Nos travaux de recherche ont pour objectif de résoudre le problème de la géodétection des réseaux enterrés. Plusieurs méthodes sont utilisées actuellement mais présentent des limites dues à la nature du sol, aux matériaux des canalisations et au produit transporté. Notre objectif est de proposer une nouvelle approche basée sur la fusion de quatre méthodes de détection et sur la récolte de plusieurs informations qui seront représentées sous forme de connaissances et permettront de raisonner à différents niveaux d’abstraction, pour détecter avec un niveau de confiance, les canalisations enterrées indépendamment de leur matériau, du produit qu’elles transportent et du sol dans lequel elles sont enterrées / Our work aims to solve the problem of reliable detection of underground networks by optimization of the existing methods. Four methods are planned to identify the underground pipelines but they have limits and depend on many factors. Our investigation aims to solve the problem of reliable detection of underground networks by aggregation of the existing methods and reasoning at different abstraction levels. For that purpose, we must be able to provide an accurate geo-detection of underground networks regardless of their material, their function or the soil in which they are buried. The information collected in the field or soil by these detection methods will be merged in order to achieve and obtain an accurate and reliable single result of geo-detection. For that, we need to check independently these distinct methods and then to aggregate the information/data they provide. Besides, the first step will consists of the representation of this information into symbolic knowledge. The second step is to overcome the limitations of current methods to provide a reliable and expressive reasoning system

Extensive overwash occurred along Florida's Atlantic and northern Gulf facing barrier islands during the passages of Hurricanes Frances, Ivan, and Jeanne in 2004. These high-energy storm events provided a unique opportunity to study the spatial depositional patterns and internal sedimentary architecture of fresh washover deposits resulting from inundation to collision regime overwash events. Sedimentological characteristics and 3-D internal architecture of the washover deposits were studied through coring, trenching, sediment analysis, ground penetrating radar (GPR) surveys, and pre- and post-storm aerial photography and LiDAR topographic survey data. The cross-shore extent of washover deposition is controlled by sediment supply, accommodation space, and the extent of cross-shore penetration of overwash flow. Antecedent morphology of the beach or barrier island is the primary factor governing sediment supply and accommodation space. Antecedent morphology coupled with spatio-temporal factors including storm position, intensity, and duration govern the extent of landward excursion of overwash flow. Washover deposition ranges from thin deposits, limited in cross-shore extent to the beach berm, to extensive sheet-like sediment bodies extending across an entire barrier island profile. Four sedimentary facies are recognized, which can be related to antecedent morphology. Berm facies, dominates the beach and seaward side of the foredune, and is characterized by a basal erosional surface and seaward dipping planar stratification. Back-berm facies extends landward from the dune crest down the backside of the foredune, exhibits little evidence of erosion along the basal contact, and is dominated by landward inclined stratification. Platform facies, largely confined to the interior platform, exhibits little evidence of erosion along the pre-storm surface, and horizontal to gently landward dipping parallel stratification, which merges landward with, and commonly overlies steeply landward dipping foreset stratification. Antecedent hummocky dunes may be preserved within platform facies. The landward most facies, backbay facies is dominated by subaqueous deposition within the back bay, and is characterized by steeply landward dipping tabular foreset and sigmoidal stratification. In the longshore direction, backbay facies exhibit trough and mound GPR reflective patterns, representing washover sediment ridges and troughs oriented parallel to the primary flow direction, and illustrate the highly 3-dimesional nature of the washover deposits.

Ground penetrating radar (GPR) has been extensively utilized as a highly efficient and non-destructive testing method for infrastructure evaluation, such as highway rebar detection, bridge decks inspection, asphalt pavement monitoring, underground pipe leakage detection, railroad ballast assessment, etc. The focus of this dissertation is to investigate the key techniques to tackle with GPR signal processing from three perspectives: (1) Removing or suppressing the radar clutter signal; (2) Detecting the underground target or the region of interest (RoI) in the GPR image; (3) Imaging the underground target to eliminate or alleviate the feature distortion and reconstructing the shape of the target with good fidelity. In the first part of this dissertation, a low-rank and sparse representation based approach is designed to remove the clutter produced by rough ground surface reflection for impulse radar. In the second part, Hilbert Transform and 2-D Renyi entropy based statistical analysis is explored to improve RoI detection efficiency and to reduce the computational cost for more sophisticated data post-processing. In the third part, a back-projection imaging algorithm is designed for both ground-coupled and air-coupled multistatic GPR configurations. Since the refraction phenomenon at the air-ground interface is considered and the spatial offsets between the transceiver antennas are compensated in this algorithm, the data points collected by receiver antennas in time domain can be accurately mapped back to the spatial domain and the targets can be imaged in the scene space under testing. Experimental results validate that the proposed three-stage cascade signal processing methodologies can improve the performance of GPR system.

The ASCE confers an overall D+ grade to American infrastructure, while the NAE lists the restoration and improvement of urban infrastructure as one of its grand engineering challenges for the 21st century, indicating that infrastructure renovation and development is a major challenge in the US. Furthermore, according to the UN World Urbanization Prospects, about 55% of the world's population lives in urban areas and this percentage is set to grow, especially in Africa and Asia. The growth of urban population poses challenges to the expansion of underground infrastructure, such as water, sewage, electricity and telecommunications. Localization and mapping of underground infrastructure are fundamental for infrastructure maintenance and development. Ground penetrating radar (GPR) is a remote sensing method capable of detecting subsurface assets that has been used in the localization and mapping of underground utilities. This thesis contributes improvements of GPR systems and imaging algorithms towards smarter infrastructure, specifically: Application of GPR imaging algorithm to improve GPR data readability and generate augmented reality (AR) content; Use of photogrammetric methods to improve GPR positioning for underground infrastructure localization and mapping.

This dissertation consists of three projects utilizing electric and electromagnetic (EM) methods to better understand critical-zone hydrogeologic conditions in select Florida wetlands and waters. First, a time-lapse electrical resistivity (ER) survey was conducted in section of mangrove forest on a barrier island in southeast Florida to image changes in pore-water salinity in the root zone. ER data show the most variability in the root zone over a 24-hour period, and, generally, the ground is more resistive during the day than overnight. Second, a suite of three-dimensional forward models, based on varying lateral boundaries and conductivities typical of a coastal wetland, were run to simulate the EM response of a commerical electromagnetic induction instrument crossing over said boundaries. Normalized profiles show the transition is sharper in a hypersaline regime than one where freshwater and clay are present. Furthermore, enough variability exists in hypersaline regimes to justify collecting profile measurements in multiple coil configurations to constrain the nature of a lateral boundary. Also, under certain circumstances, there are kinks in the EMI response even across abrupt boundaries due to concentrated current density at a layer's edge. Lastly, geophysical surveys were conducted at six wetlands in west-central Florida to characterize potential hydrostratigraphic units and compare/contrast them to the current conceptual model for cypress dome wetlands. ER was used to image the geometry of the top of limestone; ground penetrating radar (GPR) was used to image stratigraphy beneath and surrounding wetlands. These wetlands can be grouped into two models. Topographic highs surrounding wetlands are controlled by the undulating top of limestone at sites where the region is characterized by limestone ridges. In contrast, topographic highs are controlled by thick sand packages at sites regionally characterized by sand dunes over scoured limestone.

The knowledge of the dynamics of soil water is essential in agricultural, hydrological and environmental engineering as it controls plant growth, key hydrological processes, and the contamination of surface and subsurface water. Nearby remote sensing can be used for characterizing non-destructively the hydrogeophysical properties of the subsurface. In that respect, ground penetrating radar (GPR) constitutes a promising high resolution characterization tool. However, notwithstanding considerable research has been devoted to GPR, its use for assessing quantitatively the subsurface properties is constrained by the lack of appropriate GPR systems and signal analysis methods. In this study, a new integrated approach is developed to identify from GPR measurements the soil water content and hydraulic properties governing water transfer in the subsurface. It is based on hydrodynamic and electromagnetic inverse modeling. Research on GPR has focused on GPR design, forward modeling of GPR signal, and electromagnetic inversion to estimate simultaneously the depth dependent dielectric constant and electric conductivity of the shallow subsurface, which are correlated to water content and water quality. The method relies on an ultrawide band stepped frequency continuous wave radar combined with an off-ground monostatic TEM horn antenna. This radar configuration offers possibilities for real time mapping and allows for a more realistic forward modeling of the radar-antenna-subsurface system. Forward modeling is based on the exact solution of Maxwell's equations for a stratified medium. The forward model consists in elementary linear components which are linked in series and parallel. The GPR approach is validated for simple laboratory and outdoor conditions. GPR signal inversion enables the monitoring of the soil water dynamics, which can be subsequently inverted for estimating the soil hydraulic properties. A specifically designed hydrodynamic inverse modeling procedure which requires only water content data as input is further developed and validated to obtain the soil hydraulic properties under laboratory conditions.

Two new stepped-frequency continuous wave (SFCW) radar sensor prototypes, based on a coherent super-heterodyne scheme, have been developed using Microwave Integrated Circuits (MICs) and Monolithic Millimeter-Wave Integrated Circuits (MMICs) for various surface and subsurface applications, such as profiling the surface and subsurface of pavements, detecting and localizing small buried Anti-Personnel (AP) mines and measuring the liquid level in a tank. These sensors meet the critical requirements for subsurface and surface measurements including small size, light weight, good accuracy, fine resolution and deep penetration. In addition, two novel wideband microstrip quasi-TEM horn antennae that are capable of integration with a seamless connection have also been designed. Finally, a simple signal processing algorithm, aimed to acquire the in-phase (I) and quadrature (Q) components and to compensate for the I/Q errors, was developed using LabView. The first of the two prototype sensors, named as the microwave SFCW radar sensor operating from 0.6-5.6-GHz, is primarily utilized for assessing the subsurface of pavements. The measured thicknesses of the asphalt and base layers of a pavement sample were very much in agreement with the actual data with less than 0.1-inch error. The measured results on the actual roads showed that the sensor accurately detects the 5-inch asphalt layer of the pavement with a minimal error of 0.25 inches. This sensor represents the first SFCW radar sensor operating from 0.6-5.6-GHz. The other sensor, named as the millimeter-wave SFCW radar sensor, operates in the 29.72-35.7-GHz range. Measurements were performed to verify its feasibility as a surface and sub-surface sensor. The measurement results showed that the sensor has a lateral resolution of 1 inch and a good accuracy in the vertical direction with less than  0.04-inch error. The sensor successfully detected and located AP mines of small sizes buried under the surface of sand with less than 0.75 and 0.08 inches of error in the lateral and vertical directions, respectively. In addition, it also verified that the vertical resolution is not greater than 0.75 inches. This sensor is claimed as the first Ka-band millimeter-wave SFCW radar sensor ever developed for surface and subsurface sensing applications.

Radio magnetotellurics (RMT), crosshole ground penetrating radar (GPR), and crosshole electrical resistance tomography (ERT) were applied in a range of hydrogeological applications where geophysical data could improve hydrogeological characterization. A profile of RMT data collected over highly resistive granite was used to map subhorizontal fracture zones below 300m depth, as well as a steeply dipping fracture zone, which was also observed on a coinciding seismic reflection profile. One-dimensional inverse modelling and 3D forward modelling with displacement currents included were necessary to test the reliability of features found in the 2D models, where the forward models did not include displacement currents and only lower frequencies were considered. An inversion code for RMT data was developed and applied to RMT data with azimuthal electrical anisotropy signature collected over a limestone formation. The results indicated that RMT is a faster and more reliable technique for studying electrical anisotropy than are azimuthal resistivity surveys. A new sequential inversion method to estimate hydraulic conductivity fields using crosshole GPR and tracer test data was applied to 2D synthetic examples. Given careful surveying, the results indicated that regularization of hydrogeological inverse problems using geophysical tomograms might improve models of hydraulic conductivity. A method to regularize geophysical inverse problems using geostatistical models was developed and applied to crosshole ERT and GPR data collected in unsaturated sandstone. The resulting models were geologically more reasonable than models where the regularization was based on traditional smoothness constraints. Electromagnetic geophysical techniques provide an inexpensive data source in estimating qualitative hydrogeological models, but hydrogeological data must be incorporated to make quantitative estimation of hydrogeological systems feasible.

An investigation is presented of the behavior of time-reversal focusing in soils. Initial numerical models demonstrate time-reversal focusing to be effective in elastic media, including when a large number of scattering objects were present in the medium. When scattering objects are present, time-reversal focusing demonstrates superior focusing ability when compared to other excitation methods such as uniform excitation or time-delay focusing. Multiple experimental investigations of experimental time-reversal focusing performed in sand evaluate time-reversal focusing effectiveness when multiple near-surface scattering objects are present in the medium. Experimental results demonstrate that time-reversal focusing is effective in the experimental context as well as the numerical models. Further experiments examine time-reversal focusing in more extreme cases where the entire ballistic wave is blocked, and the only energy reaching the focus point is reflected from scattering objects in the medium. A comparison to other focusing methods demonstrates that under these conditions, most focusing attempts with traditional methods will fail completely while time-reversal focusing does not. Additional configurations of time-reversal focusing examine its effectiveness when scattering is caused by an asymmetrical surface layers. The impact of an asymmetrical or non-uniform excitation array is also examined for time-reversal focusing in the presence of scattering objects. An investigation of the effects of scattering object geometry on focusing resolution in time-reversal focusing is also presented. Scattering object field density is found to have a strong, but diminishing effect on focusing resolution as the scattering object field density increased. Loss of surface wave energy available for focusing due to mode-conversion is found to be correlated with the density of the scattering object field. The impact of the weak non-linear nature of the soil on time-reversal focusing is examined through a study of time-reversal focusing behavior for a variety of amplitudes that generate different levels of non-linearity in the soil. This study of nonlinearity is coupled with a study of the impact of noise on time-reversal focusing. It appears that both non-linearity and noise have an impact on time-reversal focusing effectiveness. Further, the loss from these mechanisms seems to be interrelated. Noise seems to enhance non-linear loss in the soil.

The presence of fractures, joints and karst features within rock strongly influence the hydraulic and mechanical behavior of a rock mass, and there is a strong desire to characterize these features in a noninvasive manner, such as by using ground penetrating radar (GPR). These features can alter the incident waveform and polarization of the GPR signal depending on the aperture, fill and orientation of the features. The GPR methods developed here focus on changes in waveform, polarization or texture that can improve the detection and discrimination of these features within rock bodies. These new methods are utilized to better understand the interaction of an invasive shrub, Juniperus ashei, with subsurface flow conduits at an ecohydrologic experimentation plot situated on the limestone of the Edwards Aquifer, central Texas. First, a coherency algorithm is developed for polarimetric GPR that uses the largest eigenvalue of a scattering matrix in the calculation of coherence. This coherency is sensitive to waveshape and unbiased by the polarization of the GPR antennas, and it shows improvement over scalar coherency in detection of possible conduits in the plot data. Second, a method is described for full-waveform inversion of transmission data to quantitatively determine fracture aperture and electromagnetic properties of the fill, based on a thin-layer model. This inversion method is validated on synthetic data, and the results from field data at the experimentation plot show consistency with the reflection data. Finally, growing hierarchical self-organizing maps (GHSOM) are applied to the GPR data to discover new patterns indicative of subsurface features, without representative examples. The GHSOMs are able to distinguish patterns indicating soil filled cavities within the limestone. Using these methods, locations of soil filled cavities and the dominant flow conduits were indentified. This information helps to reconcile previous hydrologic experiments conducted at the site. Additionally, the GPR and hydrologic experiments suggests that Juniperus ashei significantly impacts infiltration by redirecting flow towards its roots occupying conduits and soil bodies within the rock. This research demonstrates that GPR provides a noninvasive tool that can improve future subsurface experimentation.