La détection de cavités en milieu urbain est importante pour prévenir différentes causes d'accidents liés à des possibles effondrements. Les cavités sont aussi des cibles d'intérêts pour les archéologues, car les cavités oubliées sont de potentielles sources de matériel révélant des usages passés. Ces cavités sont de tailles différentes, d'origine anthropique ou non, en milieu extérieur ou sous des bâtiments. Leur taille, ainsi que les propriétés physiques du milieu extérieur dans lequel elles se situent, permettent l'utilisation de différentes méthodes géophysiques. Nous nous sommes concentrés sur l'utilisation de deux méthodes géophysiques, le radar de sol et la tomographie par mesures de résistivité électrique, pour localiser et déterminer les cavités métriques à sub-métrique dans le proche sous-sol (6 premiers mètres). Les mesures de radar de sol sont sensibles aux variations de permittivité diélectrique entre la cavité et le milieu extérieur. Nous montrons par des modélisations numériques un effet sur l'amplitude de la réfléchie en fonction du déport qui permet de discriminer entre une cavité vide et une cavité pleine d'eau. Nous étudions aussi l'amplitude de la réfléchie à incidence normale sur le toit d'une cavité à section carrée en fonction de sa profondeur et de sa taille. Nous mettons en évidence une relation logarithmique profondeur versus taille de cavité pour laquelle l'amplitude de la réfléchie est maximum pour les fréquences de prospection typiques du radar de sol. Par ailleurs nous confirmons qu'alors que les mesures radar permettent de déterminer avec précision les dimensions d'une anomalie dans un sous-sol homogène et peu conducteur, les mesures de résistivité électrique permettent elles de déterminer des zones de hautes résistivités à l'emplacement des cavités. Nous couplons ces deux méthodes géophysiques dans deux études de cas, en utilisant la profondeur des interfaces déterminées sur des radargrammes pour contraindre les modèles de résistivité inversés par l'ajout d'information a priori. / The detection of cavities in urban areas is important to prevent different causes of accidents related to possible collapse. The cavities are also interesting targets to archaeologists because forgotten cavities are potential sources of material revealing past uses. These cavities are of different sizes, of anthropogenic origin or not, in an outdoor setting or under buildings. Their size and the physical properties of the external environment in which they are located, allow the use of different geophysical methods. We focused on the use of two of them, Ground Penetrating Radar (GPR) and Electrical Resistivity Tomography (ERT), to locate and determine cavities in the near subsurface (first 6 meters). GPR data are sensitive to variations in dielectric permittivity between the cavity and the external environment. We show by numerical modelling an effect on the amplitude of the reflected signal depending on the offset which could enable discrimination between an empty cavity and a cavity filled with water. We also study the amplitude of the reflected wave at normal incidence on the roof of a cavity of square cross section in terms of its depth and size. We show a logarithmic relationship between the cavity size and its depth at which the amplitude of the reflection is maximum for frequencies of typical exploration with GPR. Furthermore, we confirm that while GPR data determine accurately the size of an anomaly in homogeneous low conductive medium, ERT helps to determine areas with high resistivity at the location of cavities. We combine these two geophysical methods in two case studies, using the depth of interfaces detected on radargrams as a priori information to constrain the inversion of electrical resistivity models.

The karst Biscayne aquifer is characterized by a heterogeneous spatial arrangement of porosity, making hydrogeological characterization difficult. In this dissertation, I investigate the use of ground penetrating radar (GPR), for understanding the spatial distribution of porosity variability in the Miami Limestone presented as a compilation of studies where scale of measurement is progressively increased to account for varying dimensions of dissolution features. In Chapter 2, GPR in zero offset acquisition mode is used to investigate the 2-D distribution of porosity and dielectric permittivity in a block of Miami Limestone at the laboratory scale (< 1.0 m). Petrophysical models based on fully saturated and unsaturated. water conditions are used to estimate porosity and solid dielectric permittivity of the limestone. Results show a good correspondence between analytical and GPR-based porosity estimates and show variability between 22.0-66.0 %. In Chapter 3, GPR in common offset and common midpoint acquisition mode are used to estimate bulk porosity of the unsaturated Miami Limestone at the field scale (10.0-100.0 m). Estimates of porosity are based on the assumption that the directly measured water table reflector is flat and that any deviation is attributed to changes in velocity due to porosity variability. Results show sharp changes in porosity ranging between 33.2-60.9 % attributed to dissolution areas. In Chapter 4, GPR in common offset mode is used to characterize porosity variability in the saturated Biscayne aquifer at 100-1000 m field scales. The presence of numerous diffraction hyperbolae are used to estimate electromagnetic wave velocity and asses both horizontal and vertical changes in porosity after application of a petrophysical model. Results show porosity variability between 23.0-41.0 % and confirm the presence of isolated areas that could serve as enhanced infiltration or recharge. This research allows for the identification and delineation areas of macroporosity areas at 0.01 m lateral resolution and shows variability of porosity at different scales, reaching 37.0 % within 1.3 m, associated with areas of enhanced dissolution. Such improved resolution of porosity estimates can benefit water management efforts and transport modelling and help to better understand small scale relationships between ground water and surface water interactions. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

A firn aquifer is a type of englacial water storage that forms when surface meltwater fills up the pore space in porous firn. If the retention time exceeds one year the feature is regarded as perennial. The melt and accumulation rates as well as the available pore space determine the formation and extent of the firn aquifer. Flow of water within the aquifer caused by gradients in hydraulic potential leads to redistribution of water and consequently to a change in the level of the water table. This thesis focuses on a perennial firn aquifer on the Lomonosovfonna ice field on Svalbard. Spatial and temporal variations in the depth to the water table as well as variations in reflectivity strength of the water table are analysed using data from ground penetrating radar surveys along with MATLAB and ArcGIS software tools. The results show a clear connection between surface topography, steepness of its slopes and depth to the water table. It is also proved that the depth varies between different years. During the four years of study, the water table in the area rose closer to the surface. The results also show that the reflections from the top of the water table are stronger and more frequently detected in areas with gentler water table slopes. A similar correlation is true for the surface topography slope, where a gentler slope shows a stronger reflectivity. The results support the previous research done on Holtedahlfonna’s aquifer on Svalbard as well as aquifers on Greenland. / En firnakvifer är en typ av englacial vattenlagring som formas när smältvatten från en glaciärs yta fyller upp porutrymmen i porös firn. När retentionstiden överskrider ett år betraktas akviferen som flerårig. Smält- och ackumulationshastigheten samt det tillgängliga porutrymmet avgör bildningen och utsträckningen av akviferen. Vattenflödet i akviferen orsakad av gradienter i hydraulisk potential leder till omfördelning av vattnet och därmed till förändringar i vattenytans nivå. Denna uppsats fokuserar på en akvifer på isfältet Lomonosovfonna på Svalbard. De rumsliga och tidsmässiga variationerna i djupet till vattenytan samt de rumsliga variationerna i reflektivitetsstyrkan från vattenytan analyseras med hjälp av georadarmätningar samt MATLAB- och ArcGIS-mjukvaror. Resultaten visar ett tydligt samband mellan yttopografin, dess lutning samt djupet till vattenytan. Dessutom är det bevisat att djupet varierar mellan olika år. Under den fyra år långa undersökningssperioden har vattenytan i mätområdet stigit. Vidare visar resultaten att reflektioner från vattenytan är starkare och mer frekvent observerade i områden där vattenytans lutning är svag. En liknande korrelation gäller också för yttopografin, där svagare lutning ger upphov till en starkare reflektivitet. Resultaten stödjer den tidigare forskningen gjord både på akviferen på Holtedahlfonna på Svalbard och akviferer på Grönland.

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.