Thesis (M.S.) in Forest Resources--University of Maine, 2009. / Includes vita. Includes bibliographical references (leaves 77-80).

Thesis (M.S.)--Oregon State University, 2003. / Typescript (photocopy). Includes bibliographical references (leaves 57-62). Also available online.

Thesis (M.S.)--West Virginia University, 2001. / Title from document title page. Document formatted into pages; contains vi, 134 p. : ill., maps (some col.). Includes abstract. Includes bibliographical references (p. 128-134).

Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xiv, 142 p.; also includes graphics (some col.). Includes abstract and vita. Advisor: Ronxing Li, Dept.of Civil Engineering and Geodetic Science. Includes bibliographical references (p. 134-142).

Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xvi, 141 p.; also includes graphics (some col.). Includes abstract and vita. Advisor: Alan T. Murray, Dept. of Geography. Includes bibliographical references (p. 124-141).

Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xii, 139 p.; also includes graphics (some col.). Includes abstract and vita. Advisor: Mei-Po Kwan, Dept. of Geography. Includes bibliographical references (p. 132-139).

<p> Although savanna ecosystems cover approximately 20 % of the terrestrial land surface and can have productivity equal to some closed forests, their role in the global carbon cycle is poorly understood. This study explored the applicability of a past spaceborne Lidar mission and the potential of future missions to estimate canopy height and carbon storage in these biomes. </p><p> The research used data from two Oak savannas in California, USA: the Tejon Ranch Conservancy in Kern County and the Tonzi Ranch in Santa Clara County. In the first paper we used non-parametric regression techniques to estimate canopy height from waveform parameters derived from the Ice Cloud and land Elevation Satellite&rsquo;s Geoscience Laser Altimeter System (ICESat-GLAS) data. Merely adopting the methods derived for forests did not produce adequate results but the modeling was significantly improved by incorporating canopy cover information and interaction terms to address the high structural heterogeneity inherent to savannas. Paper 2 explored the relationship between canopy height and aboveground biomass. To accomplish this we developed generalized models using the classical least squares regression modeling approach to relate canopy height to above ground woody biomass and then employed Hierarchical Bayesian Analysis (HBA) to explore the implications of using generalized instead of species composition-specific models. Models that incorporated canopy cover proxies performed better than those that did not. Although the model parameters indicated interspecific variability, the distribution of the posterior densities of the differences between composition level and global level parameter values showed a high support for the use of global parameters, suggesting that these canopy height-biomass models are universally (large scale) applicable. </p><p> As the spatial coverage of spaceborne lidar will remain limited for the immediate future, our objective in paper 3 was to explore the best means of extrapolating plot level biomass into wall-to-wall maps that provide more ecological information. We evaluated the utility of three spatial modeling approaches to address this problem: deterministic methods, geostatistical methods and an image segmentation approach. Overall, the mean pixel biomass estimated by the 3 approaches did not differ significantly but the output maps showed marked differences in the estimation precision and ability of each model to mimic the primary variable&rsquo;s trend across the landscape. The results emphasized the need for future satellite lidar missions to consider increasing the sampling intensity across track so that biomass observations are made and characterized at the scale at which they vary. </p><p> We used data from the Multiple Altimeter Beam Experimental Lidar (MABEL), an airborne photon counting lidar sensor developed by NASA Goddard to simulate ICESat-2 data. We segmented each transect into different block sizes and calculated canopy top and mean ground elevation based on the structure of the histogram of the block&rsquo;s aggregated photons. Our algorithm was able to compute canopy height and generate visually meaningful vegetation profiles at MABEL&rsquo;s signal and noise levels but a simulation of the expected performance of ICESat-2 by adjusting MABEL data's detected number of signal and noise photons to that predicted using ATLAS instrument model design cases indicated that signal photons will be substantially lower. The lower data resolution reduces canopy height estimation precision especially in areas of low density vegetation cover. </p><p> Given the clear difficulties in processing simulated ATLAS data, it appears unlikely that it will provide the kind of data required for mapping of the biophysical properties of savanna vegetation. Rather, resources are better concentrated on preparing for the Global Ecosystem Dynamics Investigation (GEDI) mission, a waveform lidar mission scheduled to launch by the end of this decade. In addition to the full waveform technique, GEDI will collect data from 25 m diameter contiguous footprints with a high across track density, a requirement that we identified as critically necessary in paper 3. (Abstract shortened by UMI.)</p>

<p> Since the late eighties, an ever increasing number of American craft breweries have opened up across the United States. Although the industry has a relatively high success rate, there are still a number of craft breweries that fail. As craft brewing is an inherently location based business, the sites selected for new brewery locations are important to that business&rsquo;s success. This research aims to examine how geodemographic information plays a role in strategic location decisions for craft breweries. By building a consumer profile for Phoenix craft brewery customers and comparing the results to the actual demographics of trade areas surrounding craft breweries, we begin to get a picture of geodemographics role in the site selection process. The research looks specifically at two locations; Bad Water Brewing Company and a site they are interested in acquiring. An analysis is performed to compare the geodemographic and behaviors of craft beer consumers in Phoenix, Arizona and those of the Bad Water Brewing location and their potential new site. This analysis ultimately results in intelligent business information related to location. The information compiled in this study can be used to make informed site selection decisions.</p>

<p> Light Detection And Ranging (LiDAR) data can be used to accurately model three- dimensional surfaces for quantifying fluvial erosion and deposition. Terrestrial LiDAR is typically used for monitoring banks, but can be used for monitoring planar forms such as point bars. Point bars are topographic features that form on the convex bank of a meander. While point bars are considered to be formed by depositional processes, they display features such as chute channels and scour holes that suggest that erosion, due to high flow events, may significantly influence point bar evolution. Through the use of Terrestrial Laser Scanning (TLS), we observed how a point bar on the White Clay Creek near Newark, Delaware, responded to a flood event with a return period of 6.1 years, and to multiple small events over a 1 year period with return periods between 1.00 and 1.25 years. Scans of the point bar were completed on April 11, 2014, May 8, 2014, and April 16, 2015. Scans were referenced to a common coordinate system, scan data representing vegetation points were removed, and three 0.1 m x 0.1 m gridded Digital Elevation Models (DEMs) were created from the remaining data. DEMs of Difference (DoDs) were calculated by subtracting the cell values in subsequent DEMs and by thresholding out positional and surface roughness errors. The 6.1 year flood that occurred between the April 11, 2014 scan and the May 8, 2014 scan resulted in 88.53 m³ of erosion and 39.12 m³ of deposition. The net volumetric change was -49.40 m³ over an area of 631.72 m². The smaller events that occurred between the May 8, 2014 scan and the April 16, 2015 scan resulted in 13.33 m³ of erosion and 53.46 m³ of deposition. The net volumetric change was x i 40.13 m³ over an area of 620.74 m². Our results suggest that 1) sediment deposited on point bars is eroded frequently by flood events; and 2) TLS can provide useful estimates of erosion and deposition. Although our results are for a short period, longer datasets can be used to calculate sediment residence times for point bar deposits. Additionally, we can gain a better understanding of how point bar deposits are preserved in the geologic record. This information is useful for creating accurate sediment budgets, remediating contamination issues, and interpreting geologic history.</p>

<p> This survey study examines cell phone usage data and focuses on the application of the data to disaster response management. Through the course of this study, the structure of cell phone usage data and its characteristics will be reviewed. Cell phone usage data provides us with valuable information about human movements and their activities. The uniqueness of the data is that it contains both spatial and temporal information and this information is free of fixed routes such as roads or any preset data capturing timing. In short, it is a very fluid kind of data which reflects our activities as humans with freedom of movement. Depending on data extraction methods, the data server can provide additional information such as application activities, battery level and charge activities. However, cell phone usage data contains shortcomings including data inconsistency and sparseness. Both the richness and the shortcomings of the data expose the hurdles required in data processing and force us to devise new ways to analyze this kind of data. Once the data has been properly analyzed, the findings can be applied to our real life problems including disaster response. By understanding human movement patterns using cell phone usage data, we will be able to allocate limited emergency resources more adequately. Even more, when disaster victims lose their cell phone functionality during a disaster, we might be able to identify or predict the locations of victims or evacuees and supply them with necessary assistance. The results of this study provide some insights to cell phone usage data and human movement patterns including the concentration of cell phone activities in specific zones and rather universal cell phone charging patterns. The potential of the data as a movement analysis resource and the application to disaster response is apparent. As a base to leverage the study to the next level, a possible conceptual model of human movement factors and data processing methods will be presented.</p>