545 resultados para backscatter


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Thesis written for Oceanography 445

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L’agrégation érythrocytaire est le principal facteur responsable des propriétés non newtoniennes sanguines pour des conditions d’écoulement à faible cisaillement. Lorsque les globules rouges s’agrègent, ils forment des rouleaux et des structures tridimensionnelles enchevêtrées qui font passer la viscosité sanguine de quelques mPa.s à une centaine de mPa.s. Cette organisation microstructurale érythrocytaire est maintenue par des liens inter-globulaires de faible énergie, lesquels sont brisés par une augmentation du cisaillement. Ces propriétés macroscopiques sont bien connues. Toutefois, les liens étiologiques entre ces propriétés rhéologiques générales et leurs effets pathophysiologiques demeurent difficiles à évaluer in vivo puisque les propriétés sanguines sont dynamiques et fortement tributaires des conditions d’écoulement. Ainsi, à partir de propriétés rhéologiques mesurées in vitro dans des conditions contrôlées, il devient difficile d’extrapoler leurs valeurs dans un environnement physiologique. Or, les thrombophlébites se développent systématiquement en des loci particuliers du système cardiovasculaire. D’autre part, plusieurs études cliniques ont établi que des conditions hémorhéologiques perturbées constituent des facteurs de risque de thrombose veineuse mais leurs contributions étiologiques demeurent hypothétiques ou corrélatives. En conséquence, un outil de caractérisation hémorhéologique applicable in vivo et in situ devrait permettre de mieux cerner et comprendre ces implications. Les ultrasons, qui se propagent dans les tissus biologiques, sont sensibles à l’agrégation érythrocytaire. De nature non invasive, l’imagerie ultrasonore permet de caractériser in vivo et in situ la microstructure sanguine dans des conditions d’écoulements physiologiques. Les signaux ultrasonores rétrodiffusés portent une information sur la microstructure sanguine reflétant directement les perturbations hémorhéologiques locales. Une cartographie in vivo de l’agrégation érythrocytaire, unique aux ultrasons, devrait permettre d’investiguer les implications étiologiques de l’hémorhéologie dans la maladie thrombotique vasculaire. Cette thèse complète une série de travaux effectués au Laboratoire de Biorhéologie et d’Ultrasonographie Médicale (LBUM) du centre de recherche du Centre hospitalier de l’Université de Montréal portant sur la rétrodiffusion ultrasonore érythrocytaire et menant à une application in vivo de la méthode. Elle se situe à la suite de travaux de modélisation qui ont mis en évidence la pertinence d’un modèle particulaire tenant compte de la densité des globules rouges, de la section de rétrodiffusion unitaire d’un globule et du facteur de structure. Ce modèle permet d’établir le lien entre la microstructure sanguine et le spectre fréquentiel du coefficient de rétrodiffusion ultrasonore. Une approximation au second ordre en fréquence du facteur de structure est proposée dans ces travaux pour décrire la microstructure sanguine. Cette approche est tout d’abord présentée et validée dans un champ d’écoulement cisaillé homogène. Une extension de la méthode en 2D permet ensuite la cartographie des propriétés structurelles sanguines en écoulement tubulaire par des images paramétriques qui mettent en évidence le caractère temporel de l’agrégation et la sensibilité ultrasonore à ces phénomènes. Une extrapolation menant à une relation entre la taille des agrégats érythrocytaires et la viscosité sanguine permet l’établissement de cartes de viscosité locales. Enfin, il est démontré, à l’aide d’un modèle animal, qu’une augmentation subite de l’agrégation érythrocytaire provoque la formation d’un thrombus veineux. Le niveau d’agrégation, la présence du thrombus et les variations du débit ont été caractérisés, dans cette étude, par imagerie ultrasonore. Nos résultats suggèrent que des paramètres hémorhéologiques, préférablement mesurés in vivo et in situ, devraient faire partie du profil de risque thrombotique.

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Cette étude vise à tester la pertinence des images RSO - de moyenne et de haute résolution - à la caractérisation des types d’occupation du sol en milieu urbain. Elle s’est basée sur des approches texturales à partir des statistiques de deuxième ordre. Plus spécifiquement, on recherche les paramètres de texture les plus pertinents pour discriminer les objets urbains. Il a été utilisé à cet égard des images Radarsat-1 en mode fin en polarisation HH et Radarsat-2 en mode fin en double et quadruple polarisation et en mode ultrafin en polarisation HH. Les occupations du sol recherchées étaient le bâti dense, le bâti de densité moyenne, le bâti de densité faible, le bâti industriel et institutionnel, la végétation de faible densité, la végétation dense et l’eau. Les neuf paramètres de textures analysés ont été regroupés, en familles selon leur définition mathématique. Les paramètres de ressemblance/dissemblance regroupent l’Homogénéité, le Contraste, la Similarité et la Dissimilarité. Les paramètres de désordre sont l’Entropie et le Deuxième Moment Angulaire. L’Écart-Type et la Corrélation sont des paramètres de dispersion et la Moyenne est une famille à part. Il ressort des expériences que certaines combinaisons de paramètres de texture provenant de familles différentes utilisés dans les classifications donnent de très bons résultants alors que d’autres associations de paramètres de texture de définition mathématiques proches génèrent de moins bons résultats. Par ailleurs on constate que si l’utilisation de plusieurs paramètres de texture améliore les classifications, la performance de celle-ci plafonne à partir de trois paramètres. Malgré la bonne performance de cette approche basée sur la complémentarité des paramètres de texture, des erreurs systématiques dues aux effets cardinaux subsistent sur les classifications. Pour pallier à ce problème, il a été développé un modèle de compensation radiométrique basé sur la section efficace radar (SER). Une simulation radar à partir du modèle numérique de surface du milieu a permis d'extraire les zones de rétrodiffusion des bâtis et d'analyser les rétrodiffusions correspondantes. Une règle de compensation des effets cardinaux fondée uniquement sur les réponses des objets en fonction de leur orientation par rapport au plan d'illumination par le faisceau du radar a été mise au point. Des applications de cet algorithme sur des images RADARSAT-1 et RADARSAT-2 en polarisations HH, HV, VH, et VV ont permis de réaliser de considérables gains et d’éliminer l’essentiel des erreurs de classification dues aux effets cardinaux.

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Ozone profiles from the Microwave Limb Sounder (MLS) onboard the Aura satellite of the NASA's Earth Observing System (EOS) were experimentally added to the European Centre for Medium-range Weather Forecasts (ECMWF) four-dimensional variational (4D-var) data assimilation system of version CY30R1, in which total ozone columns from Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY) onboard the Envisat satellite and partial profiles from the Solar Backscatter Ultraviolet (SBUV/2) instrument onboard the NOAA-16 satellite have been operationally assimilated. As shown by results for the autumn of 2005, additional constraints from MLS data significantly improved the agreement of the analyzed ozone fields with independent observations throughout most of the stratosphere, owing to the daily near-global coverage and good vertical resolution of MLS observations. The largest impacts were seen in the middle and lower stratosphere, where model deficiencies could not be effectively corrected by the operational observations without the additional information on the ozone vertical distribution provided by MLS. Even in the upper stratosphere, where ozone concentrations are mainly determined by rapid chemical processes, dense and vertically resolved MLS data helped reduce the biases related to model deficiencies. These improvements resulted in a more realistic and consistent description of spatial and temporal variations in stratospheric ozone, as demonstrated by cases in the dynamically and chemically active regions. However, combined assimilation of the often discrepant ozone observations might lead to underestimation of tropospheric ozone. In addition, model deficiencies induced large biases in the upper stratosphere in the medium-range (5-day) ozone forecasts.

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Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. An investigation of the ability of high resolution TerraSAR-X data to detect flooded regions in urban areas is described. An important application for this would be the calibration and validation of the flood extent predicted by an urban flood inundation model. To date, research on such models has been hampered by lack of suitable distributed validation data. The study uses a 3m resolution TerraSAR-X image of a 1-in-150 year flood near Tewkesbury, UK, in 2007, for which contemporaneous aerial photography exists for validation. The DLR SETES SAR simulator was used in conjunction with airborne LiDAR data to estimate regions of the TerraSAR-X image in which water would not be visible due to radar shadow or layover caused by buildings and taller vegetation, and these regions were masked out in the flood detection process. A semi-automatic algorithm for the detection of floodwater was developed, based on a hybrid approach. Flooding in rural areas adjacent to the urban areas was detected using an active contour model (snake) region-growing algorithm seeded using the un-flooded river channel network, which was applied to the TerraSAR-X image fused with the LiDAR DTM to ensure the smooth variation of heights along the reach. A simpler region-growing approach was used in the urban areas, which was initialized using knowledge of the flood waterline in the rural areas. Seed pixels having low backscatter were identified in the urban areas using supervised classification based on training areas for water taken from the rural flood, and non-water taken from the higher urban areas. Seed pixels were required to have heights less than a spatially-varying height threshold determined from nearby rural waterline heights. Seed pixels were clustered into urban flood regions based on their close proximity, rather than requiring that all pixels in the region should have low backscatter. This approach was taken because it appeared that urban water backscatter values were corrupted in some pixels, perhaps due to contributions from side-lobes of strong reflectors nearby. The TerraSAR-X urban flood extent was validated using the flood extent visible in the aerial photos. It turned out that 76% of the urban water pixels visible to TerraSAR-X were correctly detected, with an associated false positive rate of 25%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 58% and 19% respectively. These findings indicate that TerraSAR-X is capable of providing useful data for the calibration and validation of urban flood inundation models.

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Earthworms of the family Lumbricidae, which includes many common species, produce and secrete up to millimeter-sized calcite granules, and the intricate fine-scale zoning of their constituent crystals is unique for a biomineral. Granule calcite is produced by crystallization of amorphous calcium carbonate (ACC) that initially precipitates within the earthworm calciferous glands, then forms protogranules by accretion on quartz grain cores. Crystallization of ACC is mediated by migrating fluid films and is largely complete within 24 11 of ACC production and before granules leave the earthworm. Variations in the density of defects formed as a byproduct of trace element incorporation during calcite crystall growth have generated zoning that can be resolved by cathodoluminescence imaging at ultraviolet to blue wavelengths and using the novel technique of scanning electron microscope charge contrast imaging. Mapping of calcite crystal orientations by electron backscatter diffraction reveals an approximate radial fabric to the granules that reflects crystal growth from internal nucleation sites toward their margins. The survival within granules of ACC inclusions for months after they enter soils indicates that they crystallize only within the earthworm and in the presence of fluids containing biochemical catalysts. The earthworm probably promotes crystallization of ACC in order to prevent remobilization of the calcium carbonate by dissolution. Calcite granules vividly illustrate the role of transient precursors in biomineralization, but the underlying question of why earth-worms produce granules in volumes sufficient to have a measurable impact on soil carbon cycling remains to be answered.

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The combination of radar and lidar in space offers the unique potential to retrieve vertical profiles of ice water content and particle size globally, and two algorithms developed recently claim to have overcome the principal difficulty with this approach-that of correcting the lidar signal for extinction. In this paper "blind tests" of these algorithms are carried out, using realistic 94-GHz radar and 355-nm lidar backscatter profiles simulated from aircraft-measured size spectra, and including the effects of molecular scattering, multiple scattering, and instrument noise. Radiation calculations are performed on the true and retrieved microphysical profiles to estimate the accuracy with which radiative flux profiles could be inferred remotely. It is found that the visible extinction profile can be retrieved independent of assumptions on the nature of the size distribution, the habit of the particles, the mean extinction-to-backscatter ratio, or errors in instrument calibration. Local errors in retrieved extinction can occur in proportion to local fluctuations in the extinction-to-backscatter ratio, but down to 400 m above the height of the lowest lidar return, optical depth is typically retrieved to better than 0.2. Retrieval uncertainties are greater at the far end of the profile, and errors in total optical depth can exceed 1, which changes the shortwave radiative effect of the cloud by around 20%. Longwave fluxes are much less sensitive to errors in total optical depth, and may generally be calculated to better than 2 W m(-2) throughout the profile. It is important for retrieval algorithms to account for the effects of lidar multiple scattering, because if this is neglected, then optical depth is underestimated by approximately 35%, resulting in cloud radiative effects being underestimated by around 30% in the shortwave and 15% in the longwave. Unlike the extinction coefficient, the inferred ice water content and particle size can vary by 30%, depending on the assumed mass-size relationship (a problem common to all remote retrieval algorithms). However, radiative fluxes are almost completely determined by the extinction profile, and if this is correct, then errors in these other parameters have only a small effect in the shortwave (around 6%, compared to that of clear sky) and a negligible effect in the longwave.

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A method to estimate the size and liquid water content of drizzle drops using lidar measurements at two wavelengths is described. The method exploits the differential absorption of infrared light by liquid water at 905 nm and 1.5 μm, which leads to a different backscatter cross section for water drops larger than ≈50 μm. The ratio of backscatter measured from drizzle samples below cloud base at these two wavelengths (the colour ratio) provides a measure of the median volume drop diameter D0. This is a strong effect: for D0=200 μm, a colour ratio of ≈6 dB is predicted. Once D0 is known, the measured backscatter at 905 nm can be used to calculate the liquid water content (LWC) and other moments of the drizzle drop distribution. The method is applied to observations of drizzle falling from stratocumulus and stratus clouds. High resolution (32 s, 36 m) profiles of D0, LWC and precipitation rate R are derived. The main sources of error in the technique are the need to assume a value for the dispersion parameter μ in the drop size spectrum (leading to at most a 35% error in R) and the influence of aerosol returns on the retrieval (≈10% error in R for the cases considered here). Radar reflectivities are also computed from the lidar data, and compared to independent measurements from a colocated cloud radar, offering independent validation of the derived drop size distributions.

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In this paper, data from spaceborne radar, lidar and infrared radiometers on the “A-Train” of satellites are combined in a variational algorithm to retrieve ice cloud properties. The method allows a seamless retrieval between regions where both radar and lidar are sensitive to the regions where one detects the cloud. We first implement a cloud phase identification method, including identification of supercooled water layers using the lidar signal and temperature to discriminate ice from liquid. We also include rigorous calculation of errors assigned in the variational scheme. We estimate the impact of the microphysical assumptions on the algorithm when radiances are not assimilated by evaluating the impact of the change in the area-diameter and the density-diameter relationships in the retrieval of cloud properties. We show that changes to these assumptions affect the radar-only and lidar-only retrieval more than the radar-lidar retrieval, although the lidar-only extinction retrieval is only weakly affected. We also show that making use of the molecular lidar signal beyond the cloud as a constraint on optical depth, when ice clouds are sufficiently thin to allow the lidar signal to penetrate them entirely, improves the retrieved extinction. When infrared radiances are available, they provide an extra constraint and allow the extinction-to-backscatter ratio to vary linearly with height instead of being constant, which improves the vertical distribution of retrieved cloud properties.

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High-resolution satellite radar observations of erupting volcanoes can yield valuable information on rapidly changing deposits and geomorphology. Using the TerraSAR-X (TSX) radar with a spatial resolution of about 2 m and a repeat interval of 11-days, we show how a variety of techniques were used to record some of the eruptive history of the Soufriere Hills Volcano, Montserrat between July 2008 and February 2010. After a 15-month pause in lava dome growth, a vulcanian explosion occurred on 28 July 2008 whose vent was hidden by dense cloud. We were able to show the civil authorities using TSX change difference images that this explosion had not disrupted the dome sufficient to warrant continued evacuation. Change difference images also proved to be valuable in mapping new pyroclastic flow deposits: the valley-occupying block-and-ash component tending to increase backscatter and the marginal surge deposits reducing it, with the pattern reversing after the event. By comparing east- and west-looking images acquired 12 hours apart, the deposition of some individual pyroclastic flows can be inferred from change differences. Some of the narrow upper sections of valleys draining the volcano received many tens of metres of rockfall and pyroclastic flow deposits over periods of a few weeks. By measuring the changing shadows cast by these valleys in TSX images the changing depth of infill by deposits could be estimated. In addition to using the amplitude data from the radar images we also used their phase information within the InSAR technique to calculate the topography during a period of no surface activity. This enabled areas of transient topography, crucial for directing future flows, to be captured.

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Urban boundary layers (UBLs) can be highly complex due to the heterogeneous roughness and heating of the surface, particularly at night. Due to a general lack of observations, it is not clear whether canonical models of boundary layer mixing are appropriate in modelling air quality in urban areas. This paper reports Doppler lidar observations of turbulence profiles in the centre of London, UK, as part of the second REPARTEE campaign in autumn 2007. Lidar-measured standard deviation of vertical velocity averaged over 30 min intervals generally compared well with in situ sonic anemometer measurements at 190 m on the BT telecommunications Tower. During calm, nocturnal periods, the lidar underestimated turbulent mixing due mainly to limited sampling rate. Mixing height derived from the turbulence, and aerosol layer height from the backscatter profiles, showed similar diurnal cycles ranging from c. 300 to 800 m, increasing to c. 200 to 850 m under clear skies. The aerosol layer height was sometimes significantly different to the mixing height, particularly at night under clear skies. For convective and neutral cases, the scaled turbulence profiles resembled canonical results; this was less clear for the stable case. Lidar observations clearly showed enhanced mixing beneath stratocumulus clouds reaching down on occasion to approximately half daytime boundary layer depth. On one occasion the nocturnal turbulent structure was consistent with a nocturnal jet, suggesting a stable layer. Given the general agreement between observations and canonical turbulence profiles, mixing timescales were calculated for passive scalars released at street level to reach the BT Tower using existing models of turbulent mixing. It was estimated to take c. 10 min to diffuse up to 190 m, rising to between 20 and 50 min at night, depending on stability. Determination of mixing timescales is important when comparing to physico-chemical processes acting on pollutant species measured simultaneously at both the ground and at the BT Tower during the campaign. From the 3 week autumnal data-set there is evidence for occasional stable layers in central London, effectively decoupling surface emissions from air aloft.

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The potential of visible-near infrared spectra, obtained using a light backscatter sensor, in conjunction with chemometrics, to predict curd moisture and whey fat content in a cheese vat was examined. A three-factor (renneting temperature, calcium chloride, cutting time), central composite design was carried out in triplicate. Spectra (300–1,100 nm) of the product in the cheese vat were captured during syneresis using a prototype light backscatter sensor. Stirring followed upon cutting the gel, and samples of curd and whey were removed at 10 min intervals and analyzed for curd moisture and whey fat content. Spectral data were used to develop models for predicting curd moisture and whey fat contents using partial least squares regression. Subjecting the spectral data set to Jack-knifing improved the accuracy of the models. The whey fat models (R = 0.91, 0.95) and curd moisture model (R = 0.86, 0.89) provided good and approximate predictions, respectively. Visible-near infrared spectroscopy was found to have potential for the prediction of important syneresis indices in stirred cheese vats.

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The cheese industry has continually sought a robust method to monitor milk coagulation. Measurement of whey separation is also critical to control cheese moisture content, which affects quality. The objective of this study was to demonstrate that an online optical sensor detecting light backscatter in a vat could be applied to monitor both coagulation and syneresis during cheesemaking. A prototype sensor having a large field of view (LFV) relative to curd particle size was constructed. Temperature, cutting time, and calcium chloride addition were varied to evaluate the response of the sensor over a wide range of coagulation and syneresis rates. The LFV sensor response was related to casein micelle aggregation and curd firming during coagulation and to changes in curd moisture and whey fat contents during syneresis. The LFV sensor has potential as an online, continuous sensor technology for monitoring both coagulation and syneresis during cheesemaking.

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Response surface methodology was used to study the effect of temperature, cutting time, and calcium chloride addition level on curd moisture content, whey fat losses, and curd yield. Coagulation and syneresis were continuously monitored using 2 optical sensors detecting light backscatter. The effect of the factors on the sensors’ response was also examined. Retention of fat during cheese making was found to be a function of cutting time and temperature, whereas curd yield was found to be a function of those 2 factors and the level of calcium chloride addition. The main effect of temperature on curd moisture was to increase the rate at which whey was expelled. Temperature and calcium chloride addition level were also found to affect the light backscatter profile during coagulation whereas the light backscatter profile during syneresis was a function of temperature and cutting time. The results of this study suggest that there is an optimum firmness at which the gel should be cut to achieve maximum retention of fat and an optimum curd moisture content to maximize product yield and quality. It was determined that to maximize curd yield and quality, it is necessary to maximize firmness while avoiding rapid coarsening of the gel network and microsyneresis. These results could contribute to the optimization of the cheese-making process.