No description available.

This thesis investigates the sensitivity and separability of post-harvest tillage conditions using polarimetric Synthetic Aperture RADAR in southwestern Ontario. Variables examined include: linear polarizations HH, HV, and VV and polarimetric variables: pedestal height, co-polarized complex correlation coefficient magnitude, left and right co-polarized circular polarizations and co-polarized phase difference. Six fine-quad polarimetric, high incidence angle (49°) RADARSAT-2 images acquired over three dates in fall 2010 were used. Over 100 fields were monitored, coincident with satellite overpasses. OMAFRA’s AgRI, a high-resolution polygon network was used to extract average response from fields. Discrimination between tillage practices was best later in the fall season, due to sample size and low soil moisture conditions. Variables most sensitive to tillage activities include HH and VV polarizations and co-polarized complex correlation coefficient magnitude. A supervised support vector machine (SVM) classifier classified no-till and conventional tillage with 91.5% overall accuracy. These results highlight the potential of RADARSAT-2 for monitoring tillage conditions.

This thesis is focused on the utilization of RADARSAT-2 polarimetric SAR data for mapping two surficial aspects of the Umiujalik Lake area, Nunavut, Canada: i) materials, such as bedrock, boulders, organic material, sand and gravel, thick and thin till; and ii) lineaments. To achieve these tasks, RADARSAT-2 polarimetric SAR images with three west-looking, increasing incidence angles (FQ1, FQ12, and FQ20, respectively) were used alone and in combination with LANDSAT-7 ETM+ and Digital Elevation Model (DEM) image data. The surficial materials mapping study tested: i) the effects of incidence angles on mapping accuracy; and ii) non-polarimetric and polarimetric classifiers. For non-polarimetric analysis, a Maximum Likelihood Classification (MLC) algorithm was applied to different combinations of RADARSAT-2, LANDSAT-7 ETM+, and DEM images, achieving a maximum overall classification accuracy of 85%. Polarimetric analyses first included computation of polarimetric signatures to understand the scattering mechanisms of the considered surficial materials, i.e., surface, volume, and multiple scatterings. It also tested three polarimetric classifiers: supervised Wishart (overall accuracy of 48.7% from FQ12 image), and unsupervised Freeman-Wishart, and Wishart-H/ /A. Three main conclusions were reached: i) high incidence angle greatly decreases classification accuracy for the HH polarized image when used alone, but incidence angle has little effect when the HV polarization is added; ii) combining images with three incidence angles (FQ1, FQ12, and FQ20) gives higher accuracy with the maximum likelihood classifier; and iii) the medium incidence angle image (FQ12) produces the best classification accuracy using polarimetric classifiers. In the second part of the study, surface lineaments were mapped using RADARSAT-2 SAR single-polarized images, RGB HH, HV, VV composites, polarimetric total power images, and LANDSAT-7 ETM+ principal component images. Polarization effect analysis showed that regardless of beam mode, more lineaments were identified on the HH image than on the HV image, and the maximum number of lineaments was identified on the multi-polarized RGB composite. Incidence angle effects results showed that regardless of polarization modes, the FQ12 image yielded more lineaments than the FQ1 or FQ20 images. The majority of lineaments are oriented in NW and NNW directions, which correspond to the ice flow direction during the last glaciation.

The boreal forest covers 11% of the earth’s land surface and contains 37 percent of the planet’s terrestrial carbon, which is more than the combined total of both the tropical and the temperate forests [1]. This estimate translates to 703 Pg of carbon with the vast majority contained within the organic soils and peat layers [2-4]. The western-north American boreal forest is a fire ecosystem [2, 5-7] where fires typically occur every 50 to 200 years [8, 9], allowing vast quantities of carbon to re-enter the atmosphere. Understanding and estimating past fire history and the related changes in carbon budget [3, 4, 7, 10] in this biome is of significant importance for climate researchers as they attempt to model for future changes in the planet’s climate [2, 4, 11-14]. Many techniques are available to remotely sense wildfires - using optical, thermal and passive microwave remote sensors - during and immediately after an event - although resolution and availability of images due to cloud cover can make these techniques operationally challenging. Radar remote sensing can provide a complement to these optical and passive microwave techniques, since radar is not affected by cloud cover and solar illumination levels. The Advanced Land Observatory Satellite (ALOS) operates a phased array L band synthetic aperture radar (PALSAR) and Canada’s Radarsat-2 contains a C-Band (SAR) instrument. These radar satellites can be used to detect information about the boreal forest environment including the effects of wildfire. Polarimetric radar is an emerging technology whose full potential is still being actively explored and discovered. More specifically, this research is ground-breaking since very little work has been performed investigating the relationship between polarimetric radar data and historical boreal wildfire events. This area of investigation is a complex marriage of forestry, geospatial information and radar engineering that requires an extensive array of data sets to facilitate analysis. This research has demonstrated that both PALSAR L-Band and Canada’s Radarsat-2 C-Band full polarimetric radars can be used to detect and classify wildfire scars within individual images. The boreal forest is a dynamic ecosystem where both the level of burn severity and the subsequent regeneration of the forest is affected by many factors that can vary widely across small distances. This work contributes to the understanding of the relationships between remotely sensed quad-pol radar signals and both the boreal ecosystem and how wildfire interacts in this environment. / Graduate / 0478 / 0538 / 0984 / ghobart@nrcan.gc.ca

Submitted by Lucienne Costa (lucienneferreira@ufcg.edu.br) on 2018-08-13T17:06:59Z No. of bitstreams: 1 JEFFERSON APARECIDO ARESTIDES DE MELO – DISSERTAÇÃO (PPGMET) 2016.pdf: 4954301 bytes, checksum: 801b98838911a33f335fda02c77f585a (MD5) / Made available in DSpace on 2018-08-13T17:06:59Z (GMT). No. of bitstreams: 1 JEFFERSON APARECIDO ARESTIDES DE MELO – DISSERTAÇÃO (PPGMET) 2016.pdf: 4954301 bytes, checksum: 801b98838911a33f335fda02c77f585a (MD5) Previous issue date: 2016-02-29 / Capes / A linha de instabilidade (LI) Amazônica que atingiu Belém, em 08 de junho de 2008, foi monitorada e analisada por meio de medições de superfície, altitude, satélite e radar. A LI foi identificada, inicialmente, através de imagens do satélite GOES 12. O evento ocorreu durante a campanha de Belém, do Projeto CHUVA, que foi realizada durante o período de 01-30 junho de 2011, durante máxima ocorrência das linhas de instabilidades na região. Através da análise dos dados pluviométricos disponíveis percebe-se que a chuva associada à linha de instabilidade do dia 08 corresponde, aproximadamente, 29% da precipitação acumulada durante todo o experimento. A LI foi monitorada pelo radar meteorológico Banda - XPOL e permitiu a avaliação dinâmica e microfísica do sistema. Esta ultima realizada por meio da classificação de hidrometeoros com as variáveis polarimétricas. As variáveis utilizadas foram: refletividade horizontal (Zh, dBZ), refletividade diferencial (Zdr, dB), fase diferencial específica (Kdp, ° km-1), coeficiente de correlação (ρhv) e, por fim, se realizou a classificação dos hidrometeoros. O sistema apresentou fortes núcleos de refletividade que indicam a região convectiva. Esta parte da LI também é caracterizada por colunas com, relativamente, fortes Zdr e Kdp. A co-localização de colunas de Zh, Zdr e Kdp sugerem que esta é uma zona de elevada concentração de gotas de chuva com um tamanho considerável. A classificação dos hidrometeoros apresentou um resultado bem condizente com o que pode ser observado por outros pesquisadores e com as características microfísicas de outros sistemas convectivos. / A squall line (SL) Amazon, which reached Belém on June 8, 2008, was monitored and analyzed by means of surface measurements, altitude, satellite and radar. The SL was identified initially through the satellite GOES 12 images. The event was during the campaign of Belém, the Chuva Project, which was held during the period 01-30 June 2011, during maximum occurrence of squall line in the region. Through the analysis of available rainfall data we can see that the rain associated with the squall line the day 08 corresponds to approximately 29% of rainfall accumulated during all the experiment. The LI was monitored by weather radar Band - X POL and allowed the dynamic evaluation and microphysics of the system. The latter performed by hydrometeors classification with variables polarimetric. The variables used were: horizontal reflectivity (Zh, dBZ), differential reflectivity (Zdr, dB), specific differential phase (Kdp, ° km -1), correlation coefficient (ρhv) and, finally, was held the classification of hydrometeors. The system showed strong core of reflectivity indicating the convective region. This part of LI is also characterized by columns relatively strong Zdr and Kdp. The co-location columns Zh, Zdr and Kdp suggest that this is an area of high concentration of raindrops with a considerable size. The classification of hydrometeors presented the result well consistent with which can be observed by other researchers and the microphysical characteristics of other convective systems.

Les radars à synthèse d'ouverture (Synthetic Aperture Radar ou SAR) permettent de fournir des images à très haute résolution de la surface de la Terre. Les algorithmes de classification traditionnels se basent sur une hypothèse de bruit gaussien comme modèle de signal, qui est rapidement mise en défaut lorsque l'environnement devient inhomogène ou impulsionnel, comme c'est particulièrement le cas dans les images SAR polarimétriques haute résolution, notamment au niveau des zones urbaines. L'utilisation d'un modèle de bruit composé, appelé modèle SIRV, permet de mieux prendre en compte ces phénomènes et de représenter la réalité de manière plus adéquate. Cette thèse s'emploie alors à étudier l'application et l'impact de ce modèle pour la classification des images SAR polarimétriques afin d'améliorer l'interprétation des classifications au sens de la polarimétrie et à proposer des outils adaptés à ce nouveau modèle. En effet, il apparaît rapidement que les techniques classiques utilisent en réalité beaucoup plus l'information relative à la puissance de chaque pixel plutôt qu'à la polarimétrie pour la classification. Par ailleurs, les techniques de classification traditionnelles font régulièrement appel à la moyenne de matrices de covariance, calculée comme une moyenne arithmétique. Cependant, étant donnée la nature riemannienne de l'espace des matrices de covariance, cette définition n'est pas applicable et il est nécessaire d'employer une définition plus adaptée à cette structure riemannienne. Nous mettons en évidence l'intérêt d'utiliser un modèle de bruit non gaussien sur des données réelles et nous proposons plusieurs approches pour tirer parti de l'information polarimétrique qu'il apporte. L'apport de la géométrie de l'information pour le calcul de la moyenne est de même étudié, sur des données simulées mais également sur des données réelles acquises par l'ONERA. Enfin, une étude préliminaire d'une extension de ces travaux au cas de l'imagerie hyperspectrale est proposée, de par la proximité de ce type de données avec les données SAR polarimétriques. / Synthetic Aperture Radars (SAR) now provide high resolution images of the Earth surface. Traditional classification algorithms are based on a Gaussian assumption for the distribution of the signal, which is no longer valid when the background is heterogeneous, which is particularly the case for polarimetric SAR images, especially in urban areas. A compound Gaussian model, called the SIRV model, allows to take into account these phenomena. This thesis is then devoted to studying the impact of this model for the classification of polarimetric SAR images in order to improve the interpretation of classification results in a polarimetric sense, and to propose tools better suited to this model. Indeed, classical techniques using the Gaussian assumption actually use the power information of each pixel much more than the polarimetric information. Furthermore, it is often necessary to compute a mean of covariance matrices, usually by taking the standard arithmetical mean. However, the space of covariance matrices has a Riemannian structure, not an Euclidean one, which means this definition of the mean is not correct. We will then present several methods to use the actual polarimetric information thanks to the SIRV model to improve the classification results. The benefit of using a correct, Riemannian definition of the mean will also be demonstrated on simulated and real data. Finally, a preliminary study of an extension of this work to hyperspectral imagery will be presented.

L'imagerie à travers les milieux turbides comme le brouillard, les tissus, les colloïdes, etc. répond à plusieurs besoins de la vie courante. L'imagerie à travers de tels milieux diffusants est un défi auquel peuvent répondre les nouveaux systèmes d'imagerie, la théorie de l'information et l'étude des lois de transport de la lumière dans les milieux aléatoires. La thèse est divisée en deux parties adressant deux modalités d'imagerie différentes, à savoir : l'imagerie de contraste polarimétrique et l'imagerie modulée en intensité. Dans les deux cas, des systèmes d'imagerie en temps réel sont proposés et mis au point. Leurs performances sont évaluées à la fois théoriquement et expérimentalement. Dans la première partie de la thèse, une caméra polarimétrique à deux canaux instantanés conçue autour d'un prisme de Wollaston est utilisée pour imager de manière optimale une source de lumière polarisée noyée dans un brouillard. Une expérience en situation réelle a été mise en place à proximité du campus de Beaulieu à Rennes. La source est placée sur une tour de télécommunication située à plus d'un kilomètre du système imageant. Les données acquises dans diverses conditions météorologiques montrent que l'efficacité de cette caméra polarimétrique dépend de la corrélation du bruit de fond dans les deux images initiales. Ceci a été confirmé grâce à une analyse fondée sur la théorie de l'information qui montre que le contraste polarimétriques maximal est obtenu par une combinaison linéaire des deux canaux polarimétriques dont la pondération dépendant de la corrélation du bruit de fond dans les deux canaux. Un système de détection, intégrant cette représentation polarimétrique optimale, a été développé pour explorer de bout en bout les capacités offertes par l'imagerie polarimétrique à deux canaux à travers le brouillard. Ces études trouvent des applications directes dans le transport par temps dégradé, y compris pour l'aide à l'atterrissage d'aéronefs. Dans la même logique, la deuxième partie de la thèse porte sur l'apport de la modulation d'intensité plein champ pour imager les photons balistiques dans les milieux diffusants. En utilisant de concert la théorie de la diffusion et la théorie de l'information, nous avons pu montrer que, pour un budget de photons donné, il existait une fréquence de modulation minimale pour laquelle le filtrage de photons balistique devient efficace. Cette fréquence dépend des propriétés de diffusion du milieu intermédiaire et se trouve être dans la gamme du MHz en situation réelle. L'imagerie en temps réel à de telles fréquences étant un vrai défi, nous avons proposé un système de démodulation plein champ inédit basé sur l'utilisation d'un cristal électro-optique. Ce système d'imagerie, dont nous avons breveté le principe, est en mesure de démoduler avec une caméra standard une scène en temps réel et en plein champ à des fréquences de plusieurs MHz (voire GHz) sans synchronisation de phase. Un prototype de ce système a été développé permettant de confirmer qu'il était robuste, portable et rentable. Le travail présenté dans cette thèse ouvre la voie à la mise en œuvre de systèmes d'imagerie de pointe fonctionnant dans des situations réelles, allant de l'imagerie biomédicale, à la sécurité. / Imaging through turbid media like fog, tissues, colloids etc. has various applications in real-life situations. The problem of imaging through such scattering media presents a challenge that can be addressed by using novel imaging schemes, information theory and laws of light transport through random scattering media. The thesis is divided into two parts corresponding to two different imaging modalities, namely, polarimetric contrast imaging and intensity modulated light imaging. In both the cases, advanced imaging systems, capable of imaging in real-time are used and their performances are evaluated both theoretically and experimentally. In the first part of the thesis, a two-channel, snapshot polarimetric camera, based on a Wollaston prism is used to attain optimal imaging of polarized light source through fog. An original outdoor experiment is setup in the vicinity of the campus Beaulieu in Rennes, France, where a source is placed on a telecommunication tower more than a kilometer away from the imaging system. Data acquired in various weather conditions show that the efficiency of the two-channel polarimetric camera depends on the background noise correlation in the two images. Further, this was confirmed using an information theoretical analysis, which showed that a polarimetric contrast maximizing image representation is a linear combination of the two polarimetric images whose weights depend on the background noise correlation. Based on the derived optimal polarimetric representation, a detection scheme was presented, leading to an end-to-end study of two-channel polarimetric imaging through fog that may be useful in transport applications like aircraft landing/taxiing in degraded weather. The second part of the thesis deals with intensity modulated light and its potential for ballistic photon imaging through scattering media. First, using the diffusion theory of photon transport and information theory, it was shown that for a given photon budget, ballistic imaging can be achieved for a minimum modulation frequency that depends on the scattering properties of the intervening medium. In real-life situation, the minimum frequency can be in the range of MHz. Real-time imaging at these frequencies is a challenge. Hence, a novel demodulation camera system based on electro-optics was proposed and patented. The imaging system is capable of real-time, full-field demodulation at frequencies of several MHz (potentially, in GHz as well), without requiring a phase synchronized source. A prototype of the imaging system was developed and shown that a demodulation camera based on the proposed design is robust, portable and cost-effective. Finally, the work presented in this thesis pave way for implementation of advanced imaging systems in real-life situations, varying from biomedical imaging to transport safety.

This thesis outlines the procedure and theory used to calibrate the UMass eXperimental X-band Radar (UMAXX) for the purpose of monitoring meteorological events in the Pioneer Valley region. Due to the complex topography of the area, lower tilt angles are subject to partial or full beam blockage as well as ground clutter observed through the main beam or sidelobes. Additionally, there are biases internal and external to the system that impact the reflectivity and differential reflectivity measurements. These biases and corrections are addressed in this work. As the radar has been operational since September of 2018, there is ample data available to diag-nose and to perform the necessary corrections to the system. A variety of methods are employed to validate these corrections including comparing intersecting scan volumes between the UMAXX and nearby WSR-88Ds of the NEXRAD network as well as the use of membership functions. Key results of this work are: Ground clutter is principally identified through differential phase and secondarily through velocity and co-polar correlation Partial beam blockage is best estimated assuming a 1.67◦, 2-way beamwidth with an 8dB cutoff System differential phase and Differential Reflectivity bias are functions of az-imuth due to the radome panels. A linear relation between wet radome attenuation and rain rate is found Using an attenuation factor of a = .28 to determine path integrated attenuation improves correlation of reflectivity measurements between UMAXX and NEXRAD network. Ultimately, the goal is to establish UMAXX as a reliable and well understood benchmark with which to calibrate Raytheon’s dual-polarized phased array radar. The two radars operate in sufficiently close frequencies within X-band and collected data simultaneously while colocated. While phased arrays show great promise and potential in meteorologic observations, they come with many challenges that neces-sitate the use of a trustworthy baseline with which to validate its measurements. Additionally, UMAXX’s data is to be streamed to serve as a source to fill any gaps present in the National Weather Service’s network in the region.

The B0.2 V magnetic star τ Sco stands out from the larger population of massive magnetic OB stars due to its remarkable, superionized wind, apparently related to its peculiar magnetic field - a field which is far more complex than the mostly-dipolar fields usually observed in magnetic OB stars. τ Sco is therefore a puzzling outlier in the larger picture of stellar magnetism - a star that still defies interpretation in terms of a physically coherent model. Recently, two early B-type stars were discovered as τ Sco analogues, identified by the striking similarity of their UV spectra to that of τ Sco, which was - until now - unique among OB stars. We present the recent detection of their magnetic fields by the MiMeS collaboration, reinforcing the connection between the presence of a magnetic field and a superionized wind. We will also present ongoing observational efforts undertaken to establish the precise magnetic topology, in order to provide additional constrains for existing models attempting to reproduce the unique wind structure of τ Sco-like stars.

We study the polarization produced by scattering from dust in a bow shock-shaped region of enhanced density surrounding a stellar source, using the Monte Carlo radiative transfer code SLIP. Bow shocks are structures formed by the interaction of the winds of fast-moving stars with the interstellar medium. Our previous study focused on the polarization produced in these structures by electron scattering; we showed that polarization is highly dependent on inclination angle and that multiple scattering changes the shape and degree of polarization. In contrast to electron scattering, dust scattering is wavelength-dependent, which changes the polarization behaviour. Here, we explore different dust particle sizes and compositions and generate polarized spectral energy distributions for each case. We find that the polarization spectral energy distribution behaviour depends on the dust composition and grain size. Including dust emission leads to polarization changes with temperature at higher optical depth in ways that are sensitive to the orientation of the bow shock. In various scenarios and under certain assumptions, our simulations can constrain the optical depth and dust properties of resolved and unresolved bow shock-shaped scattering regions. Constraints on optical depth can provide estimates of local interstellar medium density for observed bow shocks. We also study the impact of dust grains filling the region between the star and bow shock. We see that as the density of dust between the star and bow shock increases, the resulting polarization is suppressed for all the optical depth regimes.