The Gravity Recovery and Climate Experiment (GRACE) project has two primary goals: to determine the Earth’s mean gravitational field over the lifetime of the mission and to observe the time-variable nature of the gravitational field. The Center for Space Research's (CSR) Release 4 (RL04) GRACE solutions are currently created via a least-squares process that assimilates data collected over a month using a simple boxcar window and determines a spherical harmonic representation of the monthly gravitational field. The nature of this technique obscures the time-variable gravity field on time scales shorter than one month and spatial scales shorter than a few hundred kilometers. A computational algorithm is developed here that allows increased temporal resolution of the GRACE gravity information, thus allowing the Earth's time-variable gravity to be more clearly observed. The primary technique used is a sliding-window algorithm attached to a weighted version of batch least squares estimation. A number of different temporal windowing functions are evaluated. Their results are investigated via both spectral and spatial analyses, and globally as well as in localized regions. In addition to being compared to each other, the solutions are also compared to external models and data sets, as well as to other high-frequency GRACE solutions made outside CSR. The results demonstrate that a GRACE solution made from at least eight days of data will provide a well-conditioned solution. A series of solutions made with windows of at least that length is capable of observing the expected near-annual signal. The results also indicate that the signals at frequencies greater than 3 cycles/year are often smaller than the GRACE errors, making detection unreliable. Altering the windowing technique does not noticeably improve the resolution, since the spectra of the expected errors and the expected non-annual signals are very similar, leading any window to affect them in the same manner. / text

No description available.

<p> Mapping forest resources is useful for identifying threat patterns and monitoring changes associated with landscapes. Remote Sensing and Geographic Information Science techniques are effective tools used to identify and forecast forest resource threats such as exotic plant invasion, vulnerability to climate change, and land-use/cover change. This research focused on mapping abundance and distribution of Russian-olive using soil and land-use/cover data, evaluating historic land-use/cover change using mappable water-related indices addressing the primary loss of riparian arboreal ecosystems, and detecting year-to-year land-cover changes on forest conversion processes. Digital image processing techniques were used to detect the changes of arboreal ecosystems using ArcGIS ArcInfo&reg; 9.3, ENVI&reg;, and ENVI&reg; EX platforms.</p><p> Research results showed that Russian-olive at the inundated habitats of the Missouri River is abundant compared to terrestrial habitats in the Bismarck-Mandan Wildland Urban Interface. This could be a consequence of habitat quality of the floodplain, such as its silt loam and silty clay soil type, which favors Russian-olive regeneration. Russian-olive has close assemblage with cottonwood (<i>Populus deltoides</i>) and buffaloberry (<i>Shepherdia argentea</i>) trees at the lower elevations. In addition, the Russian-olive-cottonwood association correlated with low nitrogen, low pH, and high Fe, while Russian-olive- buffaloberry association occurred in highly eroded areas.</p><p> The Devils Lake sub-watershed was selected to demonstrate how both land-use/cover modification and climatic variability have caused the vulnerability of arboreal ecosystems on the fringe to such changes. Land-cover change showed that the forest acreage declined from 9% to 1%, water extent increased from 13% to 25%, and cropland extent increased from 34% to 39% between 1992 and 2006. In addition, stochastic modeling was adapted to simulate how land-use/cover change influenced forest conversion to non-forested lands at the urban-wildland fringes in Cass County. The analysis yielded two distinct statistical groups of transition probabilities for forest to non-forest, with high transition probability of unchanged forest (0.54&le; Pff &le; 0.68) from 2006 to 2011. Generally, the land-uses, such as row crops, showed an increasing trend, while grains, hay, seeds, and other crops showed a declining trend. This information is vital to forest managers for implementing restoration and conservation practices in arboreal ecosystems.</p>

To predict the location of natural resources and reduce the cost of exploration, geophysicists rely on various techniques to map the internal structure of the earth. One common mapping method probes the earth's interior using an acoustic energy source (sound waves). The acoustic waves reflect when they impinge on a location where the acoustic velocity field oscillates rapidly (on the scale of a wavelength). When the waves reflect back to the surface, they carry kinematical information about the location of the oscillatory velocity field. A linearized wave equation models the scattering process and its solution operator is a Fourier integral operator. As such, the scattering operator has a canonical relation $\Lambda$ which describes how the operator maps oscillatory velocity fields to oscillatory wave fields at the surface. The goal of linearized inversion is to obtain an inverse operator (with inverse canonical relation) for the scattering operator. We give a geometrical condition on $\Lambda$ that is equivalent to the existence of a linearized inversion operator. Since the $L\sp2$-adjoint of the scattering operator has inverse canonical relation, geophysicists often apply it to the scattered field to obtain a map of the subsurface. I analyze the scattering operator using high-frequency asymptotics and show that if the geometrical condition fails, the scattering canonical relation is not injective. Therefore, application of the adjoint operator to the scattered wave field can produce artifacts in the resulting map of the subsurface. I demonstrate this effect numerically. I also prove that the scattering operator is continuous between a certain domain and range space iff the geometrical condition on $\Lambda$ holds. Furthermore, I have shown that it is possible to map an experiment where the geometrical condition fails into another experiment where it holds.

<p> Digital soil mapping (DSM) is a rapidly growing area of soil research that has great potential for enhancing soil survey activities and advancing knowledge of soil-landscape relationships. To date many successful studies have shown that geographic datasets can be used to model soil spatial variation. This thesis addresses two issues relevant to DSM, scale effects on digital elevation models, and predicting soil properties. The first issue examined was the effect of spatial extent on the calculation of geometric land surface parameters (LSP) (e.g. slope gradient). This is a significant issue as they represent some of the most common predictors used in DSM. To examine this issue two case studies were designed. The first evaluated the systematic effects of varying both grid and neighborhood size on LSP, while the second examined how the correlation between soil and LSP vary with grid and neighborhood size. Results of the first case study demonstrate that finer grid sizes were more sensitive to the scale of LSP calculation than larger grid sizes. While the magnitude of effect was diminished when comparing a high relief landscape to a low relief landscape, the shape and location of the effect was similar. Results of the second case study showed that the correlation between soil properties and slope curvatures were similarly optimized when varying the spatial extent, but that the effect was more sensitive to grid size than neighborhood size. Slope gradient also showed significant correlations with some of the soil properties, but was not sensitive to changes in grid or neighborhood size.</p><p> The second study attempted to predict numerous physical and chemical soil properties for several depth intervals (0-15, 15-60, 60-100, and 100-150-centimeters), using generalized linear models (GLM) and geographic datasets. The area examined was the Upper Gauley Watershed on the Monongahela National Forest, which covers approximately 82,500 acres (33,400 hectares). This watershed represents a complex landscape with contrasting geologic strata, deciduous and coniferous forests, and steep slopes. Given this landscape diversity it was still possible to fit GLM which explained on average 38 percent of the adjusted deviance for rock fragment content, and exchangeable calcium and magnesium, and phosphorus. Some of the most commonly selected environmental predictors were slope curvatures, lithology types, and relative slope position indices. This seems to validate the prominence of these variables in theoretical soil-landscape models. Had the correlation between the soil properties and slope curvatures not been optimized by varying the spatial extent, it is likely that another less suitable LSP would have been selected.</p>

<p> Properly used, social media represents a new and dynamic form of advertising. This paper analyzes the relationship between social media use and the physical location of Omaha restaurants. A pilot study showed no predictive relationship between overall social media use and physical location. The major study using 495 restaurants examined the restaurants' use of three major social media sites. Correlation analysis of the variables showed essentially no relationship between the use of social media and restaurant location. The findings indicate that restaurants with a poor physical location are not taking advantage of social media to attract customers. Likewise, restaurants with a better physical location are not using social media to attract more customers. The social media landscape may be too immature to show any identifiable spatial patterns. </p>

<p> Strain evolution and stress evolution following the 4 April 2010 M7.2 El Mayor-Cucapah earthquake are modeled using an adaptation of the strain transient detection tool developed by <i>Holt and Shcherbenko</i> 2013. The evolution of stress is calculated from postseismic strains, which are modeled from continuous GPS horizontal displacements. Strain fields are modeled in 2 ways; the total strain field based on total observed cGPS displacements, and the residual strain field, which subtracts a reference field from the total model. The residual shows anomalous strains resulting from the postseismic relaxation of the 2010 event. Anomalous and total strains are modeled in 0.1 year epochs for 2.4 years following the event. Both total and anomalous strains are converted into stress changes over time, assuming elastic incompressible behavior. Following the El Mayor event, the GPS constrained strain evolution shows the following: (1) The Southern San Andreas experiences a reduced rate of right-lateral strike slip strain accumulation between 3 July 2010 and 7 August 2012 (Figure 16a-d). (2) The San Jacinto Fault has normal rate of right-lateral strike-slip strain accumulation during this time. (3) Before the Brawley swarm of 26 August 2012, the state of strain evolves to enable unclamping of a left-lateral fault zone in the Brawley Seismic Zone (Figure 16a-d). (4) Large shear strains accumulate on the Laguna Salada Fault (northernmost segment)/southern Elsinore FZ (Figure 16a-d). We converted the strain changes into Coulomb stress changes on existing faults (both right-lateral and left-lateral). Several regions show increased Coulomb stress changes throughout the postseismic process. Furthermore, the Coulomb stress changes on the faults in the region progressively increase toward failure up to the time of the Brawley swarm.</p>

Typescript (photocopy) / iv, 199 leaves ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Geology and Mineralogy, 1983

Thesis (B.S.)--University of Missouri, School of Mines and Metallurgy, 1917. / The entire thesis text is included in file. Typescript. Illustrated by author. Howard J. Teas determined to be Howard Jones Teas from "1874-1999 MSM-UMR Alumni Directory". Title from title screen of thesis/dissertation PDF file (viewed May 7, 2009) Includes bibliographical references (p. 27).

Thesis (B.S.)--University of Missouri, School of Mines and Metallurgy, 1907. / The entire thesis text is included in file. Typescript. Illustrated by author. Title from title screen of thesis/dissertation PDF file (viewed Jan. 23, 2009).