Exploration of Ground Penetrating Radar and Time Domain Reflectometry Methods for the Determination of Pavement Dielectric Constant

Traditionally, densities of newly built roadways are checked by direct sampling (cores) or by nuclear density gauge measurements. For roadway engineers, density of asphalt pavement surfaces is essential to determine pavement quality. Unfortunately, field measurements of density by direct sampling or by nuclear measurement are slow processes. Therefore, I have explored the use of rapidly-deployed ground penetrating radar (GPR) as an alternative means of determining pavement quality. The dielectric constant of pavement surface may be a substructure parameter that correlates with pavement density, and can be used as a proxy when density of asphalt is not known from nuclear or destructive methods. The dielectric constant of the asphalt can be determined using ground penetrating radar (GPR). In order to use GPR for evaluation of road surface quality, the relationship between dielectric constants of asphalt and their densities must be established. Field measurements of GPR were taken at four highway sites in Houghton and Keweenaw Counties, Michigan, where density values were also obtained using nuclear methods in the field. Laboratory studies involved asphalt samples taken from the field sites and samples created in the laboratory. These were tested in various ways, including, density, thickness, and time domain reflectometry (TDR). In the field, GPR data was acquired using a 1000 MHz air-launched unit and a ground-coupled unit at 200 and 500 MHz. The equipment used was owned and operated by the Michigan Department of Transportation (MDOT) and available for this study for a total of four days during summer 2005 and spring 2006. The analysis of the reflected waveforms included “routine” processing for velocity using commercial software and direct evaluation of reflection coefficients to determine a dielectric constant. The dielectric constants computed from velocities do not agree well with those obtained from reflection coefficients. Perhaps due to the limited range of asphalt types studied, no correlation between density and dielectric constant was evident. Laboratory measurements were taken with samples removed from the field and samples created for this study. Samples from the field were studied using TDR, in order to obtain dielectric constant directly, and these correlated well with the estimates made from reflection coefficients. Samples created in the laboratory were measured using 1000 MHz air-launched GPR, and 400 MHz ground-coupled GPR, each under both wet and dry conditions. On the basis of these observations, I conclude that dielectric constant of asphalt can be reliably measured from waveform amplitude analysis of GJPR data, based on the consistent agreement with that obtained in the laboratory using TDR. Because of the uniformity of asphalts studied here, any correlation between dielectric constant and density is not yet apparent.

Waterpower : a geophysical and archaeological investigation of the waterpower system at the West Point Foundry, Cold Spring, New York

Waterpower: A Geophysical and Archaeological Investigation of the Waterpower System at the West Point Foundry, Cold Spring, New York, describes the results of ground penetrating radar surveys and archaeological excavation undertaken by Michigan Technological University (MTU) archaeologists during the summer of 2003 at the West Point Foundry, Cold Spring, New York. 2003 constituted MTU's second field season at the foundry. Fieldwork concentrated on the foundry's waterpower system, an intricate network of surface and subsurface drains, races, flumes, waterwheels, turbines, dams, and ponds that powered operations and regulated water flow throughout the site. Archaeologists utilized non-destructive geophysical technology, which expedited survey, facilitated placement of excavation units, and provided a model for future archaeogeophysical research at industrial sites. Features discovered during excavation provided valuable information pertaining to the waterpower system's construction and its functions. Data from ground penetrating radar surveys, archaeological excavation, historical photographs, documents, and maps permitted the development of a provisional chronology of the development of various components of the West Point Foundry's waterpower system. Information gathered during this project serves as an aid in sit interpretation and rehabilitation.

Investigations of Cloud Microphysical Response to Mixing Using Digital Holography

Cloud edge mixing plays an important role in the life cycle and development of clouds. Entrainment of subsaturated air affects the cloud at the microscale, altering the number density and size distribution of its droplets. The resulting effect is determined by two timescales: the time required for the mixing event to complete, and the time required for the droplets to adjust to their new environment. If mixing is rapid, evaporation of droplets is uniform and said to be homogeneous in nature. In contrast, slow mixing (compared to the adjustment timescale) results in the droplets adjusting to the transient state of the mixture, producing an inhomogeneous result. Studying this process in real clouds involves the use of airborne optical instruments capable of measuring clouds at the `single particle' level. Single particle resolution allows for direct measurement of the droplet size distribution. This is in contrast to other `bulk' methods (i.e. hot-wire probes, lidar, radar) which measure a higher order moment of the distribution and require assumptions about the distribution shape to compute a size distribution. The sampling strategy of current optical instruments requires them to integrate over a path tens to hundreds of meters to form a single size distribution. This is much larger than typical mixing scales (which can extend down to the order of centimeters), resulting in difficulties resolving mixing signatures. The Holodec is an optical particle instrument that uses digital holography to record discrete, local volumes of droplets. This method allows for statistically significant size distributions to be calculated for centimeter scale volumes, allowing for full resolution at the scales important to the mixing process. The hologram also records the three dimensional position of all particles within the volume, allowing for the spatial structure of the cloud volume to be studied. Both of these features represent a new and unique view into the mixing problem. In this dissertation, holographic data recorded during two different field projects is analyzed to study the mixing structure of cumulus clouds. Using Holodec data, it is shown that mixing at cloud top can produce regions of clear but humid air that can subside down along the edge of the cloud as a narrow shell, or advect down shear as a `humid halo'. This air is then entrained into the cloud at lower levels, producing mixing that appears to be very inhomogeneous. This inhomogeneous-like mixing is shown to be well correlated with regions containing elevated concentrations of large droplets. This is used to argue in favor of the hypothesis that dilution can lead to enhanced droplet growth rates. I also make observations on the microscale spatial structure of observed cloud volumes recorded by the Holodec.

Detection of complex point targets with distributed assets in a MIMO radar system

The report explores the problem of detecting complex point target models in a MIMO radar system. A complex point target is a mathematical and statistical model for a radar target that is not resolved in space, but exhibits varying complex reflectivity across the different bistatic view angles. The complex reflectivity can be modeled as a complex stochastic process whose index set is the set of all the bistatic view angles, and the parameters of the stochastic process follow from an analysis of a target model comprising a number of ideal point scatterers randomly located within some radius of the targets center of mass. The proposed complex point targets may be applicable to statistical inference in multistatic or MIMO radar system. Six different target models are summarized here – three 2-dimensional (Gaussian, Uniform Square, and Uniform Circle) and three 3-dimensional (Gaussian, Uniform Cube, and Uniform Sphere). They are assumed to have different distributions on the location of the point scatterers within the target. We develop data models for the received signals from such targets in the MIMO radar system with distributed assets and partially correlated signals, and consider the resulting detection problem which reduces to the familiar Gauss-Gauss detection problem. We illustrate that the target parameter and transmit signal have an influence on the detector performance through target extent and the SNR respectively. A series of the receiver operator characteristic (ROC) curves are generated to notice the impact on the detector for varying SNR. Kullback–Leibler (KL) divergence is applied to obtain the approximate mean difference between density functions the scatterers assume inside the target models to show the change in the performance of the detector with target extent of the point scatterers.

Estimation of scots pine defoliation by the common pine sawfly (Diprion pini L.) using multi-temporal radar data

In 1998-2001 Finland suffered the most severe insect outbreak ever recorded, over 500,000 hectares. The outbreak was caused by the common pine sawfly (Diprion pini L.). The outbreak has continued in the study area, Palokangas, ever since. To find a good method to monitor this type of outbreaks, the purpose of this study was to examine the efficacy of multi-temporal ERS-2 and ENVISAT SAR imagery for estimating Scots pine (Pinus sylvestris L.) defoliation. Three methods were tested: unsupervised k-means clustering, supervised linear discriminant analysis (LDA) and logistic regression. In addition, I assessed if harvested areas could be differentiated from the defoliated forest using the same methods. Two different speckle filters were used to determine the effect of filtering on the SAR imagery and subsequent results. The logistic regression performed best, producing a classification accuracy of 81.6% (kappa 0.62) with two classes (no defoliation, >20% defoliation). LDA accuracy was with two classes at best 77.7% (kappa 0.54) and k-means 72.8 (0.46). In general, the largest speckle filter, 5 x 5 image window, performed best. When additional classes were added the accuracy was usually degraded on a step-by-step basis. The results were good, but because of the restrictions in the study they should be confirmed with independent data, before full conclusions can be made that results are reliable. The restrictions include the small size field data and, thus, the problems with accuracy assessment (no separate testing data) as well as the lack of meteorological data from the imaging dates.

Tracking a non-cooperative target using a Doppler radar wireless sensor network

Tracking or target localization is used in a wide range of important tasks from knowing when your flight will arrive to ensuring your mail is received on time. Tracking provides the location of resources enabling solutions to complex logistical problems. Wireless Sensor Networks (WSN) create new opportunities when applied to tracking, such as more flexible deployment and real-time information. When radar is used as the sensing element in a tracking WSN better results can be obtained; because radar has a comparatively larger range both in distance and angle to other sensors commonly used in WSNs. This allows for less nodes deployed covering larger areas, saving money. In this report I implement a tracking WSN platform similar to what was developed by Lim, Wang, and Terzis. This consists of several sensor nodes each with a radar, a sink node connected to a host PC, and a Matlab© program to fuse sensor data. I have re-implemented their experiment with my WSN platform for tracking a non-cooperative target to verify their results and also run simulations to compare. The results of these tests are discussed and some future improvements are proposed.

Investigations into the degassing and eruption mechanisms of Nyamuragira volcano, Democratic Republic of the Congo (Africa)

One of two active volcanoes in the western branch of the East African Rift, Nyamuragira (1.408ºS, 29.20ºE; 3058 m) is located in the D.R. Congo. Nyamuragira emits large amounts of SO2 (up to ~1 Mt/day) and erupts low-silica, alkalic lavas, which achieve flow rates of up to ~20 km/hr. The source of the large SO2 emissions and pre-eruptive magma conditions were unknown prior to this study, and 1994-2010 lava volumes were only recently mapped via satellite imagery, mainly due to the region’s political instability. In this study, new olivine-hosted melt inclusion volatile (H2O, CO2, S, Cl, F) and major element data from five historic Nyamuragira eruptions (1912, 1938, 1948, 1986, 2006) are presented. Melt compositions derived from the 1986 and 2006 tephra samples best represent pre-eruptive volatile compositions because these samples contain naturally glassy inclusions that underwent less post-entrapment modification than crystallized inclusions. The total amount of SO2 released from the 1986 (0.04 Mt) and 2006 (0.06 Mt) eruptions are derived using the petrologic method, whereby S contents in melt inclusions are scaled to erupted lava volumes. These amounts are significantly less than satellite-based SO2 emissions for the same eruptions (1986 = ~1 Mt; 2006 = ~2 Mt). Potential explanations for this observation are: 1) accumulation of a vapor phase within the magmatic system that is only released during eruptions, and/or 2) syn-eruptive gas release from unerupted magma. Post-1994 Nyamuragira lava volumes were not available at the beginning of this study. These flows (along with others since 1967) are mapped with Landsat MSS, TM, and ETM+, Hyperion, and ALI satellite data and combined with published flow thicknesses to derive volumes. Satellite remote sensing data was also used to evaluate Nyamuragira SO2 emissions. These results show that the most recent Nyamuragira eruptions injected SO2 into the atmosphere between 15 km (2006 eruption) and 5 km (2010 eruption). This suggests that past effusive basaltic eruptions (e.g., Laki 1783) are capable of similar plume heights that reached the upper troposphere or tropopause, allowing SO2 and resultant aerosols to remain longer in the atmosphere, travel farther around the globe, and affect global climates.