Thesis (Ph.D.)--University of Hong Kong, 2000. / Includes bibliographical references (leaves 203-223) Also available in print.

Thesis--University of Illinois. (Geology). / Vita. Includes bibliographical references (leaf 33).

Thesis ( M.S.)--University of Tennessee, Knoxville, 2010. / Title from title page screen (viewed on July 23, 2010). Thesis advisor: Robert D. Hatcher, Jr. Vita. Includes bibliographical references.

Thesis (Ph. D.)--Landbouwhoogeschool, 1937. / 1 fold. col. map in pocket. Summary in English. "Stellingen" inserted between p.4 and 5. Includes bibliographical references (p. [165]-168).

Thesis (Ph.D.) -- University of Texas at Dallas, 2005 / Includes vita. Includes bibliographical references (leaves 109-117)

Thesis (M.S.)--Kent State University, 2008. / Title from PDF t.p. (viewed Oct. 5, 2009). Advisor: Peter Dahl. Keywords: Geochronology; Radiometric Dating; Plate Tectonics. Includes bibliographical references (p. 106-109).

Thesis (MS)--Montana State University--Bozeman, 2009. / Typescript. Chairperson, Graduate Committee: Robin Gerlach. Includes bibliographical references (leaves 220-225).

<p> In October of 2015, a devastating landslide killed an estimated 350 people in the community of El Cambray II, located in a Guatemala City ravine, highlighting the need to manage landslide risk in precarious urban settlements in the area. This project evaluates landslide risk management in the Guatemala City metropolitan area to better encourage at-risk community members to change behaviors to reduce landslide risk. To evaluate specific risk management initiatives, the authors tracked changes in community members&rsquo; risk perception, knowledge and behaviors by surveying communities at different points in time during the implementation of initiatives. Using these factors as metrics, we demonstrate the degree to which these factors will change when a community-based risk management initiative is implemented in a precarious settlement. To characterize landslide risk perceptions, perception of landslide risk was compared to perception of other societal risks to which community members are exposed, and a rubric of relative knowledge of landslide risk was developed. A preliminary F-N (frequency of events vs number of fatalities) plot quantifies the degree of societal acceptance of landslide risk. Landslide risk faced by settlement residents was estimated with a preliminary landslide event database, for comparison to a quantified perception of risk to understand if communities perceive risk accurately, and to identify the level of intervention that would encourage behavioral change. Perceptions and knowledge of landslide risk are not being significantly changed by the studied initiatives, but behaviors are modestly changing, particularly for community members directly involved with the implementing organization. The results of this study are being shared with risk managers to improve their selection of initiatives, and to empower at-risk communities by incorporating their knowledge and perception of risk into risk management strategies.</p><p>

<p> Landslides represent a serious hazard to people and property in the Pacific Northwest. Currently, the factors leading to sudden catastrophic failure vs. gradual slow creeping are not well understood. Utilizing high-resolution monitoring techniques at a sub-annual temporal scale can help researchers better understand the mechanics of mass wasting processes and possibly lead to better mitigation of their danger. This research used historical imagery analysis, precipitation data, aerial lidar analysis, Structure from Motion (SfM) photogrammetry, terrestrial laser scanning (TLS), and hydrologic measurements to monitor displacement of the Silt Creek Landslide in the western Cascade Mountain Range in Linn County, Oregon. This landslide complex is ~4 km long by ~400 m wide. The lower portion of the landslide reactivated following failure of an internal scarp in June 2014. Precipitation was measured on site and historical precipitation data was determined from a nearby SNOTEL site. Analysis of aerial lidar data found that the internal scarp failure deposited around 1.00 x 10⁶ <i> m</i>³ of material over an area of 1.20 x 10⁵ <i> m</i>² at the uppermost portion of the reactivated slide. Aerial lidar analysis also found that displacement rates on the slide surface were as high as 3 <i>m/yr</i> during the 2015 water year, which was the year immediately following the failure. At the beginning of the 2016 water year, very low altitude aerial images were collected and used to produce point cloud data, via SfM, of a deformed gravel road which spans a portion of the reactivated slide. The SfM data were complimentary to the aerial and TLS scans. The SfM point cloud had an average point density of > 7500 points per square meter. The resulting cloud was manipulated in 3D software to produce a model of the road prior to deformation. This was then compared to the original deformed model. Average displacement found in the deformed gravel road was 7.5 m over the 17 months between the scarp failure and the collection of the images, or ~3 <i>m/yr</i>. TLS point clouds were collected quarterly over the course of the 2016 water year at six locations along the eastern margin of the reactivated portion of the landslide. These 3D point cloud models of the landslide surface had an average density of 175 points per square meter. Scans were georeferenced to UTM coordinates and relative alignment of the scans was accomplished by first using the iterative closest point algorithm to align stable, off-slide terrain, and then applying the same rigid body translation to the entire scan. This was repeated for each scan at each location. Landmarks, such as tree trunks, were then manually selected at each location and their coordinates were recorded from the initial scan and each successive scan to measure displacement vectors. Average annual displacement for the 2016 water year ranged from a maximum of 0.92 <i>m/yr</i> in the uppermost studied area of the slide, to a low of 0.1 <i>m/yr</i> at the toe. Average standard deviation of the vectors of features on stable areas was 0.039 m, corresponding to a minimum detectable displacement of about &plusmn;4 cm. Displacement totals decreased with increasing distance downslope from the internal scarp failure. Additionally, displacement tended to increase with increasing distance laterally onto the slide body away from the right margin at all locations except the uppermost, where displacement rates were relatively uniform for all landmarks. Volumetric discharge measurements were collected for Silt Creek in 2016 using salt dilution gauging and found that discharge in the upslope portion of the study area wwas ~1 <i>m3/s</i> and increased to ~1.6 <i>m3/s</i> in the downslope portion. Landslide displacement rates were found to be much lower during the 2016 water year than during the 2015 water year, despite higher precipitation. This suggests that the over-all displacement trend was decoupled from precipitation values. Displacement rates at all locations on the slide decreased with each successive scan period with some portions of the landslide stopping by autumn of 2016, suggesting the study captured the slide as it returned to a state of stability. The spatial and temporal pattern of displacement is consistent with the interpretation that the landslide reactivation was a response to the undrained load applied by the internal scarp failure. This finding highlights the importance of detailed landslide monitoring to improve hazard estimation and quantification of landslide mechanics. (Abstract shortened by ProQuest.) </p><p>

<p> The Probabilistic Infinite Slope Analysis model (PISA-m) is a widely used computer program that uses infinite slope equations to calculate the spatially varying Factor of Safety of slopes. ESRI&rsquo;s ArcGIS software and accompanying geoprocessing tools have become a mainstay in spatial data processing, and received full support for Python with the release of version 10. With many of the geoprocessing tools now available as a Python function, the software can be used for physics-based spatial landslide hazard analysis. A model that mimics PISA-m and its processing of normally distributed soil properties was created using the Python utility as a tool for ArcGIS. The newly created ArcGIS tool is referred as the GIS Tool for Infinite Slope Stability Analysis (GIS-TISSA). The tool was tested using the example data from PISA-m and case-study data from the district of Kannur, Kerala, India. The results from both areas highlight how different slope calculations can affect the overall calculation of the Factor of Safety, as well as the new model&rsquo;s ability to accurately predict Factor of Safety of slopes in an area.</p><p>