UNT Theses and Dissertations - 8 Matching Results

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Memory and Continuity Amidst Irreversible Decline in the Texas Big Empty

Description: This thesis interrogates sense of place and place attachment in the Big Empty on the north central Texas plains. The region stretches from the Red River on the north to the Colorado River basin on the south and from the Cross Timbers on the east to the Caprock escarpment on the west. Since 1930, the Big Empty has seen sustained and severe population decline such that some counties there now register less than a quarter the population they did at their peaks during the interwar years. Through in-depth field interviews, I examine sense of place and place attachment amidst apparently irreversible decline. I also describe conditions of postindustrial rurality arising from rolling reconfigurations of economic and social relations, particularly changes in scale in farming and the diminished centrality of productivist agriculture in local economies and culture, and how these conditions become legible through the study of place.
Date: December 2016
Creator: Underwood, Robert Reed
Partner: UNT Libraries

Parcel-Based Change Detection Using Multi-Temporal LiDAR Data in the City of Surrey, British Columbia, Canada

Description: Change detection is amongst the most effective critical examination methods used in remote sensing technology. In this research, new methods are proposed for building and vegetation change detection using only LiDAR data without using any other remotely sensed data. Two LiDAR datasets from 2009 and 2013 will be used in this research. These datasets are provided by the City of Surrey. A Parcel map which shows parcels in the study area will be also used in this research because the objective of this research is detecting changes based on parcels. Different methods are applied to detect changes in buildings and vegetation respectively. Three attributes of object –slope, building volume, and building height are derived and used in this study. Changes in buildings are not only detected but also categorized based on their attributes. In addition, vegetation change detection is performed based on parcels. The output shows parcels with a change of vegetation. Accuracy assessment is done by using measures of completeness, correctness, and quality of extracted regions. Accuracy assessments suggest that building change detection is performed with better results.
Date: December 2016
Creator: Yigit, Aykut
Partner: UNT Libraries

Automated Tree Crown Discrimination Using Three-Dimensional Shape Signatures Derived from LiDAR Point Clouds

Description: Discrimination of different tree crowns based on their 3D shapes is essential for a wide range of forestry applications, and, due to its complexity, is a significant challenge. This study presents a modified 3D shape descriptor for the perception of different tree crown shapes in discrete-return LiDAR point clouds. The proposed methodology comprises of five main components, including definition of a local coordinate system, learning salient points, generation of simulated LiDAR point clouds with geometrical shapes, shape signature generation (from simulated LiDAR points as reference shape signature and actual LiDAR point clouds as evaluated shape signature), and finally, similarity assessment of shape signatures in order to extract the shape of a real tree. The first component represents a proposed strategy to define a local coordinate system relating to each tree to normalize 3D point clouds. In the second component, a learning approach is used to categorize all 3D point clouds into two ranks to identify interesting or salient points on each tree. The third component discusses generation of simulated LiDAR point clouds for two geometrical shapes, including a hemisphere and a half-ellipsoid. Then, the operator extracts 3D LiDAR point clouds of actual trees, either deciduous or evergreen. In the fourth component, a longitude-latitude transformation is applied to simulated and actual LiDAR point clouds to generate 3D shape signatures of tree crowns. A critical step is transformation of LiDAR points from their exact positions to their longitude and latitude positions using the longitude-latitude transformation, which is different from the geographic longitude and latitude coordinates, and labeled by their pre-assigned ranks. Then, natural neighbor interpolation converts the point maps to raster datasets. The generated shape signatures from simulated and actual LiDAR points are called reference and evaluated shape signatures, respectively. Lastly, the fifth component determines the similarity between evaluated and reference shape ...
Date: May 2018
Creator: Sadeghinaeenifard, Fariba
Partner: UNT Libraries

Evaluating Sea-Level Rise Hazards on Coastal Archaeological Sites, Trinity Bay, Texas

Description: This study uses the predictive modeling program Sea-Levels Affecting Marshes Model (SLAMM) to evaluate sea-level rise hazards, such as erosion and inundation, on coastal archaeological sites with a vertical rise of sea level of .98 meters from 2006 to 2100. In total 177 archaeological site locations were collected and georeferenced over GIS outputs maps of wetlands, erosion presence, surface elevation, and accretion. Wetlands data can provide useful information about characteristics of the wetland classes, which make a difference in the ability for coastal archaeological sites to combat sea level rise. Additionally, the study evaluated predicted erosion of archaeological sites by presence or absence of active erosion on a cell-by-cell basis. Elevation map outputs relative to mean tide level allowed for a calculation of individual archaeological site datums to use NOAA tidal databases to identify the potential for their inundation. Accretion maps acquired from the SLAMM run determined the potential for the archaeological site locations to combat rising sea levels and potentially provide protection from wave effects. Results show that the most significant hazard predicted to affect coastal archaeological sites is inundation. Approximately 54% of the total archaeological sites are predicted to be inundated at least half the time by 2100. The hazard of erosion, meanwhile, is expected to affect 33% of all archaeological sites by the end of the century. Although difficult to predict, the study assumes that accretion will not be able to keep pace with sea-level rise. Such findings of hazards prove that SLAMM is a useful tool for predicting potential effects of sea-level rise on coastal archaeological sites. With its ability to customize and as it is complementary, it provides itself not only an economical choice but also one that is adaptable to many scenarios.
Date: May 2018
Creator: Elliott, Patrick
Partner: UNT Libraries

Improvement of the Soil Moisture Diagnostic Equation for Estimating Root-Zone Soil Moisture

Description: Soil moisture information can be used accurately in determining the timing and amount of irrigation applied to plants. Pan and Pan et al. proposed a robust and simple daily diagnostic equation for estimating daily soil moisture. The diagnostic equation evaluates the relationship between the soil moisture loss function and the summation weighted average of precipitation. The loss function uses the sinusoidal wave function which employs day of the year (DOY) to evaluate the seasonal variation in soil moisture loss for a given year. This was incorporated into the daily diagnostic equation to estimate the daily soil moisture for a location. Solar radiation is an energy source that drives the energy and water exchanges between vegetation and the atmosphere (i.e., evapotranspiration), and thus impacts the soil moisture dry-down. In this paper, two parameters (the actual solar radiation and the clear sky solar radiation) are introduced into loss function coefficient to improve the estimation of soil moisture. After the Introduction of the solar radiation data into soil moisture loss function, a slight improvement was observed in the estimated daily soil moisture. Pan observed that generally the correlation coefficient between the estimated and the observed soil moisture is above 0.75 and the root mean square error is below 5.0 (%v/v). The introduction solar radiation data (i.e. clear sky solar radiation and actual solar) improve the correlation coefficient average for all the sites evaluated by 0.03 when the root mean square error is generally below 4.5(%v/v) for the entire root zone.
Date: May 2018
Creator: Omotere, Olumide Olubunmi
Partner: UNT Libraries

Seeds of Disempowerment: Bt cotton and Accumulation by Dispossession in the States of Maharashtra, Telangana, and Andhra Pradesh in India

Description: In 1991, India adopted neoliberalism, a system of political economic practices that promotes private property and free trade, as its political and economic system to promote development in their country. India's neoliberal reform has created issues surrounding human development, resource accumulation, and power struggles. Eleven years later, in 2002, Bt cotton was introduced to the Indian agricultural sector. This research examines how the genetically modified organism Bt cotton is being used to commodify nature in the context of agriculture under neoliberalism. The research focuses on the dispossession of the rural farmers through the commodification of agriculture using Bt cotton. Dispossession of the rural farmers happen through the implications that arise from the commodification of nature. Through Marxist theory of primitive accumulation, this research analyzes accumulation by dispossession and how it neglects the working class and its struggle in rural India. Through this examination, the research will argue alternatives to the dispossession of the working class and the commodification of nature through Bt cotton. Dispossession, in this research, is examined both through working class, but also through the dispossession of biodiversity. Through the loss of biodiversity, the rural farmers are becoming dispossessed from a more sustainable environment. Along with these goals, the research will also incorporate themes of food security through changing landscape of agriculture due to the incorporation of Bt cotton. This research argues the contradictions that are presented through the commodification of agriculture under neoliberalism and provide a contribution to social justice literature, and our understanding of the relationship between technology and the commodification of nature.
Date: May 2018
Creator: Hoyt, Andrew
Partner: UNT Libraries

Redesigning Police Beat Zone Placement to Improve 911 Response Time: A Data Driven Approach

Description: Research suggests that using data driven solutions in policing strategies improves the quality of service provided by the police department. Unfortunately, many police departments, including the Denton Police Department, do not use their spatial data to inform beat zone placement. Analysis of the current beat zone configuration found that there are disparities in the workload, as measured by number of calls for service, between beat zones. Further, there was also a statistically significant difference between the median response times across all the five beat zones in Denton. This means that the median response time varies depending on where the call for service originates. Using readily available data, these police departments can apply methods such as UPAS to improve the quality of service provided by the department. UPAS is a deterministic algorithm that produces a given number of contiguous spatial partitions of approximately equal population size; in this case, calls for service are substituted for population. Although this algorithm was originally developed to create solutions for bio-terrorism response planning, it has been applied to the problem of creating beat zones of roughly equal workload in this research. I have shown that this algorithm results in a beat zone configuration that significantly reduces the difference in workload between the busiest and least busy beat zone (~94% reduction). Assuming an equal distribution of resources across beat zones, having approximately similar workloads should lead to fewer disparities in quality of service.
Date: August 2018
Creator: Jones, Brince Robert
Partner: UNT Libraries

Social Vulnerability and Bio-Emergency Planning: Identifying and Locating At-Risk Individuals

Description: In 2006, the United States Congress passed the Pandemic All-Hazards Preparedness Act (PAHPA) which mandated that all emergency preparedness planning shall address at-risk populations. Further, in 2013, the reauthorization of this act, known as PAHPRA, defined at-risk individuals as "children, older adults, pregnant women, and individuals who may need additional response assistance." This vague definition leaves emergency managers, planners, and public health officials with the difficult task of understanding what it means to be at-risk. Further, once identified, the geographic location of at-risk individuals must be obtained. This research first uses the concept of social vulnerability to enhance the understanding of what it means to be "at-risk." Then, by comparing two data disaggregation techniques, areal weighted interpolation and dasymetric mapping, I demonstrate how error of estimation is affected by different scenarios of population distribution and service area overlap. The results extend an existing framework of vulnerability by stratifying factors into quantifiable and subjective types. Also, dasymetric mapping was shown to be a superior technique of data disaggregation compared to areal weighted interpolation. However, the difference in error estimates is low, 5 percent or less in 72 percent of the test cases. Only through local collaboration with community entities can emergency planners access the appropriate data to both: 1) understand the nature of at-risk individuals in their service areas and 2) spatially target resources needed to ensure all individuals are planned for in case of a bio-emergency.
Date: August 2018
Creator: Richardson, Brian T
Partner: UNT Libraries