976 resultados para CASSINI RADAR
Resumo:
Ground-penetrating radar (GPR) and microgravimetric surveys have been conducted in the southern Jura mountains of western Switzerland in order to map subsurface karstic features. The study site, La Grande Rolaz cave, is an extensive system in which many portions have been mapped. By using small station spacing and careful processing for the geophysical data, and by modeling these data with topographic information from within the cave, accurate interpretations have been achieved. The constraints on the interpreted geologic models are better when combining the geophysical methods than when using only one of the methods, despite the general limitations of two-dimensional (2D) profiling. For example, microgravimetry can complement GPR methods for accurately delineating a shallow cave section approximately 10 X 10 mt in size. Conversely, GPR methods can be complementary in determining cavity depths and in verifying the presence of off-line features and numerous areas of small cavities and fractures, which may be difficult to resolve in microgravimetric data.
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O GPR utiliza técnica indireta para investigação das estruturas de subsuperfície, sendo caracterizado como método não-invasivo, o qual permite extrair informações ao longo do perfil de solo sem perfurar, sondar ou escavar. Este trabalho teve o objetivo de avaliar a utilização do GPR no estabelecimento de atributos físicos do solo em área de cultivo com cana-de-açúcar, além de estabelecer sua correlação com o método do cilindro volumétrico. A área de estudo está localizada no município de Bom Sucesso - PR, sendo utilizada com cultura da cana há mais de 20 anos. Foram obtidas amostras de solos indeformadas com cilindro volumétrico nas profundidades de 0-0,1, 0,1-0,2, 0,2-0,3, 0,3-0,4 e 0,4-0,5 m, ao longo de três transeptos paralelos, sendo o central referente à linha de plantio (transepto 2) e os outros dois correspondentes às entrelinhas laterais (transeptos 1 e 3). Os valores de densidade e porosidade total, obtidos por meio das amostras físicas, foram inicialmente interpretados para verificar o estado do solo nas linhas e nas entrelinhas de cana, nas cinco profundidades. Posteriormente, foram correlacionados com os valores das constantes dielétricas (K) adquiridos pelo georradar, porém apenas para a camada de 0,4-0,5 m, uma vez que as camadas superficiais até a profundidade de 0,4 m não puderam ser avaliadas devido às limitações técnicas do equipamento, aliadas às condições físicas e químicas do solo, que acabaram por prejudicar as reflexões. A densidade mostrou-se menor nas linhas, quando comparada às entrelinhas, para as camadas de 0-0,1 e 0,2-0,3 m. A porosidade total foi menor nas entrelinhas do que nas linhas na camada de 0-0,1 m. Os valores de K foram maiores nas linhas, onde a umidade e a porosidade total foram maiores, e menores nas entrelinhas, onde as densidades encontravam se próximas ao limite crítico. A correlação de K com a densidade e porosidade total não foi significativa. Pequenas modificações na porosidade do solo em função do aumento da densidade foram suficientes para diminuir o valor de K nas entrelinhas, devido à redução na quantidade de água nos poros. Esse fato pode ser confirmado pela correlação de K com a umidade. Assim, pode-se dizer que o georradar foi extremamente sensível à variação de umidade no solo, apresentando melhores resultados para esta variável do que para a densidade e porosidade total determinada por meio do cilindro volumétrico.
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When concrete deterioration begins to occur in highway pavement, repairs become necessary to assure the rider safety, extend its useful life and restore its riding qualities. One rehabilitation technique used to restore the pavement to acceptable highway standards is to apply a thin portland cement concrete (PCC) overlay to the existing pavement. First, any necessary repairs are made to the existing pavement, the surface is then prepared, and the PCC overlay is applied. Brice Petrides-Donohue, Inc. (Donohue) was retained by the Iowa Department of Transportation (IDOT) to evaluate the present condition with respect to debonding of the PCC overlay at fifteen sites on Interstate 80 and State Highway 141 throughout the State of Iowa. This was accomplished by conducting an infrared thermographic and ground penetrating radar survey of these sites which were selected by the Iowa Department of Transportation. The fifteen selected sites were all two lanes wide and one-tenth of a mile long, for a total of three lane miles or 190,080 square feet. The selected sites are as follows: On Interstate 80 Eastbound, from milepost 35.25 to 35.35, milepost 36.00 to 36.10, milepost 37.00 to 37.10, milepost 38.00 to 38.10 and milepost 39.00 to 39.10, on State Highway 141 from milepost 134.00 to 134.10, milepost 134.90 to milepost 135.00, milepost 135.90 to 136.00, milepost 137.00 to 137.10 and milepost 138.00 to 138.10, and on Interstate 80 Westbound from milepost 184.00 to 184.10, milepost 185.00 to 185.10, milepost 186.00 to 186.10, milepost 187.00 to 187.10, and from milepost 188.00 to 188.10.
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A major issue in the application of waveform inversion methods to crosshole georadar data is the accurate estimation of the source wavelet. Here, we explore the viability and robustness of incorporating this step into a time-domain waveform inversion procedure through an iterative deconvolution approach. Our results indicate that, at least in non-dispersive electrical environments, such an approach provides remarkably accurate and robust estimates of the source wavelet even in the presence of strong heterogeneity in both the dielectric permittivity and electrical conductivity. Our results also indicate that the proposed source wavelet estimation approach is relatively insensitive to ambient noise and to the phase characteristics of the starting wavelet. Finally, there appears to be little-to-no trade-off between the wavelet estimation and the tomographic imaging procedures.
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Advances in Near-surface Seismology and Ground-penetrating Radar (SEG Geophysical Developments Series No. 15) is a collection of original papers by renowned and respected authors from around the world. Technologies used in the application of near-surface seismology and ground-penetrating radar have seen significant advances in the last several years. Both methods have benefited from new processing tools, increased computer speeds, and an expanded variety of applications. This book, divided into four sections ? ?Reviews,? ?Methodology,? ?Integrative Approaches,? and ?Case Studies? ? captures the most significant cutting-edge issues in active areas of research, unveiling truly pertinent studies that address fundamental applied problems. This collection of manuscripts grew from a core group of papers presented at a postconvention workshop, ?Advances in Near-surface Seismology and Ground-penetrating Radar,? held during the 2009 SEG Annual Meeting in Houston, Texas. This is the first cooperative publication effort between the near-surface communities of SEG, AGU, and EEGS. It will appeal to a large and diverse audience that includes researchers and practitioners inside and outside the near-surface geophysics community.
Resumo:
A major issue in the application of waveform inversion methods to crosshole ground-penetrating radar (GPR) data is the accurate estimation of the source wavelet. Here, we explore the viability and robustness of incorporating this step into a recently published time-domain inversion procedure through an iterative deconvolution approach. Our results indicate that, at least in non-dispersive electrical environments, such an approach provides remarkably accurate and robust estimates of the source wavelet even in the presence of strong heterogeneity of both the dielectric permittivity and electrical conductivity. Our results also indicate that the proposed source wavelet estimation approach is relatively insensitive to ambient noise and to the phase characteristics of the starting wavelet. Finally, there appears to be little to no trade-off between the wavelet estimation and the tomographic imaging procedures.
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A number of geophysical methods, such as ground-penetrating radar (GPR), have the potential to provide valuable information on hydrological properties in the unsaturated zone. In particular, the stochastic inversion of such data within a coupled geophysical-hydrological framework may allow for the effective estimation of vadose zone hydraulic parameters and their corresponding uncertainties. A critical issue in stochastic inversion is choosing prior parameter probability distributions from which potential model configurations are drawn and tested against observed data. A well chosen prior should reflect as honestly as possible the initial state of knowledge regarding the parameters and be neither overly specific nor too conservative. In a Bayesian context, combining the prior with available data yields a posterior state of knowledge about the parameters, which can then be used statistically for predictions and risk assessment. Here we investigate the influence of prior information regarding the van Genuchten-Mualem (VGM) parameters, which describe vadose zone hydraulic properties, on the stochastic inversion of crosshole GPR data collected under steady state, natural-loading conditions. We do this using a Bayesian Markov chain Monte Carlo (MCMC) inversion approach, considering first noninformative uniform prior distributions and then more informative priors derived from soil property databases. For the informative priors, we further explore the effect of including information regarding parameter correlation. Analysis of both synthetic and field data indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when we combine these data with a realistic, informative prior.
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Cross-hole radar tomography is a useful tool for mapping shallow subsurface electrical properties viz. dielectric permittivity and electrical conductivity. Common practice is to invert cross-hole radar data with ray-based tomographic algorithms using first arrival traveltimes and first cycle amplitudes. However, the resolution of conventional standard ray-based inversion schemes for cross-hole ground-penetrating radar (GPR) is limited because only a fraction of the information contained in the radar data is used. The resolution can be improved significantly by using a full-waveform inversion that considers the entire waveform, or significant parts thereof. A recently developed 2D time-domain vectorial full-waveform crosshole radar inversion code has been modified in the present study by allowing optimized acquisition setups that reduce the acquisition time and computational costs significantly. This is achieved by minimizing the number of transmitter points and maximizing the number of receiver positions. The improved algorithm was employed to invert cross-hole GPR data acquired within a gravel aquifer (4-10 m depth) in the Thur valley, Switzerland. The simulated traces of the final model obtained by the full-waveform inversion fit the observed traces very well in the lower part of the section and reasonably well in the upper part of the section. Compared to the ray-based inversion, the results from the full-waveform inversion show significantly higher resolution images. At either side, 2.5 m distance away from the cross-hole plane, borehole logs were acquired. There is a good correspondence between the conductivity tomograms and the natural gamma logs at the boundary of the gravel layer and the underlying lacustrine clay deposits. Using existing petrophysical models, the inversion results and neutron-neutron logs are converted to porosity. Without any additional calibration, the values obtained for the converted neutron-neutron logs and permittivity results are very close and similar vertical variations can be observed. The full-waveform inversion provides in both cases additional information about the subsurface. Due to the presence of the water table and associated refracted/reflected waves, the upper traces are not well fitted and the upper 2 m in the permittivity and conductivity tomograms are not reliably reconstructed because the unsaturated zone is not incorporated into the inversion domain.
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In this chapter our objective is to provide an overview of the effects of anomalous propagation conditions on weather radar observations, based mostly on studies performed by the authors during the last decade, summarizing results from recent publications, presentations, or unpublished material. We believe this chapter may be useful as an introductory text for graduate students, or researchers and practitioners dealing with this topic. Throughout the text a spherical symmetric atmosphere is assumed and the focus is on the occurrence of ground and sea clutter and subsequent problems for weather radar applications. Other related topics such as long-path, over-the-horizon propagation and detection of radar targets (either clutter or weather systems) at long ranges is not considered here; however readers should be aware of the potential problems these phenomena may have as range aliasing may cause these echoes appear nearer than they are ¿ for more details see the discussion about second trip echoes by Zrnic, this volume.
Resumo:
The ground-penetrating radar (GPR) geophysical method has the potential to provide valuable information on the hydraulic properties of the vadose zone because of its strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR traveltime data can allow for a significant reduction in uncertainty regarding subsurface van Genuchten-Mualem (VGM) parameters. Much of the previous work on the stochastic estimation of VGM parameters from crosshole GPR data has considered the case of steady-state infiltration conditions, which represent only a small fraction of practically relevant scenarios. We explored in detail the dynamic infiltration case, specifically examining to what extent time-lapse crosshole GPR traveltimes, measured during a forced infiltration experiment at the Arreneas field site in Denmark, could help to quantify VGM parameters and their uncertainties in a layered medium, as well as the corresponding soil hydraulic properties. We used a Bayesian Markov-chain-Monte-Carlo inversion approach. We first explored the advantages and limitations of this approach with regard to a realistic synthetic example before applying it to field measurements. In our analysis, we also considered different degrees of prior information. Our findings indicate that the stochastic inversion of the time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions compared with the corresponding priors, which in turn significantly improves knowledge of soil hydraulic properties. Overall, the results obtained clearly demonstrate the value of the information contained in time-lapse GPR data for characterizing vadose zone dynamics.
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A recently developed technique, polarimetric radar interferometry, is applied to tackle the problem of the detection of buried objects embedded in surface clutter. An experiment with a fully polarimetric radar in an anechoic chamber has been carried out using different frequency bands and baselines. The processed results show the ability of this technique to detect buried plastic mines and to measure their depth. This technique enables the detection of plastic mines even if their backscatter response is much lower than that of the surface clutter.
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Clonally reproducing hemicryptophytic rosette plants are common in the alpine belt. However, their demography, and indirectly their growth and reproductive strategy in these harsh conditions, was rarely studied. We analysed the morphology, clonal reproduction and demography of one such species, Leontopodium alpinum, in two populations of the Swiss Alps. The species forms small colonies of 1-5 (maximum 30) sterile rosettes with a few flowering stalks. After flowering, the apical meristem dies and one or two new axillary buds grow below the previous rosette in the following year, developing into short rhizomes (<2 cm), which decay after four years. The new stalk produces sterile rosettes before flowering after two to four years, depending on climatic conditions. The apical meristem often dies during the sterile stage, and is replaced by a new axillary bud. Levkovitch matrices on two stages (sterile and flowering rosettes) showed that rosette survival and clonal reproduction maintain long-lived populations (λ = 0.96). Elasticities indicated that a change in the survival of sterile rosettes had the strongest effect on population dynamics, and this stage lasts, on average, 6.8 years at 2480 m. Altogether, L. alpinum is following Tomlinson's architectural model. This growth form appears perfectly adapted to harsh alpine conditions: the clonal ramification ensures longevity to genets and the semelparous behaviour of the rosettes allows an efficient flowering, whatever the climatic conditions. L. alpinum appears to follow a common growth model among rosette possessing hemicryptophytes in the alpine belt.
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El presente estudio se enmarca en el proyecto europeo SIBERIA. Trata de explorar el uso de imágenes radar de satélite (ERS y JERS) para la actualización de la cartografía de vegetación de zonas boreales. Se dispone de 8 imágenes de amplitud y coherencia tomadas en 1998, así como de un inventario de vegetación georreferenciado de dos pequeñas zonas. Se proponen tres tipos de clasificaciones supervisadas por el método de máxima verosimilitud. La primera con las imágenes de satélite, la segunda añadiendo algunas imágenes texturales, y la tercera utilizando sólo las imágenes de los componentes principales más significativos. Se siguen los criterios establecidos en el proyecto SIBERIA para la obtención de áreas de entrenamiento. Se propone una doble validación, por una parte vía matrices de confusión a partir de áreas de verdad-terreno obtenidas por el mismo método que las áreas de entrenamiento, y por otra parte contrastando y correlacionando las clasificaciones con los parámetros de inventario disponibles para dos pequeñas áreas de verdad-terreno. Los resultados indican una sensible mejora en la clasificación con la incorporación de imágenes texturales (la precisión aumenta de un 66% a un 75%), y señalan el parámetro biomasa como el mejor correlacionado con las clasificaciones derivadas (coeficiente de correlación r de hasta 0,49). Diferentes fuentes de error permiten augurar un margen de mejora para posteriores estudios.