992 resultados para areal geology
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A great number of low-temperature geothermal fields occur in Northern-Portugal related to fractured rocks. The most important superficial manifestations of these hydrothermal systems appear in pull-apart tectonic basins and are strongly conditioned by the orientation of the main fault systems in the region. This work presents the interpretation of gravity gradient maps and 3D inversion model produced from a regional gravity survey. The horizontal gradients reveal a complex fault system. The obtained 3D model of density contrast puts into evidence the main fault zone in the region and the depth distribution of the granitic bodies. Their relationship with the hydrothermal systems supports the conceptual models elaborated from hydrochemical and isotopic water analyses. This work emphasizes the importance of the role of the gravity method and analysis to better understand the connection between hydrothermal systems and the fractured rock pattern and surrounding geology. (c) 2013 Elsevier B.V. All rights reserved.
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Mestrado em Engenharia Geotécnica e Geoambiente
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Neste trabalho, apresentam-se e discutem-se os resultados da aplicação da técnica de amostragem linear de descontinuidades em faces expostas do maciço rochoso da pedreira granítica de S. Domingos Nº 2 (Fontelo, Armamar; N de Portugal). É, igualmente, utilizada informação sobre a rede de fracturação regional, obtida através da análise morfoestrutural de mapas topográficos e mapas geológicos. São ainda referidos os métodos utilizados no tratamento dos dados de terreno com o objectivo de definir as famílias de descontinuidades e de caracterizar estatísticamente a sua atitude, espaçamento e extensão. Os resultados obtidos são comparados, à mega escala e macro-escala, no sentido de averiguar a presença de um padrão de fracturação com dimensão multiescala. Esta abordagem foi refinada através da aplicação de Sistemas de Informação Geográfica. A aplicação desta técnica para a caracterização da compartimentação do maciço poderá contribuir para aperfeiçoar a gestão sustentável do georrecurso da pedreira de S. Domingos Nº 2 (Fontelo). O controlo geomecânico do desmonte do maciço rochoso é salientado com o intuito de uma abordagem de geo-engenharia integrada dos maciços rochosos.
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A determinação do preço justo de um contrato de opções, trouxe enormes desa os a diversos ramos da Matemática procurando desenvolver e aperfeiçoar modelos e métodos que melhor representem os comportamentos dos mercados nanceiros. A avaliação de opções americanas apresenta uma di culdade acrescida, uma vez que é necessário determinar uma estratégia óptima ao seu exercício antecipado, já que estas opções podem ser exercidas em qualquer momento até à sua maturidade. Investigações recentes mostram que metodologias baseadas em técnicas de simulação podem ser usadas com sucesso neste tipo de opções (Duan and Simonato (2001), Longsta and Schwartz (2001), Stentoft (2005)). Neste trabalho, usamos métodos de Monte Carlo para avaliar opções Americanas, recorrendo à abordagem sugerida por Longsta and Schwartz (2001), combinando modelos GARCH para o subjacente com Filtered Historical Simulation (Barone, Engle and Mancini (2008)).
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During February of 1974, the western extremity of St. Jorge's Island, one of the Azores Islands group, was severely affected by intense earthquakes, causing heavy damage. One of the authors of the present work (T. P. R.) who at the time was employed in the Rosais Lighthouse, registered day after day all the phenomena he could observe, writting down a journal that is published herein. An introduction on the geology, tectonic's, and the seismology of St. Jorge’s Island, is presented. As it can be verified, this seismic crisis was associated to a short submarine vulcanic eruption.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do Grau de Mestre em Engenharia do Ambiente, perfil de Gestão e Sistemas Ambientais
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Relatório de Estágio apresentado ao Instituto Politécnico do Porto para obtenção do Grau de Mestre em Logística Orientadores do Instituto: Professor Doutor Luís Barreto e Mestre Jonas Lima Orientador da empresa: Engenheiro Vítor Carvalho
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A new upper Miocene locality at Asseiceira (Rio Maior), near the top of the "Calcários de Almoster e Santarém" unit (Almoster and Santarém limestones) is studied. Animal and plant fossils are described. Comparisons are drawn to other localities related to the same unit: Freiria and Azambujeira (middle and upper levels, both with large mammals). Small mammals from Asseiceira and Freiria point out to a rather old age amidst the upper Vallesian, MN 10 mammal-unit. This gives a fairly accurate datation for the "Calcários de Almoster e Santarém" and for the short time span of the corresponding sedimentation. Climate was warm and quite dry, with contrasting seasons and arid events. During upper Vallesian times, climate in Iberian Peninsula was varied but drier than in France, and specially so in the inner basins. However in Portugal and in Catalonia climate would he less different in comparison with that of the Rhône basin. Environmental evolution has been important: at Freiria and Azambujeira (middle level) there were mainly shallow lacustrine environments that received ressurgence waters from the nearby "Maciço calcário". Humid areas were closely surrounded by dense forests and these by broader and drier savanna or steppe areas. Still later, carbonate sedimentation ended. For some time there was still a river system with oxbows; humid areas probably were decreasing in favour of surrounding, rather dry environments. This study stressed the nced for revision of the geology of the region of Rio Maior and for a new geological mapping of that area. Environmental evolution has been important: at Freiria and Azambujeira (middle level) there were mainly shallow lacustrine environments that received ressurgence waters from the nearby "Maciço calcário".
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The development of an algorithm for the construction of auxiliary projection nets (conform, equivalent and orthographic), in the equatorial and polar versions, is presented. The algorithm for the drawing of the "IGAREA 220" counting net (ALYES & MENDES, 1972), is also presented. Those algorithms are the base of STEGRAPH program (vers. 2.0), for MS-DOS computers, which has other applications.
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We present the first image of the Madeira upper crustal structure, using ambient seismic noise tomography. 16 months of ambient noise, recorded in a dense network of 26 seismometers deployed across Madeira, allowed reconstructing Rayleigh wave Green's functions between receivers. Dispersion analysis was performed in the short period band from 1.0 to 4.0 s. Group velocity measurements were regionalized to obtain 20 tomographic images, with a lateral resolution of 2.0 km in central Madeira. Afterwards, the dispersion curves, extracted from each cell of the 2D group velocity maps, were inverted as a function of depth to obtain a 3D shear wave velocity model of the upper crust, from the surface to a depth of 2.0 km. The obtained 3D velocity model reveals features throughout the island that correlates well with surface geology and island evolution. (C) 2015 Elsevier B.V. All rights reserved.
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We present the first image of the Madeira upper crustal structure, using ambient seismic noise tomography. 16 months of ambient noise, recorded in a dense network of 26 seismometers deployed across Madeira, allowed reconstructing Rayleigh wave Green's functions between receivers. Dispersion analysis was performed in the short period band from 1.0 to 4.0 s. Group velocity measurements were regionalized to obtain 20 tomographic images, with a lateral resolution of 2.0 km in central Madeira. Afterwards, the dispersion curves, extracted from each cell of the 2D group velocity maps, were inverted as a function of depth to obtain a 3D shear wave velocity model of the upper crust, from the surface to a depth of 2.0 km. The obtained 3D velocity model reveals features throughout the island that correlates well with surface geology and island evolution. (C) 2015 Elsevier B.V. All rights reserved.
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This article evaluates the sustainability and economic potential of microalgae grown in brewery wastewater for biodiesel and biomass production. Three sustainability and two economic indicators were considered in the evaluation within a life cycle perspective. For the production system the most efficient process units were selected. Results show that harvesting and oil separation are the main process bottlenecks. Microalgae with higher lipid content and productivity are desirable for biodiesel production, although comparable to other biofuel’s feedstock concerning sustainability. However, improvements are still needed to reach the performance level of fossil diesel. Profitability reaches a limit for larger cultivation areas, being higher when extracted biomass is sold together with microalgae oil, in which case the influence of lipid content and areal productivity is smaller. The values of oil and/or biomass prices calculated to ensure that the process is economically sound are still very high compared with other fuel options, especially biodiesel.
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The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.
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Linear unmixing decomposes an hyperspectral image into a collection of re ectance spectra, called endmember signatures, and a set corresponding abundance fractions from the respective spatial coverage. This paper introduces vertex component analysis, an unsupervised algorithm to unmix linear mixtures of hyperpsectral data. VCA exploits the fact that endmembers occupy vertices of a simplex, and assumes the presence of pure pixels in data. VCA performance is illustrated using simulated and real data. VCA competes with state-of-the-art methods with much lower computational complexity.
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Este trabalho centra-se no estudo do aproveitamento expectável do maciço rochoso da pedreira da Curviã N.o 2 (Joane, Vila Nova de Famalicão, no N Portugal), através da obtenção de um bloco unitário tipo que forneça indicações para a exploração do recurso geológico para fins industriais e/ou ornamentais. Desta forma, investiga-se se num dado limite de zona geotécnica do maciço rochoso e propicio a obtenção de blocos com dimensão, avaliados apos o processo de transformação, nomeadamente, para enrocamento em obras marítimas ou balastro em obras ferroviárias. Foram seleccionados diversos afloramentos, tendo-se recorrido a técnica de amostragem linear as superfícies expostas do maciço. Esta técnica e uma das formas mais expeditas de coligir dados geológico-geotécnicos relativos as descontinuidades. Procedeu-se, ainda, a um tratamento estatístico das descontinuidades, bem como dos parâmetros geológico-geotécnicos e geomecânicos a estas associadas, propostos pela Sociedade Internacional de Mecânica das Rochas (ISRM). Todos os dados foram representados cartograficamente numa base apoiada pelos Sistemas de Informação Geográfica (SIG) e utilizadas as ferramentas de geologia estrutural, analise morfotectónica, modelação digital de terreno e cartografia de zonamento geotécnico. O zonamento geotécnico do maciço granítico foi realizado sempre em estreita ligação com o conhecimento das características do maciço ”in situ”. Pretende-se que esta metodologia contribua para um melhor conhecimento da compartimentação dos maciços rochosos em geral e, em particular, do modelo geotécnico comportamental do maciço rochoso da Curviã N.o2.