Magnetic fields pervade the universe, spanning a multitude of scales from the dipolar field on Earth, to the largest gravitationally bound structures such as galaxy clusters [1]. The magnetic fields play a vital role in the evolution of these astronomical systems. In addition to the multitude of scales, magnetic fields are present in different astronomical systems of varying strengths. The strongest observed astronomical magnetic fields are in neutron stars with a field strength of ≈ 1015 G [2], far higher than any man-made fields till date. In stark contrast magnetic fields in the interstellar medium while ubiquitous are only a few µG in field strength. Many fundamental processes in astrophysics have magnetism at their heart, be it cosmic ray particle acceleration, star formation, or the launch of radio galaxy jets, pulsars, etc. One key fundamental process that allows us to detect and characterize cosmic magnetic fields with radio astronomy is the polarization of synchrotron radiation. Synchrotron radiation is intrinsically polarized broadband continuum radiation emitted by relativistic charged particles accelerated by the presence of magnetic fields. The emissivity of the synchrotron radiation is tied to the magnetic field strength B and the spectral index α (defined such that the flux density S ∝ ν −α ) such that ε ∝ B 1+α .

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In this research, the characterization of snow cover is made from data collected in September, February and March of 2002 and 2003, during Cold-land Processes Field Experiments project of the NASA. These data include snow and forests characteristic measurements, meteorological conditions, digital elevation model (DEM) and polarimetric multifrequency SAR data (C, L and P bands) acquired from AIRSAR-POLSAR airborne sensor. These data will be used to analyze multifrequency polarimetric techniques to characterize snow cover over forested areas (open area, sparse coniferous forest, and dense coniferous forest). Different techniques have been developed to detect wet snow over different forested areas. The methodology of wet snow detection developed by Rott and Nagler (1995) is first analyzed. The best result is obtained in HH polarization (13% for the sparse coniferous forest site and 25% for the dense coniferous forest site). C-band data in circular polarizations improves these results, but the errors remain high (22% for the sparse coniferous forest site and 13% for the dense coniferous forest site). The use of [sigma][omicronn] ratio in dB [sigma][omicronn][subscript LHH] /[sigma][omicronn][subscript CHH], [sigma][omicronn][subscript LHV]/[sigma][omicronn] [subscript CHH], [sigma][omicronn][subscript LHV] /[sigma][omicronn][subscript CHV] and [sigma][omicronn][subscript LVV] /[sigma][omicronn][subscript CHH] allows to detect wet snow ([less-than or equal to] 13% errors) for both the open area and the dense coniferous forest sites. However, with this technique, higher errors ([greater-than or equal to] 16%) are obtained for the sparse coniferous forest site. The analysis of polarimetric signatures in the three bands shows that their shapes vary according to snow conditions (wet or dry) and forest densities. The pedestal height of polarimetric signatures in P band allows to apply a thresholding approach to discriminate between snow conditions (wet or dry). The error matrix generated from polarimetric signature techniques applied to snow pit measurements shows error higher than 6%. For the characterization of snow condition, target decomposition theorems show promising results. For the three bands, the Freeman-Durden and Cloude-Pottier decompositions allow to understand scattering mechanisms of snow-covered-forested areas. Also, a thresholding approach applied to volume scattering power of the Freeman-Durden decomposition in C band as well as to entropy parameter together with angle [alpha] value of Cloude-Pottier decomposition shows abilities to detect wet snow over forested areas. The technique using the volume scattered power shows detection errors higher than 16%. No classification error is obtained in the error matrix generated from entropy values over the snow pits. The analysis of backscattering coefficients as a function of forest density (open area, sparse coniferous forest and dense coniferous forest) shows variations in the signal as a function of frequency, polarization, density and forest structures as well as with ground conditions (snow-free, dry snow, wet snow). Three radar vegetation indexes (IVR, IVRD[subscript HH] and IVRD[subscript VV]) are analyzed. The IVR index in C and L bands, as well as the IVRD[subscript VV] index in L band are sensitive to forest density. The volume scattered power of the Freeman-Durden decomposition also allows to characterize forest density in C, L and P bands.In order to partially reduce the effect of forested area on the backscattering of a snow cover, image difference between the C-band backscattering coefficient (HH polarization) and the C-band volume scattered power in wet snow condition is performed. The error matrix generated over the snow pit shows that a threshold of 1.5 dB applied to the image difference leads to errors less than 6%. The obtained results clearly show the utility of multifrequency, multipolarisation and polarimetric SAR data for wet snow detection over different forested areas.

Context. The mechanisms governing planet formation are not fully understood. A new era of high-resolution imaging of protoplanetary disks has recently started, thanks to new instruments such as SPHERE, GPI, and ALMA. The planet formation process can now be directly studied by imaging both planetary companions embedded in disks and their e ff ect on disk morphology. Aims. We image disk features that could be potential signs of planet-disk interaction with unprecedented spatial resolution and sensitivity. Two companion candidates have been claimed in the disk around the young Herbig Ae /Be star HD 100546. Thus, this object serves as an excellent target for our investigation of the natal environment of giant planets. Methods. We exploit the power of extreme adaptive optics operating in conjunction with the new high-contrast imager SPHERE to image HD 100546 in scattered light. We obtained the first polarized light observations of this source in the visible (with resolution as fine as 2 AU) and new H and K band total intensity images that we analyzed with the p y n p o i n t package. Results. The disk shows a complex azimuthal morphology, where multiple scattering of photons most likely plays an important role. High brightness contrasts and arm-like structures are ubiquitous in the disk. A double-wing structure (partly due to angular di ff erential imaging processing) resembles a morphology newly observed in inclined disks. Given the cavity size in the visible (11 AU), the CO emission associated to the planet candidate c might arise from within the circumstellar disk. We find an extended emission in the K band at the expected location of b. The surrounding large-scale region is the brightest in scattered light. There is no sign of any disk gap associated to b.

Context. Understanding the diversity of planets requires studying the morphology and physical conditions in the protoplanetary disks in which they form. Aims. We aim to study the structure of the similar to 10 Myr old protoplanetary disk HD 100453, to detect features that can trace disk evolution and to understand the mechanisms that drive these features. Methods. We observed HD100453 in polarized scattered light with VLT/SPHERE at optical (0.6 mu m, 0.8 mu m) and near-infrared (1.2 mu m) wavelengths, reaching an angular resolution of similar to 0.02 '', and an inner working angle of similar to 0.09 ''. Results. We spatially resolve the disk around HD 100453, and detect polarized scattered light up to similar to 0.42 '' (similar to 48 au). We detect a cavity, a rim with azimuthal brightness variations at an inclination of similar to 38 degrees with respect to our line of sight, two shadows and two symmetric spiral arms. The spiral arms originate near the location of the shadows, close to the semi major axis. We detect a faint feature in the SW that can be interpreted as the scattering surface of the bottom side of the disk, if the disk is tidally truncated by the M-dwarf companion currently seen at a projected distance of similar to 119 au. We construct a radiative transfer model that accounts for the main characteristics of the features with an inner and outer disk misaligned by similar to 72 degrees. The azimuthal brightness variations along the rim are well reproduced with the scattering phase function of the model. While spirals can be triggered by the tidal interaction with the companion, the close proximity of the spirals to the shadows suggests that the shadows could also play a role. The change in stellar illumination along the rim induces an azimuthal variation of the scale height that can contribute to the brightness variations. Conclusions. Dark regions in polarized images of transition disks are now detected in a handful of disks and often interpreted as shadows due to a misaligned inner disk. However, the origin of such a misalignment in HD100453, and of the spirals, is still unclear, and might be due to a yet-undetected massive companion inside the cavity, and on an inclined orbit. Observations over a few years will allow us to measure the spiral pattern speed, and determine if the shadows are fixed or moving, which may constrain their origin.

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This thesis presents a theoretical description and experimental testing of two polarimetric fiber-optic strain sensors. 'The first .of these is an intrinsic sensor in which a single mode optical fiber acts as the sensing element. This sensor exhibited low strain sensitivity and high cross-sensitivity to temperature. The second sensor was of the extrinsic type, A single polarization maintaining fiber was used to deliver and collect light from the sensing element, which a was piece of photoelastic sheet PS-1. This type of sensor exhibited large dynamic range of 1:1350, resolution of 0.59ps, and strain sensitivity of the normalized signal of0.00219pe+1. / Thesis / Master of Engineering (ME)

Dramatic land-cover changes have occurred in a broad range of spatial and temporal scales over the last decades. Satellite remote sensing, which can observe the earth's surface in a consistent manner, has been playing an important role in monitoring and evaluating land-cover changes. Meanwhile, optical remote sensing, a common approach to acquiring land-cover information, is limited by weather conditions and thus is greatly constrained in areas with frequent cloud cover and rainfall. Recent advances in polarimetric SAR (PolSAR) provide a promising means to extract timely information of land-cover changes regardless of weather conditions. SAR satellite can pass through an area from different orbits, namely ascending orbit and descending orbit. The PolSAR images from the same orbit will have similar backscattering even with different incident angles. But if images are acquired from different orbits, the backscattering will vary greatly, which causes many difficulties to land cover change detection. The proposed algorithms in this study can perform land cover change detection in three situations: 1) repeat-pass images (image from the same orbit and with same incident angle, 2) images from the same orbit but with different incident angle, and 3) images from different orbits. Using images from different orbits will largely reduce the monitoring interval which is important in the surveillance of natural disasters. The present study proposes 1) a sub-pixel automatic registration technique, 2) an automatic change detection technique and 3) an iterative framework to process a time series of PolSAR images that can be applied to the PolSAR images from different orbits. Firstly, automatic registration is crucial to the change detection task because a small positional error will largely degrade the accuracy of change detection. The automatic registration technique is based on the multi-scale Harris corner detector. To improve the efficiency and robustness, the orientation angle differencing method is proposed to reject outliers. This differencing method has been proved effective even in the experiment of using PolSAR images from different orbits when less than 5% of the feature point matches are correct. Secondly, the change detection technique can automatically detect land-cover conversions and classify the newly input image. Hierarchical segmentation has been applied in the change detection which generates objects within the constraint of the previous classification map. Multivariate kernel density estimation is applied to classify newly input PolSAR image. The experiments show that the proposed change detection technique can mitigate the effect of polarimetric orientation shift when the PolSAR images are from different orbits, and it can achieve high accuracy even when complex local deformation is appeared. Lastly, the iterative framework, which integrates the automatic registration and automatic change detection techniques, is proposed to process a time series of PolSAR images. In the iterative process, no obvious decrease of classification accuracy is observed. Therefore, the proposed framework provides a potential treatment to derive land-cover dynamics from a time series of PolSAR images from different orbits. / published_or_final_version / Urban Planning and Design / Doctoral / Doctor of Philosophy

Ever since automobiles became affordable for the average American, with the introduction of the Ford Model T in 1908, making driving safer has been a priority. While driver intoxication and distraction are the leading causes of automotive fatalities, poor road conditions increase the frequency and deadliness of these incidents. Monitoring road conditions for thousands of miles of road is a huge undertaking, one too large for human surveillance. Automated systems capable of detecting and reacting to dangerous road conditions would be life-saving. These systems could be mounted to the sides of road and notify an operator of conditions in real-time. Drivers could be warned, action taken, and many lives saved. This thesis investigated the science behind polarimetric road ice detection systems. Laboratory Mueller matrix measurements of a simulated road under differing surface conditions were collected searching for a discriminatory polarization property. These Mueller matrices were decomposed into depolarization, diattenuation, and retardance. Individual sample surface polarization properties were then calculated from these three unique matrices and compared. Simulated road samples were measured under many wavelengths and angles, which gave us a larger data library from which to observe trends. Specular and off-specular reflection responses of each sample were also collected. Four polarization properties stood out for having high separation between dry and iced measurements: Depolarization Index, Linear Diattenuation, Linear Polarizance, and Linear Retardance. Through our investigation polarimetric ice detection is possible. Continued research of the polarization properties of road ice can result in the development of a road ice detection system. Proposed deployment methods of such a system have been outlined following the analysis of the data collected in this experiment. Not only is polarimetric ice detection an exciting and novel use of polarization, it has the potential to improve road safety through real-time ice response measures.