres de la xxxii déformation cosismique et postsismique (e.g., le cas du séisme de Zemmouri et la deformation postseismique en 2003), et la corrélation des taux de mouvements lents (voir le cas des mouvements asismiques à Ismetpaşa). En parallèle, un mouvement non-tectonique lié aux fluctuations de la nappe phréatique a été identifié dans le bassin de la Mitidja, lors de l'étude des mouvements postsismiques liée au séisme de Zemmouri de 2003. Enfin, nous pensons que l'application de la méthode InSAR, seule, peut ne pas être suffisante pour contraindre les paramètres de la déformation cosismique et postsismique, ou bien asismique, et qu'il est nécessaire d'associer les mesures de terrain en tectonique et géodésie (conventionnelle, GPS), et l'analyse géologique pour une meilleure estimation de la tectonique crustale. xxxiii 1

Figure 1 . 1 :

 11 Figure 1.1 : Schematic of Reid [1910]'s elastic rebound model of the earthquake cycle (modified from Wright [2002]). a) Map view of area spanning a hypothetical fault, in the instant after the last earthquake. b) The same area, in 250 years. The profile A-A', straight at the beginning of the cycle, has become curved. This is known as interseismic strain accumulation. c) The same area, 20 s later, after an earthquake. A-A' is once more a straight line, but this time with a 5 m step at the fault. B-B', straight immediately before the earthquake, is now curved with an offset of 5 m at the fault, decaying with large distances from the fault.

  time series techniques are applied to selected active faults within the Africa-Eurasia convergence zone to reveal typically slow surface deformation characteristics. After a presentation on the fundamentals of InSAR techniques, I present the postseismic deformation following the 2003 Zemmouri (Mw 6.8, Algeria) earthquake (Chapter 3), the coseismic and postseismic deformation associated with the 2004 Al Hoceima (Mw 6.4, Morocco) earthquake (Chapter 4), and the aseismic slip on the Ismetpaşa segment of the NAF (Chapter 5). Finally, a general conclusion provides with the main results and perspectives of this contribution.

Figure 2 . 1 :

 21 Figure 2.1 : Phase simulations from Hooper et al. [2007] for (a) a distributed scatterer pixel and (b) a persistent scatterer pixel. The cartoons above represent the scatterers contributing to the phase of one pixel in an image and the plots below show simulations of the phase for 100 iterations, with the smaller scatterers moving randomly between each iteration. The brighter scatterer in (b) is three times brighter than the sum of the smaller scatterers.

Figure 2 . 2 :

 22 Figure 2.2 : Sketch of the interferometric data pairs (green lines) selection for a) single (PSI) and b) multiple master (SBI) image (red circles) configurations. The SAR dataset is relevant to the Envisat ASAR acquisitions carried out from 12-July-2003 to 18-September-2010 covering the 2003 Zemmouri earthquake region.

  of the crustal deformation and the earthquake cycle requires detailed analysis of postseismic deformation, a transient response of the lithosphere to the stresses changes caused by moderate to large earthquakes. The 21 May 2003 Zemmouri earthquake and related coseismic rupture (Mw 6.8) provides a noteworthy case study for postseismic deformation associated with thrust slip

(

  7 years), SBI technique has been used with Envisat SAR data acquired by the European Space Agency. The mean velocity field deduced from the SBI reveals surface deformation of both tectonic and non-tectonic origin. The ground deformation along the coastal region has been modeled with afterslip on the coseismic fault ofBelabbes et al. [2009], has been discussed the coseismic/postseismic deformation, the signification of water level fluctuations in the Mitidja Basin and the role of poro-elastic/visco-elastic deformation.

Figure 3 . 1 :

 31 Figure 3.1 : Tectonics and seismicity of the Zemmouri-Boumerdes region shown with SRTM shaded topography. Focal mechanisms are from Global CMT project. Two destructive earthquakes and related aftershocks (Tipaza 1989 and Zemmouri 2003, green and yellow circles, respectively) limit the Mitidja-Algiers active zone (black lines are thrust faults [Maouche et al., 2011]). Dashed box is the Envisat images frame (Track 65). Black box in inset map shows the study region.

  Algiers (Figure3.2, and 3.3) using SBI technique (see Chapter 2.2 for processing details). The map reveals LOS range increase largely in three regions reaching to 12 mm/yr in the Mitidja basin, 3.5 mm/yr around Boumerdes-Zemmouri area, and 2 mm/yr around Cap Djenet (Figure3.3).

Figure 3 . 2 :

 32 Figure 3.2 : The baseline plot showing the interferogram pairs (green lines) between radar images (red circles).

Figure 3 . 3 :

 33 Figure 3.3 : Seven-year postseismic cumulative LOS range change following the 2003 Zemmouri earthquake. Movements away from the satellite are shown with yellow to red colors and, those towards the satellite with yellow to blue. The black arrows with 95% confidence ellipses are 2.5year cumulative postseismic GPS displacements from Mahsas et al. [2008]. Red line is the trace of the modeled fault on the sea floor. Numbers show the locations of time series plotted in Figure 1.4.

Figure 3 . 4 :

 34 Figure 3.4 : Time series of InSAR data (red circles) and groundwater tablemeasurements (blue squares[START_REF] Mimouni | Pollutions des eaux de la région d'Alger, leurs impacts sur l'environnement et les risques majeurs[END_REF]) in the study area. Note the strong correlation between water level fluctuations and InSAR phase changes in the Mitidja basin (plots 1 to 3). Postseismic deformation in the earthquake region (plot 4 and 5) is manifested by logarithmic decay in the InSAR time series.

  Figure A.1 in the appendix indicates that the InSAR data have an adequate resolution in constraining the shallow slip on the fault.

Figure 3 . 5 :

 35 Figure 3.5 : The smoothing operator used in the InSAR and GPS data inversion. An optimum solution can be obtained with a 0.4 smoothing factor.

Figure 3 . 6 :

 36 Figure 3.6 : Color-coded postseismic afterslip distribution on the Zemmouri earthquake rupture. Black dashed lines show the coseismic slip distribution inferred by Belabbes et al. [2009]. The afterslip distribution inverted from InSAR and GPS data shows two patches of maximum slip (40 to 65 cm) along the upper sections of the fault (<5-km-depth) complementing the coseismic slip at deeper fault sections.

Figure 3 . 7 :

 37 Figure 3.7 : Model of 7 year cumulative LOS surface deformation and GPS displacements predicted by the modeled slip distribution shown in Figure 3.6. The fault rupture projected to the surface is illustrated by the triangulated network; parallel and perpendicular profiles to the fault are located by number 1 and 2. Inset shows LOS change of modeled (red lines) and observed (blue dots) postseismic surface deformation, together with coseismic model (green lines [Belabbes et al., 2009]). Pink lines show vertical component of the LOS change predicted by the model.

Figure 3 . 8 :

 38 Figure 3.8 : Residual LOS velocity field.

  which models the Earth as a multilayered elastic to visco-elastic half-space from surface up to upper mantle. It is split into two programs, namely PSGRN and PSCMP (see Appendix B). PSGRN is used to calculate the time-dependents Green's functions required to describe the response of the model, which contains the rheology parameters. Fault geometry and slip distribution of earthquake rupture were described in PSCMP (Figure B.1).To explore possible contributions of visco-elastic relaxation following the 2003 Zemmouri earthquake, we test the possible configurations of the multi-layered half-space (see Appendix B). We built a two-layer rheological model, made up of an elastic half-space layer on a visco-elastic half-space layer (Maxwell rheology). For each configuration, different depths of the elastic half-space (12-30 km-depths) and viscosity of the lower visco-elastic half-space (10 17 -10 19 Pa.s) has been tested and searched for the viscosity leads to the minimum misfit with respect to GPS observed horizontal and InSAR LOS surface displacements. We estimate that the best-fit viscosity of lower visco-elastic half-space (> 12 km depth) is 5 x 10 19 Pa.s, respectively. Each calculation was conducted by applying the coseismic slip distribution, then allowing the viscoelastic region to relax for 7 years. Coseismic slip is simulated on a planar fault by enforcing the slip distribution deduced byBelabbes et al. [2009]. The simulated fault model located at ~13 km offshore from the epicenter with 55-km-long and 20-km-wide offshore thrust fault striking N60°, and dipping 42° SE (Figure3.9, and B.1). We find that the visco-elastic relaxation models predict successfully the subsidence observed in the InSAR results, but fail to explain large horizontal displacements at GPS sites (Figure3.9).

Figure 3 . 9 :

 39 Figure 3.9 : Model of 7-year cumulative LOS surface deformation and GPS displacements predicted by visco-elastic relaxation. Red line shows the modeled fault rupture.

  maximizing the poro-elastic response, we have chosen extreme values of Poisson's ratio (i.e., 0.33 and 0.25) as in the case of the 1997 Umbri-Marche earthquake sequence (i.e., 0.35 and 0.20 chosen by[START_REF] Riva | Viscoelastic relaxation and long-lasting after-slip following the 1997 Umbria-Marche (Central Italy) earthquakes[END_REF]). Even though the poroelastic model may explain most of the signal, it fails again to reproduce the horizontal motions observed by GPS (Figure3.10).

Figure 3 . 10 :

 310 Figure 3.10 : Model of 7-year cumulative LOS surface deformation and GPS displacements predicted by poro-elastic rebound. Red line shows the modeled fault rupture.

  region of Northern Morocco is located within the east-west trending imbricated thrust-and-fold system of the Rif Mountain range that results from collision between the African and Eurasian plates. The Rif mountain range has experienced several moderate-to-large earthquakes of mainly strike-slip mechanisms consistent with a NNW-SSE to NW-SE direction of plate convergence[START_REF] Demets | Current plate motions[END_REF][START_REF] Meghraoui | Active faulting and transpression tectonics along the plate boundary in North Africa[END_REF]. The Al Hoceima earthquakes of the May 26, 1994 (Mw 6.0) and February 24, 2004 (Mw 6.4) are the largest seismic events in the last century that occurred on conjugate strike-slip faults trending approximately NNE-SSW and NW-SE on the Rif Mountain range (Figure4.1)[Bezzeghoud and

Figure 4 . 1 :

 41 Figure 4.1 : Al Hoceima region of Morocco with shaded relief (SRTM 90m). Large beach balls are focal mechanism solutions of the 26 May 1994 and 24February 2004 Al Hoceima earthquakes[START_REF] Calvert | An integrated geophysical investigation of recent seismicity in the Al-Hoceima region of North Morocco[END_REF][START_REF] Bezzeghoud | Source parameters of the 1992 Melilla (Spain, Mw 4.8). 1994 Al Hoceima (Morocco, Mw 5.8) and 1994 Mascara (Algeria, Mw 5.7) earthquakes and seismotectonic implications[END_REF], whose epicenters are indicated by gray and black stars, respectively. Small black circles are M > 4 aftershocks from IGN with focal mechanism solutions from[START_REF] Buforn | Seismic sources on the Iberia-African plate boundary and their tectonic implications[END_REF] and[START_REF] Stich | Source analysis of the Mw 6.3 2004 Al Hoceima earthquake (Morocco) using regional apparent source time functions[END_REF]. Dashed rectangles are the frames of the Envisat radar images with arrows showing the flight direction of the satellite. The convergent plate boundary between Africa and Eurasia is depicted with a thick gray line in the inset map with arrows illustrating the direction and estimated rate (min. and max.) of convergence[START_REF] Nocquet | Geodetic measurements of crustal deformation in the Western Mediterranean and Europe[END_REF]. Red arrows indicate the recent GPS measurements[START_REF] Koulali | New GPS constraints on active deformation along the Africa-Iberia plate boundary[END_REF].

  . The African-Eurasian plate boundary forms a collision tectonics strip including the Alboran Sea, Tell Atlas Mountain ranges of Algeria and Tunisia along the Mediterranean coast to the east. The Quaternary counter-clockwise rotation of Africa with respect to Eurasia based on the global models of plate tectonics indicates an oblique convergence along the western section of North Africa, and shows a decreasing westward rate of shortening with a range of 6 mm/yr to 3 mm/yr (Figure 4.1) [DeMets

  Rif consist of the major NE-SW trending Nekor and Jebha left-lateral strike-slip faults (Figure 4.1), accompanied by N-S trending normal faults that form a graben-like structure east of Al Hoceima city and a conjugated network of relatively small (10 to 20-km-long) NW-SE and NE-SW strike-slip faults (Figure 4.2). The transpressive tectonics and existence of a complex fault network with thrust, normal and strike-slip faulting in the Rif probably reflect the rapidly changing local tectonic regime with block rotations during the Neogene and Quaternary [Meghraoui et al., 1996]. Typical prominent geomorphological features of late Pleistocene and Holocene seismogenic faulting are undocumented along the Rif neotectonic faults. The source mechanisms of the 2004 earthquake rupture, based on different observations (i.e. aftershock distribution, waveform inversion, InSAR, field observations) made by various investigators, propose a NW-SE trending right-lateral and/or a NNE-SSW trending left-lateral strike-slip faulting. However, there are inconsistencies in the literature regarding the source, location and geometry of the rupture. While based on apparent source time functions and seismic wave modeling, Stich et al. [2005] and Buforn et al. [2004] deduce NNE-SSW trending left-lateral rupture south of Al Hoceima, van der Woerd et al. [2014] based on aftershock distribution (Figure 4.3) infer two possible fault ruptures striking NW-SE with rightlateral and/or NE-SW with left-lateral mechanism. InSAR studies predict NW-SE

  infer a complex rupture with two sub-events initiated on the N10ºE left-lateral strike-slip fault and transferred to the N132ºE right-lateral strike-slip fault. The absence of coseismic surface ruptures and the complex thrust and nappe tectonic context clearly require the contribution of new methods of investigations such as InSAR to characterize blind or hidden faults.

Figure 4 . 2 :

 42 Figure 4.2 : Tectonic map of the Al Hoceima region (compiled from[START_REF] Calvert | An integrated geophysical investigation of recent seismicity in the Al-Hoceima region of North Morocco[END_REF] Ait Brahim, Tadili, et al., 2004) with surface cracks and fissures observed after the 2004 event (redrawn from AitBrahim, Nakhcha, et al., 2004). Thick white line is the surface trace of the modeled fault plane.

Figure 4 . 3 :

 43 Figure 4.3 : Aftershocks distribution of the 2004 earthquake obtained from Tahayt et al. [2009] and van der Woerd et al. [2014] in the Al Hoceima region. Blue lines show the mapped thrust and nappe structures in the mountains and normal faults that limit the Al Hoceima Quaternary Basin. Thick white line is the surface projection of our modeled coseismic fault. Dashed lines show the perpendicular profiles to the fault (see profiles on the right). Cross sections of the aftershocks are shown on the right panel with profile numbers at the right bottom. Topographic profiles are shown as black lines on the top of sections. Blue arrows indicate the tip of our modeled coseismic blind fault location.

Figure 4 . 4 :

 44 Figure 4.4 : Coseismic interferograms of the February 24, 2004 Al Hoceima earthquake. Each fringe shows 2.83 cm of surface displacement along the radar line-of-sight. Dashed lines are digitized fringes used in modeling of the interferograms. Blue line is the best model fault. Inactive thrust faults are shown to facilitate comparison of the interferograms. The gray and black arrows indicate the satellite flight direction and line-of-sight direction (right looking), respectively.

Figure 4 . 5 :

 45 Figure 4.5 : Baseline plot showing the interferogram pairs (green lines) between descending (T280) and ascending (T230) radar images (red circles).

Figure 4 . 6 :

 46 Figure 4.6 : Cumulative LOS range change (a) between 2004 and 2010 deduced from SBI time series on descending track and (b) between 2004 and mid-2007 deduced from StaMPS/MTI time series on the ascending track in the Al Hoceima region. Movements away from the satellite are shown with warm colors and those towards the satellite with cool colors, which is consistent with right-lateral sense of motion. Thick black line is the best model fault. The gray and black arrows indicate the satellite flight direction and line-of-sight direction (right looking), respectively. Numbers show the locations of time series plotted in Figure 4.7.

Figure 4 . 7 :

 47 Figure 4.7 : Time series of InSAR data (blue circles for descending and red circles for ascending). Postseismic deformation in the earthquake region is manifested by linear change in descending time series due to lack of four months data just after the earthquake and similarly linear change in ascending time series after sudden change due to the earthquake.

  ], northeast-southwest-trending right-lateral strike-slip faults are placed along the fringes of zero LOS deformation in between the two lobes of the ascending interferogram to the north of the earthquake area, similar to[START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF] fault model. Postseismic LOS deformation data (Figure4.6) and aftershocks distribution (Figure4.3) are utilized to detect the fault location and geometry since to the fault rupture did not reach to surface and the coseismic LOS deformation captured by SAR interferometry is not quite unambiguous in the south of earthquake area. Fault surfaces meshed with triangles were constructed using MATLAB ® . While the length of the triangular elements is kept approximately the same (1.7-2.1 km) along the fault, their sizes are gradually increased from 1 km to 2.5 km along the dip direction down to 20 km of depth because the resolution of inverted slip decreases with increasing depth. The digitized fringes of coseismic interferograms are used instead of unwrapped data in the inversion because most of the fringes that readily are visible could not be properly unwrapped due to poor coherence to the south of earthquake area (Figure4.4). The slip distribution on the triangular elements was then inverted with a negativity constraint on the strike-slip component (i.e., rightlateral for the modeled fault). The scale-dependent umbrella-smoothing operator of Poly3Dinv is applied to the inverted slip distribution (with a factor of 0.3) to avoid unphysical oscillatory slip. The smoothing operator with a zero slip constraint on the fault edges, including the topmost patches, prevents deducing high slip peaks where the inverted data are insufficient or absent due to using digitized contours.

Figure 4 . 9 :

 49 Figure 4.9 : Color-coded postseismic strike-slip distribution (right-lateral) on the 2004 Al Hoceima earthquake rupture with a reverse slip component (black dashed lines), which coincides with the step or/and bend of the earthquake rupture, and a normal slip component located on the main branches of the fault.

Figure 4 .

 4 Figure 4.10. As expected, the lobes of LOS decrease (blue) and increase (red) are separated by the coseismic fault in the ascending data. However, in the descending data, the fault runs through the red lobe along its northern section, which makes it difficult to explain it with a coseismic model. Therefore, we consider that the descending data contains significant errors possibly resulting from atmospheric interference and unwrapping. Consequently, we give less weighting to the descending data in the joint inversions (models shown in Figure D.2). The estimated moment released for the joint inversion is 5.0 x 10 17 Nm (Mw 5.73) for 3.3 years. It increases to 5.77 x 10 17 Nm (Mw 5.77), in the case of individual ascending datainversion. These estimates suggest that the cumulative postseismic moment release during 3.3 years is around 8 to 15% of the coseismic moment release estimated from seismology and geodesy[START_REF] Stich | Source analysis of the Mw 6.3 2004 Al Hoceima earthquake (Morocco) using regional apparent source time functions[END_REF][START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF]. The multiple faults inversion results given in Appendix D (Figure D.2-D.6) show no significant improvement. The resolution tests shown in Figure D.7 indicate that the InSAR data sets have an adequate resolution in constraining the shallow slip on the fault.

Figure 4 .

 4 Figure 4.11 : Color-coded postseismic right-lateral strike-slip afterslip distribution on the Al Hoceima earthquake rupture. The afterslip distributions inverted from ascending data show patches of slip (up to 35 cm) along mostly the upper sections of the fault (<5-km-depth) complementing the coseismic slip (black dashed lines) at deeper fault sections. Descending data on the other hand predicts a deep slip on the southern side of the fault similar to the coseismic model.

Figure 4 . 12 :

 412 Figure 4.12 : Residual maps obtained after subtracting the synthetic InSAR data (Figure D.2) from the observed data (shown in Figure 4.10). Residuals after inversion of (a) the ascending and (b) the descending data alone, and (c, d) jointly with a lower weighting for the descending data. Black line is the top of the coseismic model fault, and the dashed black line is the bottom of the coseismic model fault.

  Fig.1b) between 2003 and 2010 (Figure 5.2). Images acquired on May 6, 2007 on T479 and August 8, 2008 on T207 are chosen as the master scenes of all the interferometric pairs in each track to minimize the spatial and temporal decorrelation, and atmospheric effects. A mean radar line-of-sight (LOS) velocity field for each track is obtained and then projected to fault-parallel horizontal velocities assuming that the radar LOS displacements are due to purely horizontal motion on a N76°E trending strike-slip fault, parallel to the strike of the Ismetpaşa segment taking into account the local incidence angles that vary across the range. The fault-parallel velocity field shown in Figure 5.3 reveals very clearly the surface creep as well as the interseismic strain accumulation across the NAF. Warm colors on the southern side of the fault indicate motion away from the satellite (i.e., westward), and cool colors on the northern side of the fault indicate motion towards the satellite (i.e., eastward), consistent with a right-lateral sense of plate motion across the NAF. Surface creep is characterized by steep fault-parallel velocity gradients, and by a sharp color contrast across the fault trace along a distance of more than 100 km (Figure 5.3). In contrast, locked segments are clearly shown by gradual changes in the velocity field across the fault, particularly between Geredeand Ismetpaşa. Besides, to the south of the NAF the interseismic signal is strongly disturbed by a circular deformation pattern attributed to the postseismic displacements after the June 6, 2000 Orta earthquake[START_REF] Taymaz | Source characteristics of the 6 June 2000 Orta, Cankiri (central Turkey) earthquake: A synthesis of seismological, geological and geodetic (InSAR) observations, and internal deformation of the Anatolian plate, in The Geodynamics of the Aegean and Anatolia[END_REF][START_REF] Cakir | Synthetic aperture radar interferometry observations of the M=6.0 Orta earthquake of 6 June 2000 (NW Turkey): Reactivation of a listric fault[END_REF].Fault-parallel velocities along four different profiles are shown in Figure5.4 together with best-fit models for creeping and locked faults obtained with elastic dislocations. The velocity profiles of locked faults (at 15 km-depth) show a classic arctangent shape predicted by elastic screw dislocations across a strike-slip fault[START_REF] Savage | Geodetic determination of relative plate motion in central California[END_REF]. Conversely, the steps in the velocity profiles at the fault indicate surface creep. The shape and height of these steps are controlled by the locking depth and creep rate; abrupt vertical changes indicating creep reaching to the surface, and gradual changes showing deeper locking depths. It is worthwhile noting that fault-parallel velocities in Figure 5.4 do not correlate with topography.

Figure 5 . 2 :

 52 Figure 5.2 : Baseline versus time plot of synthetic aperture radar orbits from two Envisat tracks used to calculate the deformation field and the time series. Empty circles denote the SAR images with stars indicating the master orbits chosen for the PSI analyses.

Figure 5 . 3 :

 53 Figure 5.3 : Velocity field in the region of Ismetpaşa deduced from PSI time series. a, b) Fault-parallel horizontal velocity field (identical color scale for both tracks) between 2003 and 2010 on a SRTM shaded relief image with known active faults (black lines). The gray and black arrows to the bottom right corner show the satellite flight direction (descending) and the line-of-sight direction (right looking), respectively. Thick dashed lines with numbers are locations of profiles as shown in Figure 5.4. Red star shows the location of the PSI and GPS time series plotted in Figure 5.7. White boxes show the neighboring Envisat track used in this study.

  . Using standard deviations of PS pixels predicted by StaMPS, weighted means are calculated at every 50 m using a bin width of 100 m along these fault perpendicular profiles. The error bars of creep rates for individual profiles are estimated from the root-mean-square residuals of the line fitting using weighted means. The results reveal a ~120-km long creeping section with a creep rate varying in an oscillating manner along the fault and reaching a maximum of 20±2 mm/yr around 20 km east of Ismetpaşa (Figure 5.6). At its eastern end, it overlaps with the western part of the 1943, and the eastern part of the 1944 and 1951 earthquake ruptures (Figure 5.6a). Oscillation of creep to the east might result from atmospheric errors and hence inferred creep east of 32.5ºE (~80 km east of Ismetpaşa) requires confirmation. Note that despite some discrepancies, creep rate estimates from two different InSAR datasets in the central section of the fault are overall in good agreement. The creep rate is 8±2 mm/yr at Ismetpaşa, consistent with most previous

  Figure 5.7).

Figure 5 . 4 :

 54 Figure 5.4 : Some of the observed and modeled fault-parallel velocity profiles perpendicular to the fault. Red curves show the best fitting model to PSI data with the creep rate and depth given above. The blue curves represent an interseismic model for a locked fault at 15 km of depth. Dashed line represents the topographic elevation along the profiles. Arrows indicate the mapped active fault location. Profile-1 crosses the location of the offset wall and the geodetic network that have been used to measure the creep rate at Ismetpaşa over the last 40 years.

Figure 5 . 5 :

 55 Figure 5.5 : Estimation procedure for the creep rate using best-fitting lines to InSAR velocity profiles that extend for 3 km on both sides of the fault (pink and blue colors). Creep rate is calculated from the offset of the two lines at the fault trace (e.g., the length of black line).

Figure 5 . 6 :

 56 Figure 5.6 : Rate and extent of aseismic surface creep along the Ismetpaşa section of the North Anatolian Fault. a) A mosaicked map of fault-parallel horizontal velocity field on SAR image tracks T479 and T207. Red line shows the creeping section of the NAF and the blue pentagon indicates the location of the micro-GPS network. White star represents the location of the wall where creep was discovered by Ambraseys [1970]. White arrows show the extents previously found by Cakir et al. [2005] and Kaneko et al. [2013]. b) Creep rates with error bars along the fault are estimated from the InSAR velocities on track T479 (pink color) and track T207 (green color).

Figure 5 . 7 :

 57 Figure 5.7 : Time series of line-of-sight InSAR (blue circles) and GPS (red squares) velocities (blue pentagon shown in Figure 5.6). The LOS velocities represent the mean of all pixels in a circle of ~600 m diameter to the north and south of the fault around the GPS network. The general trend and decay of creeping rate from InSAR time series are in good agreement with GPS time series.

Figure 5 . 8 :

 58 Figure 5.8 : Modeling of aseismic slip distribution. a) Residual LOS velocities, obtained by the removal of the long-term signal due to interseismic loading and unwrapping, atmospheric and orbital errors, are used to model the aseismic slip on the fault. The blue circular anomaly located around the town of Orta is most likely due to the postseismic deformation of the 6 June 2000 Orta earthquake (Mw=6.0). Red arrows on the fault (white lines) indicate the tips of the modeled fault shown in Figure 5.9. Dashed lines show the profiles in Figure 5.8b. b) Observed (green and purple points) and modeled residual velocities (red lines) along the profiles perpendicular to the fault.

  Figure 5.8b illustrates that the model explains the LOS data reasonably well (~1.25 mm/yr RMS, Figure E.3). As expected, checkerbox tests show that slip resolution decreases with increasing depth, but as shown in supplementary Figure E.4 the InSAR data have an adequate resolution in constraining the shallow slip (< 5 km) on the fault.

Figure 5 .

 5 Figure 5.9 : (a) Variation of surface creep rate along the fault, (b) depth distribution of the variable aseismic slip on the Ismetpaşa creeping segment. Red arrow indicates the position of the geodetic network located 3.5 km east of the train station near Hamamlı village at Ismetpaşa. Slip is heterogeneously distributed along the fault and confined mostly to uppermost 5 km of the seismogenic crust with a maximum slip of ~20±2 mm/yr 20 km west of Ismetpaşa. (c) Uncertainty of the slip distribution with depth obtained from inversions of 200 InSAR data sets perturbed with synthetic noise.

  have studied the spatial distribution of aseismic creep on the Ismetpaşa segment of the NAF using Envisat ASAR data between 2003 and 2010. The surface velocity field obtained with the PSI technique provides a tighter constraint on the characteristics of surface creep compared to conventional InSAR techniques. The results reveal a surface creep rate of 8±2 mm/yr at Ismetpaşa, which reaches a maximum of 20±2 mm/yr 20 km to the east. Aseismic slip releases every year a moment of 6.2 x 1016 Nm, which is equivalent of an earthquake of Mw = 5.1. It implies that a significant portion of the fault is locked and accumulates interseismic strain to be released coseismically as demonstrated with the 1943, 1944 and 1951 earthquakes. High creep rates coincide mostly with the 1951 and eastern part of the 1944 earthquake ruptures. Measurements over the last 60 years show that creep on the Ismetpaşa segment has graded with time into a steady-state rate after the 1944 and/or 1951 earthquakes (Figure5.11), suggesting that it was probably triggered as postseismic afterslip following the 1944 earthquake as was found with the surface deformation following the 1999 Izmit earthquake[START_REF] Cakir | Onset of aseismic creep on major strike-slip faults[END_REF].

Figure 5 .

 5 Figure 5.10 : a) Geology map of the study region simplified from Herece and Akay [2003] with surface creep rates along the North Anatolian Fault obtained in this study. Geological units presumably involved in creeping are shown in colors and the others are labeled in white with abbreviations. Black and red lines represent the active fault and the creeping segment, respectively. The eastern end of the creeping section can be clearly seen in the inset rectangle. b) Creep rates and error ranges for two individual tracks are indicated in purple and green colors as in Figure 6.

Figure 5 . 11 :

 511 Figure 5.11 : Time history of surface creep at Ismetpaşa as reported by various studies following the 1944 earthquake (after Cakir et al., [2005]). Horizontal and vertical bars are the time window and error range of measurements, respectively. The question mark corresponds to the unknown effect of the 1951 earthquake on creep rate. Curve shows the fit of the exponential relaxation function to the change of the creep rate with time [Savage, 2005].

  moderate-large earthquakes in the Rif Mountain of northern Morocco expose postseismic deformation that may constitute a significant part in the earthquake cycle. We use the PSI technique with elastic dislocation models and geology along the creeping section of the NAF at Ismetpaşa, to map and deduce the velocity field and the aseismic slip distribution. Revealing the spatiotemporal nature of the creep helps us associate the creep with potential lithological controls, hence providing a new perspective to better understand the underlying causes and mechanisms. The PSI analysis of Envisat ASAR images between 2003 and 2010 reveals a clear picture of the surface creep along the fault and a new interseismic velocity field transitioning gradually between the creeping and the locked fault sections. The creep rate is found to fluctuate along a 100-km long section of the fault in a manner similar to that along the Hayward fault, reaching a maximum of ~20±2 mm/yr, close to the far field plate velocity (~25±1.5 mm/yr). At Ismetpaşa, it is in the range of 8±2 mm/yr, consistent with the previous geodetic observations. The creeping section appears to extend 30 km further east than those previously reported. Modeling of the PSI data reveals a heterogeneous creep distribution at depth with two main patches confined mostly to the uppermost 5 km portion of the seismogenic crust, releasing annually 6.2 x 10 16 Nm (Mw 5.1) geodetic moment. Our analysis combined with previous studies suggests that creep might have commenced as postseismic deformation following the 1944 earthquake, and has evolved to stable fault creep with time. There is a correlation between aseismic surface creep and the geology along the fault as it is in major part associated to rocks with low frictional strength such as the andesiticbasaltic, limestone and serpentine bodies within the fault zone. In the three individual case studies presented in this thesis, InSAR time series provide valuable information about subtle postseismic deformations. Two different types of active fault have been chosen to study postseismic deformation; a thrust fault and a right-lateral strike-slip fault. Remarkable signals of postseismic displacements have been observed in both cases following moderate to large-sized earthquakes. The InSAR analysis reveals diverse indications for two individual postseismic case studies. While the thrust fault mechanism shows opposite sign for coseismic and postseismic surface displacements, the right-lateral strike-slip shows similar sign in both coseismic and postseismic surface displacements. The third case study reveals a clear picture of surface creep, and suggests that it might have commenced as postseimic deformation about 70 years ago after two large earthquakes (Mw 7.3 -6.9). Although with relatively large time acquisition (35 days), the use of Envisat SAR images allowed the study of coseismic and postseismic deformation for moderate and large earthquakes. The perspective of using new generations of SAR images from TerraSAR-X and Sentinel (12 to 3 days image acquisition) may increase the resolution of interferograms and provide a significant reduction on temporal decorrelation phenomena. Hence, the new generation SAR sensor constellations involving multi-frequency coupled with reduced revisit time options seem extremely promising for the understanding of spatiotemporal behavior of the crustal deformation. The four possible mechanisms for postseismic deformation that could cause significant displacements near the rupture measurable by geodetic techniques are visco-elastic, poro-elastic, afterslip, and fault zone collapse or strengthening. The prominence of postseismic deformation mechanisms suggests a systems analysis of the postseismic deformation phenomena. The contribution of each of these phenomena to the observed displacement pattern can be inferred from the wavelength, pattern, and temporal decay of the displacement amplitudes.

Figure D. 2 :

 2 Figure D.2 : Time series of ascending LOS for Al Hoceima region between 2003 and 2007. Each image represents the incremental displacement towards the satellite since the time of the previous image, relative to pixels in the northwest corner.

Figure D. 3 :

 3 Figure D.3 : Model of 3.3-year cumulative LOS postseismic surface deformation predicted by the modeled slip distribution shown in Figure 4.11. Black lines show the top of the modeled fault. White dashed lines show the bottom of the modeled fault.

Figure D. 4 :

 4 Figure D.4 : Model of 3.3-year cumulative LOS postseismic surface deformation predicted by the two fault rupture inversions according to aftershocks distribution. Black line shows the main modeled fault. Blue line indicates the fault branch obtained using aftershocks distribution.

Figure D. 5 :

 5 Figure D.5 : Residual maps obtained after subtracting the synthetic InSAR data (Figure D.3) from the observed data (shown in Figure 4.10). Residuals after inversion of (a) the ascending and (b) the descending data alone, and (c, d) jointly with a lower weighting for the descending data. Black line shows the main coseismic model fault, and blue line is the secondary fault branch.

Figure D. 6 :

 6 Figure D.6 : Model of 3.3-year cumulative LOS postseismic surface deformation predicted by the two fault rupture inversions according to PS LOS change in the southern section of the fault. Black line shows the main modeled fault. Pink line indicates the fault branch obtained using PS LOS displacement fields.

Figure D. 7 :

 7 Figure D.7 : Residual maps obtained after subtracting the synthetic InSAR data (Figure D.5) from the observed data (shown in Figure 4.10). Residuals after inversion of (a) the ascending and (b) the descending data alone, and (c, d) jointly with a lower weighting for the descending data. Black line shows the main coseismic model fault, and pink line is the secondary fault branch.

Figure D. 8 :

 8 Figure D.8 : Resolution test using checker-box approach with 0.10 m slip at different depths for each cell.

Figure E. 3 :

 3 Figure E.3 : Residual LOS velocity field.

Figure E. 4 :

 4 Figure E.4 : Resolution test using checker-box approach with 0.10 m slip at different depths for each cell.

Table 3 . 1 :

 31 Large and moderate earthquakes with thrust mechanisms along the Tell Atlas. ....................................................................................................... 24

	ABBREVIATIONS
	CGPS	: Continuous GPS
	DEM	: Digital Elevation Model
	FFT	: Fast Fourier Transform
	GARCH	: Generalized Autoregressive Conditional Heteroskedasticity
	GIS	: Geographic Information Systems
	GPS	: Global Positining System
	IGN	: Instituto Geografico Nacional
	InSAR	: Interferometric Synthetic Aperture Radar
	LOS	: Line of sight
	NAF	: North Anatolian Fault
	PS	: Persistent Scatterers
	PSI	: Persistent Scatterer InSAR
	SAR	: Synthetic Aperture Radar
	SB	: Small Baseline
	SBI	: Small Baseline InSAR
	SDFP	: Slowly-Decorrelating Filtered Pixels
	SNR	: Signal to Noise Ratio
	SRTM	: Shuttle Radar Topography Mission
	StaMPS	: Stanford Method of Persistent Scatterer

ET MODELISATION DE LA DEFORMATION CRUSTALE PAR TRAITEMENT DES SERIES TEMPORELLES InSAR SUR UNE SELECTION DE FAILLES ACTIVES DE LA ZONE DE CONVERGENCE AFRIQUE-EURASIE RESUME

	Un Chapitre I d'introduction présente les éléments fondamentaux de la sub-centimétriques dans la zone épicentrale. Les résultats montrent l'existence de Eurasie (Ibérie), la collision implique une tectonique avec échappement des blocs et soulèvements cosismiques. La mise en évidence des déformations postsismiques
	technique InSAR en géodésie spatiale et sa relation aux travaux de tectonique active deux zones de déformation postsismiques en subsidence le long de la côte, localisées la fragmentation du Rif. liées au séisme d'Al Hoceima (Rif, Maroc) contribue à la localisation précise du
	initiés depuis 20 ans, suite au séisme de Landers en 1992 (Mw 7.4 en Californie). L'InSAR est une méthode robuste pour la mesure des déformations de surface dont la précision peut atteindre le millimètre par une résolution spatiale réalisée à l'aide de la télédétection (imagerie spatiale). Les méthodes ASAR (Advanced multi-temporal InSAR time series) des séries multi-temporelles appelées « Persistent Scatterer (PSI) » et « Small Baseline (SBI) » offrent l'avantage d'un traitement simultané des images SAR multiples, acquises par séries temporelles, augmentant aux mêmes emplacements des soulèvements cosismiques obtenus par l'InSAR. La modélisation des déformations postsismiques par inversion des données de surface, utilisant les dislocations élastiques en demi-espace homogène sur des ruptures triangulaires, suggère une déformation en « afterslip » sur une portion superficielle (< 5 km) de la faille cosismique, ceci en accord avec les résultats GPS. La répartition en surface des déformations postsismiques comparée à celle des sédiments meubles et à la fluctuation de la nappe phréatique (par pompage agricole local) indique séisme de 2004, et à l'identification des déplacements co-et postsismiques sur une Le Chapitre V est consacré à l'étude des mouvements lents le long de la faille nord Anatolienne en Turquie. L'utilisation de la méthode PSI associée à la modélisation de la déformation de surface en dislocation élastique, combinée aux caractéristiques géologiques observées le long de la faille dans la localité de Ismetpaşa nous a permis de déduire le champ de vitesse et l'étendue de la zone de déformation lente (par opposition à la zone de faille bloquée). Les caractéristiques spatio-temporelles de cette déformation montrent un contrôle lithologique potentiel faille « aveugle ». Les caractéristiques des déplacements lents près de la localité de Ismetpaşa montrent le rôle d'une rupture superficielle lente par rapport aux aspérités bloquées, et l'influence de l'environnement géologique sur les propriétés mécaniques de la faille nord Anatolienne. Pour les trois cas d'étude présentés dans cette thèse, l'analyse des séries temporelles InSAR donne des informations décisives sur les déformations ANALYSE Les travaux de cette thèse de Doctorat ont été menés dans le cadre de l'accord ainsi la couverture spatiale et la résolution (avec calcul des incertitudes) du signal l'existence d'une déformation d'origine non-tectonique (par compaction). La possible le long de la zone de faille, ce qui ouvre une perspective nouvelle sur les postsismiques. Deux types de faille active, l'une en mécanisme inverse et l'autre en
	en co-tutelle entre l'Université de Strasbourg (EOST) et Istanbul Technical des zones à faible déformation. En effet, les calculs sur le signal en surface tiennent déformation postsismique (sur ~7 ans) rapportée au moment sismique cumulé causes des mécanismes des ruptures sismiques. L'analyse des 55 images Envisat décrochement, ont été sélectionnés pour illustrer la déformation postsismique. Des
	University (Dept. of Geology), avec l'octroi d'une bourse d'étude annuelle de compte de la réduction du bruit d'acquisition, du délai d'enregistrement due aux équivaut à l'occurrence d'un séisme de magnitude Mw 6.3. Par conséquent, la ASAR acquises entre 2003 et 2010, illustre clairement la zone de déformation lente signaux significatifs et remarquables ont été observés pour les deux types de faille et
	l'Ambassade de France à Ankara, une bourse d'excellence EIFFEL de 10 mois, et un caractéristiques de l'atmosphère, des erreurs de résolution sur la topographie, et des déformation postsismique cumulée et les contraintes associées peuvent avoir des et montre un champ de vitesse intersismique graduel entre la zone en « creep » et la dans le cas de séismes modérés ou forts. L'analyse InSAR révèle l'existence de
	support financier de 8 mois de « TUBITAK 2214B -joint Ph.D. ». incertitudes sur la position orbitales du satellite lors de l'acquisition de l'image SAR. implications notables sur le modèle de cycle sismique et de la récurrence des forts partie bloquée de la faille. Le taux de déformation lent varie le long des 100 km de
	Comparé à la méthode InSAR désormais classique, les approches PSI et SBI séismes dans la région d'Alger. faille d'une façon comparable à la zone de « creep » de la faille de Hayward (branche La zone de convergence de plaques Afrique -Eurasie comporte des failles permettent l'analyse simultanée de la déformation de surfacepar pixel (ou parcelle Le Chapitre IV présente une analyse des déformations cosismique et de la faille de San Andreas en Californie), et atteint un maximum de ~20±2 mm/an, capables de générer de forts séismes destructeurs. L'objectif de cette thèse est une meilleure compréhension du comportement de ces failles, et du cycle sismique d'image) et empilement d'images SAR par séries temporelles. postsismique, liées au séisme du 24 février 2004 à Al Hoceima (Mw 6.4, Rif, nord proche de la vitesse des plaques (~25±1.5 mm/an). A Ismetpaşa, la vitesse du
	associé, par l'analyse des déformations co-, post-et inter-sismiques enregistrées en Le Chapitre II décrit les principes des séries temporelles PSI et SBI et leur Maroc), obtenues par un traitement des images SAR utilisant la technique SBI. A déplacement lent qui est de 8±2 mm/an, est comparable aux valeurs géodésiques des
	surface, dans la zone de convergence. Une attention particulière est portée aux application à l'étude des déplacements potsismiques et lents le long des failles noter que pour cet exemple, la localisation de la faille cosismique etait très imprécise études précédentes. La modélisation des données PSI révèle une répartition
	déformations lentes et à leur part dans le cycle sismique, mesurées en surface et actives. L'analyse de ces déplacements par des investigations détaillées le long des étant donné l'absence de ruptures bien identifiées en surface. Le déplacement en hétérogène des mouvements lents dans la couche sismogène (en profondeur), avec
	analysées à l'aide des techniques InSAR (Synthetic Aperture Radar Interferometry), failles peut contribuer à une meilleure compréhension des processus sismogènes et surface postsismique a été cartographiée en utilisant des images Envisat ASAR l'apparition de deux zones de rupture principales, limitées aux premiers 5 km depuis
	In order to buildup reliable and accurate models of the et modélisées par les méthodes de la dislocation élastique. fonctionnement des ruptures sismiques. L'étude de la déformation crustale par les acquises en mode ascendant (15 images) et descendant (15 images). La faute la surface, et relâchant 6.2 x 1016 N.m (Mw = 5.1) de moment géodésique. Nous
	techniques InSAR est consolidée par une comparaison aux résultats des données coseismique est cependant nécessaire une révision à la lumière de déformation reconnaissons ici une corrélation entre des déplacements lents asismiques et les earthquake cycle, it is important to develop further the study of small surface Cette thèse comporte VI chapitres centrés sur l'application des méthodes GPS, l'analyse sismotectonique et les caractéristiques géologiques locales, afin de postseismique d'affiner le meilleur modèle de défaut suggéré dans la pointe sud de la caractéristiques principales des roches environnantes (andésite basaltique, calcaire et displacements also linked to moderate or large sized events on Earth with new tools InSAR et multi-temporelles InSAR (PSI et SBI), avec analyse des déformations en mettre en évidence les déplacements co-et post-sismiques, lents ou rapides, en faille. L'analyse et la modélisation des données de surface impliquent l'existence serpentinites) montrant des valeurs de friction interne et de résistance au cisaillement and techniques. These techniques should see more development with the use of the surface et en profondeur des zones sismiques. Les principaux chapitres traitent surface. Cette contribution à la connaissance du cycle sismique aux abords des failles d'une rupture décrochante « aveugle », dextre, de direction NW-SE, avec courbure relativement basses le long de la faille. new generation SAR images (Sentinel, TerraSAR-X). The analysis of every significant seismic event may reveal new characterizations on the physics of earthquakes. notamment des déformations postsismiques liées aux séismes du 21 mai 2003 à actives devrait permettre une meilleure évaluation du cycle sismique, du ou zone de relais sur la gauche liée à la déformation postsismique, sur la zone de La conclusion générale (Chapitre VI) résume les principaux résultats de la Zemmouri (Mw6.8, Algérie), du 24 février 2004 à Al Hoceima (Mw 6.4, Maroc), et comportement à court et long terme de la déformation crustale et du potentiel pour déformation cosismique. Bien-que la tectonique crustale du Rif est constituée de thèse et montre comment les déplacements lents en surface associés à la déformation aux déplacements lents le long du segment Ismetpaşa de la faille nord-Anatolienne l'occurrence des séismes futurs. chevauchements et pli-failles inverses d'âge tertiaire, la tectonique fini-Quaternaire postsismique sur des failles aveugles ou cachées, et aux déplacements asismiques, (Turquie). Les images SAR ont été obtenues par les projets Category-1 2532 et Le Chapitre III montre les détails de la technique SBI appliquée à l'étude des (Pleistocène supérieur) indique des épisodes extensifs de direction E-W liés à des peuvent être identifiés et caractérisés à partir des analyses multi-temporelles InSAR. AOTR-2436 de l'Agence Spatiale Européenne, et du programme « Geohazard déformations postsismiques liées au séisme du 21 mai 2003 à Zemmouri (Mw6.8, failles normales de direction N-S, associés à des failles en décrochement conjuguées Pour le séisme de Zemmouri (Atlas du Tell, Algérie), notre étude confirme Supersites ». Atlas du Tell, nord Algérie). Les séries temporelles InSAR obtenues à partir de 31 de direction NW-SE et NE-SW.Dans ce secteur de limite des plaques Afrique-l'existence d'une rupture cachée au large dans la zone en mer, avec un « afterslip »
	images Envisat ASAR acquises de 2003 à 2010, révèlent des déplacements de l'ordre superficiel lié à une rupture complexe avec subsidence côtière co-localisée aux
	xxvi xxviii	xxv xxvii xxix

Table 3 . 1 :

 31 Large and moderate earthquakes with thrust mechanisms along the Tell Atlas.

	Location	Date	Longitude (deg)	Latitude (deg)	Mw
	Orleansville	9 Sep 1954	1.47	36.28	6.7
	El Asnam	10 Oct 1980	1.36	36.18	7.3
	Tipaza	29 Oct 1989	2.92	36.84	5.9
	Mascara	18 Aug 1994	-0.03	35.40	5.7
	Ain Temouchent	22 Dec 1999	-1.45	35.34	5.7
	Beni Ourtilane	10 Nov 2000	4.69	36.71	5.7
	Zemmouri	21 May 2003	3.65	36.83	6.8

This Ph.D. thesis is conducted in the frame of the "co-tutelle" scholarship (EOST-ITU) provided by French Embassy in Ankara. In addition, a 10-month scholarship « Bourse excellence Eiffel », and 8-month scholarship « TUBITAK 2214B -joint Ph.D. » were other sources of support for the preparation of this thesis. In addition, SAR images were obtained from the Category 1 projects 2532 and AOTR-2436 of the European Space Agency and the Geohazard Supersites program. I am obliged to acknowledge them for their generosity.

Last but not the least, my sincerest gratitude goes to my family; my father Mehmet, my mother Meral

InSAR Observations

In order to examine and model the surface deformation associated with the 2004 Al Hoceima earthquake, the coseismic and postseismic surface displacement fields have been mapped using InSAR technique.

Coseismic InSAR data

We use the ASAR data of Envisat satellite's to examine the coseismic surface displacement of the earthquake on both ascending and descending geometry (Figure 4.1). Interferograms have been calculated using DORIS InSAR processing software [START_REF] Kampes | Radar interferometry with public domain tools[END_REF] and precise satellite orbits from Delft University [START_REF] Scharoo | Precise orbit determination and gravity field improvement for the ERS satellites[END_REF]]. Topographical effects have been removed from the interferograms using the SRTM 3-arcsec (~90 m) posting digital elevation model [START_REF] Farr | Shuttle radar topography mission produces a wealth of data[END_REF]. The interferograms have been filtered using a weighted power spectrum technique [START_REF] Goldstein | Radar interferogram filtering for geophysical applications[END_REF]].

The interferograms are shown in Figure 4.4 with wrapped fringes, each representing half a wavelength (i.e. 2.83 cm) range change along the radar line-ofsight (LOS). Having the shortest temporal (7 months) and spatial (16 m) baseline, the ascending interferogram experienced minimum decorrelation (Figure 4.4); which occurs due to large baselines, agricultural activities within the time span between image pairs (mainly descending pair), and steep slopes in the ragged terrain. On the contrary, both the ascending and the descending interferograms though include postseismic deformation, which should be considered, since they cover all of the recorded aftershocks. The descending interferogram shows three lobes of deformation with a maximum of five fringes (~12 cm) in the eastern lobe, whereas two lobes of deformation can be seen in ascending interferogram with a peak-to-peak line-of-sight displacement of about 23 cm (eight fringes). Although the two lobes in the coastal regions are clearly visible in the both interferograms, the southern lobe is rather obscured due to the poor coherence. The only common lobe in both interferograms is the one located immediately southwest of Al Hoceima city (Figure 4.4). The continuity of the fringes across the north portion of the fault in the ascending interferogram implies that the earthquake rupture did not reach the surface, which is also confirmed by the absence of the aftershocks above 3 km of depth (Figure 4.3) [van der Woerd et al., 2014].

After testing faults with varying dip direction and angles, the best model is determined by a N50ºW-trending right-lateral strike-slip fault of about 21 km that dips 78º-79º eastward with a restraining bend or step to the left around 2 km (Figure 4.8 and 4.9). The location and the azimuth of the north section of the fault is well constrained, as we are forced to place the fault between the two lobes of the ascending interferogram (Figure 4.4b). This fault geometry is the same as that of [START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF] in the northern section, except its southernmost section where the postseismic surface deformation and aftershocks distribution require a bend or step to the left and NW-SE trending planar fault after the bend. However, the presence of the poor coherence does not allow us to better constrain the location or connection of the bend or step. We assume a continuous fault rupture with a bend to the left, as it is a common feature along strike-slip faults. geodetic moment determined from modeling is also in good agreement with those obtained from seismological observations [Ait Brahim et al., 2004;[START_REF] Stich | Source analysis of the Mw 6.3 2004 Al Hoceima earthquake (Morocco) using regional apparent source time functions[END_REF], and InSAR studies [START_REF] Akoglu | The 1994-2004 Al Hoceima (Morocco) earthquake sequence: Conjugate fault ruptures deduced from InSAR[END_REF][START_REF] Biggs | Fault identification for buried strike-slip earthquakes using InSAR: The 1994 and 2004 Al Hoceima, Morocco earthquakes[END_REF][START_REF] Cakir | Surface deformation associated with the Mw 6.4, 24 February 2004 Al Hoceima, Morocco, earthquake deduced from InSAR: implications for the active tectonics along North Africa[END_REF].

As shown in Figure 4.8, the slip model successfully reproduces the main features of the observed interferograms with RMS (root mean square) misfits well below an individual fringe (2.83 cm).

While the descending residual interferograms show no clear remaining fringes, the ascending residual interferograms contain some residuals in the near field after inversions. Furthermore, the depth of the coseismic slip along the south section could not be well constrained due to the poor coherence and absence of aftershocks in this region, where some residual fringes are present. The presence of deep coseismic slip with large amplitudes suggests that the earthquake probably nucleated at depths below 8 km (Figure 4.9), which may explain why the rupture did not break the surface. Consequently, some of the remaining fringes in the residual interferograms are most probably due to atmospheric artifacts, unmodeled fault complexity in the near field and/or contribution of the aftershocks (M > 5) to the interferograms.

Modeling of postseismic deformation

In Mapping Tools (GMT) [START_REF] Wessel | New improved version of Generic Mapping Tools released[END_REF][START_REF] Wessel | Generic Mapping Tools: Improved version released[END_REF] with a 1-km search radius. Then we contour the data every 0.2 cm taking into account the sampling interval for each contour length to avoid the unrealistic weighting of the longer contours. We invert for the optimal slip distribution and seek models that minimize the misfit, while preserving smoothness of the model afterslip distribution. Smoothing (i.e., 0.3) and right-lateral strike-slip constraints are applied to avoid models with oscillating slip patterns that are favored by a free inversion without such additional constraints. We do not apply any dip-slip constraint for the postseismic models with regard to diminishing the inversion parameters and maintaining the simplicity. We apply a zero slip constraint on the fault edges, except the topmost patches where the inverted data are sufficient to obtain a reasonable slip.

In our modeling, we invert the ascending and descending data sets separately and jointly to see similarities and differences they predict (Figure 4.11 and 4.12). As can be seen from

Introduction

Understanding the mechanics of major active faults is important for better understanding of the earthquake physics and reliable seismic hazard evaluations [START_REF] Carpenter | Weakness of the San Andreas Fault revealed by samples from the active fault zone[END_REF]. The majority of active faults may be locked, accumulating strain over a long period of time and releasing it abruptly by producing earthquakes, some faults freely slip over time, accumulating little or no strain and generating no significant earthquakes [START_REF] Thatcher | Systematic inversion of geodetic data in central California[END_REF][START_REF] Burford | Slip on the San Andreas fault in central California from alignment array surveys[END_REF]. Knowledge of the extent and rate of aseismic slip on the fault plane is therefore important parameters for reliable assessment of seismic hazard as it effectively reduces the fault surface area capable of rupture in earthquakes. Its spatiotemporal variation along faults has also important implications for forecasting the timing, locations, and potential sizes of future earthquakes and for understanding the fault behavior [Bürgmann et al., 2000].

The Ismetpaşa creeping segment was ruptured by the 1944 Bolu-Gerede (M=7.3), and 1951 Kurşunlu (M=6.9) earthquakes, part of the westward migrating earthquake sequence of the NAF during the 20 th century (Figure 5.1) [START_REF] Barka | Strike-slip fault geometry in Turkey and its influence on earthquake activity[END_REF][START_REF] Barka | Slip distribution along the North Anatolian fault associated with the large earthquakes of the period 1939-1967[END_REF][START_REF] Stein | Progressive failure on the North Anatolian fault since 1939 by earthquake stress triggering[END_REF]. Based on the railway maintenance reports, [START_REF] Ambraseys | Some characteristic features of the Anatolian fault zone[END_REF] estimated a rapid right-lateral surface creep of 50 mm/yr following the 1944 earthquake until the 1951 event. The spatiotemporal evolution of the surface creep at Ismetpaşa remained, however, unknown until the mid 2000s despite its discovery in the late sixties [START_REF] Ambraseys | Some characteristic features of the Anatolian fault zone[END_REF]. Offset measurements on the walls of the railway station at Ismetpaşa town suggested that the creep rate had decreased to 20 mm/yr between 1957 and 1969 [START_REF] Ambraseys | Some characteristic features of the Anatolian fault zone[END_REF]. A micro-geodetic network installed across the fault at Ismetpaşa in 1972, added with other geodetic measurements (LIDAR and InSAR) along the creeping segment show an exponential or logarithmic decrease of creep rate reaching a steady slip rate of about 9 mm/yr over the last decade [START_REF] Aytun | Creep measurements in the Ismetpaşa region of the North Anatolian Fault Zone, in: Multidisciplinary approach to earthquake prediction[END_REF][START_REF] Eren | Strain analysis along the North Anatolian fault by using geodetic surveys[END_REF][START_REF] Deniz | Determination of crustal movement in Turkey by terrestrial geodetic methods[END_REF][START_REF] Cakir | Creeping along the Ismetpaşa section of the North Anatolian Fault (Western Turkey: Rate and extent from InSAR[END_REF][START_REF] Kutoglu | Determination of 30-year Creep on the Ismetpaşa segment of the North Anatolian Fault using an old geodetic network[END_REF][START_REF] Karabacak | Monitoring aseismic creep along the North Anatolian Fault (Turkey) using ground-based LIDAR[END_REF][START_REF] Ozener | Quantifying aseismic creep on the Ismetpaşa segment of the North Anatolian Fault Zone (Turkey) by 6 years of GPS observations[END_REF][START_REF] Kaneko | Interseismic deformation and creep along the central section of the North Anatolian fault (Turkey): InSAR observations and implications for rate-andstate friction properties[END_REF]. Using the conventional InSAR method, [START_REF] Cakir | Creeping along the Ismetpaşa section of the North Anatolian Fault (Western Turkey: Rate and extent from InSAR[END_REF] identified, for the first time, a 70 km-long lateral extent of the creeping section, which is roughly confirmed later on by [START_REF] Kaneko | Interseismic deformation and creep along the central section of the North Anatolian fault (Turkey): InSAR observations and implications for rate-andstate friction properties[END_REF] using stacking of independent InSAR data (ALOS). [START_REF] Barka | Strike-slip fault geometry in Turkey and its influence on earthquake activity[END_REF][START_REF] Şaroğlu | Active Fault Map of Turkey, General Directorate of Mineral Research and Exploration[END_REF]. The dashed rectangles are the Envisat image frames with track numbers used in this study.

Chapter VI :

CONCLUSIONS

the case of 2003 Zemmouri postseismic deformation) and correlate the estimated creep rates obtained from InSAR analysis and modeling (e.g. the case of Ismetpaşa aseismic slip). Furthermore, ground water level changes data was critical to detect the non-tectonic origin subsidence in the Mitidja Basin for the Zemmouri study.

Consequently, InSAR alone may not be sufficient enough to constrain the needed parameters for postseismic or aseismic slip, so as to field observations, additional measurements and/or geological analysis may be necessary for better estimations in some cases.

APPENDICES