Browsing by Subject "Geographical Information Systems"
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Item Bayesian Networks and Geographical Information Systems for Environmental Risk Assessment for Oil and Gas Site Development(2013-04-03) Varela Gonzalez, Patricia YsoldaThe objective of this work is to develop a Bayesian Network (BN) model to produce environmental risk maps for oil and gas site developments and to demonstrate the model?s scalability from a point to a collection of points. To reach this objective, a benchmark BN model was formulated as a ?proof of concept? using Aquifers, Ecoregions and Land Use / Land Cover maps as local and independent input variables. This model was then used to evaluate the probabilistic geographical distribution of the Environmental Sensibility of Oil and Gas (O&G) developments for a given study area. A Risk index associated with the development of O&G operation activities based on the spatial environmental sensibility was also mapped. To facilitate the Risk assessment, these input variables (maps) were discretized into three hazard levels: high, moderate and low. A Geographical Information System (GIS) platform was used (ESRI ArcMap 10), to gather, modify and display the data for the analysis. Once the variables were defined and the hazard data was included on feature classes (layer shapefile format), Python 2.6 software was used as the computational platform to calculate the probabilistic state of all the Bayesian Network?s variables. This allowed to define Risk scenarios both on prognostic and diagnostic analysis and to measure the impact of changes or interventions in terms of uncertainty. The resulting Python ? ESRI ArcMap computational script was called ?BN+GIS, which populated maps describing the spatial variability of the states of the Environmental Sensibility and of the corresponding Risk index. The latter in particular, represents a tool for decision makers to choose the most suitable location for placing a drilling rig, since it integrates three fundamental environmental variables. Also, results show that is possible to back propagate the information from the Environmental Sensibility to define the inherent triggering scenarios (hazard variables). A case of study is presented to illustrate the applicability of the proposed methodology on a specific geographical setting. The Barnett Shale was chosen as a benchmark study area because sufficient information on this region was available, and the importance that it holds on the latest developments of unconventional plays in the country. The main contribution of this work relies in combining Bayesian Networks and GIS to define environmental Risk scenarios that can facilitate decision-making for O&G stakeholders such as land owners, industry operators, regulators and Non-Governmental Organizations (NGOs), before and during the development of a given site.Item Bio-energy Logistics Network Design Under Price-based Supply and Yield Uncertainty(2014-12-10) Memisoglu, GokhanIn this dissertation, we study the design and planning of bio-energy supply chain networks. This dissertation consists of 3 studies that focus on different aspects of bio-energy supply chain systems. In the first study, we consider planning and design of an extended supply chain for bio-energy networks in an integrated fashion while simultaneously addressing strategic and tactical decisions pertaining to location, production, inventory, and distribution in a multi-period planning horizon setting. For an efficient solution of our model, we suggest a Benders Decomposition based algorithm that can handle realistic size problems for design and analysis purposes. We provide computational results that demonstrate the efficiency of the solution approach on a wide ranging set of problem instances. Furthermore, we develop a realistic case by utilizing data pertaining to the state of Texas and conduct an extensive analysis on the effects of varying input parameters on the design outcomes for a bio-energy supply chain network. In the second study, we consider a two-stage stochastic problem to model farm-to-biorefinery biomass logistics while designing a policy that encourages farmers to plant biomass energy crops by offering them a unit wholesale price. In the first-stage, the model determines the supply chain network structure as well as the policy parameter, which is the biomass wholesale price offered to farmers. Second-stage problem is to determine the logistical decisions such as transportation, salvaging and out-sourcing. To solve this problem, we propose a solution framework that uses an algorithm based on the L-shaped method along with a Sample Average Approximation (SAA) approach. An extensive case study by varying some of the problem input parameters is conducted in Texas and the effects on the policy parameter (wholesale price), supply chain network design and expected total system cost are observed. In the last study, we propose a two-stage stochastic program to model a multi-period biomass-biofuel supply chain system to maximize the expected total system profit. We utilize a similar policy used in the second study to stimulate biomass energy crop production. Our model determines the policy parameter and the supply chain network structure in the first-stage and the tactical decisions for every time period in the second-stage. To solve this problem efficiently, we propose a solution algorithm based on the L-shaped method. Moreover, we also employ SAA approach in our solution methodology to statistically justify our solution quality. A case study is conducted in Texas for different biofuel prices and we analyze changes in the expected system profit the policy parameter and the supply chain network structure. Our case study results indicate that biofuel price needs to be at least $2.62/gal for the system to have a profit.Item Texas historic sites and diversity(2011-05) McKnight, Kimberly Anne; Holleran, Michael; Smith, GregoryThere are 34 state-supported historic sites that are managed by the Texas Historical Commission (THC) and the Texas Parks and Wildlife Department (TPWD). These sites have been acquired over the years with various justifications and acquisition histories and are not a planned system of historic sites. With the rapidly changing demographics in Texas, it is clear that new strategies need to be developed so that these sites better represent the history of all Texans. The thesis investigation begins with a history of diversity initiatives within the preservation movement. Next, I present an innovative method for identifying potential areas of focus for diversity initiatives at state historic sites using Geographic Information Systems (GIS). I developed a spatial analysis methodology to quantify the level of diversity of the web content of each of the 34 state historic sites. Each historic site’s web site was then ranked according to its relevance to four ethnic groups: African Americans, Hispanics, Asians and Native Americans. Additionally, I generated population maps, descriptive maps, and analytical maps in order to understand how historic sites interact with the surrounding population. Finally, I present a set of strategies for existing state historic sites that will provide greater diversity in interpretative techniques and promotion. The goal of the GIS-based spatial analysis and the subsequent development of strategies aimed at targeted sites is to broaden the appeal of historic sites to a more diverse audience.Item The use of GIS for hazard mitigation for historic resources(2011-05) Cynkar, Grace Alexandra; Holleran, Michael; Penick, Monica Michelle, 1972-; Scott, RodGeographical Information Systems (GIS) offers preservationists a unique tool with the potential to revolutionize hazard mitigation for historic resources. The program’s ability to link information to a specific geographical location and efficiently disperse this information can solve two of the most destructive issues of current natural disaster response practices: a lack of organized information and an efficient means of disseminating this data. The resources necessary to implement a GIS program and to the requisite cooperation between both public and private preservation organizations may seem prohibitive to many preservation programs; yet, the benefits make this initial investment cost-effective. Despite efforts to mitigate disasters, both natural and man-made, their effects constantly threaten historic resources. In the past two decades, the United States has made significant strides toward a greater protection of these sites; yet damage continues to occur. In this thesis, I have investigated methods of risk mitigation implemented in the United States at both the state and local level, and in the public and private sectors, using New Orleans, Louisiana after Hurricanes Katrina and Rita as a case study. Through this analysis, I discovered that a lack of accessible, organized information and cooperation between preservationists compounded the damage caused by the actual event itself. I argue that the implementation of GIS could solve many of these issues by providing a means of both consolidating data and distributing it among responders. In this work, I demonstrate the ability of GIS to easily solve the problems of current mitigation practices for historic resources. By discussing the tools and basic functions of the program, I clearly illustrate this utility to those unfamiliar with the program, while arguing its potential as a mitigation implement to all preservationists.